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As discussed above, ANOVAs are used to make comparisons across three or more groups of a dependent variable(s) with one or more independent variables. ANOVA is appropriate whenever you want to test differences between the means of an interval-ratio level dependent variable across three or more categories of an independent variable. There are two techniques for doing ANOVA: one-way ANOVA and two-way ANOVA.
One-Way ANOVA
The One-Way ANOVA compares the means of two or more independent groups in order to determine whether there is statistical evidence that the associated population means are significantly different. This technique might be useful for analyzing field studies, experiment and quasi-experiment data (Kansas State Universities Library, 2022). It must be noted that while both the One-Way ANOVA and the Independent Samples T-Test can be used to compare the means for two groups, only the One-Way ANOVA can compare the means across three or more groups.
Two-way ANOVA
The Two-way ANOVA is similar to the one-way ANOVA except that it allows you to consider two independent variables (instead of one) while comparing the means of three or more groups of data. Before running an ANOVA, it is important to ensure that assumptions are met. Box 10.5.4.3 highlights some key assumptions.
Box 10.6 – Some Assumptions about ANOVA
• Your dependent variable should be measured at the continuous level (i.e., they are interval or ratio variables).
• Your two independent variables should each consist of two or more nominal or ordinal, independent groups.
Ex. Gender (2 groups: male or female), ethnicity (3 groups: Caucasian, African American and Hispanic)
• You should have independence of observations, which means that there is no relationship between the observations in each group or between the groups themselves.
• There should be no significant outliers.
• Your dependent variable should be approximately normally distributed for each combination of the groups of the two independent variables.
See UBC’s research commons for guidance on how to run an ANOVA and other procedures in SPSS https://researchcommons.library.ubc.ca/introduction-to-spss-for-statistical-analysis/
Presenting ANOVA Results
SPSS (and most other statistical programs) presents two output tables for ANOVA results: descriptives and ANOVA. From the descriptives, you will need to record N, Mean, Std. Deviation and Std. Error. From the ANOVA table, you will need to record df, F and Sig.
ANOVAs are reported like the t test, but there are two degrees-of-freedom numbers to report. First report the between-groups degrees of freedom, then report the within-groups degrees, separated by a common. After that report the F statistic (rounded off to two decimal places) and the significance level. In addition, note the following:
• If there were significant differences, state the means and standard deviations for each group.
• If Statistically significant, you might need to dig deeper to state which group is significantly different from which. In SPSS or the statistical program you are using, simply run a post-test. Post tests (e.g. Tukey Ad hoc Post test) can be used to indicate which group is significantly different from which [see https://www.statology.org/anova-post-hoc-tests/ for further discussions and examples of post-tests]
One-Way ANOVA
An one way analysis of variance showed that the effect of international status on grades was significant, F(3,155) = 9.94, p = .007. Post hoc analyses using the Tukey post hoc criterion for significance indicated that the average grade was significantly lower for international students (M = 70.2, SD = 2.16) than in the other two groups (regional domestic and local domestic) combined (M = 73.2, SD = 4.56), F(3, 155) = 9.37, p = .033.
OR
There was not a statistically significant difference between groups as demonstrated by one-way ANOVA (F(3,188) = .179, p = .910).
PS**Note that if the results are not significant, you should not do a post hoc analysis.
Two-Way or Multiple Factor ANOVA
Your finding narrative should include the following:
• Identify that you are reporting on a two-way ANOVA and the variables of concern
• State the significant level (e.g. .05 level)
• Identify the effect of each of variables e.g. Independent variable #1 yield an F ratio of F (df, df)=__, p=__)
• Highlight the statistics (M and SD) for each of the attributes for Independent Variable #1 and Independent variable #2
Box 10.7 – Examples
Students’ grades in Sociology 222 were subjected to a two-way analysis of variance considering gender (females, non-females) and study status (part-time, full-time). All effects were statistically significant at the .05 significance level. The main effect of gender yielded an F ratio of F(1, 24) = 44.4, p < .001, indicating that the mean grade was significantly greater for females (M = 4.78, SD = 1.99) than for non-females (M = 2.17, SD = 1.25). The main effect of study status yielded an F ratio of F(1, 24) = 25.4, p < .01, indicating that the mean grade was significantly higher among part-time students (M = 5.49, SD = 2.25) than full-time students (M = 0.88, SD = 1.21). The interaction effect was non-significant, F(1, 24) = 1.22, p > .05.
Chi Square
To report chi-square results in your paper, you need to identify and report on the following four values from your output: degrees of freedom and sample size in parentheses, the Pearson chi-square value (rounded to two decimal places), and the significance level In APA, chi square results are reported using the following format:
X2 (degrees of freedom, N = sample size) = chi-square statistic value, p = p value.
Let us assume that you conducted a chi-square to determine the relationship between gender and whether or not students pass Sociology 222. The first thing you would want to do is identify the four values e.g., df =2, N=1525, chi square statistic= 11.6, p=.0071
Next, you would report your chi-square results and interpret it as follows:
A chi-square test of independence was performed to examine the relation between gender and whether or not students pass SOCI 200. The relation between these variables was significant, X2 (2, N = 1525) = 11.6, p = .0071. This indicates that students who identified as males were more likely to fail than students who identified with other genders.
Remember, you must always interpret the results, i.e., state what the results mean.
Box 10.8 – Reporting Chi Square Results
Here are some general guidelines for reporting chi-square results:
• It is okay to include the crosstab results in your paper. However, please ensure that cross table tables follow the standard APA format: Independent variables in column and dependent variables in the row. Include numbers (and percentages in parentheses) in each cell. If the format of IV in columns and DV in rows is used, percentage the IV.
• If you include a cross table, interpret the results.
• You can cite the exact p values (e.g. p =.0013) or you note if the p value is less than .001 e.g. p < .001.
• It is important to state your hypothesis before reporting your results.
• The calculated chi-square should be stated at two decimal places
• To assess the strength of the association, we compute phi (for 2 rows x 2 columns tables i.e. 2 rows and 2 columns). For larger than 2 rows X 2 columns tables, we compute Cramer’s V. Below are some general rules of thumb to determine the strength of the relationships:
• 0.00 to 0.10 weak relationship
• 0.11 to 0.30 moderate relationship
• Greater than 0.30 strong relationship
See Healey, J. F. (2009). Statistics: A Tool for Social Research (Eight Edition). Wadsworth Cengage Learning. | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/10%3A_Quantitative_Data_Analysis/10.06%3A_Analysis_of_Variance_%28ANOVA%29.txt |
Box 10.9 – Student Testimony – Making Data Visualizations with R
My thesis made use of simple graphics in R to present basic word frequencies of key terms in my data. R is an open-source coding tool with as much flexibility as its coding language will allow. It can organize information and visualize data through infographics, plots, charts, you name it. Despite its wide applicability, however, the language can be forbidding to the uninitiated coder. I found that each term and function can easily become dependent on more subtle information about the logic of R, resulting in many late nights on Reddit forums to understand my botched attempts to make a simple graph. In the hope that my suffering with R can make the process easier for you, I have presented a simple five step guide to descriptive statistics on R along with some resources for further exploration.
Alexander Wilson, Sociology Honours student, 2020-2021
Download R, RStudio and Install a Plotting Package
Once you have downloaded both, you should be able to start up the RStudio application, which will take you to a blank coding terminal. The RStudio package is to help make coding through R easier. It is neater and will predict the coding functions you are trying to type in.
After opening R, type in (or copy): install.packages(“ggplot2”)
Which should install the latest version of the data visualization package ggplot2.
Starting up ggplot
The following link will take you to the website of ggplot2, which has extra resources for downloading and a cheat sheet of the relevant functions you will need to know.
Plotting Package & Cheat Sheet: ggplot2 download | SourceForge.net
Once you have downloaded ggplot2, you will need to load it to use it. The load function is below:
library(ggplot2)
Input your data
To be able to visualize data on R, first it must be organized within the system. This can be simply done through the creation of basic quantitative variables. You can create a simple bivariate data frame in R like so:
data.frame(age = c(9, 10, 11, 12, 13), grade = c(6, 7, 8, 9, 10))
Where age has five cases, namely 9, 10, 11, 12, 13; and grade has five cases, 6, 7, 8, 9, 10. It is helpful to name the data.frame for simple use like so:
age_grade <- data.frame(age = c(9, 10, 11, 12, 13), grade = c(6, 7, 8, 9, 10))
From here, you can begin to plot simple descriptive statistics by typing “age_grade” into the ggplot functions outlined below.
ggplot Legend and Functions
For instance, taking our previous example, you could create a simple box chart of our data.frame (age_grade).
First you begin with the basic form of all ggplot functions
ggplot(data = <DATA>, Mapping = aes(<MAPPINGS>)) + <GEOM_FUNCTION>()
where:
data = your file of data (in this case age)
mapping = which is determined by the function aes and then the axes that your function is using (i.e. x, y, z). It typically runs like so, aes(x = weight, y = age).
GEOM FUNCTION = the various charts you can visualize your data through (such as boxplots, geom_boxplot())
Put these together with your data like so:
ggplot(data = age_grade, mapping = aes(x = age, y = grade) + geom_boxplot())
And you should be presented with the simple following chart:
Use the following legend to be able to map out your coordinates according to many different visualizations. For simple repeated use, save your ggplot function like so:
age_grade_plot <- ggplot(data = age_grade, mapping = aes(x = age, y = grade))
And then simply add age_grade_plot to the geom function you want to use:
age_grade_plot + geom_bar()
And you should get that function. Screenshot it and it is yours to present in your paper!
Table 10.5 - Terminology with R
Term Definition
Data Data you visualize and a set of outlines of how you want to make it look appealing (choice of colour, bolding, etc.).
Layers Layers are the statistical summaries of that data which will be represented by geometric objects, geoms for short, that show what you see on the plot: points, lines, polygons, and so forth.
Scales Scales show the ratio or proportion in which you have mapped your data onto your graphic.
Coord Coord stands for a coordinate system. The coordinate system describes where the data is shown on the plane of the graphic. It provides axes and gridlines to conceptualize the data onto space. A coordinate system, coord for short, describes how data coordinates are mapped to the plane of the graphic. It also provides axes and gridlines to make it possible to read the graph.
Faceting Faceting can break up the data into smaller subsets and make decisions about how to use these smaller groupings of data.
Theme The theme refers to choices of presentation such as colour or font.
Source: Wilson, A. (2021). Driver’s of Dissidence: A Discourse Analysis of Vancouver’s Road to Ride-Hailing. Undergraduate Thesis. (p. 13).
Table 10.6 - R Functions
Term Definition
Getting Started Basic structure: ggplot(mpg, aes(x = displ, y = hwy) +
Layers develop: geom_point()
You can add colour to the last component. IE: ggplot(mpg, aes(x = disl, y = hwy, colour = class).
Faceting entails splitting the data into subsets and displaying the same graph for each subset.
It is done with the function, facet_wrap()
Geom Functions geom_smooth() fits a smoother to the data and displays the smooth and its standard error.
geom_boxplot() produces a box-and-whisker plot to summarize the distribution of a set of points.
geom_histogram() and geom_freqpoly() show the distribution of continuous variables.
geom_bar() shows the distribution of categorical variables.
geom_path() and geom_line() draw lines between the data points. A line plot is constrained to produce lines that travel from left to right, while paths can go in any direction. Lines are typically used to explore how things change over time.
Histograms and Frequency Polygons ggplot(mpg, aes(hwy)) + geom_histogram()
stat_bin() using bins = 30
or ggplot(mpg, aes(hwy)) + geom_freqpoly(binwidth= 2.5)
Bar Charts geom_bar()
Time Series with Line and Path Plots ggplot(economics, aes(date, unemploy / pop)) +
geom_line()
Source: Wickham, H. (2016). Getting started with ggplot2. ggplot2 (pp. 11-31). Springer International Publishing. https://doi.org/10.1007/978-3-319-24277-4_2 | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/10%3A_Quantitative_Data_Analysis/10.07%3A_Student_Testimonial-_Data_Visualizations_with_R.txt |
Correlation coefficients are used to measure the strength of the relationship between numeric variables. The most common correlation coefficients are Pearson’s r and spearman’s rho (rho (ρ), or rs.) which both can range from -1 to +1. If the coefficient is between 0 and 1, then as one variable increases, the other also increases (positive correlation). If the correlation coefficient is between -1 and 0, as one variable increases the other decreases (negative correlation). Note that unlike the Pearson correlation coefficient, the Spearman correlation does not require continuous-level data (interval or ratio), because it uses ranks instead of assumptions about the distributions of the two variables. This allows us to analyze the association between variables of ordinal measurement levels. A Spearman correlation analysis can therefore be used in many cases in which the assumptions of the Pearson correlation (continuous-level variables, linearity, heteroscedasticity, and normality) are not met. In your papers, correlations can be presented in two ways:
• The descriptive statistics are presented for all the variables (refer to the Table 10.4.2.6)
• A correlation matrix is produced. Typically, a correlation matrix is “square”, with the same variables shown in the rows and columns (see Table 10.6.1)
Table 10.6 - Sample Correlation Matrix
Always studies with partners Always participates in class Always completes assignments Always visits office hours
Always study with partners 1 0.87 -0.65 0.48
Always participates in class 0.87 1 0.77 0.66
Always completes assignments -0.65 0.77 1 0.89
Always visits office hours 0.48 0.66 0.89 1
Reporting Correlations
When reporting correlations, you need to record the correlation value (r), sample size (N) and significance (P) and whether the test is two-tailed or one tailed. Below is an example:
A correlation analysis was done to determine the relationship between studying with partners and participation in classes This relationship was not statistically significant (r = -.65, N =1525, p <.460 two-tailed.
Note:
• If the relationship was statistically significant (p <.05), then we would calculate r2 (.054 x .054) to determine the strength of the relationship. r2 tells us the explained variance.
• A r2 value of 0 to.3 can be interpreted as weak; 0.31 to .59 can be seen as moderate and .6 or higher is good (note that social scientists do not have consensus on this. This is just a rule of thumb)
Additional Resources
See UBC Research Commons for tutorials on how to generate and interpret correlations and regressions in SPSS https://researchcommons.library.ubc.ca/introduction-to-spss-for-statistical-analysis/
10.09: Regressions
Linear Regression
As you will see in journal articles, regression results are often reported in tables. This is due to the fact that a typical regression usually comprises many independent variables and more than one model. A typical regression table usually lists the independent variables in the rows and beta coefficients (b) with standard Errors (s.e) in parentheses in the columns. Significant coefficients are indicated with asterisks. Beta coefficients and standard errors are also organized in columns according to the model (where there are multiple models). In the text of your findings section, you should present the standardized slope (beta) along with the t-test and the corresponding significance level. Social researchers also report the percentage of variance explained (r2) along with the corresponding F test. Cronk (2012) suggests the following format for reporting regression findings:
1. A multiple linear regression was calculated to predict DV based on IV1 and IV2
2. A significant regression equation was found F(df regression, df residual) =F, p= sig, with an r2 of ___
3. Respondents predicted that DV = constant coefficient +IV1 coefficient + IV2 Coefficient
4. Interpret the meaning of the IV coefficients
5. State if the IVs are statistically significant (see the coefficient sig)
6. If the regression model contains many variables, you need to report on the overall fit of the model.
Here is an example:
A multiple linear regression was calculated to predict grades in SOCI 200 and age. A significant regression equation was found: age significantly predicted grades in SOCI 200, b = -.14, t(152) = 10.53, p < .001. Age also explained a significant proportion of variance in SOCI 200 grades, r2= .36 or 36% of variation in SOCI 200 grades.
You should also report on regression equation using the following formula
Y =intercept +b (Independent variables),
where Y is the dependent variable and b are the beta coefficients of the independent variables
E.g., Predicted Sociology 222 Grades = intercept + (−.14)*Age
Logistic Regression
Unlike linear regression where the outcome variable is continuous, with logistic regression, the outcome variable is binary. However, like linear regression, the results of logistic regressions are generally reported in tabular formats, with the independent variables in the rows and the following statistics in the column: beta coefficient (b), standard error (s.e), Wald’s X2 , degree of freedom (df), p value and odds ratio (eβ). In the text of your paper, you should comment on an overall evaluation of the logistic model; provide statistical tests of individual predictors; highlight goodness-of-fit statistics and provide an assessment of the predicted probabilities (Peng et al, 2002). You should also present the regression equation including the Y-intercept. Your write up could look like the below:
A logistic regression was performed to ascertain the effects of age, education, study status, residential status and gender on the likelihood that students pass or fail SOCI 200. The logistic regression model was statistically significant, X2 (6, N = 200) = 24.53, p = .002. The model explained 33.0% (Nagelkerke r2) of the variance SOCI 200 grades and correctly classified 73.0% of cases.
Next, discuss the odds ratio for the Independent variables and confidence interval. For example:
Students aged 20 years and younger were twice as likely to pass Sociology 222 than students aged 21 years and older (OR=2.02, 95%CI [1.7, 2.5]).
Let us assume that age, study status and gender are statistically significant and the corresponding betas are -0.0261, 0.477 and -.0361 respectively, and the y-intercept is .5340. The logistic regression equation would be written similar to a linear regression equation, i.e.,
Y =intercept +b (Independent variables)
Predicted logit of (Sociology 222 Grades) = 0.5340 + (−0.0261)*Age + (0.477)*study status +(-0.0361 gender)
For a summary of reporting logistic regression in your paper, see Peng et al (2002).
Additional Resources
Research Commons Resources for Logistic Regressions
Remember to visit UBC Research Commons for tutorials on how to generate and interpret logistic regressions and other procedures in SPSS https://researchcommons.library.ubc.ca/introduction-to-spss-for-statistical-analysis/ | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/10%3A_Quantitative_Data_Analysis/10.08%3A_Correlations.txt |
As we mentioned earlier, it is important to not just state the results of your statistical analyses. You should interpret the meanings, because this will enable you to answer your research questions. At the end of your analysis, you should be able to conclude whether your hypotheses are confirmed or rejected. To ensure you are able to draw conclusions from your analyses, we offer the following suggestions:
• Highlight key findings from the data.
• Making generalized comparisons
• Assess the right strength of the claim. Are hypotheses supported? To what extent? To what extent do generalizations hold?
• Examine the goodness of fit.
Your conclusions could be framed in statements such as:
“Most respondents …..”
“Group A (e.g., Young adults) were more likely to ___than group B (older adults)
“Given the low degree of fit, other variables/factors might explain the relationship discovered”
Box 10.10 – Statistical Analysis Checklist
Access and Organize the Dataset
• I have checked whether an Institutional Ethics Review is needed. If it is needed, I have obtained it.
• I have recorded all the ways that I manipulated the data
• I have inspected the data set and have noted the limitations (e.g., sampling, non-response, measurement, coverage) and have inspected it for reliability and validity.
• I have inspected the data to ensure that it meets the requirements and assumptions of the statistical techniques that I wish to perform
Cleaning, Coding, and Recoding
• I have re-coded variables as appropriate.
• I have cleaned and processed the data set to make sure it is ready for analysis.
Research Design
• If it is secondary data I am using, my methodology has documented their method for deriving the data.
• My methodology documented the procedures for the quantitative data analysis.
• I have highlighted my research questions and how my findings relate to them
Statistical Analysis
• I have reported on the goodness of fit measures such as r2 and chi-square for the likelihood ratio test in order to show that your model fits the data well.
• I have not interpreted coefficients for models that do not fit the data.
• I have not merely provided statistical results, I have also interpreted the results.
• You must test relationships. Univariate statistics are not enough for quantitative research. Make some inferences supported by tests of significance. Correlations, Chi-square, ANOVAs, Regressions (Linear and Logistics) etc.
• I have stored all my statistical results in a central file which I can use to write up my results.
Statistical Presentation
• My tables and figures conform to the referencing styles that I am using.
• Report both statistically significant and non-statistically significant results. Do not be tempted to ignore the non-statistically significant results. They also tell a story.
• I have avoided generalizations that my statistics cannot make.
• I have discussed all of the relevant demographics
10.11: Summary
In this chapter, we discussed the presentation of quantitative data in your theses and highlighted some of the most popular quantitative techniques used in the social sciences. We note that quantitative data analysis involves examining many variables, but we cannot overemphasize the importance of carefully selecting the variables that will enable you to best answer your research question. We also caution you to justify how you process the data (e.g., re-coding) and the techniques chosen, noting the assumptions and limitations. Remember, if your approach is different from how other researchers have done similar research, you should explain why. Finally, it is important to remember that the goal of quantitative data analysis is to answer research questions based on numerical data. Hence, you must interpret and draw conclusions from the data presented. Your analysis will not be complete unless your readers understand the practical relevance of the findings.
10.12: Additional Resources
Denis, D. J. (2018). SPSS data analysis for univariate, bivariate, and multivariate statistics. John Wiley & Sons.
• This concise and very easy-to-use primer introduces readers to a host of computational tools useful for making sense out of data, whether that data come from the social, behavioral, or natural sciences. The book places great emphasis on both data analysis and drawing conclusions from empirical observations. It also provides formulas where needed in many places, while always remaining focused on concepts rather than mathematical abstraction. Assuming only minimal, prior knowledge of statistics, SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics is an excellent “how-to” book for undergraduate and graduate students alike. This book is also a welcome resource for researchers and professionals who require a quick, go-to source for performing essential statistical analyses and data management tasks (Source: Publisher).
Abu-Bader, S. H. (2021). Using statistical methods in social science research: With a complete SPSS guide. Oxford University Press
• This book not only guides social scientists through different tests, but also provides students and researchers alike with information that will help them in their own practice. With focus on the purpose, rationale, and assumptions made by each statistical test, and a plethora of research examples that clearly display their applicability and function in real-world practice, Professor Abu-Bader creates a step-by-step description of the process needed to clearly organize, choose a test or statistical technique, analyze, interpret, and report research findings (Source: Publisher).
Stockemer, D., Stockemer, & Glaeser. (2019). Quantitative methods for the social sciences. Springer International Publishing.
• This textbook introduces students to the four pillars of survey research and quantitative analysis: (1) the importance of survey research, (2) preparing a survey, (3) conducting a survey and (4) analyzing a survey. Students are shown how to create their own questionnaire based on some theoretically derived hypotheses to achieve empirical findings for a solid dataset. Lastly, they use said data to test their hypotheses in a bivariate and multivariate realm. The book explains the theory, rationale and mathematical foundations of these tests. In addition, it provides clear instructions on how to conduct the tests in SPSS and Stata. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research or quantitative methods classes in the social sciences (Source: Publisher).
Cleff, T. (2019). Applied statistics and multivariate data analysis for business and economics: A modern approach using SPSS, Stata, and Excel. Springer.
• The textbook covers a range of topics, from data collection and scaling to the presentation and simple univariate analysis of quantitative data, while also providing advanced analytical procedures for assessing multivariate relationships. Accordingly, it addresses all topics typically covered in university courses on statistics and advanced applied data analysis. In addition, it does not limit itself to presenting applied methods, but also discusses the related use of Excel, SPSS, and Stata (Source: Publisher).
Online tutorials for running Statistical Analyses and Interpreting results | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/10%3A_Quantitative_Data_Analysis/10.10%3A_Drawing_Conclusions_From_Your_Data.txt |
Learning Objectives
By the end of this chapter, you should be able to:
• Interpret and articulate the significance of the results
• Engage the central problems in your field with your data, and articulate new insights and understandings based on your research
• Concisely summarize the limitations in your data and spot areas for future improvement
Suggested Timeline: Finish Early March
The data analysis section is one of the most important sections of your paper because it ties together all the sections of your thesis. It answers the research question(s) posed in the introduction, builds on the literature review, evaluates methodological strengths and limitations (and implications), interprets the findings, identifies further gaps in the field and makes recommendations. The road toward writing up your discussion will be paved with many difficult decisions. You will have to discard potentially interesting findings that do not relate to your research question(s), summarize vast swathes of data, and endlessly scrutinize over your closing statements. It can therefore be a deeply emotional process, one that forces you to feel the heartbreak of data that does not make it into your final write-up. You will also carefully consider the internal implications of each section.
The discussion builds on data analysis, providing you with the opportunity to step back from the intimacy and particularity of data analysis. It is in the discussion section that you return once again to the bird’s eye view of writing the literature review, this time attempting to situate the literature within the context of your data analysis. Discursively, your task will be to persuasively convince your reader of the general importance of your argument, to say that your research means something beyond itself—be it in action, policy, social programs, pedagogy, or further research.
This chapter will help you to question and determine the significance of your work, and offers checklists to ensure that your findings are situated within the larger scholarly conversation (see Box 11.1.1). It will begin by discussing general rules of the discursive task such as how are discussion sections usually written? What tense, stance, and style should I employ? Next, it will discuss interpretation (the act of determining the meaning of your results) and how it is should be framed to answer your research question. We remind you to interpret the meaning of your data with respect to the literature—there will likely be many possible directions forward, and it will be your task to choose only a coherent few. Finally, the chapter ends with guidance for presenting the limitations of your research without excessive humility or vanity.
11.02: The Contents of the Discussion
There are four key things to include in your discussion:
1. Summary and explanation of key findings
2. Engagement with the literature
3. Synthesis and application of results
4. Limitations and recommendations for future work
These can be broken into tasks (see Box 11.1.1).
Box 11.1 – Tasks of the Discussion
• Restate the research problem
• Recap the major findings
• Explain the meaning of the findings
• Highlight the relevance of your study and how it helps fill the gap
• Compare the findings with existing studies
• Acknowledge the limitations of the study and implication on the findings
• Recommend further research
Summary and Explanation of the Key Findings
There are two things that will help you to summarize your kind findings: first, revisit your research question(s) and ensure that the materials being discussed help to answer them; second, revisit your findings/results and highlight only the results that pertain to your research question(s). It is important that you are not discussing trivial data such as the demographic composition of your sample (unless it has a key bearing on the results) or reviewing central tendency data (unless you have tested an hypothesis which has a bearing on your research question). While there might be interesting insights in those data, typically, they do not answer the research question in and of themselves. The ease at which you can identify your key findings will depend on the kind of analysis that you have done. For qualitative research, you need to revisit the key themes. If you cannot itemize the key themes from your findings, now is the time to revisit your analysis, look at the codes and patterns and itemize the most important 5 to 7 themes. For quantitative data, it is important to visit your hypotheses and the statistical tests used to examine them. As Greetham (2019) argues, you need to remind yourself and your readers what the questions and sub-questions are.
After you have identified the key findings and themes that relate to your research question, it is important to not just repeat what was previously highted in your results section. You need to explain the results in a manner that tells a cohesive story. This means putting the findings into context or to “engage in productive speculation” (Hinshaw in APA, 2006). You need to highlight why these findings are important and the wider implications for knowledge, and their applications or other productive uses. For example, looking at the article from Hou, Shellenberg & Berry (2018) which discusses immigrants’ sense of belonging to Canada and their source country, we see that after discussing the findings they extrapolated a framework for categorization determination of immigrants’ belonging and they explained why this is important:
Looking at the determinants of membership in each of the four profiles, we can separate those factors that existed pre-migration from those that arose post-migration. The reason for this separation is that there are differing implications of the findings, because more can be done to improve outcomes when dealing with post-migration factors than for those that existed prior to migration (p. 1627)
Of course the example above is from professional and experienced writers, and it takes considerable skills to be able to extrapolate from findings. However, we want you to notice how they direct attention to the difference between pre and post-migration to justify the distinction. Through this, they are able to introduce the significance of their distinction, that “more can be done to improve outcomes” after migration than before. In two sentences, they are able to justify the central analysis of their paper. To do the same, it is important to ask yourselves the following questions:
• What do these findings mean? How/why are these findings useful?
• Why do these findings matter? Why should anyone care? Do they have the potential to impact structure, policy or change? Is there the potential for application?
• Are there new ways in which the findings can be categorized?
In essence, we do not want you to simply regurgitate the results. Try to answer the question: so what? And remember, limit your discussion to a few salient issues.
Engagement with Literature
This is perhaps the most important task in your discussion. The literature can be integrated in your paper in two ways: First you can relate your findings to previous works. Second, you might find that your literature review (as good as it might be in relation to your research question) does not anticipate your findings. This usually happens because your findings are either new or unexpected. While you may not need to re-do the literature review, you will definitely need to dig deeper into it. This digging will not produce a comprehensive literature review (certainly not as the original), but it will be more specific to the issues that you want to explain further. In that case, you will be introducing new sources to explain and/situate your findings. Please note that it is generally okay to introduce new literature in the discussion if the findings are surprising (just do not introduce new findings in the conclusion, which we will discuss later). Regardless of the approach taken, you must attempt to compare your findings with existing literature.
Engagement with the literature is important because it helps demonstrate why your results are significant. It establishes continuity with the scholarship and shows how your findings fit within it. It also justifies the relevance of the research by highlighting your contribution to the advancement of knowledge in the area. Going back to the discussion from Hou, Shellenberg & Berry (2018, p. 1629), we can see how this continuity/contribution is established:
…these findings in Canada provide further support to the assertion by Berry (2017) that there may be some general principles of intercultural relations in all societies that could provide the basis for developing policies intended to improve relations and outcomes for both immigrants and those already settled in a country.
In the above case, we see how Hou et al., (2018) findings built on their previous work and applied it to multicultural policy in Canada. Their findings are linked with Berry’s (2017) assertion that basic intercultural policies exist which can be appealed to in order to improve migrant-domestic relations. They, thus, are able to once again reaffirm, through their evidence, that Berry’s assertion is an attractive one. To similarly engage with the literature, we suggest that you ask these three questions about the relationship between your findings and the literature:
• Are my findings similar or different to previous studies? Why?
• Do other findings support the claims I am making?
• How might these findings be applied?
Synthesis and Application of Results
If you have not yet done so, review your discussion so far to ensure that you have connected all the previous chapters (e.g., theory, literature review, methodology, specific aspects of the research problems etc.). This will help to ensure that your story is cohesive, and will allow you to put it to practical application. Drisko (2005, p. 592) asserts this as follows:
Authors should make each major contribution of the study clear and explicit. Beyond linking the current work to the prior literature, the discussion may point out newly apparent definitional or conceptual limitations, illustrate the impact of context and population specific understandings, point out subjugated knowledge, or identify variation in processes unmentioned in the summative literature.
Drisko (2005) suggests that you not only engage with the literature, but go beyond it. This means that you not only anticipate conceptual limitations, but, where applicable, suggest new definitions and contexts for the field to consider. As we suggested in Chapter 1, the discussion should once again engage in that collective conversation that repeats: what next? It is your task as a researcher to not only engage with what has happened in the past, but to apply it to the future, to attempt to answer the question of what is next for your (sub)discipline.
In addition to stating the contributions, you should also consider lessons learnt and propose recommendations. Consider the statement by Hou et al (2018, p. 1628) who noted that the results have implications for addressing principles and policies for immigrants’ integration in Canada:
…general principles of intercultural relations in all societies that could provide the basis for developing policies intended to improve relations and outcomes for both immigrants and those already settled in a country…[include]: a culturally and economically secure place for both newcomers and members of the larger society; opportunities for mutual engagement and social interaction; and support for establishing and maintaining multiple identities and social interactions during and after the settlement process.
In building from the previous statement we showed how Hou et al (2018) applied their findings to recommending cultural and economic security, opportunities for interaction, and support for multiple identities. Hou et al (2018) concisely demonstrate how a straightforward connection to the literature can be immediately developed into recommendations for policy or future research. If you find a similar consensus in your research (agreement between your findings and other researchers), consider how this relative certainty should be acted upon. If all researchers agree on something, ask yourself: does policy already engage with this fact? And if not, attempt to answer: how could policy alter or expand its work to address this finding?
Limitations and recommendations for future studies
Regardless of how groundbreaking and innovative your research is, it will have limitations. Think about the design, methodology, and theoretical insights that might limit the generalizability of your results and highlight them. If you are unable to identify any limitations in your study, we suggest two things: first, ask your supervisor or research mentor for their honest feedback on what could have made the study even better. Second, think about what you would’ve liked to do but was not able to do in the current project. Your research is personal and is likely dear to you, so you might be unwilling to state anything that could potentially undermine it, yet you must demonstrate reflexivity and the willingness to adopt an outsider looking in posture (i.e. what might your readers criticize your study for?). The transparency that highlighting your limitations offers will enable your readers to have a better understanding of your work (Cömert & Al-Beyati, 2020). They might also enable you to answer why you got the results you presented.
Box 11.2 – Change to a Key Takeaways Box
• Do not have too many limitations. Pick out the main ones e.g., “the study used secondary data, so I had no control over the variables” or “the study is purely quantitative; however, qualitative data would have provided deeper insights from respondents”
• Try to limit your discussion of your limitation to a paragraph (maximum two, if you need to expand on a point).
• Do not point to limitations that could’ve been easily resolved e.g. do not say “More insights could have been gleaned about this relationship if a regression was done instead of a correlation.” Since it is possible for you to do it, then you should just run the regression.
• Do not discredit your findings while highlighting your limitations. E.g., instead of saying “due to the fact that the data was collected two decade ago, it has little ramifications on present situation”, you could say “despite the fact that the data in 2 decades old, it provides baseline data and insights into how presentation generations approach this problem”
• Highlight the strengths: as the above example demonstrates, show that despite the limitations, the study has merits. Do not state a limitation without reaffirming the merits of the study
• Common limitations include sample characteristics, how the participants were selected, measurement, general methodology and analytical approach (Cömert & Al-Beyati, 2020). Remember, emphasize the strengths of your work as well.
Stating the limitations offers an excellent bridge-in for your recommendations and agenda for future research. This is important because it allows you to take stock of your contribution to the scholarship and outline a vision of where you want it to go. It is also a crucial step in affirming in your own mind what your next project might be. Remember, no project answers all the questions there are about a topic. Be sure to point on where you see the field going next. Here are some pointers to help you make suggestions for future research:
• Limitations: Based on your limitations, what might future research do to improve on those and possibly expand the scholarship.
• Findings: Think about what aspects of your findings might be (a) surprising (maybe confirmatory studies are needed); embryonic (if you discovered a new idea, outline some of the potential applications or way it can develop); new questions raised by your findings (your findings might raise more questions e.g, why did you uncover the results you got); theory (what theoretical or analytical approach could elevate the field?).
• Trends in field: Your might indicate how your research could fit into an emerging trend (e.g., using big data or decolonizing methodology to understand a phenomena)
Box 11.3 – Assessing Your Discussion
Greetham (2019, p. 227) suggests that to assessessing the success of your discussion by asking the following questions: Have I addressed
• what difficulties I encountered and how they affected the work plan?
• the limitations of the research and how they might have affected the strength of the findings? Did any bias enter into the research process?
• the strengths and weaknesses of my research and the data in respect to answering the research questions and hypotheses?
• the extent to which the data supported my propositions? How strong is the evidence? Is it conclusive, nebulous or tentative?
• whether the data confirm or falsify my proposition and why?
Other considerations
Students invariably ask how long should the discussion be? There are no rules concerning the length. As a benchmark, in most journal articles of 35 pages double-space, discussions are usually 2-3 pages long. Şanlı et al (2013, p.22) offers that:
Generally the length of the ‘Discussion ‘ section should not exceed the sum of other sections (introduction, material and methods, and results), and it should be completed within 6-7 paragraphs [of no] more than 200 words each.
Instead of worrying about the length, we suggest that you examine the checklist in Box 10.2 and ensure that you have covered everything. We also suggest that you get feedback from your mentor or supervisor before submitting the final version. Like most other things in the social sciences, there are no definitive rules to follow. This means that the length of your discussion section will be contextual and will be determined by the nature of your findings, the amount of explanation required (which will depend on the extent to which your findings contradict the literature or are surprising).
Another question that students sometimes have is: how much literature do I need to include in the discussion? Again, there are no definitive answers here. The issue is not the quantity but the quality of your arguments. You need to identify the main findings and examine them in light of the applicable literature. You need to identify which support, which contradict and what might help you to understand why you got the results you present. It is only those sources that you need to cite. Remember, you do not need to go in depth into the sources that you quote (unless they explain your results). Instead, be concise and do not lose your voice when incorporating the literature. | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/11%3A_Writing_the_Discussion_and_Conclusion/11.01%3A_Introduction-_Data_Analyzed_What_Now.txt |
After writing your discussion, it should be pretty easy to write your conclusion. Your conclusion is intended to leave a strong impression to your reasers (Caulfield, 2020), and generally comprises three things: (1) reaffirmation of you research question(s) or thesis statement; (2) a summary of the results/how the argument developed; and (3) suggestions for key take-aways from the article (Caulfiels, 2020). For empirical papers, one needs to restate both the research problem and research questions. This means reminding readers why the problem was important, the questions asked and the answers abstained. This needs not take up more than a paragraph. Remember, the key findings are what informed your discussion, and the research problem and questions should be retrievable from the introduction. For papers without a research question (such as theoretical and argumentative theses), Caulfield (2020) suggests you revert to the problem and thesis statement presented in the introduction, restate them and demonstrate how they were developed throughout the rest of the thesis.
The way you write the suggested takeaways will also depend on whether your paper is empirical or argumentative. According to Caulfield (2020), non-empirical papers (theoretical and argumentative theses) can close with a call to action, i.e., a list of practical suggestions that the concerned groups, organizations or people can take to remedy the situation. More theoretically-driven thesis can end with a reaffirmation of the significance of the arguments raised. However, empirical arguments might subtly highlight practical actions that might be needed to summarize the kinds of future research that are needed. See Box 11.4.1 for a checklist for writing your conclusion.
Box 11.5 – McCombe’s Checklist for Writing a Conclusion
McCombe’s (2019) checklist for writing a conclusion. I have….
• Clearly and concisely answered the main research question.
• Summarized my overall argument or key takeaways.
• Mentioned any important limitations of the research.
• Offered relevant recommendations.
• Explained what my research has contributed to knowledge.
• Not introduced any new data or arguments.
Source: McCombe (2019, Mar. 26). How to write a thesis conclusion: checklist and Examples. Scribbr. https://www.scribbr.com/dissertation/write-conclusion/
11.04: Summary
The discussion and conclusion summarize what your research has achieved. The discussion begins with a paragraph that reduces the complexity of your findings to a single sentence on each major component. It then takes the momentum of those findings and bashes them up against other key findings in the field. This collision attempts to alter and amend rigid and soft discoveries in the field, also inquiring: how does my research challenge or support what others have been saying? Does it pick sides, or join them together? After engaging in this academic conflict, the discussion then waves its peace sign, seeking resolution between competing arguments in the field. This synthesis seeks to overcome doubts about the findings and apply your research outside of research. It asks the vital question once our doubts have been clarified through evidence or argument: how can these new assertions be put into practice? Finally, the limitations of your research are disclosed with attention to how future researchers and practitioners can overcome those limitations.
The conclusion again reiterates the significance of your findings with a renewed boldness. With the limitations discussed, it is time to offer your final word on the project. Align this proclamation with key conflicts and origins of your work. Your ‘take-aways’ will immediately appear grounded and memorable to your reader. Think hard about what the purpose of your article was, why it began and what it discovered, and affirm its significance.
11.06: Additional Resources
Cals, J. W., & Kotz, D. (2013). Effective writing and publishing scientific papers, part VI: discussion. Journal of clinical epidemiology, 66(10), 1064.
UBC Centre for Writing and Scholarly Communication (2022). Guides to Writing and Research. https://writing.library.ubc.ca/writing-resources/guides-to-writing-and-research/ | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/11%3A_Writing_the_Discussion_and_Conclusion/11.03%3A_Writing_Your_Conclusions.txt |
Learning Objectives
By the end of this chapter, you should be able to:
• Understand the importance of the dissemination process
• Understand the rudiments of oral and poster presentations
• Anticipate hard questions in question period
Suggested Timeline: Look for conferences once your findings are nearly done
So you have finished your thesis. Accept our warmest congratulations! You have spent a year fixating on your contribution, contorting your thoughts around the significance of your findings. It is only right that you share your work with others. If you are enrolled in a formal research-based program such as Honours, maybe an undergraduate conference is a requirement of your program, or maybe you are required to share your work with your cohort (class presentation) or to your department.
Some of you might be relishing the opportunity to showcase your brilliance or to get feedback on your work. We applaud you. For others, the thought of sharing your work with others is outright frightening. We are here to assure you that it is doable with carefully planning, practice and mindfulness (see Chapter 4).
The truth is there is nothing that we can say to change your initial feeling about presenting your work. However, we hope to offer strategies to help you to approach presenting your work (orally or via posters) in a systematic and effective way that takes some of the pressure off you. We begin with a discussion of the application process to conferences, before providing tips for structuring your presentation. In particular, we share ideas on how you can shrink all your research into a concise 10 minute oral presentation. Next, we offer guidelines for poster design and presentations before finishing off with tips on how to deal with the question period. We encourage you not to be daunted by the task of sharing your work. For what it is worth, remember that “conferring” your findings with others will integrate you in a community of like-minded scholars and provide validation for your research.
12.02: Types of Conference Presentations
Conference presentations take many forms. Before submitting an abstract to a conference, be sure to consider what kind of presentation you want to make. Below, we discuss some common presentation types:
• Traditional Paper/Oral Presentation: This is the standard oral presentation (usually 15 minutes plus additional time at the end for questions) where one or more speakers (joint-presenters) share research results, completed works, innovative concepts, theoretical application, methodologies or tools.
• Student Presentation: These are similar to the traditional paper/oral presentations described above, but with an emphasis on students work. By providing a separate avenue for students to share their work or labelling the presentation as “students”, the pressure can be lessened. Sometimes, students have separate sessions, but other times, they are grouped with other paper presentations. If this is the case, the presentation is usually identified as student presentations in the program.
• Poster Presentation: This is a less formal opportunity to share your work in a visual format. We discuss this in greater depth later in the chapter.
• Panel Presentation: This is where multiple speakers present their perspective on a common issue usually for 60 to 90 minutes. While many students prefer to present posters or shorter oral presentations, if a group of students have a common research interest or concern, they can apply to a conference to present on a panel. The speakers are responsible for coordinating the panel and assigning roles (such as moderator). Each speaker on a panel is usally given at least one individual question as well as an introductory and closing remark.
• Roundtables: are similar to panel in the sense that a group of discussants seated around a table comment on a theme. Roundtable presenters bring targeted questions to pose to participants at the table in order to learn from and with those attending. It is quite unlikely that you will present your work on a roundtable, but you can check out conference websites if you wish to learn more (see Box for a list of potential conference).
• Lightning Round-Tables: These are opportunities to network by briefly summarizing your work to a small audience (usually in 15 minutes or less) followed by an interactive discussion. Discussants will then move to another table and repeat the procedude. This provides the opportunity to get more intimate connections for other participants and attendees.
In addition to the above presentations, at conference, you will likely see expert lectures, keynote addresses and debates. These are presented by established academics in the field so we will not discuss them. However, it is a great idea to go to these presentations at conferences. For the rest of the chapter, we will focus on oral presentations and posters because these are what you will most likely present at conferences. If you wish to submit an abstract for other presentation types, be sure to discuss it with your advisor, supervisor or mentor.
12.03: Applying to Conferences
If conferences are not built into your program, keep your eyes and ears in December-January for conferences “Call for Abstracts.” A Call for Abstracts is a description of the themes at a conference and an invitation for your to indicate your interest in participating by submitting an abstract. As we discussed in Chapter 2, researchers often write abstracts when they complete their research, because it is only then that they have a clear idea what your findings and contributions are. This might mean delaying dissemination of your research until after your thesis is submitted. However, if a conference or presentation is part of your program, you will still need to draft an abstract before you finish analyzing your results. The timeline in this manual assumes that for an 8 months program, you’d be doing data analysis in January. That means that you should have some preliminary findings or a general sense of how the results are trending by that time. It is okay to submit an abstact based on a preliminary or partial analysis of your data. Hence, if you have analyzed data concerning one hypothesis or research question, you can share that at a conference. Be sure to inform your audience that analysis is ongoing. Alternatively, you could share your methodology or a general research idea. Do not feel shy about sharing partial aspects of your work. Afterall, conference presentations are usually no more than 15 minutes, which means, you could only share a limited portion of your work, even if analysis was complete.
Once you have finished or near finished collecting data, keep the topic in mind while you search the internet for potential conferences to apply to. Almost all the conferences you apply to will expect a short brief about yourself, potentially a CV, and an abstract summarizing your research to a lay audience in 250 words (see Chapter 2 for writing abstracts). So to prepare for application to conferences, create a short brief about your research interests, look up other CV’s of professors in your field, and create your research abstract. In addition have a look at previously successful abstracts and try to emulate the style.
Box 12.1 – Some Academic Conferences to Consider
1. Canadian Sociological Association CSA@Congress – CSA Conference Website (csa-scs.ca)
2. McGill Undergraduate Research Conference Undergraduate Research Conference | Faculty of Science – McGill University
3. UT Undergraduate Research Conference Student Research | Department of Sociology (utoronto.ca)
4. UBC Sociology Undergraduate Research Conference Annual Sociology Undergraduate Research Conference Archives – Department of Sociology (ubc.ca)
5. UBC Multidisciplinary Undergraduate Research Conference (MURC) Multidisciplinary Undergraduate Research (MURC) Conference | Student Services (ubc.ca)
6. International Conference on Education and Social Science ISER » ISER International Conference 2019-2020
7. International Conference on Economics and Social Science TheIRES » TheIRES International Conference 2019-20 | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/12%3A_Presenting_Your_Research/12.01%3A_Introduction-_Speech.txt |
A well-organized oral presentation typically has the following elements: a background, research question, outline of research and the talk (methods), findings/discussion, and conclusion. Below, we elaborate on 12 tips to help you successfully showcase these elements and excute a noteworthy presentation.
Planning
Planning is fundamental to you delivering a successful oral presentation. Almost every conference you attend will have a set of guidelines for you to adhere to (e.g., the time limit). Begin by familiarizing yourself with those guidelines. Remember that you will not be able your entire thesis or all the interesting findings on one 18×24 poster or in a 15 minutes presentation. You will need to zoom in on a specific issue or research question from within your thesis. We reiterate: do not attempt to present your entire thesis.
Box 12.3.1.1 shows an example of how one might plan a 15 minutes oral presentation. When planning, highlight the significant portions of each section: the introduction, literature review, methods, findings, discussion, and conclusion. Give rough outlines of how much time each section will take, and test this outline to ensure you will not be going over (example of fifteen-minute speech plan in Box 12.3.1.1). It is best to try to get your practice done at least one minute less than the designated time (e.g., aim to finish a 15 minutes presentation in 14 minutes). On the day, nerves, technical issues and other factors can make you go for longer than you practices. In general, program chairs keep very strict timing and give you frequent time updates during your presentation. Planning with built-in flexibility can help calm your nerves before and during your presentation.
Box 12.2 – Example Outline of Oral Presentation
Section Time (15 minutes total)
Introduction (Hook, engaging example etc.) 2 minute
Research Question & Outline of the talk 2 minute
Literature Review (optional) 3 minutes
Methods 1 minute
Findings 4 minutes
Discussion/Conclusion 3 minutes
The Introduction
Because oral presentations at conferences are so short, you must aim to quickly entice your audience. Common ways to do this include starting with a historical anecdote or story related to your topic, unpacking a key quote from your qualitative study, introducing a paradox in your field, asking a provoking question to your audience, and inquiring what a seemingly straightforward concept in your field really means in practice.
Research Question(s) & Order
Once you have introduced your topic, immediately state your research question(s) and use that momentum to guide your listeners through the methods and findings. If outlined on a slide, put it on the same slide or on the next. After this, aim to implicate it in the context of your presentation. Answer how your presentation will be structured and tell your audience how this structure will address your research question.
Literature Review (optional)
This is a section that you can skip in a presentation, but if you do decide to keep it, make it sparse. We suggest picking one or two key authors that inspired your study or to separate the key concepts in the literature that have inspired your study. As with all types of research, outline the literature with close attention to the gap you are going to fulfill.
Methods (necessary, but shortened)
Give the short version of your methods. You are allowed, in an oral presentation, to just be as simple as saying a “grounded theory approach”. Suggest to your audience that they can ask you further about your methods in the question period. This is a place where you should also consider talking about the limitations of your research. However, saving it for after the conclusion to make clear to your audience that the implications of your study can be strengthened in future research, is another useful strategy.
Findings (the heart, but keep it concise and forceful)
Consider shortening your findings to just two or three themes. Especially in qualitative research, going down every rabbit hole with regard to your findings will distract from the core point of your presentation: your contribution. Highlight only those findings which you think are (1) unique, (2) useful to others, (3) best answer your research question, and (4) capable of being conveyed in your very limited timeframe. For instance, Wilson’s (2021) research on Uber had five themes which he shortened to three for his fifteen minutes conference presentation. As he explained, “I chose the three themes that addressed the legislative impact of Uber’s framing in order to best address one of my RQ’s: “did Uber’s framing in the media affect the final legislative decisions?”
Discussion
The discussion is a section that can be easily truncated into your conclusion or at the end of the findings section. It is essential, however, that you implicate the meaning of your findings for the field. What was the gap you fulfilled? How do your findings corroborate with past research on your subject? Whenever covering any of your findings, consider how they affect the field of your audience: what does your work say about their work? Likewise, in disseminating your research for the community, this final part is essential: how does your findings affect their day to day lives? Will it affect a policy that governs their behaviour etc?
Conclusion, Limitations, and Implications
The conclusion is where you outline what you have said, what is missing from your study and what can be done in the future. Clearly summarize the key findings of your talk before talking about what is missing. Once you have summarized the findings, be humble! Talk about the limitations of your research and briefly discuss how they could be addressed in future studies. Once the ground is laid, now you are ready to resoundingly end your presentation: summarize the major themes of your research into implications – the contribution of your work. Why should everyone remember the work you do? It is entirely based upon your ability to convince them that the research is worth remembering into the future: in future work, research, and reflection. Implications often take two forms: for future research and for action outside of research. When speaking to academics, the first is more important. When discussing with the broader community, the latter will likely be higher valued.
Designing Your Slides
The most important thing to remember about designing your slides is to keep them clean, clear and engaging. Do not include too many text on one page and ensure that the colours used are accessible. You might also consider using concept maps (Google slides has lots of pyramid animations). Whatever you do, keep slides sparse, do not pick Roman fonts, be consistent and bold quotes. For additional tips, see Campbell (n.d.) suggestions at https://www.exordo.com/blog/presenting-at-a-conference/
Trimming the Excess
It is unlikely that you will get the timing right on your first practice run. It is okay to allow yourself to go over (or under) to begin but ensure you can make the necessary adjustments to each section of your presentation. If you are still extremely over the time limit (and you should aim to go a little under, so you can take it slow for your presentation), then you should cut full sections. Consider removing your literature review, compressing your discussion into your findings or conclusion, and/or taking off one of your findings sections. If you are still over the limit, consider shortening your research question or focusing on fewer research questions. If your presentation is too short, consider expanding on your findings and the discussions.
Tips From Soothsayers
For more elocutionary or body language tips, there are many business school videos on these topics (Abrahams, 2018).
Fear of Public Speaking/Cooling Off Before You Speak
Composure and confidence will make your presentation go over smoother. Speaking with confidence – in a clear, steady voice – is essential to winning the confidence of your audience. However, sometimes you are just overrun by nerves. If that is the case, you are not alone. Fear of public speaking is a extremely common, but there are things that you can do to help calm those nerves. See (Sawchunk, 2022) for a list of suggestion at the following link https://www.mayoclinic.org/diseases-conditions/specific-phobias/expert-answers/fear-of-public-speaking/faq-20058416
Box 12.3 – Student Testimony – Negotiating with Your Nerves
A quick online search for “presentation tips” will yield an overwhelming number of suggestions, but everyone’s nervousness may come from different places. Before you dive into looking for advice, ask yourself why you are nervous. Worried about presentation content? Create a list of major points you want to get across. Worried about going overtime? Cut down on unnecessary content and time each slide. Worried that you’ll feel intimidated by the audience? Plant a friend in the audience and look at them. Regardless, it’s important to give yourself enough time to prepare and practice for the presentation.
Here is four pieces of advice that helps me get through every presentation:
1. Remember that you know something that the audience doesn’t. (No audience is all-knowing. Presenting your ideas and teaching others should be an empowering experience.)
2. Mention some things you find interesting and are passionate about related to the content. (This could be a surprising finding in your research, or an interesting encounter during data collection.)
3. Prepare a script, rely on bullet points sentences, and avoid long paragraphs. (Bullet points help you stay on track with all the information you want to cover and give you room to improvise if needed.)
4. Create a presentation ritual. (Find something that calms you down or makes you feel confident. This can be wearing a shirt you feel confident in or drinking some warm tea before you practice and present.)
Our nervousness often comes from a prediction of how we think the audience is going to perceive us, and our brains are great at coming up with reasons why we might not deliver a satisfactory presentation. Don’t be fooled – these thoughts are often inaccurate. Learn to doubt your doubts!
Youcheng (Mark) Ding, UBC Sociology Honours Student, 2019-2020 | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/12%3A_Presenting_Your_Research/12.04%3A_Oral_Presentations.txt |
All of the rules for oral presentations apply to some degree to poster presentations, but with some important qualifications. As most poster presentations do not have the same oral component (online conferences excepted), the structure of your talk is not constrained by what you can say in ten minutes. It is constrained by what you can put in a 18×24 poster. Most people will not spend more than ten minutes on your poster, and if they do, their eyes will have to be flagged by vital information early. It is therefore important that your poster is able to quickly convey the bigger picture of your argument, quickly shouting why your audience should care about it before going into the other relevant details. The following tips are aimed at that purpose.
The General Rule about Font and Spacing
Posters typically use a 16 pt font and it is an unspoken rule that 60% of your poster should be empty space and the rest image and text. We suggest picking two fonts: 18 pt for bolded statements and titles, and 16 pt for regular text. Also, academic conferences will often state their own rules for the poster presentation. Write down these rules and organize everything else accordingly.
Titles are your Vitals
The titles will give to your reader a sense of the direction of your entire paper. It is therefore important that they are exceptionally clear and purposeful. While it is okay to say “introduction, RQ, Methods,” we suggest that you be even more to the point: “North Van’s Taxi Crisis, Discourse Analysis, Results: Ahistorical Representation etc.” Make use of subtitles (even with a slightly different coloured font which thematically fits your colour schema) to etch the entire purpose of your poster and grab the reader’s attention.
Put That RQ in Bold
Try to put your research question in a separate, bolded, enlarged section so your reader will be able to immediately decide if your poster is related to their interest.
Concept Maps & Diagrams
Even if you do not use the concept map, it is good to draw out your poster or oral presentation on a concept map before constructing your final script. This way you can easily narrow down the structure of your presentation. And just as it makes things easier for you to conceptualize, so will it make things easier for your audience, so consider adding them as an outline of your paper or to explain a complicated relationship in your findings. Powerpoint and Google slides both have solid tools for designing diagrams and concept maps.
Avoid Big Text Blurbs
Do not use wordy paragraphs on your poster. A poster must aim to balance telling with showing. Make use of diagrams, select key quotations, and one sentence summaries of your key findings. In quantitative research, this task will be much easier, since the poster can be simply structured to highlight graphs of the key findings.
Data Visualizations
Data visualization is important on posters, especially for quantitative research. Please check out Chapter 9 for how you can make data visualizations on R, a free open-source coding platform for the social sciences.
Aesthetic Considerations
Aesthetic concerns apply, but balanced alongside clarity. You want to grab your audience’s attention, but then justify that attention by elucidating an important point in their field. Use consistent and complementary colour schemes. Try primary colours, but nothing too gaudy like neon. Look up a colour wheel and research a scheme that will work for you. Consider downloading and using the templates of posters like the one’s UBC posts every year. Do not use different fonts etc.
Engaging Your Audience
At academic conferences, it is not necessary that you talk to everyone that looks at your poster. You are more than welcome to play the sheepish store clerk who smiles and waits patiently to see if the customers in their store will buy their goods. An alternative to this, however, is to attempt to engage passersby in your work. For instance, ask them politely if they want an overview of the work or if they also have done research in the same field. Direct them to the research question and to the key findings of your research. Let them know if you think your research will have implications for their field. By touching on these questions near the heart of their disciplines, you can show to them your value as a contributor. | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/12%3A_Presenting_Your_Research/12.05%3A_Poster_Presentations.txt |
After considering all the rules heretofore listed, there is one which will determine the value of the rest: know your subject! The more confident you are on the research matter, the more flexible you will be if a surprising turn occurs in your presentation. The kind of surprising turns which are deliberately given their chance is the question section.
Question section will often be up to twenty minutes of fielded questions from the audience per panel (sometimes five minutes per presenter). In most cases, the questioner will be friendly and wish to flatter your work; it is highly unlikely there will be an all out attack on your work. Common questions will be directed to “expand on” your methods, that finding, or discussion; so try to anticipate the most obvious gaps in your findings, discussion and methods. Likewise accept the question generously, as if it is exactly the question you wanted, thanking them for the time to give it, and ensure you have answered it fully by ending with another question: “have I answered your question fully?”
Often times, the person asking the question is more experienced than you in the field. If you get a contention, be open to their feedback and then be clear about why you may or may not have found the similar result. Extensive argument will not help you look good in the conference, so offer your contact information in case you want to talk more and move on. Remember, if you see a debate is going nowhere, it is better to say “I’d love to discuss that with you some more after this presentation” and move on to other questions. Likewise, if you are unable to answer a question, be honest. Say something like “I haven’t thought about that yet” or “I don’t have the answer now, but would be happy to share it with you later.” At the end of the presentation, ask for the questioner’s contact details, and do contact them.
Ultimately, the question period will show your audience how truly confident you are on your topic, so try and frame your answers around the knowledge you are most comfortable with. If two sections of your paper adequately address the questioner’s concern, pick the one you are most confident with and try to add more insight to that issue then the question even asks for.
12.07: Summary
The presentation is really a representation of your thesis. It is not your work in its entirety, but rather an enlarged picture of a significant aspect. With this in mind, whether an oral or poster presentation, the narrative will function the same as your research. You will introduce your field, engage with something missing in that field, articulate a research question that addresses that gap, and then discuss how your research has answered the challenge. To ensure this is concise, we suggested that you narrow your research question and select only a few finding sections which address it. This way your presentation will have a constrained but engaging narrative, able to grab at the concerns of your audience immediately with little fluff. The last core point we sought to impress was your nerves. A presentation is all about confidence, so trust that the work and planning you have done translates to a deserved pride you feel when sharing it with others. If you naturally fear public speaking, see the resources listed in the chapter for help.
In closing, we would like to reiterate our pride for your successful completion of the prior stages of research. It takes courage to share your work with others, to hope that it is worthy of being accepted while simultaneously recognizing its limitations. This effort, however, is what makes our work alive: capable of beginning new discussions, interacting with old ones, and translating them to the perceptions of listeners who can then share it with others, either in action, speech, or further research. | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/12%3A_Presenting_Your_Research/12.06%3A_Question_Period.txt |
Learning Objectives
By the end of this chapter, you should be able to:
• Find journals related to your research
• Edit your paper for the requirements of that publication
• Understand how the peer-review process works
• Practice self-care and understanding how to handle decisions from journals
Suggested Timeline: The summer after your research
After spending months of agonizing work, laboring over the various components of your project, it seems fitting that it should be published so that others can view it long after you complete it. But while there is a growing expectation that the end goal of research is publication, this does not have to be your goal. It is completely acceptable if you do not wish to publish. In writing your dissertation, it is better to work toward producing the best possible thesis than to be concerned about publication. After your paper has been graded, then you can decide on whether you want to try to get it published. If you do decide to publish, we encourage you to consider all possibilities: research and evaluation reports, editorials, blogs or the peer review. Each route comes with different challenges and you will need to tailor your writing accordingly.
Given the diverse requirement of each of the publication option, we will focus on the peer review process in this chapter (additional resources for publishing through other avenues are provided at the end of the chapter). Peer review requires the intense and grueling process of demonstrating your unique contribution to experts (reviewers) in the field. The good news is that there is a growing body of undergraduate publications and thousands are downloaded each year (Stenberg, 2016). The bad news is that it is extremely difficult to get undergraduate work published in peer-reviewed journals, except in undergraduate journals. Studies published in peer-reviewed journals and books must first meet (extremely high) the standard set for the specific publication. If the paper does not meet the specific format stipulated or if the editor does not believe the paper will make a significant contribution to the field, you will likely get a “desk reject” –i.e., the editor rejects the paper without sending it out to experts for feedback. Studies that you read in peer-reviewed journals and books have been evaluated by experts in the field (peer-reviewers) and have benefited from feedback (and often substantive changes). There is no sugar-coating it, peer review publication is extremely difficult. One of the world’s largest academic publishers, Elsiever (2018), notes that the risk of rejection to one of its journals is really high. It estimates that, depending on the journal, up to 60 per cent of articles get desk rejects, and of the remainder that goes to peer review, only about 50 per cent gets accepted for publication after making major or minor revisions (Elsiever, 2018). Peer review is not for the faint of heart. You will need to be prepared for the possibility of rejection every time your work goes through the process. The best chance of getting your work published in a peer-reviewed journal is through an undergraduate research journal. While this is scary, our ultimate goal is to prepare so that you understand the process and are able to make the best decision on what to do with your research. This chapter is divided into three sections: (1) Selecting publication venues and understanding the peer review process; (2) preparing your manuscripts for submission; and (3) Responding to peer-review and revisiting good academic writing principles. | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/13%3A_Publishing_Your_Research/13.01%3A_Introduction-_Contemplating_Publication.txt |
The peer review process refers to the procedure through which a manuscript is assessed by editors and peers (a panel of experts such as university professors, authors and practitioners in the field) to determine its suitability for publication. While acceptance criteria for manuscripts might vary across different publications, typically, peers evaluate submissions based on criteria of originality, methodological rigour, writing quality and the importance of the contribution (Carr et al, 2018, p. 606).
Box 13.1 – Peer Review Terminologies
1. Peer review: the process where manuscripts are assessed by experts for quality, contributions, originality and scientific rigor.
2. Double-blind peer review: This is when neither the reviewers nor the authors know each other. The editor acts as a conduit through which the author submits the manuscript and the reviewers submit feedback. Steps are usually taken to anonymize documents. Most academic journals use a double blind review process.
3. Single-blind peer review: This is when the reviewers know who authored the paper but the author does not know who the reviewers are. This is often the case for book submissions.
4. Non-blind peer review: This is when both the reviewers and the author know each other. For example, calls for chapters in an edited book usually disclose the name of the book editor(s) so the author knows who is reviewing their work. Neither the submission nor the feedback are anonymous.
5. Desk reject: This is when a manuscript is rejected by the editor without it being sent out for peer review.
6. Revise and resubmit: This is when the editor provides the author with the opportunity to revise the original manuscript to take into account feedback received from peers. A revise and resubmit does not guarantee acceptance. Often, it is sent to reviewers again for another round of peer-review.
7. Acceptance: When the editor accepts the author for publication (usually subjected to copyediting) and/or minor revisions.
8. Copyediting: This is the process of revising the manuscript to improve its quality, correct grammatical and factual errors and improve its general readability.
9. Proof-reading: The author is given a final opportunity to read the copy-edited paper and make changes before publication. This is intended to catch any errors made in the editing process.
10. Predatory journal: a journal deemed to have compromised the peer-review process and is not recommended for publishing your manuscript with.
11. Open Access publication: A publication that has an open license for copyright resulting in the reduction or removal of barriers to access (i.e., there is no fee or requirement to have an institutional account to access it)
12. APC (Article Processing charge): also called ‘publication fees’. This is a fee sometimes charged to authors on acceptance of their articles of publication.
Is my work publishable in a peer-reviewed journal or book?
Before preparing your manuscript or searching for a source to publish, you need to determine whether your project is publishable. There are many factors that can affect whether the project is publishable. Two factors that can affect whether your paper will be favorably received are: novelty and methodology. By novelty, we mean, is the paper advancing new knowledge? Is it making an original contribution to the field through either empirical findings or theoretical and methodological advances? Many undergraduate projects are assessed on your ability to to utilize existing methods and theories, analyze and interpret findings and drawing conclusions. There is often little requirement to make an original contribution to the field. Hence, a great honours thesis might not be publishable in a traditional academic journal (unless it offer new insights into an existing problem). For example, let us assume that you are researching international students’ friendship making ability in host countries. You might have surveyed 50 students on your campus and analyzed their results in a sophisticated way. But, if this is merely replicating the hundreds of studies already published on this topic, peer-reviewed journals will likely have little appetite for your work. Hence, it is important to think about the advice offered in Chapters 1 & 2 about finding your niche and ensuring that you are making a contribution. While it is okay to replicate existing studies, you must be able to demonstrate that the replication is adding to existing knowledge, i.e., you must be adding new insights. This could mean comparing different social contexts (e.g., is there something unique about your study population or the environment? Are you making use of a theory in a new way? Are you utilizing methods that have not been used before? Have you made discoveries that were not known?). Your research needs to be filling a gap, otherwise, you are unlikely to impress editors and peer-reviewers.
Second, having a novel research does not automatically mean that your project is publishable. Your research needs to be supported by suitable evidence. Hence, how you collect the data, the size of the sample and methodological concerns are important. For example, going back to the study of international friendship formation. Let us assume that you are investigating intergenerational effects (i.e., parents’ own international students experiences) and no such work exists. Certainly, this is exciting, and editors and peer reviewers might be excited about this work. However, if you interviewed only 5 of your friends, while this might be acceptable for your undergraduate thesis, editors and peer-reviewers would be less impressed by the small sample size. Your work might be dismissed for not being rigorous enough and for lacking sufficient data to produce robust findings. Likewise, if you utilize census data on a relatively small group e.g., St. Vincent international students studying in Fort McMurray (say n=50), even if your findings are impressive, the small sample size will not allow you to perform rigorous statistical analysis e.g. regressions. Hence, methodology must support the novelty of your research. Answering these questions can prevent you from wasting time preparing an article for a peer review journal.
Please note that peer-review is not the only option for publishing your findings. You might also consider writing a research report for a community organization of concern, writing a letter to the editor of a paper (or Op Ed), blogging your findings etc. Certainly, there are other questions that you must answer before you decide to pursue the peer-reviewed publication route (we discuss some of these later in the chapter); however, we offer these two as foundational questions to help guide your decision making. | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/13%3A_Publishing_Your_Research/13.02%3A_Understanding_Peer-Review.txt |
So, you believe that your research is original, novel and is supported methodologically –and hence is worth the peer-review route. This is great. The next step is to consider which peer-reviewed source to submit your paper. Here, we discuss three options: undergraduate journals, contributors to an edited book, or mainstream journals.
Undergraduate Students’ Journal
There are hundreds of undergraduate journals which are peer-reviewed (usually reviewed by faculty and other experts in the field). These might be great places for you to gain publication experience, particularly for papers with small samples. These journals typically follow the standard peer review process and produce high quality products but are strictly devoted to undergraduate work. In addition to gaining experience of the peer review process and having a publication line on your CV (if your paper is accepted), your chances of getting accepted is likely higher than in standard mainstream journals. This is because you are competing against your undergraduate peers rather than your professors. Another advantage is that unlike standard peer-review journals that emphasize methodology, ground-breaking findings and significant contributions to the field, undergraduate journals are more likely to emphasize analysis, interpretation, logic, drawing conclusions, coherence etc. Furthermore, they might be more likely to accept strong review essays. You need to check the submission criteria of the journal you are considering. There is a growing number of journals that are dedicated to undergraduate publications (see Sacredheart University, 2020).
Edited Volume
Another avenue for publishing your work is in edited volumes. Book publishers often issue calls for chapters in edited books outlining specific criteria for acceptance. Often, these are often non-blind peer review or single-blind reviews but they can be double-blind reviews as well. For book chapters that are double-blind reviewed, there is little difference in the review process compared to a double-blind journal. However, for single-blind or non-blind reviews, the editor might ask for you to submit a bio outlining your previous work. Because the process is usually competitive, more established academics might be favoured for these submissions. Although acceptance rate can be very low, it is worth exploring “Calls for book chapters” to determine if your work fits the criteria and better understand the process. You can go to any of the major academic publishers and search for “call for chapters” or search generally on the internet (see Box 13.3.1). Bear in mind that it is highly unlikely that your undergraduate work would get accepted in an edited volume. We can only advise you to give it your best shot, get feedback and manage your expectations (we discuss strategies for dealing with rejection below). Please note that everyone has experienced a rejection at one point in their publication career –even the most brilliant professor whom you esteem).
Peer-reviewed Journals
Most academic journals are double-blind peer reviewed. This is important for upholding the integrity of the review process. As mentioned earlier, publishing in a mainstream journal is an extremely difficult undertaking (see Elseiver, 2018). Before we discuss strategies that can improve your chances of success, it is important to understand how to choose which journal to submit your paper to. Here are some strategies:
• Ask your supervisor or mentor: The trusted advice from an experienced person can be invaluable. They might be able to provide tips on different journal’s appetite for certain work, what journals to avoid and offer advice on whether your work is publishable.
• Check the reference list of your work: Checking where the articles that you cite are published can give you a good sense of what research is accepted where. Be mindful that many of the articles you cite might be in highly prestigious journals which might be more difficult to publish in –even for the most experienced academic. It is always good advice to talk with your supervisor or mentor about your choice. Again, they might be able to give you advice, which could help prevent heartbreaks and disappointment.
• Scope out the major journal publishers and search their journal lists. Among the major publishers are Elsevier, Springer-Verlag, John Wiley & Sons, Taylor and Francis, Sage Publications, Open Journal Systems/Public Knowledge Projects. You can visit any of these cites and browse a full list of their journals.
Box 13.2 – Some of the Major Academic Book Publishers
1. Springer/Palgrave Macmillan: Generally known for their works in the social sciences and humanities
2. Princeton University Press
3. Routledge is also known for publishing work in Humanities and Social Science, publishing about 2,000 new books annually
4. Cambridge University Press
5. Oxford University Press
For a more complete list of social sciences publishers, see Publishers Global (2021) Social Sciences Publishers’ Directory. https://www.publishersglobal.com/directory/subject/social-sciences-publishers | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/13%3A_Publishing_Your_Research/13.03%3A_Where_to_Submit.txt |
At this stage, you might decide to try to publish in an undergraduate journal, a major academic journal or respond to a call in an edited volume. This is an important decision; however, you now need to tailor your manuscript to fit the guidelines of the journal or edited volume. For journals, it is important to carefully read the Aims and Scope. This will tell you what topics and concerns the journal is interested in. It will also provide information such as whether the journal is peer-reviewed, frequency of publications, types of readers (academic versus practice), speed of publication, and types of articles that are considered (e.g. original research, review essays, reflection pieces, book reviews etc.). You should also search the website to try to find out acceptance rates. Many journals indicate the chances of acceptance. Journals also provide guidelines (style, word count, referencing style, presentation of tables and figures etc.) on how to organize your paper. You must follow the guidelines precisely. Editors are likely to give desk rejects for papers that do not follow guidelines. For book chapter calls, be sure to read the call very carefully. Note the overall goals of the book and tailor your paper accordingly. Like journals, calls also have important information on how to format the paper. It is also very important that you follow the guidelines exactly.
Improving your chances of getting published
We cannot overemphasize the importance of doing your research about the publication source before submitting your paper. In addition to reading information about the journal or call, it is important to know that in general, the kind of articles that get accepted demonstrate relevance to the journal’s aims and scope, have important findings and make significant contribution to the field (see ch. 1 &2), has strong analysis, interpretation and well-supported discussions and conclusions, and is well-written. We discuss these next:
• Alignment with aims and scope: You must read the aims and scope of the publication carefully. Even if you have the perfect manuscript, if it does not align with the aims and scope of the journal, it will be rejected. This means that you must also give attention to the audience. Again, even if you write an impressive paper but situate it within a local context, an editor might reject it if the journal is catering to an international audience. This means that you might be forced to consider a different journal (one whose aims and scope your paper aligns with). Remember, alignment with aims and scope can save you disappointment and your time. Also, do not ever submit a paper to a journal without getting advice and feedback from a more experienced individual.
• Important findings and significant contributions: In Chapters 2 and 6, we discussed finding gaps, occupying your niche and significance of your findings. It is extremely important that you highlight why your findings are important and the kind of contributions your manuscript is making to the field. Remember, your significance could be in the form of: (a) new and original findings or methods; (b) synthesis or reconciling disparate theories or ideas in the field; (c) reinterpreting previous works or theory; or (d) making new application of an existing finding, theory or method. In essence, consider whether your contribution will advance empirical knowledge, theory, methods or a combination.
• Well-supported analysis, interpretation, discussions and conclusions: In Chapters 9 to 11, we discussed writing your findings, and the importance of having strong analysis and interpretation of your results. Peer-reviewers will be scrutinizing your findings and your interpretation so it is important to spend time making sure that your claims are well-supported by evidence. Your discussion must also continue the conversation that you began in the literature review and your findings. You must demonstrate how your findings contribute to the wider puzzle. In essence, there must be cohesiveness between all sections of your paper.
• Effective Writing: Your writing is an important element of your manuscript. A poorly written manuscript will not get published even if the findings are significant. Before we discuss general writing tips, it is important to structure your paper according to the guidelines of the journal or book. You cannot submit your thesis in its existing form. Usually, you will need to rewrite the entire thesis to comply with the requirement of the journal that you wish to submit it to (unless of course, your thesis took the form of a journal article). Even if your thesis was written as a journal article, you need to carefully review the publishers’ requirements and make changes as needed. Most publishers provide templates and outline how the manuscript is to be organized. Box 13.5.1 below provides some general guidelines.
Box 13.3 – Typical Sections in a Peer-Reviewed Manuscript
• Cover Page: Pay attention to the information that the publisher wants on the cover page. Some publishers require only the title formatted in specific ways. Others may require institutional affiliation and other details. Be sure to read the guidelines carefully.
• Abstract: This is a summary (usually between 100 and 250 words) of the research question, methodology, findings and significance. It is important to invest time in writing an effective abstract because it offers the first real impression on what the paper is about (see Chapter 2). Lantsoght (2019) note that without a concluding sentence that highlights the implication/significance of the work, the abstract is incomplete.
• Keywords: Up to 5 words (under the abstract) that help your paper to get visibility. It is important to choose keywords that will draw people to your article. Do not be afraid to use the buzz words in the specific sub-discipline.
• Introduction: This is where you outline the research problem, what is known about it and your research question. It is important that you hint to the gaps in the field and the significance of your study in this section.
• Literature Review: In your thesis you might have presented a general overview of the literature in the area. For your journal article, you need to be more precise and synthesize materials that relate to your research question. Note that you are not only summarizing the literature to show that you are knowledgeable about the subject area, you also need to establish the gap, and position your paper as contributing to filling that gap. You must also reaffirm the significance of your paper.
• Methods/Procedures: This is an important part of your manuscript. You must identify your population and variables (if applicable), data sources, measurements, limitations, analytical strategies etc. The aim is to make your paper replicable (produce similar results) if someone were to repeat the study.
• Results/Findings: This is where you highlight your empirical observations and new discoveries. Again, you might have tons of findings but you must only report those that pertain to the research question.
• Discussion: This offers a summary of the key findings and offers explanations for them. The aim is to demonstrate how your study adds to existing knowledge. You can also highlight the limitations.
• Conclusions: This is where you reiterate the answer(s) to your research question, highlight the implications and make recommendations
• References: It is important to follow the reference style required by the publisher and organize your reference list accordingly.
• Tables and Figures: Most journals will require that you provide tables and figures at the end of the paper (each on a separate page) or in a separate document. | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/13%3A_Publishing_Your_Research/13.04%3A_Assessing_the_Journal_and_Improving_Publication_Success.txt |
The increasing pressure on young academics to publish in order to enhance their careers has led to the exploitation of the system by some publishers. These publishers do not conduct proper peer review processes or offer customer service and have been named predatory journals by Bealle (Richtig et al, 2018, p. 1441). Beall (2016) outlines 27 criteria to determine if a journal is a “potential, possible, or probable predatory scholarly open-access publisher” that covers issues such as editor and staff, business management, integrity and journal standards. While the list is not exhaustive and has faced many criticisms (see Olivarez et al, 2018), it is widely used to assess the quality of journals. Predatory journals are a threat to academic integrity because their poor standards are seen to allow “infected” knowledge into the scientific archive. This has implications for future research. In addition, if your work is published in a predatory journal, it might be dismissed by graduate schools, universities and employers as invalid. After all the hard work you have put into your project, it would be painful to have your labour invalidated by a compromised peer review process. Hence, it is important that you check to ensure that the journal to which you intend to submit your paper is not classified as a “predatory publisher”. You can check Bealls list at https://beallslist.net/.
Open Access
Another consideration in the publishing landscape is whether to publish open access. Traditionally, journals are subscription based, that is, they charge subscription fees from users (mostly large institutions). Recently, they have faced pressures from Open Access journals, which make articles readily available online without restrictions. Instead of users paying subscription fees, open access journals usually charge the authors a fee to publish (called article processing charge, APC). Many predatory journals exploit this model to gain fees from authors, but many open-access journals uphold excellent peer-review standards. In fact, many mainstream journals now offer open-access options for authors who want their work to reach a larger audience and to be unrestricted. If you choose to publish open access, be mindful of the APC and be sure to check that the journal is not a predatory journal (Beall, 2016).
Writing a cover letter
Many journals recommend writing a cover letter to accompany your manuscript. Cover letters introduce your paper and highlight the importance. You can also make suggestions for possible peer reviewers (which some journals require). If the journal to which you are submitting your manuscript recommends it, you should write a cover letter. This is because the editors/administrators will likely use it as part of the screening process (i.e., to help determine which article should proceed to peer review). Hence, you must ensure that you treat it as important. Most journal publishers provide templates and guidance on how to write a cover letter. Please observe the directions carefully. In general, a good cover letter to a manuscript has the following components:
• Personal salutation: You should research who the editor is and offer personal salutations.
• The title of your manuscript and the name of the journal to which you are submitting the article
• A summary of your paper, and outline its importance to the field and to its audience. Outline who would benefit from the manuscript (e.g., students, practitioners, policy makers, academics etc).
• Confirmation that the paper is not under consideration elsewhere and disclosure of any conflicts of interest, fundings (or the lack thereof).
• If required, suggestions of the names of potential peer-reviewers (these must be scholars in the field to whom you have no personal connection or relationship).
Overall, it is important to view the cover letter template of the publisher to which you wish to submit (if it is provided). If no template is provided, adhere to the components discussed above. However, please be guided by the following additional considerations:
• Do not let your cover page exceed a page
• Utilize institutional letterhead (if you are able to obtain it) but provide your personal contact information.
• Your summary is different from your abstract. Instead of replicating your abstract, focus on why your manuscript is significant and how it fits within the journal (refer to the aims and scope).
• Keep your language clear and simple.
Table 13.1 - Links to Selected Cover Letter Templates and Guidance
Publisher Links
Elsevier https://www.elsevier.com/__data/prom...20Template.doc
Springer https://www.springer.com/gp/authors-...tters/10285574
Taylor and Francis https://authorservices.taylorandfran...-cover-letter/
American Psychological Association (APA) https://apastyle.apa.org/style-gramm.../cover-letters | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/13%3A_Publishing_Your_Research/13.05%3A_Further_Considerations_for_Journal_Submission-_Open_Access_Cover_Letters_and_Preda.txt |
Writing for an academic publication can be daunting. Here are some writing tips to help you:
• Be clear: While you want to use the jargon of the discipline, there is no need to try to make your sentence more complex than it ought. Say what you mean. Offer definitions of key concepts when they first appear
• Do not over-cite or rely on quotations: You must project a confident tone so there is no need to provide a citation after every sentence. Likewise, feel free to paraphrase and analyze statements. Do not use too many quotes and always explain quotes in your own words.
• Organization is paramount: According to Carr et al (2018), it is imperative to determine how each section of the paper will be organized ahead of writing. For example, they suggest determining the main points of each major section and create sub-headings that correspond to each point (Carr et al, 2018, p.609).
• Do not make false or blanket statements e.g. “There are no previous research on this topic.” Instead of making such a blanket statement, you might qualify it by stating “there is little research on this topic” or “a literature review search reveals no pre-existing work”.
• Avoid dead words and phrases (Swales & Feak, 2004): Dead words are extraneous, make sentences unnecessarily lengthy, superfluous and sometimes, confusing e.g. “indeed”, “basically”, “really”
• Use the active voice: There is a perception that the passive voice is more objective but it can make the sentence clunky. The active voice is a more direct, precise, and clear way to communicate your ideas (Carr et al, 2018).
• Be professional: do not use contractions (e.g. don’t, won’t) or casual language.
• Know your genre: Read the other articles from the journal you want to publish in and pay attention to their writing style. Carefully emulate their organization to improve the familiarity of your own work.
• Read Chapter 5 on academic writing for more tips specific to your genre!
Common mistakes
The following are a list of common mistakes made in academic submissions:
• Not providing evidence for claims e.g., not providing (relevant) supporting quotes to substantiate a point or stating that a relationship is statistically significant without stating the degree of significance and the direction (direction and magnitude).
• Not interpreting the meaning of the results: it is important to state what the findings mean in real life. Explain potential implications.
• The submission does not follow the journal’s guidelines. You must ensure that your work adheres to the limit, formatting suggestions, spelling, referencing style and other guidelines set.
• Failing to introduce the importance of the topic. The introduction should highlight the relevance of the topic, not just highlight previous studies. You should justify why the knowledge is worth pursuing. You must ensure that you justify why the answers to the research question are worth knowing.
• Weak literature reviews: It is important that you spend time to develop your literature review so that it captures a full breath of the literature. Leaving out key debates or authors in the field suggests unfamiliarity with the literature. In the highly competitive peer-reviewed world, such mistakes might be grounds for a rejection. It is also important to synthesize rather than merely providing an annotated bibliography. Your literature review must be analytical.
• Repackaging a thesis without making major revision: Your thesis is unlikely to meet the specific criteria of a journal article in its original form (unless it was intentionally written for the specific journal). This means that major revisions will be needed before it is ready for submission to a journal or other peer review format. Substantive re-analysis of the data might be required, the literature review might need updating and to be brought into more focus in accordance with the research question. In addition, your thesis statement might have several research questions but you might need to limit them to only one or two for your journal article. Overall, it is important that you approach your manuscript for peer review as a separate work from your dissertation. Substantive changes in style, form and content might be required.
• Incomplete methodology: You must provide context, exact procedure, ethics review process, theoretical and analytical framing and justification for methods, sample selection and analysis. You must assume that your readers know nothing about your study and provide complete information.
• Shallow discussions: Your discussion must link your literature review with your findings and must demonstrate how the study answers the research question. In short, your discussion must explain why you got the results you got and how it fits within the literature. It should also demonstrate the significance.
• Vague conclusions: It is important to remember that your conclusion is reiterating answers to your research questions. You might also reflect on the limitations in the current study and offer recommendations for future studies, policy or other social action. However, it is important to not introduce new literature in your conclusion. As a general rule, there should be few citations in your conclusion, but you must ensure that any citation referred to in the conclusion has been mentioned previously in the manuscript.
Box 13.4 – Checklist for Submission
1. The paper is not under consideration for publication elsewhere
2. I have received feedback from a professor, mentor or someone with peer-review publication
3. The paper aligns with the aims, scope, audience and general description of the publisher
4. The paper adheres to style and guidelines “guidelines for authors”, set by the publication
5. I have included a cover letter (always a good idea)
6. The paper has original results or methods
7. The literature review is up-to-date with current works
8. There is a clear message that has been put in context of previous work (i.e., the gap I am filling is clear)
9. I have reviewed similar publications (e.g., other works published in the journal)
10. I have proof-read the submission
11. I have obtained copyright permission for materials obtained elsewhere (if required)
12. Referencing are complete, accurate and adhere to the style
13. I understand that my paper may be rejected. I will take feedback to improve my work going forward. | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/13%3A_Publishing_Your_Research/13.06%3A_Some_Tips_for_Good_Writing_Revisited.txt |
After submitting your article, it can take months or even a year (sometimes longer) before you receive initial feedback from the editor. Calls for contributions to edited volumes (e.g., books) tend to indicate a decision date, so there is usually less anxiety about when the outcome will be known. Many journals also allow authors to track the progress of their articles so you know where it is in the review process. Nonetheless, if this is your first publication, you are likely anxious to know the outcome. This is normal, even for seasoned authors. Remember, be patient –there is no need to contact the editor within the first two or three months. If you feel like you are unable to bear the suspense, talk to a mentor, your supervisor or a professor to get their advice on whether you should contact the journal and how to frame your message.
For double-blind peer review articles, an editor/administrator usually conducts an initial quality check. This could result in a desk rejection (with an explanation why) or it is sent out to referees (peer-reviewers) for evaluation. Some journals give reviewers a deadline within which to submit their reports, but others give a more relaxed timeline. This process can take a while. The reviewers will carefully read the manuscript, consult other literature if needed and write a report, which is sent to the editor. Please note that some journals give general guidance on how to evaluate the manuscript while others have specific scorecards (which are not available to the authors). Based on the recommendations of reviewers, the editor might decide to: (a) accept as is –this is extremely rare; (b) accept with revisions; (c) revise and resubmit (taking into account all the comments from the reviewers); (d) referred to a more suitable journal; (e) rejected. Most published papers have received a ‘revise and resubmit’ at some stage in the peer review process.
Obviously, dealing with acceptance (even with revision) at any stage in the peer-review process is a joyous occasion. You should be extremely proud of your achievement. Only a handful of people ever get to publish in a peer-reviewed academic journal. Please note that an acceptance with revision is not a free pass. You must complete the revisions by the date set. When you make your revisions, you should write a letter to the editor outlining all the suggestions and how you dealt with each (see APA 2021 for guidance). Remember to be courteous, even if you disagree with the suggestions. While it is okay to disagree with suggestions, consult with an experienced professional and do not blast the reviewers. Sometimes it is not worth the battle.
If you receive a desk rejection or a rejection after peer review, you will be gutted. You might feel like a failure, personally attacked and you might question your abilities or purpose. These feelings are normal. Everyone who gets a rejection feels a range of negative emotions. There is no need to attempt to stifle them. Talk about it with someone, express your disappointment, shame, hurt, grief or whatever emotion you are feeling. Do not obsess over the comments. Instead, take some time to refresh yourself and engage in some self-care (hang out with friends, go to a spa, go for long walks, or anything else that helps you through difficult times –see Chapter 4 for more self-care tips). When you feel like you are ready to pick up the paper (this could be months after), read the feedback with the goal to learn what you can from the experience. Discuss them with a trusted person (try to resist the temptation to isolate yourself from constructive feedback). After the discussion, you will need to decide whether you want to revise the manuscript and submit it to another journal or if you want to abandon the project completely. If you submit it to another journal, be sure to make the changes that the reviewers provided. Ensure that you address all the feedback so that the manuscript is truly improved. Whatever decision you make, do not make it in isolation –discuss it with a trusted colleague or mentor. Academia is a lonely and isolating endeavor, so you need to make an effort to find a mentor or a more experienced expert for support.
If you receive a decision to submit the paper to a different journal, then you should. However, take note of any comments, feedback or suggestions that are offered before you submit it to a different journal. More often than not, the comments you receive will help to improve the paper.
As mentioned earlier, the overwhelming majority of accepted papers first received a “revise and resubmit” which might mean “major revision” or “minor revisions”. The comments might offer substantial changes that might require making major changes to the structure or content of your paper. You should attempt to incorporate all the suggestions. If you disagree with any, be sure to discuss your argument with a trusted mentor or expert before you launch an attack on the reviewers or editors. Failure to accept suggestions is likely to go well with editors so be discerning in which comments you want to disagree with. Remember, you should write a letter outlining all the suggestions offered and how you respond to them. You must be courteous in all your responses (even if you believe the comments were silly).
Box 13.5 Resources and tips for publishing in non peer-reviewed sources
Editorials
Evaluation Reports
Academic Blogs
13.08: Summary
The decision to submit a manuscript for publication is an important one. It requires significant investment in time as well as emotional and mental labour. Converting a thesis to a manuscript for either a book or a journal requires significant tailoring. It is imperative that you have a mentor to support you throughout the entire process, from writing to handling decisions. Given how competitive the peer review process is, you must adhere strictly to publishers recommendations and best practices. Crucially, you must remember to separate your personal identity from your submission. A rejection of your manuscript is not a rejection of you. Engage in self-care and adopt an open mind to learning from the experience. | textbooks/socialsci/Social_Work_and_Human_Services/Practicing_and_Presenting_Social_Research_(Robinson_and_Wilson)/13%3A_Publishing_Your_Research/13.07%3A_Receiving_and_Dealing_with_Decisions.txt |
Chapter 1 Learning Objectives
• Provide examples of how salience and accessibility influence information processing.
• Review, differentiate and give examples of the cognitive heuristics that influence social judgment.
• Summarize and give examples of the importance of social cognition in everyday life.
Once we have developed a set of schemas and attitudes, we naturally use that information to help us judge and respond to others. Our expectations help us think about, size up, and make sense of individuals, groups of people, and the relationships among people. If we have learned, for example, that someone is friendly and interested in us, we are likely to approach them; if we have learned that they are threatening or unlikable, we will be more likely to withdraw. And if we believe that a person has committed a crime, we may process new information in a manner that helps convince us that our judgment was correct. In this section, we will consider how we use our stored knowledge to come to accurate (and sometimes inaccurate) conclusions about our social worlds. Table 2.1 “How Expectations Influence Our Social Cognition” summarizes the concepts that we will discuss, some of the many ways that our existing schemas and attitudes influence how we respond to the information around us.
Table 2.1 How Expectations Influence Our Social Cognition
Cognitive Process Description Example
Cognitive accessibility Some schemas and attitudes are more accessible than others. We may think a lot about our new haircut because it is important for us.
Salience Some stimuli, such as those that are unusual, colorful, or moving, grab our attention. We may base our judgments on a single unusual event and ignore hundreds of other events that are more usual.
Representativeness heuristic We tend to make judgments according to how well the event matches our expectations. After a coin has come up heads many times in a row, we may erroneously think that the next flip is more likely to be tails.
Availability heuristic Things that come to mind easily tend to be seen as more common. We may overestimate the crime statistics in our own area because these crimes are so easy to recall.
Anchoring and adjustment Although we try to adjust our judgments away from them, our decisions are overly based on the things that are most highly accessible in memory. We may buy more of a product when it is advertised in bulk than when it is advertised as a single item.
Counterfactual thinking We may “replay” events such that they turn out differently—especially when only minor changes in the events leading up to them make a difference. We may feel particularly bad about events that might not have occurred if only a small change might have prevented them.
False consensus bias We tend to see other people as similar to us. We are surprised when other people have different political opinions or values.
Overconfidence We tend to have more confidence in our skills, abilities, and judgments than is objectively warranted. Eyewitnesses are often extremely confident that their identifications are accurate, even when they are not.
Automatic Versus Controlled Cognition
A good part of both cognition and social cognition is spontaneous or automatic. Automatic cognition refers to thinking that occurs out of our awareness, quickly, and without taking much effort (Ferguson & Bargh, 2003; Ferguson, Hassin, & Bargh, 2008). The things that we do most frequently tend to become more automatic each time we do them until they reach a level where they don’t really require us to think about them very much. Most of us can ride a bike and operate a television remote control in an automatic way. Even though it took some work to do these things when we were first learning them, it just doesn’t take much effort anymore. And because we spend a lot of time making judgments about others, many of these judgments (and particularly those about people we don’t know very well and who don’t matter much to us) are made automatically (Willis & Todorov, 2006).
Because automatic thinking occurs outside of our conscious awareness, we frequently have no idea that it is occurring and influencing our judgments or behaviors. You might remember a time when you came back from your classes, opened the door to your dorm room, and 30 seconds later couldn’t remember where you had put your keys! You know that you must have used the keys to get in, and you know you must have put them somewhere, but you simply don’t remember a thing about it. Because many of our everyday judgments and behaviors are performed “on automatic,” we may not always be aware that they are occurring or influencing us.
It is, of course, a good thing that many things operate automatically because it would be a real pain to have to think about them all the time. If you couldn’t drive a car automatically, you wouldn’t be able to talk to the other people riding with you or listen to the radio at the same time—you’d have to be putting most of your attention into driving. On the other hand, relying on our snap judgments about Bianca—that she’s likely to be expressive, for instance—can be erroneous. Sometimes we need to—and should—go beyond automatic cognition and consider people more carefully. When we deliberately size up and think about something—for instance another person—we call it thoughtful cognition or controlled cognition.
Although you might think that controlled cognition would be more common and that automatic thinking would be less likely, that is not always the case. The problem is that thinking takes effort and time, and we often don’t have too many of those things available. As a result, we frequently rely on automatic cognition, and these processes—acting outside of our awareness—have a big effect on our behaviors. In the following Research Focus, we will consider an example of a study that uses a common social cognitive procedure known as priming — a technique in which information is temporarily brought into memory through exposure to situational events—and that shows that priming can influence judgments entirely out of awareness.
Research Focus
Behavioral Effects of Priming
• >In one demonstration of how automatic cognition can influence our behaviors without us being aware of them, John Bargh and his colleagues (Bargh, Chen, & Burrows, 1996) conducted two studies, each with the exact same procedure. In the experiments, they showed college students sets of five scrambled words. The students were to unscramble the five words in each set to make a sentence. Furthermore, for half of the research participants, the words were related to the stereotype of the elderly. These participants saw words such as “in Florida retired live people” and “bingo man the forgetful plays.”
• >The other half of the research participants also made sentences but did so out of words that had nothing to do with the elderly stereotype. The purpose of this task was to prime (activate) the schema of elderly people in memory for some of the participants but not for others.
• >The experimenters then assessed whether the priming of elderly stereotypes would have any effect on the students’ behavior—and indeed it did. When each research participant had gathered all his or her belongings, thinking that the experiment was over, the experimenter thanked him or her for participating and gave directions to the closest elevator. Then, without the participant knowing it, the experimenters recorded the amount of time that the participant spent walking from the doorway of the experimental room toward the elevator. As you can see in the following figure, the same results were found in both experiments—the participants who had made sentences using words related to the elderly stereotype took on the behaviors of the elderly—they walked significantly more slowly (in fact, about 12% more slowly across the two studies) as they left the experimental room.
Figure 2.3 Automatic Priming and Behavior
In two separate experiments, Bargh, Chen, and Borroughs (1996) found that students who had been exposed to words related to the elderly stereotype walked more slowly than those who had been exposed to more neutral words.
• >To determine if these priming effects occurred out of the conscious awareness of the participants, Bargh and his colleagues asked the third group of students to complete the priming task and then to indicate whether they thought the words they had used to make the sentences had any relationship to each other or could possibly have influenced their behavior in any way. These students had no awareness of the possibility that the words might have been related to the elderly or could have influenced their behavior.
• >The point of these experiments, and many others like them, is clear—it is quite possible that our judgments and behaviors are influenced by our social situations, and this influence may be entirely outside of our conscious awareness. To return again to Bianca, it is even possible that we notice her nationality and that our beliefs about Italians influence our responses to her, even though we have no idea that they are doing so and really believe that they have not. It is in this way that our stereotypes may have their insidious effects, and it is exactly these processes that may have led to a mistaken eyewitness account in the case of Rickie Johnson.
Salience and Accessibility Determine Which Expectations We Use
We each have a large number of schemas that we might bring to bear on any type of judgment we might make. When thinking about Bianca, for instance, we might focus on her nationality, her gender, her physical attractiveness, her intelligence, or any of many other possible features. And we will react to Bianca differently depending on which schemas we use. Schema activation is determined both by characteristics of the person we are judging—the salience of the characteristics—and by the current activation of the schema in the individual—the cognitive accessibility of the schema.
Salience
• One determinant of which schemas are likely to be used in social justice is the extent to which we attend to particular features of the person or situation that we are responding to. We are more likely to judge people on the basis of characteristics that are salient, meaning that they attract our attention when we see something or someone with them. Things that are unusual, negative, colorful, bright and moving are more salient and thus more likely to be attended to than are things that do not have these characteristics (McArthur & Post, 1977; Taylor & Fiske, 1978).
Which of these people are more salient and therefore more likely to attract your attention? Erich Ferdinand – The Purger – CC BY 2.0; Hamad AL-Mohannna – Jump – CC BY-ND 2.0; LethaColleen – Session 5: Finished! – CC BY-NC-ND 2.0.
We are more likely to initially judge people on the basis of their sex, race, age, and physical attractiveness, rather than on, say, their religious orientation or their political beliefs, in part because these features are so salient when we see them (Brewer, 1988). Another thing that makes something particularly salient is its infrequency or unusualness. Because Bianca is from Italy and very few other people in our school are, that characteristic is something that we notice—it is salient, and we are therefore likely to attend to it. That she is also a woman is—at least in this context—less salient.
The salience of the stimuli in our social worlds may sometimes lead us to make judgments on the basis of information that is actually less informative than is other less salient information. Imagine, for instance, that you wanted to buy a new music player for yourself. You’ve been trying to decide whether to get the iPod or the Zune. You went online and checked out Consumer Reports, and you found that although the players differed on many dimensions, including price, battery life, ability to share music, and so forth, the Zune was nevertheless rated significantly higher by the owners than was the iPod. As a result, you decide to go purchase one the next day. That night, however, you go to a party, and a friend of yours shows you her iPod. You check it out, and it seems really great. You tell her that you were thinking of buying a Zune, and she tells you that you are crazy. She says she knows someone who had one and had a lot of problems—it didn’t download music right, the battery went out right after it went out of warranty, and so forth—and that she would never buy one. Would you still buy the Zune, or would you switch your plans?
If you think about this question logically, the information that you just got from your friend isn’t really all that important—you now know the opinions of one more person, but that can’t really change the overall consumer ratings of the two machines very much. On the other hand, the information your friend gives you and the chance to use her iPod is highly salient. The information is right there in front of you, in your hand, whereas the statistical information from Consumer Reports is only in the form of a table that you saw on your computer. The outcome in cases such as this is that people frequently ignore the less salient, but more important, information, such as the likelihood that events occur across a large population—these statistics are known as base rates — in favor of the actually less important, but nevertheless more salient, information.
Another case in which we ignore base-rate information occurs when we use the representativeness heuristic (remember that heuristic refers to a simplifying strategy that we use to make judgments). The representativeness heuristic occurs when we base our judgments on information that seems to represent, or match, what we expect will happen while ignoring more informative base-rate information. Consider, for instance, the following puzzle. Let’s say that you went to a hospital, and you checked the records of the babies that were born today (Table 2.2 “Using the Representativeness Heuristic”). Which pattern of births do you think that you are most likely to find?
Table 2.2 Using the Representativeness Heuristic
List A List B
6:31 a.m. Girl 6:31 a.m. Boy
8:15 a.m. Girl 8:15 a.m. Girl
9:42 a.m. Girl 9:42 a.m. Boy
1:13 p.m. Girl 1:13 p.m. Girl
3:39 p.m. Boy 3:39 p.m. Girl
5:12 p.m. Boy 5:12 p.m. Boy
7:42 p.m. Boy 7:42 p.m. Girl
11:44 p.m. Boy 11:44 p.m. Boy
Most people think that list B is more likely, probably because list B looks more random and thus matches (is “representative of”) our ideas about randomness. But statisticians know that any pattern of four girls and four boys is equally likely and thus that List B is no more likely than List A. The problem is that we have an image of what randomness should be, which doesn’t always match what is rationally the case. Similarly, people who see a coin that comes up heads five times in a row will frequently predict (and perhaps even bet!) that tails will be next—it just seems like it has to be. But mathematically, this erroneous expectation (known as the gambler’s fallacy) is simply not true: The base-rate likelihood of any single coin flip being tails is only 50%, regardless of how many times it has come up heads in the past.
To take one more example, consider the following information:
I have a friend who is short, shy and writes poetry. Which of the following is she? (Choose one.)
1. A professor of psychology
2. A professor of Chinese
Can you see how you might be led, potentially incorrectly, into thinking that my friend is a professor of Chinese? Why? Because the description (“short, shy, and writes poetry”) just seems so representative or stereotypical of our expectations about Chinese people. But the base rates tell us something completely different, which might make us wary. For one, because I am a psychology professor, it’s much more likely that I know more psychology professors than Chinese professors. And at least on my campus, the number of professors in the psychology department is much bigger than the number of professors of Chinese. Although base rates suggest that “psychology” would be the right answer, the use of the representative heuristic might lead us (probably incorrectly) to guess “Chinese” instead.
Cognitive Accessibility
Although which characteristics we use to think about objects or people is determined in part by the salience of their characteristics (our perceptions are influenced by our social situation), individual differences in the person who is doing the judging are also important (our perceptions are influenced by person variables). People vary in the schemas that they find important to use when judging others and when thinking about themselves. One way to consider this importance is in terms of the cognitive accessibility of the schema. Cognitive accessibility refers to the extent to which a schema is activated in memory and thus likely to be used in information processing.
You probably know people who are golf nuts (or maybe tennis or some other sports nuts). All they can talk about is golf. For them, we would say that golf is a highly accessible construct. Because they love golf, it is important to their self-concept; they set many of their goals in terms of the sport, and they tend to think about things and people in terms of it (“if he plays golf, he must be a good person!”). Other people have highly accessible schemas about eating healthy food, exercising, environmental issues, or really good coffee, for instance. In short, when a schema is accessible, we are likely to use it to make judgments of ourselves and others.
Although accessibility can be considered a person variable (a given idea is more highly accessible for some people than for others), accessibility can also be influenced by situational factors. When we have recently or frequently thought about a given topic, that topic becomes more accessible and is likely to influence our judgments. This is, in fact, the explanation for the results of the priming study you read about earlier—people walked slower because the concept of the elderly had been primed and thus was currently highly accessible for them.
Because we rely so heavily on our schemas and attitudes—and particularly on those that are salient and accessible—we can sometimes be overly influenced by them. Imagine, for instance, that I asked you to close your eyes and determine whether there are more words in the English language that begin with the letter R or that have the letter R as the third letter. You would probably try to solve this problem by thinking of words that have each of the characteristics. It turns out that most people think there are more words that begin with R, even though there are in fact more words that have R as the third letter.
You can see that this error can occur as a result of cognitive accessibility. To answer the question, we naturally try to think of all the words that we know that begin with R and that have R in the third position. The problem is that when we do that, it is much easier to retrieve the former than the latter because we store words by their first, not by their third, letter. We may also think that our friends are nice people because we see them primarily when they are around us (their friends). And the traffic might seem worse in our own neighborhood than we think it is in other places, in part because nearby traffic jams are more accessible for us than are traffic jams that occur somewhere else. And do you think it is more likely that you will be killed in a plane crash or in a car crash? Many people fear the former, even though the latter is much more likely: Your chances of being involved in an aircraft accident are about 1 in 11 million, whereas your chances of being killed in an automobile accident are 1 in 5,000—over 50,000 people are killed on U.S. highways every year. In this case, the problem is that plane crashes, which are highly salient, are more easily retrieved from our memory than are car crashes, which are less extreme.
The tendency to make judgments of the frequency of an event or the likelihood that an event will occur, on the basis of the ease with which the event can be retrieved from memory is known as the availability heuristic (Schwarz & Vaughn, 2002; Tversky & Kahneman, 1973). The idea is that things that are highly accessible (in this case, the term availability is used) come to mind easily and thus may overly influence our judgments. Thus, despite the clear facts, it may be easier to think of plane crashes than car crashes because the former are so highly salient. If so, the availability heuristic can lead to errors in judgments.
Still another way that the cognitive accessibility of constructs can influence information processing is through their effects on processing fluency. Processing fluency refers to the ease with which we can process information in our environments. When stimuli are highly accessible, they can be quickly attended to and processed, and they, therefore, have a large influence on our perceptions. This influence is due, in part, to the fact that our body reacts positively to information that we can process quickly, and we use this positive response as a basis of judgment (Reber, Winkielman, & Schwarz, 1998; Winkielman & Cacioppo, 2001).
In one study demonstrating this effect, Norbert Schwarz and his colleagues (Schwarz et al., 1991) asked one set of college students to list 6 occasions when they had acted either assertively or unassertively and asked another set of college students to list 12 such examples. Schwarz determined that for most students, it was pretty easy to list 6 examples but pretty hard to list 12.
The researchers then asked the participants to indicate how assertive or unassertive they actually were. You can see from Figure 2.4 “Processing Fluency” that the ease of processing influenced judgments. The participants who had an easy time listing examples of their behavior (because they only had to list 6 instances) judged that they did in fact have the characteristics they were asked about (either assertive or unassertive), in comparison with the participants who had a harder time doing the task (because they had to list 12 instances). Other research has found similar effects—people rate that they ride their bicycles more often after they have been asked to recall only a few rather than many instances of doing so (Aarts & Dijksterhuis, 1999), and they hold an attitude with more confidence after being asked to generate few rather than many arguments that support it (Haddock, Rothman, Reber, & Schwarz, 1999).
Figure 2.4 Processing Fluency
When it was relatively easy to complete the questionnaire (only 6 examples were required), the student participants rated that they had more of the trait than when the task was more difficult (12 answers were required). Data are from Schwarz et al. (1991).
We are likely to use this type of quick and “intuitive” processing, based on our feelings about how easy it is to complete a task when we don’t have much time or energy for more in-depth processing, such as when we are under time pressure, tired, or unwilling to process the stimulus in sufficient detail. Of course, it is very adaptive to respond to stimuli quickly (Sloman, 2002; Stanovich & West, 2002; Winkielman, Schwarz, & Nowak, 2002), and it is not impossible that in at least some cases, we are better off making decisions based on our initial responses than on a more thoughtful cognitive analysis (Loewenstein, Weber, Hsee, & Welch, 2001). For instance, Dijksterhuis, Bos, Nordgren, and van Baaren (2006) found that when participants were given tasks requiring decisions that were very difficult to make on the basis of cognitive analysis of the problem, they made better decisions when they didn’t try to analyze the details carefully but simply relied on their unconscious intuition.
In sum, people are influenced not only by the information they get but by how they get it. We are more highly influenced by things that are salient and accessible and thus easily attended to, remembered, and processed. On the other hand, information that is harder to access from memory is less likely to be attended to, or takes more effort to consider is less likely to be used in our judgments, even if this information is statistically equally informative or even more informative.
The False Consensus Bias Makes Us Think That We Are More Like Others Than We Really Are
The tendency to base our judgments on the accessibility of social constructs can lead to still other errors in judgment. One such error is known as the false consensus bias: the tendency to overestimate the extent to which other people are similar to us. For instance, if you are in favor of abortion rights, opposed to gun control, and prefer rock music to jazz, then you are likely to think that other people share these beliefs (Ross, Greene, & House, 1977). In one demonstration of the false consensus bias, Joachim Krueger and his colleagues (Krueger & Clement, 1994) gave their research participants, who were college students, a personality test. Then they asked the same participants to estimate the percentage of other students in their school who would have answered the questions the same way that they did. The students who agreed with the items thought that others would agree with them too, whereas the students who disagreed thought that others would also disagree. You can see that the false consensus bias also occurs through the operation of cognitive accessibility: Once we have indicated our own belief, it becomes highly accessible, and it colors our estimates about other people.
Although it is commonly observed, the false consensus bias does not occur in all dimensions. Specifically, the false consensus bias is not usually observed on judgments of positive personal traits that we highly value as important. People (falsely, of course) report that they have better personalities (e.g., a better sense of humor), that they engage in better behaviors (e.g., they are more likely to wear seat belts), and that they have brighter futures than almost everyone else (Chambers, 2008). These results suggest that although in most cases we assume that we are similar to others, in cases of valued personal characteristics the goals of self-concern lead us to see ourselves more positively than we see the average person.
Perceptions of What “Might Have Been” Lead to Counterfactual Thinking
In addition to influencing our judgments about ourselves and others, the salience and accessibility of information can have an important effect on our own emotions—for instance, our self-esteem. Our emotional reactions to events are often colored not only by what did happen but also by what might have happened. If we can easily imagine an outcome that is better than what actually happened, then we may experience sadness and disappointment; on the other hand, if we can easily imagine that a result might have been worse than what actually happened, we may be more likely to experience happiness and satisfaction. The tendency to think about events according to what might have been known as counterfactual thinking (Roese, 1997).
Imagine, for instance, that you were participating in an important contest, and you won the silver medal. How would you feel? Certainly, you would be happy that you won, but wouldn’t you probably also be thinking a lot about what might have happened if you had been just a little bit better—you might have won the gold medal! On the other hand, how might you feel if you won the bronze medal (third place)? If you were thinking about the counterfactual (the “what might have been”), perhaps the idea of not getting any medal at all would have been highly accessible—you’d be happy that you got the medal you did get.
Medvec, Madey, and Gilovich (1995) investigated exactly this idea by videotaping the responses of athletes who won medals in the 1992 summer Olympic Games. They videotaped the athletes both as they learned that they had won a silver or a bronze medal and again as they were awarded the medal. Then they showed these videos, without any sound, to people who did not know which medal which athlete had won. The raters indicated how they thought the athlete was feeling, on a range from “agony” to “ecstasy.” The results showed that the bronze medalists did indeed seem to be, on average, happier than were the silver medalists. Then in a follow-up study, raters watched interviews with many of these same athletes as they talked about their performance. The raters indicated what we would expect on the basis of counterfactual thinking—the silver medalists talked about their disappointments in having finished second rather than first, whereas the bronze medalists focused on how happy they were to have finished third rather than fourth.
Does the bronze medalist look happier to you than the silver medalist? Medvec, Madey, and Gilovich (1995) found that, on average, bronze medalists were happier than silver medalists. Wikimedia Commons – CC BY-SA 2.0.
You might have experienced counterfactual thinking in other situations. I remember once that I was driving across the country and my car was having some engine trouble. I really, really wanted to make it home when I got near the end of my journey because I could tell that I was going to be very disappointed if the car broke down only a few miles before I got home (it would have been really easy to have imagined making it the whole way, making it even more painful if I did not). Counterfactual thinking has even been observed on juries—people who are asked to award monetary damages to others who had been in an accident offered them substantially more in compensation if they were almost not injured than they did if the accident did not seem close to not occurring (Miller, Turnbull, & McFarland, 1988).
Again, the moral of the story is clear—our thinking is frequently influenced by processes that we are not aware of and that may lead us to make judgments that seem reasonable but are objectively inaccurate. In the case of counterfactual thinking, the cognitive accessibility of the potential alternative outcome leads to some very paradoxical effects.
Anchoring and Adjustment Lead Us to Accept Ideas That We Should Revise
In some cases, we may be aware of the danger of acting on our expectations and attempt to adjust for them. Perhaps you have been in a situation where you are beginning a course with a new professor and you know that a good friend of yours does not like him. You may be thinking that you want to go beyond your negative expectations and prevent this knowledge from biasing your judgment. However, the accessibility of the initial information frequently prevents this adjustment from occurring—leading us to anchor on the initial construct and not adjust sufficiently. This is called the problem of anchoring and adjustment.
Tversky and Kahneman (1974) asked some of the student participants in one of their studies to solve this multiplication problem quickly and without using a calculator:
1 × 2 × 3 × 4 × 5 × 6 × 7 × 8
They asked other participants to solve this problem:
8 × 7 × 6 × 5 × 4 × 3 × 2 × 1
They found that students who saw the first problem gave an estimated answer of about 512, whereas the students who saw the second problem estimated about 2,250. Tversky and Kahneman argued that the students couldn’t solve the whole problem in their head, so they did the first few multiplications and then used the outcome of this preliminary calculation as their starting point, or anchor. Then the participants used their starting estimate to find an answer that sounded plausible. In both cases, the estimates were too low relative to the true value of the product (which is 40,320)—but the first set of guesses was even lower because they started from a lower anchor.
Of course, savvy marketers have long used the anchoring phenomenon to help them. You might not be surprised to hear that people are more likely to buy more products when they are listed as four for \$1.00 than when they are listed as \$0.25 each (leading people to anchor on the four and perhaps adjust only a bit away) and when a sign says “buy a dozen” rather than “buy one.”
And it is no accident that a car salesperson always starts negotiating with a high price and then works down. The salesperson is trying to get the consumer anchored on the high price with the hope that it will have a big influence on the final sale value.
Overconfidence
Still another potential judgmental bias, and one that has powerful and often negative effects on our judgments, is the tendency to be overconfident in our own skills, abilities, and judgments. We often have little awareness of our own limitations, leading us to act as if we are more certain about things than we should be, particularly on tasks that are difficult. Adams and Adams (1960) found that for words that were difficult to spell, people were correct in spelling them only about 80% of the time, even though they indicated that they were “100% certain” that they were correct. David Dunning and his colleagues (Dunning, Griffin, Milojkovic, & Ross, 1990) asked college students to predict how another student would react in various situations. Some participants made predictions about a fellow student whom they had just met and interviewed, and others made predictions about their roommates. In both cases, participants reported their confidence in each prediction, and accuracy was determined by the responses of the target persons themselves. The results were clear: Regardless of whether they judged a stranger or a roommate, the students consistently overestimated the accuracy of their own predictions (Figure 2.5).
Figure 2.5
Dunning et al. (1990) found that, regardless of whether they were judging strangers or their roommates, students were overconfident. The percentage confidence that they assigned to their own predictions was significantly higher than the actual percentage of their predictions that were correct.
Making matters even worse, Kruger and Dunning (1999) found that people who scored low rather than high on tests of spelling, logic, grammar, and humor appreciation were also most likely to show overconfidence by overestimating how well they would do. Apparently, poor performers are doubly cursed—they not only are unable to predict their own skills but also are the most unaware that they can’t do so (Dunning, Johnson, Ehrlinger, & Kruger, 2003).
The tendency to be overconfident in our judgments can have some very negative effects. When eyewitnesses testify in courtrooms regarding their memories of a crime, they often are completely sure that they are identifying the right person. But their confidence doesn’t correlate much with their actual accuracy. This is, in part, why so many people have been wrongfully convicted on the basis of inaccurate eyewitness testimony given by overconfident witnesses (Wells & Olson, 2003).
The Importance of Cognitive Biases in Everyday Life
Perhaps you are thinking that the use of heuristics and the tendency to be influenced by salience and accessibility don’t seem that important—who really cares if we buy an iPod when the Zune is better, or if we think there are more words that begin with the letter R than there actually are? These aren’t big problems in the overall scheme of things. But it turns out that what seems perhaps to be pretty small errors and biases on the surface can have profound consequences for people.
For one, if the errors occur for a lot of people, they can really add up. Why would so many people continue to buy lottery tickets or to gamble their money in casinos when the likelihood of them ever winning is so low? One possibility, of course, is the representative heuristic—people ignore the low base rates of winning and focus their attention on the salient likelihood of winning a huge prize. And the belief in astrology, which all scientific evidence suggests is not accurate, is probably driven in part by the salience of the occasions when the predictions do occur—when a horoscope is correct (which it will, of course, be sometimes), the correct prediction is highly salient and may allow people to maintain the (overall false) belief.
People may also take more care to prepare for unlikely events than for more likely ones because the unlikely ones are more salient or accessible. For instance, people may think that they are more likely to die from a terrorist attack or as a result of homicide than they are from diabetes, stroke, or tuberculosis. But the odds are much greater of dying from the health problems than from terrorism or homicide. Because people don’t accurately calibrate their behaviors to match the true potential risks, the individual and societal costs are quite large (Slovic, 2000).
Salience and accessibility also color how we perceive our social worlds, which may have a big influence on our behavior. For instance, people who watch a lot of violent television shows also tend to view the world as more dangerous in comparison to those who watch less violent TV (Doob & Macdonald, 1979). This follows from the idea that our judgments are based on the accessibility of relevant constructs. We also overestimate our contribution to joint projects (Ross & Sicoly, 1979), perhaps in part because our own contributions are so obvious and salient, whereas the contributions of others are much less so. And the use of cognitive heuristics can even affect our views about global warming. Joireman, Barnes, Truelove, and Duell (2010) found that people were more likely to believe in the existence of global warming when they were asked about it on hotter rather than colder days and when they had first been primed with words relating to heat. Thus the principles of salience and accessibility, because they are such an important part of our social judgments, can create a series of biases that can make a difference.
Research has found that even people who should know better—and who need to know better—are subject to cognitive biases. Economists, stock traders, managers, lawyers, and even doctors have been found to make the same kinds of mistakes in their professional activities that people make in their everyday lives (Byrne & McEleney, 2000; Gilovich, Griffin, & Kahneman, 2002; Hilton, 2001). And the use of cognitive heuristics is increased when people are under time pressure (Kruglanski & Freund, 1983) or when they feel threatened (Kassam, Koslov, & Mendes, 2009), exactly the situations that may occur when professionals are required to make their decisions.
Although biases are common, they are not impossible to control, and psychologists and other scientists are working to help people make better decisions. One possibility is to provide people with better feedback. Weather forecasters, for instance, are quite accurate in their decisions, in part because they are able to learn from the clear feedback that they get about the accuracy of their predictions. Other research has found that accessibility biases can be reduced by leading people to consider multiple alternatives rather than focusing only on the most obvious ones, and particularly by leading people to think about exactly the opposite possible outcomes than the ones they are expecting (Hirt, Kardes, & Markman, 2004). And people can also be trained to make better decisions. For instance, Lehman, Lempert, and Nisbett (1988) found that graduate students in medicine, law, and chemistry, but particularly those in psychology, all showed significant improvement in their ability to reason correctly over the course of their graduate training.
Social Psychology in the Public Interest
The Validity of Eyewitness Testimony
• >As we have seen in the story of Rickie Johnson that opens this chapter, one social situation in which the accuracy of our person-perception skills is vitally important in the area of eyewitness testimony (Charman & Wells, 2007; Toglia, Read, Ross, & Lindsay, 2007; Wells, Memon, & Penrod, 2006). Every year, thousands of individuals such as Rickie Johnson are charged with and often convicted of crimes based largely on eyewitness evidence. In fact, more than 100 people who were convicted prior to the existence of forensic DNA have now been exonerated by DNA tests, and more than 75% of these people were victims of mistaken eyewitness identification (Wells, Memon, & Penrod, 2006; Fisher, 2011).
• >The judgments of eyewitnesses are often incorrect, and there is only a small correlation between how accurate and how confident an eyewitness is. Witnesses are frequently overconfident, and one who claims to be absolutely certain about his or her identification is not much more likely to be accurate than one who appears much less sure, making it almost impossible to determine whether a particular witness is accurate or not (Wells & Olson, 2003).
• >To accurately remember a person or an event at a later time, we must be able to accurately see and store the information in the first place, keep it in memory over time, and then accurately retrieve it later. But the social situation can influence any of these processes, causing errors and biases.
• >In terms of initial encoding of the memory, crimes normally occur quickly, often in situations that are accompanied by a lot of stress, distraction, and arousal. Typically, the eyewitness gets only a brief glimpse of the person committing the crime, and this may be under poor lighting conditions and from far away. And the eyewitness may not always focus on the most important aspects of the scene. Weapons are highly salient, and if a weapon is present during the crime, the eyewitness may focus on the weapon, which would draw his or her attention away from the individual committing the crime (Steblay, 1997). In one relevant study, Loftus, Loftus, and Messo (1987) showed people slides of a customer walking up to a bank teller and pulling out either a pistol or a checkbook. By tracking eye movements, the researchers determined that people were more likely to look at the gun than at the checkbook and that this reduced their ability to accurately identify the criminal in a lineup that was given later.
• >People may be particularly inaccurate when they are asked to identify members of a race other than their own (Brigham, Bennett, Meissner, & Mitchell, 2007). In one field study, for example, Meissner and Brigham (2001) sent White, Black, and Hispanic students into convenience stores in El Paso, Texas. Each of the students made a purchase, and the researchers came in later to ask the clerks to identify photos of the shoppers. Results showed that the White, Black, and Mexican American clerks demonstrated the own-race bias: They were all more accurate at identifying customers belonging to their own racial or ethnic group than they were at identifying people from other groups. There seems to be some truth to the adage that “They all look alike”—at least if an individual is looking at someone who is not of his or her race.
One source of error in eyewitness testimony is the relative difficulty of accurately identifying people who are not of one’s own race. Kira Westland – sisters – CC BY-NC-ND 2.0; Dillan K – Sisters – CC BY-NC-ND 2.0; Bill Lile – Robertos Brothers – CC BY-NC-ND 2.0.
• >Even if information gets encoded properly, memories may become distorted over time. For one thing, people might discuss what they saw with other people, or they might read the information relating to it from other bystanders or in the media. Such postevent information can distort the original memories such that the witnesses are no longer sure what the real information is and what was provided later. The problem is that the new, inaccurate information is highly cognitively accessible, whereas the older information is much less so. Even describing a face makes it more difficult to recognize the face later (Dodson, Johnson, & Schooler, 1997).
• >In an experiment by Loftus and Palmer (1974), participants viewed a film of a traffic accident and then, according to random assignment to experimental conditions, answered one of three questions:
1. “About how fast were the cars going when they hit each other?”
2. “About how fast were the cars going when they smashed each other?”
3. “About how fast were the cars going when they contacted each other?”
• >As you can see in the following figure, although all the participants saw the same accident, their estimates of the speed of the cars varied by condition. People who had seen the “smashed” question estimated the highest average speed, and those who had seen the “contacted” question estimated the lowest.
Figure 2.6 Reconstructive Memory
Participants viewed a film of a traffic accident and then answered a question about the accident. According to random assignment, the blank was filled by either “hit,” “smashed,” or “contacted” each other. The wording of the question influenced the participants’ memory of the accident. Data are from Loftus and Palmer (1974).
• >The situation is particularly problematic when the eyewitnesses are children because research has found that children are more likely to make incorrect identifications than are adults (Pozzulo & Lindsay, 1998) and are also subject to the own-race identification bias (Pezdek, Blandon-Gitlin, & Moore, 2003). In many cases, when sex abuse charges have been filed against babysitters, teachers, religious officials, and family members, the children are the only source of evidence. The likelihood that children are not accurately remembering the events that have occurred to them creates substantial problems for the legal system.
• >Another setting in which eyewitnesses may be inaccurate is when they try to identify suspects from mug shots or lineups. A lineup generally includes the suspect and five to seven other innocent people (the fillers), and the eyewitness must pick out the true perpetrator. The problem is that eyewitnesses typically feel pressured to pick a suspect out of the lineup, which increases the likelihood that they will mistakenly pick someone (rather than no one) as the suspect.
• >Research has attempted to better understand how people remember and potentially misremember the scenes of and people involved in crimes and to attempt to improve how the legal system makes use of eyewitness testimony. In many states, efforts are being made to better inform judges, juries, and lawyers about how inaccurate eyewitness testimony can be. Guidelines have also been proposed to help ensure those child witnesses are questioned in a nonbiased way (Poole & Lamb, 1998). Steps can also be taken to ensure that lineups yield more accurate eyewitness identifications. Lineups are fairer when the fillers resemble the suspect when the interviewer makes it clear that the suspect might or might not be present (Steblay, Dysart, Fulero, & Lindsay, 2001), and when the eyewitness has not been shown the same pictures in a mug-shot book prior to the lineup decision. And several recent studies have found that witnesses who make accurate identifications from a lineup reach their decision faster than do witnesses who make mistaken identifications, suggesting that authorities must take into consideration not only the response but how fast it is given (Dunning & Perretta, 2002).
• >In addition to distorting our memories for events that have actually occurred, misinformation may lead us to falsely remember information that never occurred. Loftus and her colleagues asked parents to provide them with descriptions of events that did (e.g., moving to a new house) and did not (e.g., being lost in a shopping mall) happen to their children. Then (without telling the children which events were real or made-up) the researchers asked the children to imagine both types of events. The children were instructed to “think real hard” about whether the events had occurred (Ceci, Huffman, Smith, & Loftus, 1994). More than half of the children generated stories regarding at least one of the made-up events, and they remained insistent that the events did in fact occur even when told by the researcher that they could not possibly have occurred (Loftus & Pickrell, 1995). Even college students are susceptible to manipulations that make events that did not actually occur seem as if they did (Mazzoni, Loftus, & Kirsch, 2001).
• >The ease with which memories can be created or implanted is particularly problematic when the events to be recalled have important consequences. Therapists often argue that patients may repress memories of traumatic events they experienced as children, such as childhood sexual abuse, and then recover the events years later as the therapist leads them to recall the information—for instance, by using dream interpretation and hypnosis (Brown, Scheflin, & Hammond, 1998).
• >But other researchers argue that painful memories such as sexual abuse are usually very well remembered, that few memories are actually repressed and that even if they are, it is virtually impossible for patients to accurately retrieve them years later (McNally, Bryant, & Ehlers, 2003; Pope, Poliakoff, Parker, Boynes, & Hudson, 2007). These researchers have argued that the procedures used by the therapists to “retrieve” the memories are more likely to actually implant false memories, leading the patients to erroneously recall events that did not actually occur. Because hundreds of people have been accused, and even imprisoned, on the basis of claims about “recovered memory” of child sexual abuse, the accuracy of these memories has important societal implications. Many psychologists now believe that most of these claims of recovered memories are due to implanted, rather than real, memories (Loftus & Ketcham, 1994).
• >Taken together, then, the problems of eyewitness testimony represent another example of how social cognition—the processes that we use to size up and remember other people—may be influenced, sometimes in a way that creates inaccurate perceptions, by the operation of salience, cognitive accessibility, and other information-processing biases.
Key Takeaways
• We use our schemas and attitudes to help us judge and respond to others. In many cases, this is appropriate, but our expectations can also lead to biases in our judgments of ourselves and others.
• A good part of our social cognition is spontaneous or automatic, operating without much thought or effort. On the other hand, when we have the time and the motivation to think about things carefully, we may engage in thoughtful, controlled cognition.
• Which expectations we use to judge others are based on both the situational salience of the things we are judging and the cognitive accessibility of our own schemas and attitudes.
• Variations in the accessibility of schemas lead to biases such as the availability heuristic, the representativeness heuristic, the false consensus bias, and biases caused by counterfactual thinking.
• The potential biases that are the result of everyday social cognition can have important consequences, both for us in our everyday lives but even for people who make important decisions affecting many other people. Although biases are common, they are not impossible to control, and psychologists and other scientists are working to help people make better decisions.
• The operation of cognitive biases, including the potential for new information to distort information already in memory, can help explain the tendency for eyewitnesses to be overconfident and frequently inaccurate in their recollections of what occurred at crime scenes.
Exercises & Critical Thinking
1. Give an example of a time when you may have committed one of the cognitive errors listed in Table 2.1 “How Expectations Influence Our Social Cognition”. What factors (e.g., availability? salience?) caused the error, and what was the outcome of your use of the shortcut or heuristic?
2. Go to the website http://thehothand.blogspot.com, which analyzes the extent to which people accurately perceive “streakiness” in sports. Consider how our sports perceptions are influenced by our expectations and the use of cognitive heuristics.
Attribution
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Chapter 2 Learning Objectives
• Discuss Freud’s Theory of psychosexual development.
• Describe the major tasks of child and adult psychosocial development according to Erikson.
• Discuss Piaget’s view of cognitive development and apply the stages to understanding childhood cognition.
• Describe Kohlberg’s theory of moral development.
Freud
Psychosexual Theory of Development
Freud (1856–1939) believed that personality develops during early childhood. For Freud, childhood experiences shape our personalities and behavior as adults. Freud viewed development as discontinuous; he believed that each of us must pass through a serious of stages during childhood and that if we lack proper nurturance and parenting during a stage, we may become stuck, or fixated, in that stage. Freud’s stages are called the stages of psychosexual development. According to Freud, children’s pleasure-seeking urges are focused on a different area of the body, called an erogenous zone, at each of the five stages of development: oral, anal, phallic, latency, and genital.
Erikson
Psychosocial Theory of Development
Erikson (1902–1994) (Figure 1), another stage theorist, took Freud’s theory and modified it as psychosocial theory. Erikson’s psychosocial development theory emphasizes the social nature of our development rather than its sexual nature. While Freud believed that personality is shaped only in childhood, Erikson proposed that personality development takes place all through the lifespan. Erikson suggested that how we interact with others is what affects our sense of self, or what he called the ego identity.
Erik Erikson proposed the psychosocial theory of development. In each stage of Erikson’s theory, there is a psychosocial task that we must master in order to feel a sense of competence. (Figure 1).
Stage Age (years) Developmental Task Description
1 0–1 Trust vs. mistrust Trust (or mistrust) that basic needs, such as nourishment and affection, will be met
2 1–3 Autonomy vs. shame/doubt Develop a sense of independence in many tasks
3 3–6 Initiative vs. guilt Take initiative on some activities—may develop guilt when unsuccessful or boundaries overstepped
4 7–11 Industry vs. inferiority Develop self-confidence in abilities when competent or sense of inferiority when not
5 12–18 Identity vs. confusion Experiment with and develop identity and roles
6 19–29 Intimacy vs. isolation Establish intimacy and relationships with others
7 30–64 Generativity vs. stagnation Contribute to society and be part of a family
8 65– Integrity vs. despair Assess and make sense of life and meaning of contributions
Erikson’s Psychosocial Stages of Development – Table 1
Piaget
Cognitive Theory of Development
Piaget (1896–1980) is another stage theorist who studied childhood development (Figure 2). Instead of approaching development from a psychoanalytical or psychosocial perspective, Piaget focused on children’s cognitive growth. He believed that thinking is a central aspect of development and that children are naturally inquisitive. However, he said that children do not think and reason like adults (Piaget, 1930, 1932). His theory of cognitive development holds that our cognitive abilities develop through specific stages, which exemplifies the discontinuity approach to development. As we progress to a new stage, there is a distinct shift in how we think and reason.
Jean Piaget spent over 50 years studying children and how their minds develop. (Figure 2).
Schemata are concepts (mental models) that are used to help us categorize and interpret information. By the time children have reached adulthood, they have created schemata for almost everything. When children learn new information, they adjust their schemata through two processes: assimilation and accommodation. First, they assimilate new information or experiences in terms of their current schemata: assimilation is when they take in information that is comparable to what they already know. Accommodation describes when they change their schemata based on new information. This process continues as children interact with their environment.
Age (years) Stage Description Developmental issues
0–2 Sensorimotor The world experienced through senses and actions Object permanence
Stranger anxiety
2–6 Preoperational Use words and images to represent things, but lack logical reasoning Pretend play
Egocentrism
Language development
7–11 Concrete operational Understand concrete events and analogies logically; perform arithmetical operations Conservation
Mathematical transformations
12– Formal operational Formal operations
Utilize abstract reasoning
Abstract logic
Moral reasoning
Piaget’s Stages of Cognitive Development – Table 2
sensorimotor stage, which lasts from birth to about 2 years old. During this stage, children learn about the world through their senses and motor behavior. Young children put objects in their mouths to see if the items are edible, and once they can grasp objects, they may shake or bang them to see if they make sounds. Between 5 and 8 months old, the child develops object permanence, which is the understanding that even if something is out of sight, it still exists (Bogartz, Shinskey, & Schilling, 2000). According to Piaget, young infants do not remember an object after it has been removed from sight. Piaget studied infants’ reactions when a toy was first shown to an infant and then hidden under a blanket. Infants who had already developed object permanence would reach for the hidden toy, indicating that they knew it still existed, whereas infants who had not developed object permanence would appear confused.
brief video above demonstrating different children’s ability to understand object permanence.
preoperational stage, which is from approximately 2 to 7 years old. In this stage, children can use symbols to represent words, images, and ideas, which is why children in this stage engage in pretend play. A child’s arms might become airplane wings as he zooms around the room, or a child with a stick might become a brave knight with a sword. Children also begin to use language in the preoperational stage, but they cannot understand adult logic or mentally manipulate information (the term operational refers to logical manipulation of information, so children at this stage are considered to be pre-operational). Children’s logic is based on their own personal knowledge of the world so far, rather than on conventional knowledge. For example, dad gave a slice of pizza to 10-year-old Keiko and another slice to her 3-year-old brother, Kenny. Kenny’s pizza slice was cut into five pieces, so Kenny told his sister that he got more pizza than she did. Children in this stage cannot perform mental operations because they have not developed an understanding of conservation, which is the idea that even if you change the appearance of something, it is still equal in size as long as nothing has been removed or added.
egocentrism, which means that the child is not able to take the perspective of others. A child at this stage thinks that everyone sees, thinks, and feels just as they do. Let’s look at Kenny and Keiko again. Keiko’s birthday is coming up, so their mom takes Kenny to the toy store to choose a present for his sister. He selects an Iron Man action figure for her, thinking that if he likes the toy, his sister will too. An egocentric child is not able to infer the perspective of other people and instead attributes his own perspective.
concrete operational stage, which occurs from about 7 to 11 years old. In this stage, children can think logically about real (concrete) events; they have a firm grasp on the use of numbers and start to employ memory strategies. They can perform mathematical operations and understand transformations, such as addition is the opposite of subtraction, and multiplication is the opposite of division. In this stage, children also master the concept of conservation: Even if something changes shape, its mass, volume, and number stay the same. For example, if you pour water from a tall, thin glass to a short, fat glass, you still have the same amount of water. Remember Keiko and Kenny and the pizza? How did Keiko know that Kenny was wrong when he said that he had more pizza?
reversibility, which means that objects can be changed and then returned back to their original form or condition. Take, for example, water that you poured into the short, fat glass: You can pour water from the fat glass back to the thin glass and still have the same amount (minus a couple of drops).
formal operational stage, which is from about age 11 to adulthood. Whereas children in the concrete operational stage are able to think logically only about concrete events, children in the formal operational stage can also deal with abstract ideas and hypothetical situations. Children in this stage can use abstract thinking to problem solve, look at alternative solutions, and test these solutions. In adolescence, a renewed egocentrism occurs. For example, a 15-year-old with a very small pimple on her face might think it is huge and incredibly visible, under the mistaken impression that others must share her perceptions.
Kohlberg
Theory of Moral Development
Kohlberg (1927–1987) extended upon the foundation that Piaget built regarding cognitive development. Kohlberg believed that moral development, like cognitive development, follows a series of stages. To develop this theory, Kohlberg posed moral dilemmas to people of all ages, and then he analyzed their answers to find evidence of their particular stage of moral development. Before reading about the stages, take a minute to consider how you would answer one of Kohlberg’s best-known moral dilemmas, commonly known as the Heinz dilemma:
In Europe, a woman was near death from a special kind of cancer. There was one drug that the doctors thought might save her. It was a form of radium that a druggist in the same town had recently discovered. The drug was expensive to make, but the druggist was charging ten times what the drug cost him to make. He paid \$200 for the radium and charged \$2,000 for a small dose of the drug. The sick woman’s husband, Heinz, went to everyone he knew to borrow the money, but he could only get together about \$1,000, which is half of what it cost. He told the druggist that his wife was dying and asked him to sell it cheaper or let him pay later. But the druggist said: “No, I discovered the drug and I’m going to make money from it.” So Heinz got desperate and broke into the man’s store to steal the drug for his wife. Should the husband have done that? (Kohlberg, 1969, p. 379)
stages of moral reasoning (Figure 3). According to Kohlberg, an individual progresses from the capacity for pre-conventional mortality (before age 9) to the capacity for conventional morality (early adolescence), and toward attaining post-conventional morality (once formal operational thought is attained), which only a few fully achieve. Kohlberg placed in the highest stage responses that reflected the reasoning that Heinz should steal the drug because his wife’s life is more important than the pharmacist making money. The value of human life overrides the pharmacist’s greed.
Kohlberg identified three levels of moral reasoning: pre-conventional, conventional, and post-conventional: Each level is associated with increasingly complex stages of moral development. (Figure 3).
In a Different Voice: Psychological Theory and Women’s Development, Gilligan (1982) criticized her former mentor’s theory because it was based only on upper-class White men and boys. She argued that women are not deficient in their moral reasoning—she proposed that males and females reason differently. Girls and women focus more on staying connected and the importance of interpersonal relationships. Therefore, in the Heinz dilemma, many girls and women respond that Heinz should not steal the medicine. Their reasoning is that if he steals the medicine, is arrested, and is put in jail, then he and his wife will be separated, and she could die while he is still in prison.
Additional Resources
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Chapter 3 Learning Objectives
• Explain what sociological theories are and how they are used.
• Understand the similarities and differences between structural functionalism, conflict theory, and symbolic interactionism.
Sociologists develop theories to explain social occurrences such as protest rallies. (Photo courtesy of voanews.com/Wikimedia Commons)
Sociologists study social events, interactions, and patterns, and they develop a theory in an attempt to explain why things work as they do. In sociology, a theory is a way to explain different aspects of social interactions and to create a testable proposition, called a hypothesis, about society (Allan 2006).
social solidarity, and hypothesized that differences in suicide rates might be explained by religion-based differences. Durkheim gathered a large amount of data about Europeans who had ended their lives, and he did indeed find differences based on religion. Protestants were more likely to commit suicide than Catholics in Durkheim’s society, and his work supports the utility of theory in sociological research.
Sociological Theories or Perspectives Different sociological perspectives enable sociologists to view social issues through a variety of useful lenses.
Sociological Paradigm Level of Analysis Focus
Structural Functionalism Macro or mid The way each part of society functions together to contribute to the whole
Conflict Theory Macro The way inequalities contribute to social differences and perpetuate differences in power
Symbolic Interactionism Micro One-to-one interactions and communications
Functionalism
institutions, or patterns of beliefs and behaviors focused on meeting social needs, such as government, education, family, healthcare, religion, and the economy.
function of any recurrent activity as the part it played in social life as a whole, and therefore the contribution it makes to social stability and continuity (Radcliff-Brown 1952). In a healthy society, all parts work together to maintain stability, a state called dynamic equilibrium by later sociologists such as Parsons (1961).
functions are the unsought consequences of a social process. A manifest function of college education, for example, includes gaining knowledge, preparing for a career, and finding a good job that utilizes that education. The latent functions of your college years include meeting new people, participating in extracurricular activities, or even finding a spouse or partner. Another latent function of education is creating a hierarchy of employment based on the level of education attained. Latent functions can be beneficial, neutral, or harmful. Social processes that have undesirable consequences for the operation of society are called dysfunctions. In education, examples of dysfunction include getting bad grades, truancy, dropping out, not graduating, and not finding suitable employment.
Criticism
Global Culture?
Some sociologists see the online world contributing to the creation of an emerging global culture. Are you a part of any global communities? (Photo courtesy of quasireversible/flickr)
Criticism
Farming and Locavores: How Sociological Perspectives Might View Food Consumption
Food Inc. depicts as resulting from Monsanto’s patenting of seed technology. Another topic of study might be how nutrition varies between different social classes.
Symbolic Interactionist Theory
dramaturgical analysis. Goffman used theater as an analogy for social interaction and recognized that people’s interactions showed patterns of cultural “scripts.” Because it can be unclear what part a person may play in a given situation, he or she has to improvise his or her role as the situation unfolds (Goffman 1958).
Attribution
Theoretical Perspectives by Rice University under the Creative Commons Attribution-NonCommercial 4.0 license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/03%3A_The_Sociocultural_Dimension/3.01%3A_Chapter_3-_Theoretical_Perspectives.txt |
Chapter 4 Learning Objectives
• Distinguish material culture and nonmaterial culture.
• List and define the several elements of culture.
• Describe certain values that distinguish the United States from other nations.
Culture is as the symbols, language, beliefs, values, and artifacts that are part of any society. As this definition suggests, there are two basic components of culture: ideas and symbols on the one hand and artifacts (material objects) on the other. The first type, called nonmaterial culture, includes the values, beliefs, symbols, and language that define a society. The second type, called material culture, includes all the society’s physical objects, such as its tools and technology, clothing, eating utensils, and means of transportation. These elements of culture are discussed next.
• Symbols
Every culture is filled with symbols, or things that stand for something else and that often evoke various reactions and emotions. Some symbols are actually types of nonverbal communication, while other symbols are in fact material objects. As the symbolic interactionist perspective discussed in Chapter 1 “Sociology and the Sociological Perspective” emphasizes, shared symbols make social interaction possible.
Let’s look at nonverbal symbols first. A common one is shaking hands, which is done in some societies but not in others. It commonly conveys friendship and is used as a sign of both greeting and departure. Probably all societies have nonverbal symbols we call gestures, movements of the hands, arms, or other parts of the body that are meant to convey certain ideas or emotions. However, the same gesture can mean one thing in one society and something quite different in another society (Axtell, 1998). In the United States, for example, if we nod our head up and down, we mean yes, and if we shake it back and forth, we mean no. In Bulgaria, however, nodding means no, while shaking our head back and forth means yes! In the United States, if we make an “O” by putting our thumb and forefinger together, we mean “OK,” but the same gesture in certain parts of Europe signifies an obscenity. “Thumbs up” in the United States means “great” or “wonderful,” but in Australia it means the same thing as extending the middle finger in the United States. Certain parts of the Middle East and Asia would be offended if they saw you using your left hand to eat, because they use their left hand for bathroom hygiene.
The meaning of a gesture may differ from one society to another. This familiar gesture means “OK” in the United States, but in certain parts of Europe it signifies an obscenity. An American using this gesture might very well be greeted with an angry look. d Wang – ok – CC BY-NC-ND 2.0.
Some of our most important symbols are objects. Here the U.S. flag is a prime example. For most Americans, the flag is not just a piece of cloth with red and white stripes and white stars against a field of blue. Instead, it is a symbol of freedom, democracy, and other American values and, accordingly, inspires pride and patriotism. During the Vietnam War, however, the flag became to many Americans a symbol of war and imperialism. Some burned the flag in protest, prompting angry attacks by bystanders and negative coverage by the news media.
Other objects have symbolic value for religious reasons. Three of the most familiar religious symbols in many nations are the cross, the Star of David, and the crescent moon, which are widely understood to represent Christianity, Judaism, and Islam, respectively. Whereas many cultures attach no religious significance to these shapes, for many people across the world they evoke very strong feelings of religious faith. Recognizing this, hate groups have often desecrated these symbols.
As these examples indicate, shared symbols, both nonverbal communication and tangible objects, are an important part of any culture but also can lead to misunderstandings and even hostility. These problems underscore the significance of symbols for social interaction and meaning.
• Language
Perhaps our most important set of symbols is language. In English, the word chair means something we sit on. In Spanish, the word silla means the same thing. As long as we agree how to interpret these words, a shared language and thus society are possible. By the same token, differences in languages can make it quite difficult to communicate. For example, imagine you are in a foreign country where you do not know the language and the country’s citizens do not know yours. Worse yet, you forgot to bring your dictionary that translates their language into yours, and vice versa, and your iPhone battery has died. You become lost. How will you get help? What will you do? Is there any way to communicate your plight?
As this scenario suggests, language is crucial to communication and thus to any society’s culture. Children learn language from their culture just as they learn about shaking hands, about gestures, and about the significance of the flag and other symbols. Humans have a capacity for language that no other animal species possesses. Our capacity for language in turn helps make our complex culture possible.
Language is a key symbol of any culture. Humans have a capacity for language that no other animal species has, and children learn the language of their society just as they learn other aspects of their culture. Bill Benzon – IMGP3639 – talk – CC BY-SA 2.0.
In the United States, some people consider a common language so important that they advocate making English the official language of certain cities or states or even the whole country and banning bilingual education in the public schools (Ray, 2007). Critics acknowledge the importance of English but allege that this movement smacks of anti-immigrant prejudice and would help destroy ethnic subcultures. In 2009, voters in Nashville, Tennessee, rejected a proposal that would have made English the city’s official language and required all city workers to speak in English rather than their native language (R. Brown, 2009).
Language, of course, can be spoken or written. One of the most important developments in the evolution of society was the creation of written language. Some of the preindustrial societies that anthropologists have studied have written language, while others do not, and in the remaining societies the “written” language consists mainly of pictures, not words. Figure 3.1 “The Presence of Written Language (Percentage of Societies)” illustrates this variation with data from 186 preindustrial societies called the Standard Cross-Cultural Sample (SCCS), a famous data set compiled several decades ago by anthropologist George Murdock and colleagues from information that had been gathered on hundreds of preindustrial societies around the world (Murdock & White, 1969). In Figure 3.1 “The Presence of Written Language (Percentage of Societies)”, we see that only about one-fourth of the SCCS societies have a written language, while about equal proportions have no language at all or only pictures.
Figure 3.1 The Presence of Written Language (Percentage of Societies)
Source: Data from Standard Cross-Cultural Sample.
To what extent does language influence how we think and how we perceive the social and physical worlds? The famous but controversial Sapir-Whorf hypothesis, named after two linguistic anthropologists, Edward Sapir and Benjamin Lee Whorf, argues that people cannot easily understand concepts and objects unless their language contains words for these items (Whorf, 1956). Language thus influences how we understand the world around us. For example, people in a country such as the United States that has many terms for different types of kisses (e.g. buss, peck, smack, smooch, and soul) are better able to appreciate these different types than people in a country such as Japan, which, as we saw earlier, only fairly recently developed the word kissu for kiss.
Another illustration of the Sapir-Whorf hypothesis is seen in sexist language, in which the use of male nouns and pronouns shapes how we think about the world (Miles, 2008). In older children’s books, words like fireman and mailman are common, along with pictures of men in these jobs, and critics say they send a message to children that these are male jobs, not female jobs. If a teacher tells a second-grade class, “Every student should put his books under his desk,” the teacher obviously means students of both sexes but may be sending a subtle message that boys matter more than girls. For these reasons, several guidebooks promote the use of nonsexist language (Maggio, 1998). Table 3.1 “Examples of Sexist Terms and Nonsexist Alternatives” provides examples of sexist language and nonsexist alternatives.
Table 3.1 Examples of Sexist Terms and Nonsexist Alternatives
Term Alternative
Businessman Businessperson, executive
Fireman Fire fighter
Chairman Chair, chairperson
Policeman Police officer
Mailman Letter carrier, postal worker
Mankind Humankind, people
Man-made Artificial, synthetic
Waitress Server
He (as generic pronoun) He or she; he/she; s/he
“A professor should be devoted to his students” “Professors should be devoted to their students”
The use of racist language also illustrates the Sapir-Whorf hypothesis. An old saying goes, “Sticks and stones may break my bones, but names will never hurt me.” That may be true in theory but not in reality. Names can hurt, especially names that are racial slurs, which African Americans growing up before the era of the civil rights movement routinely heard. According to the Sapir-Whorf hypothesis, the use of these words would have affected how whites perceived African Americans. More generally, the use of racist terms may reinforce racial prejudice and racial stereotypes.
Sociology Making a Difference
Overcoming Cultural and Ethnic Differences
• >People from many different racial and ethnic backgrounds live in large countries such as the United States. Because of cultural differences and various prejudices, it can be difficult for individuals from one background to interact with individuals from another background. Fortunately, a line of research, grounded in contact theory and conducted by sociologists and social psychologists, suggests that interaction among individuals from different backgrounds can indeed help overcome tensions arising from their different cultures and any prejudices they may hold. This happens because such contact helps disconfirm stereotypes that people may hold of those from different backgrounds (Dixon, 2006; Pettigrew & Tropp, 2005).
• >Recent studies of college students provide additional evidence that social contact can help overcome cultural differences and prejudices. Because many students are randomly assigned to their roommates when they enter college, interracial roommates provide a “natural” experiment for studying the effects of social interaction on racial prejudice. Studies of such roommates find that whites with black roommates report lowered racial prejudice and greater numbers of interracial friendships with other students (Laar, Levin, Sinclair, & Sidanius, 2005; Shook & Fazio, 2008).
• >It is not easy to overcome cultural differences and prejudices, and studies also find that interracial college roommates often have to face many difficulties in overcoming the cultural differences and prejudices that existed before they started living together (Shook & Fazio, 2008). Yet the body of work supporting contact theory suggests that efforts that increase social interaction among people from different cultural and ethnic backgrounds in the long run will reduce racial and ethnic tensions.
• Norms
Cultures differ widely in their norms, or standards and expectations for behaving. We already saw that the nature of drunken behavior depends on society’s expectations of how people should behave when drunk. Norms of drunken behavior influence how we behave when we drink too much.
Norms are often divided into two types, formal norms and informal norms. Formal norms, also called mores (MOOR-ayz) and laws, refer to the standards of behavior considered the most important in any society. Examples in the United States include traffic laws, criminal codes, and, in a college context, student behavior codes addressing such things as cheating and hate speech. Informal norms, also called folkways and customs, refer to standards of behavior that are considered less important but still influence how we behave. Table manners are a common example of informal norms, as are such everyday behaviors as how we interact with a cashier and how we ride in an elevator.
Many norms differ dramatically from one culture to the next. Some of the best evidence for cultural variation in norms comes from the study of sexual behavior (Edgerton, 1976). Among the Pokot of East Africa, for example, women are expected to enjoy sex, while among the Gusii a few hundred miles away, women who enjoy sex are considered deviant. In Inis Beag, a small island off the coast of Ireland, sex is considered embarrassing and even disgusting; men feel that intercourse drains their strength, while women consider it a burden. Even nudity is considered terrible, and people on Inis Beag keep their clothes on while they bathe. The situation is quite different in Mangaia, a small island in the South Pacific. Here sex is considered very enjoyable, and it is the major subject of songs and stories.
While many societies frown on homosexuality, others accept it. Among the Azande of East Africa, for example, young warriors live with each other and are not allowed to marry. During this time, they often have sex with younger boys, and this homosexuality is approved by their culture. Among the Sambia of New Guinea, young males live separately from females and engage in homosexual behavior for at least a decade. It is felt that the boys would be less masculine if they continued to live with their mothers and that the semen of older males helps young boys become strong and fierce (Edgerton, 1976).
Although many societies disapprove of homosexuality, other societies accept it. This difference illustrates the importance of culture for people’s attitudes. philippe leroyer – Lesbian & Gay Pride – CC BY-NC-ND 2.0.
Other evidence for cultural variation in norms comes from the study of how men and women are expected to behave in various societies. For example, many traditional societies are simple hunting-and-gathering societies. In most of these, men tend to hunt and women tend to gather. Many observers attribute this gender difference to at least two biological differences between the sexes. First, men tend to be bigger and stronger than women and are thus better suited for hunting. Second, women become pregnant and bear children and are less able to hunt. Yet a different pattern emerges in some hunting-and-gathering societies. Among a group of Australian aborigines called the Tiwi and a tribal society in the Philippines called the Agta, both sexes hunt. After becoming pregnant, Agta women continue to hunt for most of their pregnancy and resume hunting after their child is born (Brettell & Sargent, 2009).
Some of the most interesting norms that differ by culture govern how people stand apart when they talk with each other (Hall & Hall, 2007). In the United States, people who are not intimates usually stand about three to four feet apart when they talk. If someone stands more closely to us, especially if we are of northern European heritage, we feel uncomfortable. Yet people in other countries—especially Italy, France, Spain, and many of the nations of Latin America and the Middle East—would feel uncomfortable if they were standing three to four feet apart. To them, this distance is too great and indicates that the people talking dislike each other. If a U.S. native of British or Scandinavian heritage were talking with a member of one of these societies, they might well have trouble interacting, because at least one of them will be uncomfortable with the physical distance separating them.
• Rituals
Different cultures also have different rituals, or established procedures and ceremonies that often mark transitions in the life course. As such, rituals both reflect and transmit a culture’s norms and other elements from one generation to the next. Graduation ceremonies in colleges and universities are familiar examples of time-honored rituals. In many societies, rituals help signify one’s gender identity. For example, girls around the world undergo various types of initiation ceremonies to mark their transition to adulthood. Among the Bemba of Zambia, girls undergo a month-long initiation ceremony called the chisungu, in which girls learn songs, dances, and secret terms that only women know (Maybury-Lewis, 1998). In some cultures, special ceremonies also mark a girl’s first menstrual period. Such ceremonies are largely absent in the United States, where a girl’s first period is a private matter. But in other cultures the first period is a cause for celebration involving gifts, music, and food (Hathaway, 1997).
Boys have their own initiation ceremonies, some of them involving circumcision. That said, the ways in which circumcisions are done and the ceremonies accompanying them differ widely. In the United States, boys who are circumcised usually undergo a quick procedure in the hospital. If their parents are observant Jews, circumcision will be part of a religious ceremony, and a religious figure called a moyel will perform the circumcision. In contrast, circumcision among the Maasai of East Africa is used as a test of manhood. If a boy being circumcised shows signs of fear, he might well be ridiculed (Maybury-Lewis, 1998).
Are rituals more common in traditional societies than in industrial ones such as the United States? Consider the Nacirema, studied by anthropologist Horace Miner more than 50 years ago (Miner, 1956). In this society, many rituals have been developed to deal with the culture’s fundamental belief that the human body is ugly and in danger of suffering many diseases. Reflecting this belief, every household has at least one shrine in which various rituals are performed to cleanse the body. Often these shrines contain magic potions acquired from medicine men. The Nacirema are especially concerned about diseases of the mouth. Miner writes, “Were it not for the rituals of the mouth, they believe that their teeth would fall out, their gums bleed, their jaws shrink, their friends desert them, and their lovers reject them” (p. 505). Many Nacirema engage in “mouth-rites” and see a “holy-mouth-man” once or twice yearly.
Spell Nacirema backward and you will see that Miner was describing American culture. As his satire suggests, rituals are not limited to preindustrial societies. Instead, they function in many kinds of societies to mark transitions in the life course and to transmit the norms of the culture from one generation to the next.
• Changing Norms and Beliefs
Our examples show that different cultures have different norms, even if they share other types of practices and beliefs. It is also true that norms change over time within a given culture. Two obvious examples here are hairstyles and clothing styles. When the Beatles first became popular in the early 1960s, their hair barely covered their ears, but parents of teenagers back then were aghast at how they looked. If anything, clothing styles change even more often than hairstyles. Hemlines go up, hemlines go down. Lapels become wider, lapels become narrower. This color is in, that color is out. Hold on to your out-of-style clothes long enough, and eventually they may well end up back in style.
Some norms may change over time within a given culture. In the early 1960s, the hair of the four members of the Beatles barely covered their ears, but many parents of U.S. teenagers were very critical of the length of their hair. U.S. Library of Congress – public domain.
A more important topic on which norms have changed is abortion and birth control (Bullough & Bullough, 1977). Despite the controversy surrounding abortion today, it was very common in the ancient world. Much later, medieval theologians generally felt that abortion was not murder if it occurred within the first several weeks after conception. This distinction was eliminated in 1869, when Pope Pius IX declared abortion at any time to be murder. In the United States, abortion was not illegal until 1828, when New York state banned it to protect women from unskilled abortionists, and most other states followed suit by the end of the century. However, the sheer number of unsafe, illegal abortions over the next several decades helped fuel a demand for repeal of abortion laws that in turn helped lead to the Roe v. Wade Supreme Court decision in 1973 that generally legalized abortion during the first two trimesters.
Contraception was also practiced in ancient times, only to be opposed by early Christianity. Over the centuries, scientific discoveries of the nature of the reproductive process led to more effective means of contraception and to greater calls for its use, despite legal bans on the distribution of information about contraception. In the early 1900s, Margaret Sanger, an American nurse, spearheaded the growing birth-control movement and helped open a birth-control clinic in Brooklyn in 1916. She and two other women were arrested within 10 days, and Sanger and one other defendant were sentenced to 30 days in jail. Efforts by Sanger and other activists helped to change views on contraception over time, and finally, in 1965, the U.S. Supreme Court ruled in Griswold v. Connecticut that contraception information could not be banned. As this brief summary illustrates, norms about contraception changed dramatically during the last century.
Other types of cultural beliefs also change over time (Figure 3.2 “Percentage of People Who Say They Would Vote for a Qualified African American for President” and Figure 3.3 “Percentage of People Who Agree Women Should Take Care of Running Their Homes”). Since the 1960s, the U.S. public has changed its views about some important racial and gender issues. Figure 3.2 “Percentage of People Who Say They Would Vote for a Qualified African American for President”, taken from several years of the General Social Survey (GSS), shows that the percentage of Americans who would vote for a qualified black person as president rose almost 20 points from the early 1970s to the middle of 1996, when the GSS stopped asking the question. If beliefs about voting for an African American had not changed, Barack Obama would almost certainly not have been elected in 2008. Figure 3.3 “Percentage of People Who Agree Women Should Take Care of Running Their Homes”, also taken from several years of the GSS, shows that the percentage saying that women should take care of running their homes and leave running the country to men declined from almost 36% in the early 1970s to only about 15% in 1998, again, when the GSS stopped asking the question. These two figures depict declining racial and gender prejudice in the United States during the past quarter-century.
Figure 3.2 Percentage of People Who Say They Would Vote for a Qualified African American for President
Source: Data from General Social Surveys, 1972–1996.
Figure 3.3 Percentage of People Who Agree Women Should Take Care of Running Their Homes
Source: Data from General Social Surveys, 1974–1998.
• Values
Values are another important element of culture and involve judgments of what is good or bad and desirable or undesirable. A culture’s values shape its norms. In Japan, for example, a central value is group harmony. The Japanese place great emphasis on harmonious social relationships and dislike interpersonal conflict. Individuals are fairly unassertive by American standards, lest they be perceived as trying to force their will on others (Schneider & Silverman, 2010). When interpersonal disputes do arise, Japanese do their best to minimize conflict by trying to resolve the disputes amicably. Lawsuits are thus uncommon; in one case involving disease and death from a mercury-polluted river, some Japanese who dared to sue the company responsible for the mercury poisoning were considered bad citizens (Upham, 1976).
• Individualism in the United States
American culture promotes competition and an emphasis on winning in the sports and business worlds and in other spheres of life. Accordingly, lawsuits over frivolous reasons are common and even expected. Clyde Robinson – Courtroom – CC BY 2.0.
In the United States, of course, the situation is quite different. The American culture extols the rights of the individual and promotes competition in the business and sports worlds and in other areas of life. Lawsuits over the most frivolous of issues are quite common and even expected. Phrases like “Look out for number one!” abound. If the Japanese value harmony and group feeling, Americans value competition and individualism. Because the Japanese value harmony, their norms frown on self-assertion in interpersonal relationships and on lawsuits to correct perceived wrongs. Because Americans value and even thrive on competition, our norms promote assertion in relationships and certainly promote the use of the law to address all kinds of problems.
Figure 3.4 “Percentage of People Who Think Competition Is Very Beneficial” illustrates this difference between the two nations’ cultures with data from the 2002 World Values Survey (WVS), which was administered to random samples of the adult populations of more than 80 nations around the world. One question asked in these nations was, “On a scale of one (‘competition is good; it stimulates people to work hard and develop new ideas’) to ten (‘competition is harmful; it brings out the worst in people’), please indicate your views on competition.” Figure 3.4 “Percentage of People Who Think Competition Is Very Beneficial” shows the percentages of Americans and Japanese who responded with a “one” or “two” to this question, indicating they think competition is very beneficial. Americans are about three times as likely as Japanese to favor competition.
Figure 3.4 Percentage of People Who Think Competition Is Very Beneficial
Source: Data from World Values Survey, 2002.
The Japanese value system is a bit of an anomaly, because Japan is an industrial nation with very traditional influences. Its emphasis on group harmony and community is more usually thought of as a value found in traditional societies, while the U.S. emphasis on individuality is more usually thought of as a value found in industrial cultures. Anthropologist David Maybury-Lewis (1998, p. 8) describes this difference as follows: “The heart of the difference between the modern world and the traditional one is that in traditional societies people are a valuable resource and the interrelations between them are carefully tended; in modern society things are the valuables and people are all too often treated as disposable.” In industrial societies, continues Maybury-Lewis, individualism and the rights of the individual are celebrated and any one person’s obligations to the larger community are weakened. Individual achievement becomes more important than values such as kindness, compassion, and generosity.
Other scholars take a less bleak view of industrial society, where they say the spirit of community still lives even as individualism is extolled (Bellah, Madsen, Sullivan, Swidler, & Tipton, 1985). In American society, these two simultaneous values sometimes create tension. In Appalachia, for example, people view themselves as rugged individuals who want to control their own fate. At the same time, they have strong ties to families, relatives, and their neighbors. Thus their sense of independence conflicts with their need for dependence on others (Erikson, 1976).
• The Work Ethic
Another important value in the American culture is the work ethic. By the 19th century, Americans had come to view hard work not just as something that had to be done but as something that was morally good to do (Gini, 2000). The commitment to the work ethic remains strong today: in the 2008 General Social Survey, 72% of respondents said they would continue to work even if they got enough money to live as comfortably as they would like for the rest of their lives.
Cross-cultural evidence supports the importance of the work ethic in the United States. Using earlier World Values Survey data, Figure 3.5 “Percentage of People Who Take a Great Deal of Pride in Their Work” presents the percentage of people in United States and three other nations from different parts of the world—Mexico, Poland, and Japan—who take “a great deal of pride” in their work. More than 85% of Americans feel this way, compared to much lower proportions of people in the other three nations.
Figure 3.5 Percentage of People Who Take a Great Deal of Pride in Their Work
Source: Data from World Values Survey, 1993.
Closely related to the work ethic is the belief that if people work hard enough, they will be successful. Here again the American culture is especially thought to promote the idea that people can pull themselves up by their “bootstraps” if they work hard enough. The WVS asked whether success results from hard work or from luck and connections. Figure 3.6 “Percentage of People Who Think Hard Work Brings Success” presents the proportions of people in the four nations just examined who most strongly thought that hard work brings success. Once again we see evidence of an important aspect of the American culture, as U.S. residents were especially likely to think that hard work brings success.
Figure 3.6 Percentage of People Who Think Hard Work Brings Success
Source: Data from World Values Survey, 1997.
If Americans believe hard work brings success, then they should be more likely than people in most other nations to believe that poverty stems from not working hard enough. True or false, this belief is an example of the blaming-the-victim ideology introduced in Chapter 1 “Sociology and the Sociological Perspective”. Figure 3.7 “Percentage of People Who Attribute Poverty to Laziness and Lack of Willpower” presents WVS percentages of respondents who said the most important reason people are poor is “laziness and lack of willpower.” As expected, Americans are much more likely to attribute poverty to not working hard enough.
Figure 3.7 Percentage of People Who Attribute Poverty to Laziness and Lack of Willpower
Source: Data from World Values Survey, 1997.
We could discuss many other values, but an important one concerns how much a society values women’s employment outside the home. The WVS asked respondents whether they agree that “when jobs are scarce men should have more right to a job than women.” Figure 3.8 “Percentage of People Who Disagree That Men Have More Right to a Job Than Women When Jobs Are Scarce” shows that U.S. residents are more likely than those in nations with more traditional views of women to disagree with this statement.
Figure 3.8 Percentage of People Who Disagree That Men Have More Right to a Job Than Women When Jobs Are Scarce
Source: Data from World Values Survey, 2002.
• Artifacts
The last element of culture is the artifacts, or material objects, that constitute a society’s material culture. In the most simple societies, artifacts are largely limited to a few tools, the huts people live in, and the clothing they wear. One of the most important inventions in the evolution of society was the wheel. Figure 3.9 “Primary Means of Moving Heavy Loads” shows that very few of the societies in the SCCS use wheels to move heavy loads over land, while the majority use human power and about one-third use pack animals.
Figure 3.9 Primary Means of Moving Heavy Loads
Source: Data from Standard Cross-Cultural Sample.
Although the wheel was a great invention, artifacts are much more numerous and complex in industrial societies. Because of technological advances during the past two decades, many such societies today may be said to have a wireless culture, as smartphones, netbooks and laptops, and GPS devices now dominate so much of modern life. The artifacts associated with this culture were unknown a generation ago. Technological development created these artifacts and new language to describe them and the functions they perform. Today’s wireless artifacts in turn help reinforce our own commitment to wireless technology as a way of life, if only because children are now growing up with them, often even before they can read and write.
The iPhone is just one of the many notable cultural artifacts in today’s wireless world. Technological development created these artifacts and new language to describe them and their functions—for example, “There’s an app for that!” Philip Brooks – iPhone – CC BY-NC-ND 2.0.
Sometimes people in one society may find it difficult to understand the artifacts that are an important part of another society’s culture. If a member of a tribal society who had never seen a cell phone, or who had never even used batteries or electricity, were somehow to visit the United States, she or he would obviously have no idea of what a cell phone was or of its importance in almost everything we do these days. Conversely, if we were to visit that person’s society, we might not appreciate the importance of some of its artifacts.
In this regard, consider once again India’s cows, discussed in the news article that began this chapter. As the article mentioned, people from India consider cows holy, and they let cows roam the streets of many cities. In a nation where hunger is so rampant, such cow worship is difficult to understand, at least to Americans, because a ready source of meat is being ignored.
Anthropologist Marvin Harris (1974) advanced a practical explanation for India’s cow worship. Millions of Indians are peasants who rely on their farms for their food and thus their existence. Oxen and water buffalo, not tractors, are the way they plow their fields. If their ox falls sick or dies, farmers may lose their farms. Because, as Harris observes, oxen are made by cows, it thus becomes essential to preserve cows at all costs. In India, cows also act as an essential source of fertilizer, to the tune of 700 million tons of manure annually, about half of which is used for fertilizer and the other half of which is used as fuel for cooking. Cow manure is also mixed with water and used as flooring material over dirt floors in Indian households. For all of these reasons, cow worship is not so puzzling after all, because it helps preserve animals that are very important for India’s economy and other aspects of its way of life.
According to anthropologist Marvin Harris, cows are worshipped in India because they are such an important part of India’s agricultural economy. Francisco Martins – Cow in Mumbai – CC BY-NC 2.0.
If Indians exalt cows, many Jews and Muslims feel the opposite about pigs: they refuse to eat any product made from pigs and so obey an injunction from the Old Testament of the Bible and from the Koran. Harris thinks this injunction existed because pig farming in ancient times would have threatened the ecology of the Middle East. Sheep and cattle eat primarily grass, while pigs eat foods that people eat, such as nuts, fruits, and especially grains. In another problem, pigs do not provide milk and are much more difficult to herd than sheep or cattle. Next, pigs do not thrive well in the hot, dry climate in which the people of the Old Testament and Koran lived. Finally, sheep and cattle were a source of food back then because beyond their own meat they provided milk, cheese, and manure, and cattle were also used for plowing. In contrast, pigs would have provided only their own meat. Because sheep and cattle were more “versatile” in all of these ways, and because of the other problems pigs would have posed, it made sense for the eating of pork to be prohibited.
In contrast to Jews and Muslims, at least one society, the Maring of the mountains of New Guinea, is characterized by “pig love.” Here pigs are held in the highest regard. The Maring sleep next to pigs, give them names and talk to them, feed them table scraps, and once or twice every generation have a mass pig sacrifice that is intended to ensure the future health and welfare of Maring society. Harris explains their love of pigs by noting that their climate is ideally suited to raising pigs, which are an important source of meat for the Maring. Because too many pigs would overrun the Maring, their periodic pig sacrifices help keep the pig population to manageable levels. Pig love thus makes as much sense for the Maring as pig hatred did for people in the time of the Old Testament and the Koran.
Key Takeaways
• The major elements of culture are symbols, language, norms, values, and artifacts.
• Language makes effective social interaction possible and influences how people conceive of concepts and objects.
• Major values that distinguish the United States include individualism, competition, and a commitment to the work ethic.
For Your Review
1. How and why does the development of language illustrate the importance of culture and provide evidence for the sociological perspective?
2. Some people say the United States is too individualistic and competitive, while other people say these values are part of what makes America great. What do you think? Why?
Attributions
Sociology by the University of Minnesota under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/03%3A_The_Sociocultural_Dimension/3.02%3A_Chapter_4-_The_Elements_of_Culture.txt |
Chapter 5 Learning Objectives
• Describe the fundamental process of social categorization and its influence on thoughts, feelings, and behavior.
• Define stereotypes and describe the ways that stereotypes are measured.
• Review the ways that stereotypes influence our behavior.
Thinking about others in terms of their group memberships is known as social categorizationthe natural cognitive process by which we place individuals into social groups. Social categorization occurs when we think of someone as a man (versus a woman), an old person (versus a young person), a Black person (versus an Asian or White person), and so on (Allport, 1954/1979). Just as we categorize objects into different types, so we categorize people according to their social group memberships. Once we do so, we begin to respond to those people more as members of a social group than as individuals.
Imagine for a moment that two college students, John and Sarah, are talking at a table in the student union at your college or university. At this point, we would probably not consider them to be acting as group members, but rather as two individuals. John is expressing his opinions, and Sarah is expressing hers. Imagine, however, that as the conversation continues, Sarah brings up an assignment that she is completing for her women’s studies class. It turns out that John does not think there should be a women’s studies program at the college, and he tells Sarah so. He argues that if there is a women’s studies program, then there should be a men’s studies program too. Furthermore, he argues that women are getting too many breaks in job hiring and that qualified men are the targets of discrimination. Sarah feels quite the contrary—arguing that women have been the targets of sexism for many, many years and even now do not have the same access to high-paying jobs that men do.
You can see that an interaction that began at individual level, as two individuals conversing, has now turned to the group level, in which John has begun to consider himself as a man, and Sarah has begun to consider herself as a woman. In short, Sarah is now arguing her points not so much for herself as she is as a representative of one of her ingroups—namely, women—and John is acting as a representative of one of his ingroups—namely, men. Sarah feels that her positions are correct, and she believes they are true not only for her but for women in general. And the same is true of John. You can see that these social categorizations may create some potential for misperception, and perhaps even hostility. And John and Sarah may even change their opinions about each other, forgetting that they really like each other as individuals, because they are now responding more as group members with opposing views.
Imagine now that while John and Sarah are still talking, some students from another college, each wearing the hats and jackets of that school, show up in the student union. The presence of these outsiders might change the direction of social categorization entirely, leading both John and Sarah to think of themselves as students at their own college. And this social categorization might lead them to become more aware of the positive characteristics of their college (the excellent basketball team, lovely campus, and intelligent students) in comparison with the characteristics of the other school. Now, rather than perceiving themselves as members of two different groups (men versus women), John and Sarah might suddenly perceive themselves as members of the same social category (students at their college).
Perhaps this example will help you see the flexibility of social categorization. We sometimes think of our relationships with others at the individual level and sometimes at the group level. And which groups we use in social categorization can change over time and in different situations. I think you would agree that you are more likely to categorize yourself as a member of your college or university when your basketball or football team has just won a really important game, or at your commencement day ceremony, than you would on a normal evening out with your family. In these cases, your membership as a university student is simply more salient and important than it is every day, and you are more likely to categorize yourself accordingly.
• Spontaneous Social Categorization
Social categorization occurs spontaneously, without much thought on our part (Crisp & Hewstone, 2007). Shelley Taylor and her colleagues (Taylor, Fiske, Etcoff, & Ruderman, 1978) showed their research participants a slide and tape presentation of three male and three female college students who had supposedly participated in a discussion group. During the presentation, each member of the discussion group made a suggestion about how to advertise a college play. The statements were controlled so that across all the research participants, the statements made by the men and the women were of equal length and quality. Furthermore, one half of the participants were told that when the presentation was over, they would be asked to remember which person had made which suggestion, whereas the other half of the participants were told merely to observe the interaction without attending to anything in particular.
After they had viewed all the statements made by the individuals in the discussion group, the research participants were given a memory test (this was entirely unexpected for the participants who had not been given memory instructions). The participants were shown the list of all the statements that had been made, along with the pictures of each of the discussion group members, and were asked to indicate who had made each of the statements. The research participants were not very good at this task, and yet when they made mistakes, these errors were very systematic.
As you can see in Table 12.1 “Name Confusions”, the mistakes were such that the statements that had actually been made by a man were more frequently wrongly attributed to another man in the group than to another woman, and the statements actually made by a woman were more frequently attributed to other women in the group than to a man. The participants evidently categorized the speakers by their gender, leading them to make more within-gender than across-gender confusions.
Interestingly, and suggesting that categorization is occurring all the time, the instructions that the participants had been given made absolutely no difference. There was just as much categorization for those who were not given any instructions as for those who were told to remember who said what. Other research using this technique has found that we spontaneously categorize each other on the basis of many other group memberships, including race, academic status (student versus teacher), social roles, and other social categories (Fiske, Haslam, & Fiske, 1991; Stangor, Lynch, Duan, & Glass, 1992).
Table 12.1 Name Confusions
Instructions Within race errors Between race errors
Memory 5.78 4.29
No memory 6.57 4.36
Taylor, Fiske, Etcoff, and Ruderman (1978) demonstrated that people categorized others spontaneously. Even without any instructions to categorize, people nevertheless confused others by their sex.
The conclusion is simple, if perhaps obvious: Social categorization is occurring all around us all the time. Indeed, social categorization occurs so quickly that people may have difficulty not thinking about others in terms of their group memberships (see Figure 12.3).
Figure 12.3 If you are like most people, you will have a strong desire to categorize this person as either male or female. drburtoni – Transgenders March, Portland 2015 SERIES – CC BY-NC-ND 2.0.
• The Benefits of Social Categorization
The tendency to categorize others is normally quite useful. In some cases, we categorize because doing so provides us with information about the characteristics of people who belong to certain social groups (Lee, Jussim, & McCauley, 1995). If you found yourself lost in a city, you might look for a police officer or a taxi driver to help you find your way. In this case, social categorization would probably be useful because a police officer or a taxi driver might be particularly likely to know the layout of the city streets. Of course, using social categories will only be informative to the extent that the stereotypes held by the individual about that category are accurate. If police officers were actually not that knowledgeable about the city layout, then using this categorization would not be informative.
It has been argued that there is a kernel of truth in most stereotypes, and this seems to be the case. There is a correlation between how group members perceive the stereotypes of their own groups and how people from other groups perceive those same stereotypes (Judd & Park, 1993; Swim, 1994). This truth may come in part from the roles that individuals play in society. For instance, the stereotypes (which are held by many people) that women are “nurturing” and that men are “dominant” may occur in part because, on average, men and women find themselves in different social roles within a culture (Eagly & Steffen, 1984). In most cultures, men are more likely to be in higher-status occupations, such as doctors and lawyers, whereas women are more likely to play the role of homemakers and child-care workers. In this sense, the stereotypes are at least partly true for many of the members of the social category, in terms of their actual behaviors. Because men are more likely to be leaders than are women, they may well be, on average, more dominant; and because women are more likely to take care of children, they may, on average, act in a more nurturing way than do men.
On the other hand, we sometimes categorize others not because it seems to provide more information about them but because we may not have the time (or the motivation) to do anything more thorough. Using our stereotypes to size up another person might simply make our life easier (Macrae, Bodenhausen, Milne, & Jetten, 1994). According to this approach, thinking about other people in terms of their social category memberships is a functional way of dealing with the world—things are complicated, and we reduce complexity by relying on our stereotypes.
• The Negative Outcomes of Social Categorization
Although thinking about others in terms of their social category memberships has some potential benefits for the person who does the categorizing, categorizing others, rather than treating them as unique individuals with their own unique characteristics, has a wide variety of negative, and often very unfair, outcomes for those who are categorized.
One problem is that social categorization distorts our perceptions such that we tend to exaggerate the differences between people from different social groups while at the same time perceiving members of groups (and particularly outgroups) as more similar to each other than they actually are. This overgeneralization makes it more likely that we will think about and treat all members of a group the same way. Tajfel and Wilkes (1963) performed a simple experiment that provided a picture of the potential outcomes of categorization. As you can see in Figure 12.4 “Perceptual Accentuation”, the experiment involved having research participants judge the length of six lines. In one of the experimental conditions, participants simply saw six lines, whereas in the other condition, the lines were systematically categorized into two groups—one comprising the three shorter lines and one comprising the three longer lines.
Figure 12.4 Perceptual Accentuation
Lines C and D were seen as the same length in the noncategorized condition, but line C was perceived as longer than line D when the lines were categorized into two groups. From Tajfel (1970).
Tajfel found that the lines were perceived differently when they were categorized, such that the differences between the groups and the similarities within the groups were emphasized. Specifically, he found that although lines C and D (which are actually the same length) were perceived as equal in length when the lines were not categorized, line D was perceived as being significantly longer than line C in the condition in which the lines were categorized. In this case, categorization into two groups—the “short lines group” and the “long lines group”—produced a perceptual bias such that the two groups of lines were seen as more different than they really were.
Similar effects occur when we categorize other people. We tend to see people who belong to the same social group as more similar than they actually are, and we tend to judge people from different social groups as more different than they actually are. The tendency to see members of social groups as similar to each other is particularly strong for members of outgroups, resulting in outgroup homogeneitythe tendency to view members of outgroups as more similar to each other than we see members of ingroups (Linville, Salovey, & Fischer, 1986; Ostrom & Sedikides, 1992; Meissner & Brigham, 2001). I’m sure you’ve had this experience yourself, when you found yourself thinking or saying, “Oh, them, they’re all the same!”
Patricia Linville and Edward Jones (1980) gave research participants a list of trait terms and asked them to think about either members of their own group (e.g., Blacks) or members of another group (e.g., Whites) and to place the trait terms into piles that represented different types of people in the group. The results of these studies, as well as other studies like them, were clear: People perceive outgroups as more homogeneous than the ingroup. Just as White people used fewer piles of traits to describe Blacks than Whites, young people used fewer piles of traits to describe elderly people than they did young people, and students used fewer piles for members of other universities than they did for members of their own university.
Outgroup homogeneity occurs in part because we don’t have as much contact with outgroup members as we do with ingroup members, and the quality of interaction with outgroup members is often more superficial. This prevents us from really learning about the outgroup members as individuals, and as a result, we tend to be unaware of the differences among the group members. In addition to learning less about them because we see and interact with them less, we routinely categorize outgroup members, thus making them appear more cognitively similar (Haslam, Oakes, & Turner, 1996).
Once we begin to see the members of outgroups as more similar to each other than they actually are, it then becomes very easy to apply our stereotypes to the members of the groups without having to consider whether the characteristic is actually true of the particular individual. If men think that women are all alike, then they may also think that they all have the same characteristics—they’re all “emotional” and “weak.” And women may have similarly simplified beliefs about men (they’re “insensitive,” “unwilling to commit,” etc.). The outcome is that the stereotypes become linked to the group itself in a set of mental representations (Figure 12.5). The stereotypes are “pictures in our heads” of the social groups (Lippman, 1922). These beliefs just seem right and natural, even though they are frequently distorted overgeneralizations (Hirschfeld, 1996; Yzerbyt, Schadron, Leyens, & Rocher, 1994).
Figure 12.5 opacity – oral histories presenter – CC BY-NC-ND 2.0.
Stereotypes are the beliefs associated with social categories. The figure shows links between the social category of college professors and its stereotypes as a type of neural network or schema. The representation also includes one image (or exemplar) of a particular college professor whom the student knows.
Our stereotypes and prejudices are learned through many different processes. This multiplicity of causes is unfortunate because it makes stereotypes and prejudices even more likely to form and harder to change. For one, we learn our stereotypes in part through our communications with parents and peers (Aboud & Doyle, 1996) and from the behaviors we see portrayed in the media (Brown, 1995). Even 5-year-old children have learned cultural norms about the appropriate activities and behaviors for boys and girls and also have developed stereotypes about age, race, and physical attractiveness (Bigler & Liben, 2006). And there is often good agreement about the stereotypes of social categories among the individuals within a given culture. In one study assessing stereotypes, Stephanie Madon and her colleagues (Madon et al., 2001) presented U.S. college students with a list of 84 trait terms and asked them to indicate for which groups each trait seemed appropriate (Figure 12.6 “Current Stereotypes Held by College Students”). The participants tended to agree about what traits were true of which groups, and this was true even for groups of which the respondents were likely to never have met a single member (Arabs and Russians). Even today, there is good agreement about the stereotypes of members of many social groups, including men and women and a variety of ethnic groups.
Figure 12.6 Current Stereotypes Held by College Students
Americans % Blacks % Italians %
Materialistic 53.6 Musical 27.6 Loyal to family ties 62.7
Lazy 30.4 Pleasure loving 26 Tradition loving 47.5
Individualistic 28.6 Loud 20.7 Passionate 39
Pleasure loving 28 Aggressive 15.5 Religious 37.3
Industrious 23.2 Artistic 13.8 Quick tempered 35.6
Germans % Jews % Chinese %
Intelligent 45.8 Very religious 52.5 Intelligent 60.3
Industrious 37.3 Intelligent 49.2 Loyal to family ties 41.4
Nationalistic 30.5 Tradition loving 32.2 Reserved 36.2
Scientifically minded 27.1 Shrewd 30.5 Industrious 32.8
Methodical 20.3 Loyal to family ties 28.8 Tradition loving 31
Once they become established, stereotypes (like any other cognitive representation) tend to persevere. We begin to respond to members of stereotyped categories as if we already knew what they were like. Yaacov Trope and Eric Thompson (1997) found that individuals addressed fewer questions to members of categories about which they had strong stereotypes (as if they already knew what these people were like) and that the questions they did ask were likely to confirm the stereotypes they already had.
In other cases, stereotypes are maintained because information that confirms our stereotypes is better remembered than information that disconfirms them. When we see members of social groups perform behaviors, we tend to better remember information that confirms our stereotypes than we remember information that disconfirms our stereotypes (Fyock & Stangor, 1994). If we believe that women are bad drivers and we see a woman driving poorly, then we tend to remember it, but when we see a woman who drives particularly well, we tend to forget it. This is of course another example of the general principle of assimilation—we tend to perceive the world in ways that make it fit our existing beliefs more easily than we change our beliefs to fit the reality around us.
And stereotypes become difficult to change because they are so important to us—they become an integral and important part of our everyday lives in our culture. Stereotypes are frequently expressed on TV, in movies, and in chat rooms and blogs, and we learn a lot of our beliefs from these sources. Our friends also tend to hold beliefs similar to ours, and we talk about these beliefs when we get together with them (Schaller & Conway, 1999). In short, stereotypes and prejudice are powerful largely because they are important social norms that are part of our culture (Guimond, 2000).
Because they are so highly cognitively accessible, and because they seem so “right,” our stereotypes easily influence our judgments of and responses to those we have categorized. The social psychologist John Bargh once described stereotypes as “cognitive monsters” because their activation was so powerful and because the activated beliefs had such insidious influences on social judgment (Bargh, 1999). Making things even more difficult, stereotypes are strongest for the people who are in most need of change—the people who are most prejudiced (Lepore & Brown, 1997).
Because stereotypes and prejudice often operate out of our awareness, and also because people are frequently unwilling to admit that they hold them, social psychologists have developed methods for assessing them indirectly. In the next section we will consider two of these approaches—the bogus pipeline procedure and the Implicit Association Test (IAT).
Research Focus
Measuring Stereotypes Indirectly
• >One difficulty in measuring stereotypes and prejudice is that people may not tell the truth about their beliefs. Most people do not want to admit—either to themselves or to others—that they hold stereotypes or that they are prejudiced toward some social groups. To get around this problem, social psychologists make use of a number of techniques that help them measure these beliefs more subtly and indirectly.
• >One indirect approach to assessing prejudice is called the bogus pipeline procedure (Jones & Sigall, 1971). In this procedure, the experimenter first convinces the participants that he or he has access to their “true” beliefs, for instance, by getting access to a questionnaire that they completed at a prior experimental session. Once the participants are convinced that the researcher is able to assess their “true” attitudes, it is expected that they will be more honest in answering the rest of the questions they are asked because they want to be sure that the researcher does not catch them lying. The bogus pipeline procedure suggests that people may frequently mask their negative beliefs in public—people express more prejudice when they are in the bogus pipeline than they do when they are asked the same questions more directly.
• >Other indirect measures of prejudice are also frequently used in social psychological research, for instance—assessing nonverbal behaviors such as speech errors or physical closeness. One common measure involves asking participants to take a seat on a chair near a person from a different racial or ethnic group and measuring how far away the person sits (Sechrist & Stangor, 2001; Word, Zanna, & Cooper, 1974). People who sit farther away are assumed to be more prejudiced toward the members of the group.
• >Because our stereotypes are activated spontaneously when we think about members of different social groups, it is possible to use reaction-time measures to assess this activation and thus to learn about people’s stereotypes and prejudices. In these procedures, participants are asked to make a series of judgments about pictures or descriptions of social groups and then to answer questions as quickly as they can, but without making mistakes. The speed of these responses is used to determine an individual’s stereotypes or prejudice.
• >The most popular reaction-time implicit measure of prejudice—the Implicit Association Test (IAT)—is frequently used to assess stereotypes and prejudice (Nosek, Greenwald, & Banaji, 2007). In the IAT, participants are asked to classify stimuli that they view on a computer screen into one of two categories by pressing one of two computer keys, one with their left hand and one with their right hand. Furthermore, the categories are arranged such that the responses to be answered with the left and right buttons either “fit with” (match) the stereotype or do not “fit with” (mismatch) the stereotype. For instance, in one version of the IAT, participants are shown pictures of men and women and also shown words related to gender stereotypes (e.g., strong, leader, or powerful for men and nurturing, emotional, or weak for women). Then the participants categorize the photos (“Is this picture a picture of a man or a woman?”) and answer questions about the stereotypes (“Is this the word strong?) by pressing either the Yes button or the No button using either their left hand or their right hand.
• >When the responses are arranged on the screen in a “matching” way, such that the male category and the “strong” category are on the same side of the screen (e.g., on the right side), participants can do the task very quickly and they make few mistakes. It’s just easier, because the stereotypes are matched or associated with the pictures in a way that makes sense. But when the images are arranged such that the women and the strong categories are on the same side, whereas the men and the weak categories are on the other side, most participants make more errors and respond more slowly. The basic assumption is that if two concepts are associated or linked, they will be responded to more quickly if they are classified using the same, rather than different, keys.
• >Implicit association procedures such as the IAT show that even participants who claim that they are not prejudiced do seem to hold cultural stereotypes about social groups. Even Black people themselves respond more quickly to positive words that are associated with White rather than Black faces on the IAT, suggesting that they have subtle racial prejudice toward Blacks.
• >Because they hold these beliefs, it is possible—although not guaranteed—that they may use them when responding to other people, creating a subtle and unconscious type of discrimination. Although the meaning of the IAT has been debated (Tetlock & Mitchell, 2008), research using implicit measures does suggest that—whether we know it or not, and even though we may try to control them when we can—our stereotypes and prejudices are easily activated when we see members of different social categories (Barden, Maddux, Petty, & Brewer, 2004).
• >Do you hold implicit prejudices? Try the IAT yourself, here: https://implicit.harvard.edu/implicit
• Although in some cases the stereotypes that are used to make judgments might actually be true of the individual being judged, in many other cases they are not. Stereotyping is problematic when the stereotypes we hold about a social group are inaccurate overall, and particularly when they do not apply to the individual who is being judged (Stangor, 1995). Stereotyping others is simply unfair. Even if many women are more emotional than are most men, not all are, and it is not right to judge any one woman as if she is.
In the end, stereotypes become self-fulfilling prophecies, such that our expectations about the group members make the stereotypes come true (Snyder, Tanke, & Berscheid, 1977; Word, Zanna, & Cooper, 1974). Once we believe that men make better leaders than women, we tend to behave toward men in ways that makes it easier for them to lead. And we behave toward women in ways that makes it more difficult for them to lead. The result? Men find it easier to excel in leadership positions, whereas women have to work hard to overcome the false beliefs about their lack of leadership abilities (Phelan & Rudman, 2010). And self-fulfilling prophecies are ubiquitous—even teachers’ expectations about their students’ academic abilities can influence the students’ school performance (Jussim, Robustelli, & Cain, 2009).
Of course, you may think that you personally do not behave in these ways, and you may not. But research has found that stereotypes are often used out of our awareness, which makes it very difficult for us to correct for them. Even when we think we are being completely fair, we may nevertheless be using our stereotypes to condone discrimination (Chen & Bargh, 1999). And when we are distracted or under time pressure, these tendencies become even more powerful (Stangor & Duan, 1991).
Furthermore, attempting to prevent our stereotype from coloring our reactions to others takes effort. We experience more negative affect (particularly anxiety) when we are with members of other groups than we do when we are with people from our own groups, and we need to use more cognitive resources to control our behavior because of our anxiety about revealing our stereotypes or prejudices (Butz & Plant, 2006; Richeson & Shelton, 2003). When we know that we need to control our expectations so that we do not unintentionally stereotype the other person, we may try to do so—but doing so takes effort and may frequently fail (Macrae, Bodenhausen, Milne, & Jetten, 1994).
Social Psychology in the Public Interest
Stereotype Threat
• >Our stereotypes influence not only our judgments of others but also our beliefs about ourselves, and even our own performance on important tasks. In some cases, these beliefs may be positive, and they have the effect of making us feel more confident and thus better able to perform tasks. Because Asian students are aware of the stereotype that “Asians are good at math,” reminding them of this fact before they take a difficult math test can improve their performance on the test (Walton & Cohen, 2003). On the other hand, sometimes these beliefs are negative, and they create negative self-fulfilling prophecies such that we perform more poorly just because of our knowledge about the stereotypes.
• >One of the long-standing puzzles in the area of academic performance concerns why Black students perform more poorly on standardized tests, receive lower grades, and are less likely to remain in school in comparison with White students, even when other factors such as family income, parents’ education, and other relevant variables are controlled. Claude Steele and Joshua Aronson (1995) tested the hypothesis that these differences might be due to the activation of negative stereotypes. Because Black students are aware of the (inaccurate) stereotype that “Blacks are intellectually inferior to Whites,” this stereotype might create a negative expectation, which might interfere with their performance on intellectual tests through fear of confirming that stereotype.
• >In support of this hypothesis, Steele and Aronson’s research revealed that Black college students performed worse (in comparison with their prior test scores) on math questions taken from the Graduate Record Examination (GRE) when the test was described to them as being “diagnostic of their mathematical ability” (and thus when the stereotype was relevant) but that their performance was not influenced when the same questions were framed as “an exercise in problem solving.” And in another study, Steele and Aronson found that when Black students were asked to indicate their race before they took a math test (again activating the stereotype), they performed more poorly than they had on prior exams, whereas the scores of White students were not affected by first indicating their race.
• >Steele and Aronson argued that thinking about negative stereotypes that are relevant to a task that one is performing creates stereotype threat—performance decrements that are caused by the knowledge of cultural stereotypes. That is, they argued that the negative impact of race on standardized tests may be caused, at least in part, by the performance situation itself. Because the threat is “in the air,” Black students may be negatively influenced by it.
• >Research has found that the experience of stereotype threat can help explain a wide variety of performance decrements among those who are targeted by negative stereotypes. For instance, when a math task is described as diagnostic of intelligence, Latinos and particularly Latinas perform more poorly than do Whites (Gonzales, Blanton, & Williams, 2002). Similarly, when stereotypes are activated, children with low socioeconomic status perform more poorly in math than do those with high socioeconomic status, and psychology students perform more poorly than do natural science students (Brown, Croizet, Bohner, Fournet, & Payne, 2003). Even groups who typically enjoy advantaged social status can be made to experience stereotype threat. White men performed more poorly on a math test when they were told that their performance would be compared with that of Asian men (Aronson, Lustina, Good, Keough, & Steele, 1999), and Whites performed more poorly than Blacks on a sport-related task when it was described to them as measuring their natural athletic ability (Stone, 2002).
• >Stereotype threat is created in situations that pose a significant threat to self-concern, such that our perceptions of ourselves as important, valuable, and capable individuals are threatened. In these situations, there is a discrepancy between our positive concept of our skills and abilities and the negative stereotypes suggesting poor performance. When our stereotypes lead us to be believe that we are likely to perform poorly on a task, we experience a feeling of unease and status threat.
• >Research has found that stereotype threat is caused by both cognitive and affective factors. On the cognitive side, individuals who are experiencing stereotype threat show an impairment in cognitive processing that is caused by increased vigilance toward the environment and attempts to suppress their stereotypical thoughts. On the affective side, stereotype threat creates stress as well as a variety of affective responses including anxiety (Schmader, Johns, & Forbes, 2008).
• >Stereotype threat is not, however, absolute—we can get past it if we try. What is important is to reduce the self-concern that is engaged when we consider the relevant negative stereotypes. Manipulations that affirm positive characteristics about oneself or one’s group are successful at reducing stereotype threat (Alter, Aronson, Darley, Rodriguez, & Ruble, 2010; Greenberg et al., 2003; McIntyre, Paulson, & Lord, 2003). In fact, just knowing that stereotype threat exists and may influence performance can help alleviate its negative impact (Johns, Schmader, & Martens, 2005).
Key Takeaways
• Beliefs about the characteristics of the groups and the members of those groups are known as stereotypes.
• Prejudice refers to an unjustifiable negative attitude toward an outgroup.
• Stereotypes and prejudice may create discrimination.
• Stereotyping and prejudice begin from social categorization—the natural cognitive process by which we place individuals into social groups.
• Social categorization influences our perceptions of groups—for instance, the perception of outgroup homogeneity.
• Once our stereotypes and prejudices become established, they are difficult to change and may lead to self-fulfilling prophecies, such that our expectations about the group members make the stereotypes come true.
• Stereotypes may influence our performance on important tasks through stereotype threat.
Exercises and Critical Thinking
1. Look again at the pictures in Figure 12.2, and consider your thoughts and feelings about each person. What are your stereotypes and prejudices about them? Do you think your stereotypes are accurate?
2. On which (if any) social categories do you categorize others? Why do you (or don’t you) categorize? Is your behavior fair or unfair to the people you are categorizing?
3. Think of a task that one of the social groups to which you belong is considered to be particularly good (or poor) at. Do you think the cultural stereotypes about your group have ever influenced your performance on a task?
Attribution
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Chapter 6 Learning Objectives
• Review the causes and outcomes of ingroup favoritism.
• Summarize the results of Henri Tajfel’s research on minimal groups.
• Outline the personality and cultural variables that influence ingroup favoritism.
We have now seen that social categorization occurs whenever we think about others in terms of their category memberships rather than on the basis of other, more personal information about the individual. And we have seen that social categorization can have a variety of negative consequences for the people who are the targets of our stereotypes. But social categorization becomes even more important, and has even more powerful effects upon our reactions to others, when the categorization becomes more emotionally involving, and particularly when the categorization involves categorization into liked ingroups and potentially disliked outgroups (Amodio & Devine, 2006).
Because our ancestors lived in small social groups that were frequently in conflict with other groups, it was evolutionarily functional for them to view members of other groups as different and potentially dangerous (Brewer & Caporael, 2006; Navarrete, Kurzban, Fessler, & Kirkpatrick, 2004). Differentiating between “us” and “them” probably helped keep us safe and free from disease, and as a result, the human brain became very efficient in making these distinctions (Mahajan et al., 2011; Phelps et al., 2000; Van Vugt & Schaller, 2008; Zaraté, Stoever, MacLin, & Arms-Chavez, 2008). The problem is that these naturally occurring tendencies may lead us to prefer people who are like us, and in some cases even to unfairly reject people from outgroups.
• Liking “Us” More Than “Them”: Ingroup Favoritism
In his important research on group perceptions, Henri Tajfel and his colleagues (Tajfel, Billig, Bundy, & Flament, 1971) demonstrated how incredibly powerful the role of self-concern is in group perceptions. He found that just dividing people into arbitrary groups produces ingroup favoritism – the tendency to respond more positively to people from our ingroups than we do to people from outgroups.
In Tajfel’s research, small groups of high school students came to his laboratory for a study supposedly concerning “artistic tastes.” The students were first shown a series of paintings by two contemporary artists, Paul Klee and Wassily Kandinsky. Supposedly on the basis of their preferences for each painting, the students were divided into two groups (they were called the X group and the Y group). Each boy was told which group he had been assigned to and that different boys were assigned to different groups. But none of them were told the group memberships of any of the other boys.
The boys were then given a chance to allocate points to other boys in their own group and to boys in the other group (but never to themselves) using a series of payoff matrices, such as those shown in Figure 12.7 “Examples of Matrices Used in the Minimal Intergroup Studies of Tajfel and His Colleagues”. The charts divided a given number of rewards between two boys, and the boys thought that the rewards would be used to determine how much each boy would be paid for his participation. In some cases, the division was between two boys in the boy’s own group (the ingroup); in other cases, the division was between two boys who had been assigned to the other group (the outgroup); and in still other cases, the division was between a boy in the ingroup and a boy in the outgroup. Tajfel then examined the goals that the boys used when they divided up the points.
Figure 12.7 Examples of Matrices Used in the Minimal Intergroup Studies of Tajfel and His Colleagues From Tajfel (1970).
• A comparison of the boys’ choices in the different matrices showed that they allocated points between two boys in the ingroup or between two boys in the outgroup in an essentially fair way, so that each boy got the same amount. However, fairness was not the predominant approach when dividing points between ingroup and outgroup. In this case, rather than exhibiting fairness, the boys displayed ingroup favoritism, such that they gave more points to other members of their own group in relationship to boys in the other group. For instance, the boys might assign 8 points to the ingroup boy and only 3 points to the outgroup boy, even though the matrix also contained a choice in which they could give the ingroup and the outgroup boys 13 points each. In short, the boys preferred to maximize the gains of the other boys in their own group in comparison with the boys in the outgroup, even if doing so meant giving their own group members fewer points than they could otherwise have received.
Perhaps the most striking part of Tajfel’s results is that ingroup favoritism was found to occur on the basis of such arbitrary and unimportant groupings. In fact, ingroup favoritism occurs even when the assignment to groups is on such trivial things as whether people “overestimate” or “underestimate” the number of dots shown on a display, or on the basis of a completely random coin toss (Billig & Tajfel, 1973; Locksley, Ortiz, & Hepburn, 1980). Tajfel’s research, as well other research demonstrating ingroup favoritism, provides a powerful demonstration of a very important social psychological process: Groups exist simply because individuals perceive those groups as existing. Even in a case where there really is no group (at least no meaningful group in any real sense), we still perceive groups and still demonstrate ingroup favoritism.
• The Outcomes of Ingroup Favoritism
The tendency to favor their ingroup develops quickly in young children, beginning at the age of 3 years and increasing up to about 6 years of age, and almost immediately begins to influence their behavior (Aboud, 2003; Aboud & Amato, 2001). Young children show greater liking for peers of their own sex and race and typically play with same-sex others after the age of 3. And there is a norm that we should favor our ingroups: People like people who express ingroup favoritism better than those who are more egalitarian (Castelli & Carraro, 2010). Ingroup favoritism is found for many different types of social groups, in many different settings, on many different dimensions, and in many different cultures (Bennett et al., 2004; Pinter & Greenwald, 2011). Ingroup favoritism also occurs on trait ratings, such that ingroup members are rated as having more positive characteristics than are outgroup members (Hewstone, 1990). People also take credit for the successes of other ingroup members, remember more positive than negative information about ingroups, are more critical of the performance of outgroup than of ingroup members, and believe that their own groups are less prejudiced than are outgroups (Shelton & Richeson, 2005).
People also talk differently about their ingroups than their outgroups, such that they describe the ingroup and its members as having broad positive traits (“We are generous and friendly”) but describe negative ingroup behaviors in terms of the specific behaviors of single group members (“Our group member, Bill, hit someone”) (Maass & Arcuri, 1996; Maass, Ceccarielli, & Rudin, 1996; von Hippel, Sekaquaptewa, & Vargas, 1997). These actions allow us to spread positive characteristics to all members of our ingroup but reserve negative aspects for individual group members, thereby protecting the group’s image.
People also make trait attributions in ways that benefit their ingroups, just as they make trait attributions that benefit themselves. This general tendency, known as the ultimate attribution error, results in the tendency for each of the competing groups to perceive the other group extremely and unrealistically negatively (Hewstone, 1990). When an ingroup member engages in a positive behavior, we tend to see it as a stable internal characteristic of the group as a whole. Similarly, negative behaviors on the part of the outgroup are seen as caused by stable negative group characteristics. On the other hand, negative behaviors from the ingroup and positive behaviors from the outgroup are more likely to be seen as caused by temporary situational variables or by behaviors of specific individuals and are less likely to be attributed to the group.
• Ingroup Favoritism Has Many Causes
Ingroup favoritism has a number of causes. For one, it is a natural part of social categorization—we categorize into ingroups and outgroups because it helps us simplify and structure our environment. It is easy, and perhaps even natural, to believe in the simple idea that “we are better than they are.” People who report that they have strong needs for simplifying their environments also show more ingroup favoritism (Stangor & Leary, 2006).
Ingroup favoritism also occurs at least in part because we belong to the ingroup and not the outgroup (Cadinu & Rothbart, 1996). We like people who are similar to ourselves, and we perceive other ingroup members as similar to us. This also leads us to favor other members of our ingroup, particularly when we can clearly differentiate them from members of outgroups. We may also prefer ingroups because they are more familiar to us (Zebrowitz, Bronstad, & Lee, 2007).
But the most important determinant of ingroup favoritism is simple self-enhancement. We want to feel good about ourselves, and seeing our ingroups positively helps us do so (Brewer, 1979). Being a member of a group that has positive characteristics provides us with the feelings of social identity – the positive self-esteem that we get from our group memberships. When we can identify ourselves as a member of a meaningful social group (even if it is a relatively trivial one), we can feel better about ourselves.
We are particularly likely to show ingroup favoritism when we are threatened or otherwise worried about our self-concept (Maner et al., 2005; Solomon, Greenberg, & Pyszczynski, 2000). And people express higher self-esteem after they have been given the opportunity to derogate outgroups, suggesting that ingroup favoritism does make us feel good (Lemyre & Smith, 1985; Rubin & Hewstone, 1998). Furthermore, when individuals feel that the value of their ingroup is being threatened, they respond as if they are trying to regain their own self-worth—by expressing more positive attitudes toward ingroups and more negative attitudes toward outgroups (Branscombe, Wann, Noel, & Coleman, 1993; Spears, Doosje, & Ellemers, 1997). Fein and Spencer (1997) found that participants expressed less prejudice after they had been given the opportunity to affirm and make salient an important and positive part of their own self-concept. In short, when our group seems to be good, we feel good; when our group seems to be bad, we feel bad.
In some cases, we may be able to feel good about our group memberships even when our own individual outcomes are not so positive. Schmitt, Silvia, and Branscombe (2000) had groups of female college students perform a creativity task and then gave them feedback indicating that although they themselves had performed very poorly, another woman in their group had performed very well. Furthermore, in some experimental conditions, the women were told that the research was comparing the scores of men and women (which was designed to increase categorization by gender). In these conditions, rather than being saddened by the upward comparison with the other woman, participants used the successful performance of the other woman to feel good about themselves, as women.
• When Ingroup Favoritism Does Not Occur
Although people have a general tendency to show ingroup favoritism, there are least some cases in which it does not occur. One situation in which ingroup favoritism is unlikely is when the members of the ingroup are clearly inferior to other groups on an important dimension. The players on a baseball team that has not won a single game all season are unlikely to be able to feel very good about themselves as a team and are pretty much forced to concede that the outgroups are better, at least as far as playing baseball is concerned. Members of low-status groups show less ingroup favoritism than do members of high-status groups and may even display outgroup favoritism, in which they admit that the other groups are better than they are (Clark & Clark, 1947).
Another case in which people judge other members of the ingroup very negatively occurs when a member of one’s own group behaves in a way that threatens the positive image of the ingroup. A student who behaves in a way unbecoming to university students, or a teammate who does not seem to value the importance of the team, is disparaged by the other group members, often more than the same behavior from an outgroup member would be. The strong devaluation of ingroup members who threaten the positive image and identity of the ingroup is known as the black sheep effect.
• Personality and Cultural Determinants of Ingroup Favoritism
To this point, we have considered ingroup favoritism as a natural part of everyday life. Because the tendency to favor the ingroup is a normal byproduct of self-concern, most people do, by and large, prefer their ingroups over outgroups. And yet not everyone is equally ingroup-favoring in all situations. There are a number of individual difference measures that predict prejudice, and these differences become particularly likely to show up under circumstances in which the desire to protect the self becomes important (Guimond, Dambrun, Michinov, & Duarte, 2003).
Some people are more likely than others to show ingroup favoritism because they are particularly likely to rely on their group memberships to create a positive social identity. These differences in group identification can be measured through self-report measures such as the Collective Self-Esteem Scale (Luhtanen & Crocker, 1992). The scale assesses the extent to which the individual values his or her memberships in groups in public and private ways, as well as the extent to which he or she gains social identity from those groups. People who score higher on the scale show more ingroup favoritism in comparison with those who score lower on it (Stangor & Thompson, 2002). The scale, from Luhtanen and Crocker (1992), is shown in Table 12.2 “The Collective Self-Esteem Scale”.
Table 12.2 The Collective Self-Esteem Scale
Membership I am a worthy member of the social groups I belong to.
I feel I don’t have much to offer to the social groups I belong to [R].
I am a cooperative participant in the social groups I belong to.
I often feel I’m an unclean member of my social group [R].
Private I often regret that I belong to some of the social groups I do [R].
In general, I’m glad to be a member of the social groups I belong to.
Overall, I often feel that the social groups of which I am a member are not worthwhile [R].
I feel good about the social groups I belong to.
Public Overall, my social groups are considered good by others.
Most people consider my social groups, on the average, to be more ineffective than other social groups [R].
In general, others respect the social groups that I am a member of.
In general, others think that the social groups I am a member of are unworthy [R].
Identity Overall, my group memberships have very little to do with how I feel about myself [R].
The social groups I belong to are an important reflection of who I am.
The social groups I belong to are unimportant in my sense of what kind of a person I am [R].
In general, belonging to social groups is an important part of my self-image.
[R] = Item is reversed before scoring.
Another personality dimension that relates to the desires to protect and enhance the self and the ingroup and thus also relates to greater ingroup favoritism, and in some cases prejudice toward outgroups, is the personality dimension of authoritarianism (Adorno, Frenkel-Brunswik, Levinson, & Sanford, 1950; Altemeyer, 1988). Authoritarianism is a personality dimension that characterizes people who prefer things to be simple rather than complex and who tend to hold traditional and conventional values. Authoritarians are ingroup-favoring in part because they have a need to self-enhance and in part because they prefer simplicity and thus find it easy to think simply: “We are all good and they are all less good.” Political conservatives tend to show more ingroup favoritism than do political liberals, perhaps because the former are more concerned with protecting the ingroup from threats posed by others (Jost, Glaser, Kruglanski, & Sulloway, 2003; Stangor & Leary, 2006).
People with strong goals toward other-concern display less ingroup favoritism and less prejudice. People who view it as particularly important to connect with and respect other people—those who are more focused on tolerance and fairness toward others—are less ingroup-favoring and more positive toward the members of groups other than their own. The desire to be fair and to accept others can be assessed by individual difference measures such as desire to control one’s prejudice (Plant & Devine, 1998) and humanism (Katz & Hass, 1988).
Social dominance orientation (SDO) is a personality variable that refers to the tendency to see and to accept inequality among different groups (Pratto, Sidanius, Stallworth, & Malle, 1995). People who score high on measures of SDO believe that there are and should be status differences among social groups, and they do not see these as wrong. High SDO individuals agree with statements such as “Some groups of people are simply inferior to other groups,” “In getting what you want, it is sometimes necessary to use force against other groups,” and “It’s OK if some groups have more of a chance in life than others.” Those who are low on SDO, on the other hand, believe that all groups are relatively equal in status and tend to disagree with these statements. People who score higher on SDO also show greater ingroup favoritism.
Stereotyping and prejudice also varies across cultures. Spencer-Rodgers, Williams, Hamilton, Peng, and Wang (2007) tested the hypothesis that Chinese participants, because of their collectivist orientation, would find social groups more important than would Americans (who are more individualistic) and that as a result, they would be more likely to infer personality traits on the basis of group membership—that is, to stereotype. Supporting the hypothesis, they found that Chinese participants made stronger stereotypical trait inferences than Americans did on the basis of a target’s membership in a fictitious group.
Key Takeaways
• Ingroup favoritism is a fundamental and evolutionarily functional aspect of human perception, and it occurs even in groups that are not particularly meaningful.
• Ingroup favoritism is caused by a variety of variables, but particularly important is self-concern: We experience positive social identity as a result of our membership in valued social groups.
• Ingroup favoritism develops early in children and influences our behavior toward ingroup and outgroup members in a variety of ways.
• Personality dimensions that relate to ingroup favoritism include authoritarianism and social dominance orientation—dimensions that relate to less ingroup favoritism include a desire to control one’s prejudice and humanism.
• There are at least some cultural differences in the tendency to show ingroup favoritism and to stereotype others.
Exercises and Critical Thinking
1. Consider some of the important social groups to which you belong. Do your group memberships lead to ingroup favoritism or even prejudice?
2. Describe a time when the members of one of your important social groups behaved in a way that increased group identity (e.g., showing the black sheep effect). What was the outcome of the actions?
Attribution
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Chapter 7 Learning Objectives
• Review the causes of discrimination and the ways that we can reduce it.
• Summarize the conditions under which intergroup contact does or does not reduce prejudice and discrimination.
We have seen that social categorization is a basic part of human nature and one that helps us to simplify our social worlds, to draw quick (if potentially inaccurate) conclusions about others, and to feel good about ourselves. In many cases, our preferences for ingroups may be relatively harmless—we may prefer to socialize with people who share our race or ethnicity, for instance, but without particularly disliking the others. But categorizing others may also lead to prejudice and discrimination, and it may even do so without our awareness. Because prejudice and discrimination are so harmful to so many people, we must all work to get beyond them.
Discrimination influences the daily life of its victims in areas such as employment, income, financial opportunities, housing and educational opportunities, and medical care. Discrimination has been blamed for the large percentage of Blacks living in poverty and for their lack of access to high-paying jobs (Williams & Rucker, 1996). Blacks have higher mortality rates than Whites for 8 of the 10 leading causes of death in the United States (Williams, 1999) and have less access to and receive poorer-quality health care, even controlling for other variables such as level of health insurance. Suicide rates among lesbians and gays are substantially higher than rates for the general population, and it has been argued that this in part due to the negative outcomes of prejudice, including negative attitudes and resulting social isolation (Halpert, 2002). And in some rare cases, discrimination even takes the form of hate crimes such as gay bashing.
More commonly, members of minority groups also face a variety of small hassles, such as bad service in restaurants, being stared at, and being the target of jokes (Swim, Hyers, Cohen, Fitzgerald, & Bylsma, 2003). But even these everyday “minor” forms of discrimination can be problematic because they may produce anger and anxiety among stigmatized group members and may lead to stress and other psychological problems (Klonoff, Landrine, & Campbell, 2000; Klonoff, Landrine, & Ullman, 1999). Stigmatized individuals who report experiencing more exposure to discrimination or other forms of unfair treatment also report more depression, anger, and anxiety and lower levels of life satisfaction and happiness (Swim, Hyers, Cohen, & Ferguson, 2001).
Of course most of us do try to keep our stereotypes and our prejudices out of mind, and we work hard to avoid discriminating (Richeson & Shelton, 2007). But even when we work to keep our negative beliefs under control, this does not mean that they easily disappear. Neil Macrae and his colleagues (Macrae, Bodenhausen, Milne, & Jetten, 1994) asked British college students to write a paragraph describing a skinhead (a member of a group that is negatively stereotyped in England). One half of the participants were asked to be sure to not use their stereotypes when they were judging him, whereas the other half simply wrote whatever came to mind. Although the participants who were asked to suppress their thoughts were able to do it, this suppression didn’t last very long. After they had suppressed their stereotypes, these beliefs quickly popped back into mind, making it even more likely that they would be used immediately later.
But stereotypes are not always and inevitably activated when we encounter people from other groups. We can and we do get past them, although doing so may take some effort on our part (Blair, 2002). There are a number of techniques that we can use to try to improve our attitudes toward outgroups, and at least some of them have been found to be effective. Kawakami, Dovidio, Moll, Hermsen, and Russin (2000) found that students who practiced responding in nonstereotypical ways to members of other groups became better able to avoid activating their negative stereotypes on future occasions. And a number of studies have found that we become less prejudiced when we are exposed to and think about group members who have particularly positive or nonstereotypical characteristics. For instance, Blair, Ma, and Lenton (2001) asked their participants to imagine a woman who was “strong” and found that doing so decreased stereotyping of women. Similarly, Bodenhausen, Schwarz, Bless, and Wanke (1995) found that when White students thought about positive Black role models—such as Oprah Winfrey and Michael Jordan—they became less prejudiced toward Blacks.
• Reducing Discrimination by Changing Social Norms
One variable that makes us less prejudiced is education. People who are more educated express fewer stereotypes and prejudice in general. This is true for students who enroll in courses that are related to stereotypes and prejudice, such as a course on gender and ethnic diversity (Rudman, Ashmore, & Gary, 2001), and is also true more generally—education reduces prejudice, regardless of what particular courses you take (Sidanius, Sinclair, & Pratto, 2006).
The effects of education on reducing prejudice are probably due in large part to the new social norms that people are introduced to in school. Social norms define what is appropriate and inappropriate, and we can effectively change stereotypes and prejudice by changing the relevant norms about them. Jetten, Spears, and Manstead (1997) manipulated whether students thought that the other members of their university favored equal treatment of others or believed that others thought it was appropriate to favor the ingroup. They found that perceptions of what the other group members believed had an important influence on the beliefs of the individuals themselves. The students were more likely to show ingroup favoritism when they believed that the norm of their ingroup was to do so, and this tendency was increased for students who had high social identification with the ingroup.
Sechrist and Stangor (2001) selected White college students who were either high or low in prejudice toward Blacks and then provided them with information indicating that their prejudiced or unprejudiced beliefs were either shared or not shared by the other students at their university. Then the students were asked to take a seat in a hallway to wait for the next part of the experiment. A Black confederate was sitting in one seat at the end of the row, and the dependent measure was how far away the students sat from her.
As you can see in Figure 12.8 “The Role of Norms in Intergroup Behavior”, high prejudice students who learned that other students were also prejudiced sat farther away from the Black confederate in comparison with high prejudice individuals who were led to believe that their beliefs were not shared. On the other hand, students who were initially low in prejudice and who believed these views were shared sat closer to the Black confederate in comparison with low prejudice individuals who were led to believe that their beliefs were not shared. These results demonstrate that our perceptions of relevant social norms can strengthen or weaken our tendencies to engage in discriminatory behaviors.
Figure 12.8 The Role of Norms in Intergroup Behavior
White college students who were low in prejudice toward Blacks sat closer to the Black confederate when they had been told that their beliefs were shared with other group members at their university. On the other hand, White college students who were high in prejudice sat farther away from the Black confederate when they had been told that their beliefs were shared with other group members at their university. Data are from Sechrist and Stangor (2001).
The influence of social norms is powerful, and long-lasting changes in beliefs about outgroups will occur only if they are supported by changes in social norms. Prejudice and discrimination thrive in environments in which they are perceived to be the norm, but they die when the existing social norms do not allow it. And because social norms are so important, the behavior of individuals can help create or reduce prejudice and discrimination. Discrimination, prejudice, and even hate crimes such as gay bashing will be more likely to continue if people do not respond to or confront them when they occur.
What this means is that if you believe that prejudice is wrong, you must confront it when you see it happening. Czopp, Monteith, and Mark (2006) had White participants participate in a task in which it was easy to unintentionally stereotype a Black person, and as a result, many of the participants did so. Then, confederates of the experimenter confronted the students about their stereotypes, saying things such as “Maybe it would be good to think about Blacks in other ways that are a little more fair?” or “It just seems that you sound like some kind of racist to me. You know what I mean?” Although the participants who had been confronted experienced negative feelings about the confrontation and also expressed negative opinions about the person who confronted them, the confrontation did work. The students who had been confronted expressed less prejudice and fewer stereotypes on subsequent tasks than did the students who had not been confronted.
As this study concluded, taking steps to reduce prejudice is everyone’s duty—having a little courage can go a long way in this regard. Confronting prejudice can lead other people to think that we are complaining and therefore to dislike us (Kaiser & Miller, 2001; Shelton & Stewart, 2004), but confronting prejudice is not all negative for the person who confronts. Although it is embarrassing to do so, particularly if we are not completely sure that the behavior was in fact prejudice, when we fail to confront, we may frequently later feel guilty that we did not (Shelton, Richeson, Salvatore, & Hill, 2006).
• Reducing Prejudice Through Intergroup Contact
One of the reasons that people may hold stereotypes and prejudices is that they view the members of outgroups as different from them. We may become concerned that our interactions with people from different racial groups will be unpleasant, and these anxieties may lead us to avoid interacting with people from those groups (Mallett, Wilson, & Gilbert, 2008). What this suggests is that a good way to reduce prejudice is to help people create closer connections with members of different groups. People will be more favorable toward others when they learn to see those other people as more similar to them, as closer to the self, and to be more concerned about them.
The idea that intergroup contact will reduce prejudice, known as the contact hypothesis, is simple: If children from different ethnic groups play together in school, their attitudes toward each other should improve. And if we encourage college students to travel abroad, they will meet people from other cultures and become more positive toward them.
One important example of the use of intergroup contact to influence prejudice came about as a result of the important U.S. Supreme Court case Brown v. Board of Education in 1954. In this case, the Supreme Court agreed, based in large part on the testimony of psychologists, that busing Black children to schools attended primarily by White children, and vice versa, would produce positive outcomes on intergroup attitudes, not only because it would provide Black children with access to better schools, but also because the resulting intergroup contact would reduce prejudice between Black and White children. This strategy seemed particularly appropriate at the time it was implemented because most schools in the United States then were highly segregated by race.
The strategy of busing was initiated after the Supreme Court decision, and it had a profound effect on schools in the United States. For one, the policy was very effective in changing school makeup—the number of segregated schools decreased dramatically during the 1960s after the policy was begun. Busing also improved the educational and occupational achievement of Blacks and increased the desire of Blacks to interact with Whites, for instance, by forming cross-race friendships (Stephan, 1999). Overall, then, the case of desegregating schools in the United States supports the expectation that intergroup contact, at least in the long run, can be successful in changing attitudes. Nevertheless, as a result of several subsequent U.S. Supreme Court decisions, the policy of desegregating schools via busing was not continued past the 1990s.
Although student busing to achieve desegregated schools represents one prominent example of intergroup contact, such contact occurs in many other areas as well. Taken together, there is substantial support for the effectiveness of intergroup contact in improving group attitudes in a wide variety of situations, including schools, work organizations, military forces, and public housing. Pettigrew and Tropp (2006) conducted a meta-analysis in which they reviewed over 500 studies that had investigated the effects of intergroup contact on group attitudes. They found that attitudes toward groups that were in contact became more positive over time. Furthermore, positive effects of contact were found on both stereotypes and prejudice and for many different types of contacted groups.
The positive effects of intergroup contact may be due in part to increases in other-concern. Galinsky and Moskowitz (2000) found that leading students to take the perspective of another group member—which increased empathy and closeness to the person—also reduced prejudice. And the behavior of students on college campuses demonstrates the importance of connecting with others and the dangers of not doing so. Sidanius, Van Laar, Levin, and Sinclair (2004) found that students who joined exclusive campus groups, including fraternities, sororities, and minority ethnic organizations (such as the African Student Union), were more prejudiced to begin with and became even less connected and more intolerant of members of other social groups over the time that they remained in the organizations. It appears that memberships in these groups focused the students on themselves and other people who were very similar to them, leading them to become less tolerant of others who are different.
Although intergroup contact does work, it is not a panacea because the conditions necessary for it to be successful are frequently not met. Contact can be expected to work only in situations that create the appropriate opportunities for change. For one, contact will only be effective if it provides information demonstrating that the existing stereotypes held by the individuals are incorrect. When we learn more about groups that we didn’t know much about before, we learn more of the truth about them, leading us to be less biased in our beliefs. But if our interactions with the group members do not allow us to learn new beliefs, then contact cannot work.
When we first meet someone from another category, we are likely to rely almost exclusively on our stereotypes (Brodt & Ross, 1998). However, when we get to know the individual well (e.g., as a student in a classroom learns to know the other students over a school year), we may get to the point where we ignore that individual’s group membership almost completely, responding to him or her entirely at the individual level (Madon et al., 1998). Thus contact is effective in part because it leads us to get past our perceptions of others as group members and to individuate them.
When we get past group memberships and focus more on the individuals in the groups, we begin to see that there is a great deal of variability among the group members and that our global and undifferentiating group stereotypes are actually not that informative (Rothbart & John, 1985). Successful intergroup contact tends to reduce the perception of outgroup homogeneity. Contact also helps us feel more positively about the members of the other group, and this positive affect makes us like them more.
Intergroup contact is also more successful when the people involved in the contact are motivated to learn about the others. One factor that increases this motivation is interdependence—a state in which the group members depend on each other for successful performance of the group goals (Neuberg & Fiske, 1987). The importance of interdependence can be seen in the success of cooperative learning techniques, such as the jigsaw classroom (Aronson, Blaney, Stephan, Sikes, & Snapp, 1978; Aronson, 2004).
The jigsaw classroom is an approach to learning in which students from different racial or ethnic groups work together, in an interdependent way, to master material. The class is divided into small learning groups, where each group is diverse in ethnic and gender composition. The assigned material to be learned is divided into as many parts as there are students in the group, and members of different groups who are assigned the same task meet together to help develop a strong report. Each student then learns his or her own part of the material and presents this piece of the puzzle to the other members of his or her group. The students in each group are therefore interdependent in learning all the material. A wide variety of techniques, based on principles of the jigsaw classroom, are in use in many schools around the United States and the world, and research studying these approaches has found that cooperative, interdependent experiences among students from different social groups are effective in reducing negative stereotyping and prejudice (Stephan, 1999).
In sum, we can say that contact will be most effective when it is easier to get to know, and become more respectful of, the members of the other group and when the social norms of the situation promote equal, fair treatment of all groups. If the groups are treated unequally, for instance, by a teacher or leader who is prejudiced and who therefore treats the different groups differently, or if the groups are in competition rather than cooperation, there will be no benefit. In cases when these conditions are not met, contact may not be effective and may in fact increase prejudice, particularly when it confirms stereotypical expectations (Stangor, Jonas, Stroebe, & Hewstone, 1996). Finally, it is important that enough time be allowed for the changes to take effect. In the case of busing in the United States, for instance, the positive effects of contact seemed to have been occurring, but they were not happening particularly fast.
Let’s consider in the next section still another way that intergroup contact can reduce prejudice—the idea that prejudice can be reduced for people who have friends who are friends with members of the outgroup—the extended-contact hypothesis.
Research Focus
The Extended-Contact Hypothesis
• >Although the contact hypothesis proposes that direct contact between people from different social groups will produce more positive attitudes between them, recent evidence suggests that prejudice can also be reduced for people who have friends who are friends with members of the outgroup, even if the individual does not have direct contact with the outgroup members himself or herself. This hypothesis is known as the extended-contact hypothesis. Supporting this prediction, Wright, Aron, McLaughlin-Volpe, and Ropp (1997) found in two correlational studies that college students who reported that their own friends had friends who were from another ethnic group reported more positive attitudes toward that outgroup than did students who did not have any friends who had outgroup friends, even controlling for the participants’ own outgroup friendships.
• >Wright et al. (1997) also tested the extended-contact hypothesis experimentally. Participants were four groups of 14 students, and each group spent a whole day in the lab. On arrival, 7 participants were assigned to the “green” group, and 7 to the “blue” group, supposedly on the basis of similar interests. To create strong ingroup identity and to produce competition between the groups, the group members wore blue and green t-shirts and engaged in a series of competitive tasks. Participants then expressed their initial thoughts and feelings about the outgroup and its members.
• >Then, supposedly as part of an entirely different study, one participant was randomly selected from each group, and the two were taken to a separate room in which they engaged in a relationship-building task that has been shown to quickly create feelings of friendship between two strangers. Then the two members from each team were then reunited with their original groups, where they were encouraged to describe their experience with the other group member in the friendship-building task.
• >In the final phase, the groups then engaged in another competitive task, and participants rated their thoughts and feelings about the outgroup and its members again. As you can see in the following figure, and supporting the extended-contact hypothesis, results showed that the participants (including those who did not participate in the closeness task themselves) were more positive toward the outgroup after than before the two team members had met. This study, as well as many other studies, supports the importance of cross-group friendships in promoting favorable outgroup attitudes (Page-Gould, Mendoza-Denton, & Tropp, 2008; Shook & Fazio, 2008).
Figure 12.9 The Extended-Contact Hypothesis
This figure shows how members of the two groups, which were in competition with each other, rated each other before and after the experimental manipulation of friendship. You can see that group relationships, which were becoming more negative, changed to being more positive after the intervention. Data are from Wright, Aron, McLaughlin-Volpe, and Ropp (1997).
• Moving Others Closer to Us: The Benefits of Recategorization
The research on intergroup contact suggests that although contact may improve prejudice, it may make it worse if it is not implemented correctly. Improvement is likely only when the contact moves the members of the groups to feel that they are closer to each other rather than further away from each other. In short, groups are going to have better attitudes toward each other when they see themselves more similarly to each other—when they feel more like one large group than a set of smaller groups.
This fact was demonstrated in a very convincing way in one of the most well known of all social psychological studies. In the “Robbers’ Cave Experiment,” Sherif, Harvey, White, Hood, and Sherif (1961) studied the group behavior of 11-year-old boys at a summer camp. Although the boys did not know it, the researchers carefully observed the behaviors of the children during the camp session, with the goal of learning about how group conflict developed and how it might be resolved among the children.
During the first week of the camp, the boys were divided into two groups that camped at two different campsites. During this time, friendly relationships developed among the boys within each of the two groups. Each group developed its own social norms and group structure and became quite cohesive, with a strong positive social identity. The two groups chose names for themselves (the Rattlers and the Eagles), and each made their own group flag and participated in separate camp activities.
At the end of this one-week baseline period, it was arranged that the two groups of boys would become aware of each other’s presence. Furthermore, the researchers worked to create conditions that led to increases in each group’s social identity and at the same time created negative perceptions of the other group. The researchers arranged baseball games, a tug-of-war, and a treasure hunt and offered prizes for the group that won the competitions. Almost immediately, this competition created ingroup favoritism and prejudice, and discrimination quickly followed. By the end of the second week, the Eagles had sneaked up to the Rattlers’ cabin and stolen their flag. When the Rattlers discovered the theft, they in turn raided the Eagles’ cabin, stealing things. There were food fights in the dining room, which was now shared by the groups, and the researchers documented a substantial increase in name-calling and stereotypes of the outgroup. Some fistfights even erupted between members of the different groups.
The researchers then intervened by trying to move the groups closer to each other. They began this third stage of the research by setting up a series of situations in which the boys had to work together to solve a problem. These situations were designed to create interdependence by presenting the boys with superordinate goals—goals that were both very important to them and yet that required the cooperative efforts and resources of both the Eagles and the Rattlers to attain. These goals involved such things as the need to pool money across both groups in order to rent a movie that all the campers wanted to view, or the need to pull together on ropes to get a food truck that had become stuck back onto the road. As the children worked together to meet these goals, the negative perceptions of the group members gradually improved; there was a reduction of hostility between the groups and an emergence of more positive intergroup attitudes.
This strategy was effective because it led the campers to perceive both the ingroup and the outgroup as one large group (“we”) rather than as two separate groups (“us” and “them”). As differentiation between the ingroup and the outgroup decreases, so should ingroup favoritism, prejudice, and conflict. The differences between the original groups are still present, but they are potentially counteracted by perceived similarities in the second superordinate group. The attempt to reduce prejudice by creating a superordinate categorization is known as the goal of creating a common ingroup identity (Gaertner & Dovidio, 2008), and we can diagram the relationship as follows:
interdependence and cooperation → common ingroup identity → favorable intergroup attitudes.
A substantial amount of research has supported the predictions of the common ingroup identity model. For instance, Samuel Gaertner and his colleagues (Gaertner, Mann, Murrell, & Dovidio, 1989) tested the hypothesis that interdependent cooperation in groups reduces negative beliefs about outgroup members because it leads people to see the others as part of the ingroup (by creating a common identity). In this research, college students were brought to a laboratory where they were each assigned to one of two teams of three members each, and each team was given a chance to create its own unique group identity by working together. Then, the two teams were brought into a single room to work on a problem. In one condition, the two teams were told to work together as a larger, six-member team to solve the problem, whereas in the other condition, the two teams worked on the problem separately.
Consistent with the expected positive results of creating a common group identity, the interdependence created in the condition where the teams worked together increased the tendency of the team members to see themselves as members of a single, larger team, and this in turn reduced the tendency for each group to show ingroup favoritism.
But the benefits of recategorization are not confined to laboratory settings—they also appear in our everyday interactions with other people. Jason Neir and his colleagues (Neir et al., 2001) had Black and White interviewers approach White students who were attending a football game. The dependent measure was whether or not they agreed to help the interviewer by completing a questionnaire. However, the interviewers also wore hats representing either one of the two universities who were playing in the game. As you can see in Figure 12.10 “Recategorization and Helping Behavior”, the data were analyzed both by whether the interviewer and the student were of the same race (either both White or one White and one Black) and also by whether they wore hats from the same or different universities. As expected on the basis of recategorization and the common ingroup identity approach, the White students were significantly more likely to help the Black interviewers when they wore a hat of the same university as that worn by the interviewee. The hat evidently led the White students to recategorize the interviewer as part of the university ingroup, leading to more helping. However, whether the individuals shared university affiliation did not influence helping for the White participants, presumably because they already saw the interviewer as a member of the ingroup (the interviewer was also White).
Figure 12.10 Recategorization and Helping Behavior
In this field study, White and Black interviewers asked White students attending a football game to help them by completing a questionnaire. The data were analyzed both by whether the request was to a White (ingroup) or Black (outgroup) student and also by whether the individual whose help was sought wore the same hat that they did or a different hat. Results supported the common ingroup identity model. Helping was much greater for outgroup members when hats were the same. Data are from Neir et al. (2001).
Again, the implications of these results are clear and powerful. If we want to improve attitudes among people, we must get them to see each other as more similar and less different. And even relatively simple ways of doing so, such as wearing a hat that suggests an ingroup identification, can be successful.
Key Takeaways
• Changing our stereotypes and prejudices is not easy, and attempting to suppress them may backfire. However, with appropriate effort, we can reduce our tendency to rely on our stereotypes and prejudices.
• One approach to changing stereotypes and prejudice is by changing social norms—for instance, through education and laws enforcing equality.
• Prejudice will change faster when it is confronted by people who see it occurring. Confronting prejudice may be embarrassing, but it also can make us feel that we have done the right thing.
• Intergroup attitudes will be improved when we can lead people to focus more on their connections with others. Intergroup contact, extended contact with others who share friends with outgroup members, and a common ingroup identity are all examples of this process.
Exercises and Critical Thinking
1. Does your college or university support efforts to increase intergroup contact? If so, do the efforts seem to be successful in reducing prejudice?
2. Have you ever confronted or failed to confront a person who you thought was expressing prejudice or discriminating? Why did you confront (or not confront) that person, and how did doing so make you feel?
3. Imagine you are a teacher in a classroom and you see that some children expressing prejudice or discrimination toward other children on the basis of their race. What techniques would you use to attempt to reduce these negative behaviors?
Attribution
Principles of Social Psychologyby the University of Minnesota under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/04%3A_The_Social_Change_Dimension/4.03%3A_Chapter_7-_Reducing_Discrimination.txt |
Chapter 8 Learning Objectives
• Describe the targets of nineteenth-century mob violence in U.S. cities.
• Discuss why the familiar saying “The more things change, the more they stay the same” applies to the history of race and ethnicity in the United States.
• Critique the biological concept of race.
• Discuss why race is a social construction.
• Explain why ethnic heritages have both good and bad consequences.
• Describe any two manifestations of racial and ethnic inequality in the United States.
• Explain how and why racial inequality takes a hidden toll on people of color.
• Provide two examples of white privilege.
• Understand cultural explanations for racial and ethnic inequality.
• Describe structural explanations for racial and ethnic inequality.
• Summary of the debate over affirmative action.
• Describe any three policies or practices that could reduce racial and ethnic inequality in the United States.
Introduction
Social Problems in the News
“Anger, Shock over Cross Burning in Calif. Community,” the headline said. This cross burning took place next to a black woman’s home in Arroyo Grande, California, a small, wealthy town about 170 miles northwest of Los Angeles. The eleven-foot cross had recently been stolen from a nearby church.
• >This hate crime shocked residents and led a group of local ministers to issue a public statement that said in part, “Burning crosses, swastikas on synagogue walls, hateful words on mosque doors are not pranks. They are hate crimes meant to frighten and intimidate.” The head of the group added, “We live in a beautiful area, but it’s only beautiful if every single person feels safe conducting their lives and living here.”
• >Four people were arrested four months later for allegedly burning the cross and charged with arson, hate crime, terrorism, and conspiracy. Arroyo Grande’s mayor applauded the arrests and said in a statement, “Despite the fact that our city was shaken by this crime, it did provide an opportunity for us to become better educated on matters relating to diversity.”
• >Sources: (Jablon, 2011; Lerner, 2011; Mann, 2011)
• Cross burnings like this one recall the Ku Klux Klan era between the 1880s and 1960s, when white men dressed in white sheets and white hoods terrorized African Americans in the South and elsewhere and lynched more than 3,000 black men and women. Thankfully, that era is long gone, but as this news story reminds us, racial issues continue to trouble the United States.
In the wake of the 1960s urban riots, the so-called Kerner Commission (Kerner Commission, 1968)Kerner Commission. (1968). Report of the National Advisory Commission on civil disorders. New York, NY: Bantam Books. appointed by President Lyndon Johnson to study the riots famously warned, “Our nation is moving toward two societies, one black, one white—separate and unequal.” The commission blamed white racism for the riots and urged the government to provide jobs and housing for African Americans and to take steps to end racial segregation.
More than four decades later, racial inequality in the United States continues to exist and in many ways has worsened. Despite major advances by African Americans, Latinos, and other people of color during the past few decades, they continue to lag behind non-Hispanic whites in education, income, health, and other social indicators. The faltering economy since 2008 has hit people of color especially hard, and the racial wealth gap is deeper now than it was just two decades ago.
Why does racial and ethnic inequality exist? What forms does it take? What can be done about it? This chapter addresses all these questions. We shall see that, although racial and ethnic inequality has stained the United States since its beginnings, there is hope for the future as long as our nation understands the structural sources of this inequality and makes a concerted effort to reduce it. Later chapters in this book will continue to highlight various dimensions of racial and ethnic inequality. Immigration, a very relevant issue today for Latinos and Asians and the source of much political controversy, receives special attention in Chapter 15 “Population and the Environment”’s discussion of population problems.
A Historical Prelude
Race and ethnicity have torn at the fabric of American society ever since the time of Christopher Columbus when an estimated 1 million Native Americans populated the eventual United States. By 1900, their numbers had dwindled to about 240,000, as tens of thousands were killed by white settlers and US troops and countless others died from disease contracted from people with European backgrounds. Scholars say this mass killing of Native Americans amounted to genocide (Brown, 2009).
African Americans also have a history of maltreatment that began during the colonial period, when Africans were forcibly transported from their homelands to be sold as slaves in the Americas. Slavery, of course, continued in the United States until the North’s victory in the Civil War ended it. African Americans outside the South were not slaves but were still victims of racial prejudice. During the 1830s, white mobs attacked free African Americans in cities throughout the nation, including Philadelphia, Cincinnati, Buffalo, and Pittsburgh. The mob violence stemmed from a “deep-seated racial prejudice…in which whites saw blacks as ‘something less than human’” (Brown, 1975) and continued well into the twentieth century, when white mobs attacked African Americans in several cities, with at least seven antiblack riots occurring in 1919 that left dozens dead. Meanwhile, an era of Jim Crow racism in the South led to the lynching of thousands of African Americans, segregation in all facets of life, and other kinds of abuses (Litwack, 2009).
During the era of Jim Crow racism in the South, several thousand African Americans were lynched. US Library of Congress – public domain.
African Americans were not the only targets of native-born white mobs back then (Dinnerstein & Reimers, 2009). As immigrants from Ireland, Italy, Eastern Europe, Mexico, and Asia flooded into the United States during the nineteenth and early twentieth centuries, they, too, were beaten, denied jobs, and otherwise mistreated. During the 1850s, mobs beat and sometimes killed Catholics in cities such as Baltimore and New Orleans. During the 1870s, whites rioted against Chinese immigrants in cities in California and other states. Hundreds of Mexicans were attacked and/or lynched in California and Texas during this period.
Nazi racism in the 1930s and 1940s helped awaken Americans to the evils of prejudice in their own country. Against this backdrop, a monumental two-volume work by Swedish social scientist Gunnar Myrdal (Myrdal, 1944) attracted much attention when it was published. The book, An American Dilemma: The Negro Problem and Modern Democracy, documented the various forms of discrimination facing blacks back then. The “dilemma” referred to by the book’s title was the conflict between the American democratic ideals of egalitarianism and liberty and justice for all and the harsh reality of prejudice, discrimination, and lack of equal opportunity.
The Kerner Commission’s 1968 report reminded the nation that little, if anything, had been done since Myrdal’s book to address this conflict. Sociologists and other social scientists have warned since then that the status of people of color has actually been worsening in many ways since this report was issued (Massey, 2007; Wilson, 2009). Evidence of this status appears in the remainder of this chapter.
The Meaning of Race and Ethnicity
To begin our understanding of racial and ethnic inequality, we first need to understand what race and ethnicity mean. These terms may seem easy to define but are much more complex than their definitions suggest.
• Race
Let’s start first with race, which refers to a category of people who share certain inherited physical characteristics, such as skin color, facial features, and stature. A key question about race is whether it is more of a biological category or a social category. Most people think of race in biological terms, and for more than three hundred years, or ever since white Europeans began colonizing nations filled with people of color, people have been identified as belonging to one race or another based on certain biological features.
It is certainly easy to see that people in the United States and around the world differ physically in some obvious ways. The most noticeable difference is skin tone: Some groups of people have very dark skin, while others have very light skin. Other differences also exist. Some people have very curly hair, while others have very straight hair. Some have thin lips, while others have thick lips. Some groups of people tend to be relatively tall, while others tend to be relatively short. Using such physical differences as their criteria, scientists at one point identified as many as nine races: African, American Indian or Native American, Asian, Australian Aborigine, European (more commonly called “white”), Indian, Melanesian, Micronesian, and Polynesian (Smedley, 2007).
Although people certainly do differ in these kinds of physical features, anthropologists, sociologists, and many biologists question the value of these categories and thus the value of the biological concept of race (Smedley, 2007). For one thing, we often see more physical differences within a race than between races. For example, some people we call “white” (or European), such as those with Scandinavian backgrounds, have very light skins, while others, such as those from some Eastern European backgrounds, have much darker skins. In fact, some “whites” have darker skin than some “blacks,” or African Americans. Some whites have very straight hair, while others have very curly hair; some have blonde hair and blue eyes, while others have dark hair and brown eyes. Because of interracial reproduction going back to the days of slavery, African Americans also differ in the darkness of their skin and in other physical characteristics. In fact, it is estimated that at least 30 percent of African Americans have some white (i.e., European) ancestry and that at least 20 percent of whites have African or Native American ancestry. If clear racial differences ever existed hundreds or thousands of years ago (and many scientists doubt such differences ever existed), in today’s world these differences have become increasingly blurred.
President Barack Obama had an African father and a white mother. Although his ancestry is equally black and white, Obama considers himself an African American, as do most Americans. In several Latin American nations, however, Obama would be considered white because of his white ancestry. Steve Jurvetson – Barak Obama on the Primary – CC BY 2.0.
Another reason to question the biological concept of race is that an individual or a group of individuals is often assigned to a race arbitrarily. A century ago, for example, Irish, Italians, and Eastern European Jews who left their homelands were not regarded as white once they reached the United States but rather as a different, inferior (if unnamed) race (Painter, 2010). The belief in their inferiority helped justify the harsh treatment they suffered in their new country. Today, of course, we call people from all three backgrounds white or European.
In this context, consider someone in the United States who has a white parent and a black parent. What race is this person? American society usually calls this person black or African American, and the person may adopt this identity (as does President Barack Obama, who had a white mother and African father). But where is the logic for doing so? This person, as well as President Obama, is as much white as black in terms of parental ancestry.
Or consider someone with one white parent and another parent who is the child of one black parent and one white parent. This person thus has three white grandparents and one black grandparent. Even though this person’s ancestry is thus 75 percent white and 25 percent black, she or he is likely to be considered black in the United States and may well adopt this racial identity. This practice reflects the traditional one-drop rule in the United States that defines someone as black if she or he has at least one drop of black blood, and that was used in the antebellum South to keep the slave population as large as possible (Staples, 2005). Yet in many Latin American nations, this person would be considered white (see Note 3.7 “Lessons from Other Societies”). With such arbitrary designations, the race is more of a social category than a biological one.
Lessons from Other Societies
The Concept of Race in Brazil
• >As the text discusses, race was long considered a fixed, biological category, but today it is now regarded as a social construction. The experience of Brazil provides very interesting comparative evidence for this more accurate way of thinking about race.
• >When slaves were first brought to the Americas almost four hundred years ago, many more were taken to Brazil, where slavery was not abolished until 1888, than to the land that eventually became the United States. Brazil was then a colony of Portugal, and the Portuguese used Africans as slave labor. Just as in the United States, a good deal of interracial reproduction has occurred since those early days, much of it initially the result of the rape of women slaves by their owners, and Brazil over the centuries has had many more racial intermarriages than the United States. Also like the United States, then, much of Brazil’s population has multiracial ancestry. But in a significant departure from the United States, Brazil uses different criteria to consider the race to which a person belongs.
• >Brazil uses the term preto, or black, for people whose ancestry is solely African. It also uses the term Branco, or white, to refer to people whose ancestry is both African and European. In contrast, as the text discusses, the United States commonly uses the term black or African American to refer to someone with even a small amount of African ancestry and white for someone who is thought to have solely European ancestry or at least “looks” white. If the United States were to follow Brazil’s practice of reserving the term black for someone whose ancestry is solely African and the term white for someone whose ancestry is both African and European, many of the Americans commonly called “black” would no longer be considered black and instead would be considered white.
• >As sociologist Edward E. Telles (2006, p. 79) summarizes these differences, “[Blackness is differently understood in Brazil than in the United States. A person considered black in the United States is often not so in Brazil. Indeed, some U.S. blacks may be considered white in Brazil. Although the value given to blackness is similarly low [in both nations], who gets classified as black is not uniform.” The fact that someone can count on being considered “black” in one society and not “black” in another society underscores the idea that race is best considered a social construction rather than a biological category.
• >Sources: Barrionuevo & Calmes, 2011; Klein & Luno, 2009; Telles, 2006
• A third reason to question the biological concept of race comes from the field of biology itself and more specifically from the studies of genetics and human evolution. Starting with genetics, people from different races are more than 99.9 percent the same in their DNA (Begley, 2008). To turn that around, less than 0.1 percent of all DNA in our bodies accounts for the physical differences among people that we associate with racial differences. In terms of DNA, then, people with different racial backgrounds are much, much more similar than dissimilar.
Even if we acknowledge that people differ in the physical characteristics we associate with race, modern evolutionary evidence reminds us that we are all, really, of one human race. According to evolutionary theory, the human race began thousands and thousands of years ago in sub-Saharan Africa. As people migrated around the world over the millennia, natural selection took over. It favored dark skin for people living in hot, sunny climates (i.e., near the equator), because the heavy amounts of melanin that produce dark skin protect against severe sunburn, cancer, and other problems. By the same token, natural selection favored light skin for people who migrated farther from the equator to cooler, less sunny climates, because dark skins there would have interfered with the production of vitamin D (Stone & Lurquin, 2007). Evolutionary evidence thus reinforces the common humanity of people who differ in the rather superficial ways associated with their appearances: We are one human species composed of people who happen to look different.
• Race as a Social Construction
The reasons for doubting the biological basis for racial categories suggest that race is more of a social category than a biological one. Another way to say this is that race is a social construction, a concept that has no objective reality but rather is what people decide it is (Berger & Luckmann, 1963). In this view, the race has no real existence other than what and how people think of it.
This understanding of race is reflected in the problems, outlined earlier, in placing people with multiracial backgrounds into any one racial category. We have already mentioned the example of President Obama. As another example, golfer Tiger Woods was typically called an African American by the news media when he burst onto the golfing scene in the late 1990s, but in fact, his ancestry is one-half Asian (divided evenly between Chinese and Thai), one-quarter white, one-eighth Native American, and only one-eighth African American (Leland & Beals, 1997).
Historical examples of attempts to place people in racial categories further underscore the social constructionism of race. In the South during the time of slavery, the skin tone of slaves lightened over the years as babies were born from the union, often in the form of rape, of slave owners and other whites with slaves. As it became difficult to tell who was “black” and who was not, many court battles over people’s racial identity occurred. People who were accused of having black ancestry would go to court to prove they were white in order to avoid enslavement or other problems (Staples, 1998).
Although race is a social construction, it is also true that race has real consequences because people do perceive race as something real. Even though so little of DNA accounts for the physical differences we associate with racial differences, that low amount leads us not only to classify people into different races but also to treat them differently—and, more to the point, unequally—based on their classification. Yet modern evidence shows there is little if any, scientific basis for the racial classification that is the source of so much inequality.
• Ethnicity
Because of the problems in the meaning of race, many social scientists prefer the term ethnicity in speaking of people of color and others with distinctive cultural heritages. In this context, ethnicity refers to the shared social, cultural, and historical experiences, stemming from common national or regional backgrounds, that make subgroups of a population different from one another. Similarly, an ethnic group is a subgroup of a population with a set of shared social, cultural, and historical experiences; with relatively distinctive beliefs, values, and behaviors; and with some sense of identity of belonging to the subgroup. So conceived, the terms ethnicity and ethnic group avoid the biological connotations of the terms race and racial group.
At the same time, the importance we attach to ethnicity illustrates that it, too, is in many ways a social construction, and our ethnic membership thus has important consequences for how we are treated. In particular, history and current practice indicate that it is easy to become prejudiced against people with different ethnicities from our own. Much of the rest of this chapter looks at the prejudice and discrimination operating today in the United States against people whose ethnicity is not white and European. Around the world today, ethnic conflict continues to rear its ugly head. The 1990s and 2000s were filled with ethnic cleansing and pitched battles among ethnic groups in Eastern Europe, Africa, and elsewhere. Our ethnic heritages shape us in many ways and fill many of us with pride, but they also are the source of much conflict, prejudice, and even hatred, as the hate crime story that began this chapter so sadly reminds us.
Dimensions of Racial and Ethnic Inequality
Racial and ethnic inequality manifests itself in all walks of life. The individual and institutional discrimination just discussed is one manifestation of this inequality. We can also see stark evidence of racial and ethnic inequality in various government statistics. Sometimes statistics lie, and sometimes they provide all too true a picture; statistics on racial and ethnic inequality fall into the latter category. Table 3.2 “Selected Indicators of Racial and Ethnic Inequality in the United States” presents data on racial and ethnic differences in income, education, and health.
Table 3.2 Selected Indicators of Racial and Ethnic Inequality in the United States
White African American Latino Asian Native American
Median family income, 2010 (\$) 68,818 39,900 41,102 76,736 39,664
Persons who are college educated, 2010 (%) 30.3 19.8 13.9 52.4 14.9 (2008)
Persons in poverty, 2010 (%) 9.9 (non-Latino) 27.4 26.6 12.1 28.4
Infant mortality (number of infant deaths per 1,000 births), 2006 5.6 12.9 5.4 4.6 8.3
Asian Americans have higher family incomes than whites on the average. Although Asian Americans are often viewed as a “model minority,” some Asians have been less able than others to achieve economic success, and stereotypes of Asians and discrimination against them remain serious problems. LindaDee2006 – CC BY-NC-ND 2.0.
The picture presented by Table 3.2 “Selected Indicators of Racial and Ethnic Inequality in the United States” is clear: US racial and ethnic groups differ dramatically in their life chances. Compared to whites, for example, African Americans, Latinos, and Native Americans have much lower family incomes and much higher rates of poverty; they are also much less likely to have college degrees. In addition, African Americans and Native Americans have much higher infant mortality rates than whites: Black infants, for example, are more than twice as likely as white infants to die. Later chapters in this book will continue to highlight various dimensions of racial and ethnic inequality.
Although Table 3.2 “Selected Indicators of Racial and Ethnic Inequality in the United States” shows that African Americans, Latinos, and Native Americans fare much worse than whites, it presents a more complex pattern for Asian Americans. Compared to whites, Asian Americans have higher family incomes and are more likely to hold college degrees, but they also have a higher poverty rate. Thus many Asian Americans do relatively well, while others fare relatively worse, as just noted. Although Asian Americans are often viewed as a “model minority,” meaning that they have achieved economic success despite not being white, some Asians have been less able than others to climb the economic ladder. Moreover, stereotypes of Asian Americans and discrimination against them remain serious problems (Chou & Feagin, 2008). Even the overall success rate of Asian Americans obscures the fact that their occupations and incomes are often lower than would be expected from their educational attainment. They thus have to work harder for their success than whites do (Hurh & Kim, 1999).
• The Increasing Racial/Ethnic Wealth Gap
At the beginning of this chapter, we noted that racial and ethnic inequality has existed since the beginning of the United States. We also noted that social scientists have warned that certain conditions have actually worsened for people of color since the 1960s (Hacker, 2003; Massey & Sampson, 2009).
Recent evidence of this worsening appeared in a report by the Pew Research Center (2011). The report focused on racial disparities in wealth, which includes a family’s total assets (income, savings, and investments, home equity, etc.) and debts (mortgage, credit cards, etc.). The report found that the wealth gap between white households on the one hand and African American and Latino households, on the other hand, was much wider than just a few years earlier, thanks to the faltering US economy since 2008 that affected blacks more severely than whites.
According to the report, whites’ median wealth was ten times greater than blacks’ median wealth in 2007, a discouraging disparity for anyone who believes in racial equality. By 2009, however, whites’ median wealth had jumped to twenty times greater than blacks’ median wealth and eighteen times greater than Latinos’ median wealth. White households had a median net worth of about \$113,000, while black and Latino households had a median net worth of only \$5,700 and \$6,300, respectively (see Figure 3.5 “The Racial/Ethnic Wealth Gap (Median Net Worth of Households in 2009)”). This racial and ethnic difference is the largest since the government began tracking wealth more than a quarter-century ago.
Figure 3.5 The Racial/Ethnic Wealth Gap (Median Net Worth of Households in 2009)
Source: Pew Research Center, 2011.
• The Hidden Toll of Racial and Ethnic Inequality
An increasing amount of evidence suggests that being black in a society filled with racial prejudice, discrimination, and inequality takes what has been called a “hidden toll” on the lives of African Americans (Blitstein, 2009). As we shall see in later chapters, African Americans on the average have worse health than whites and die at younger ages. In fact, every year there are an additional 100,000 African American deaths than would be expected if they lived as long as whites do. Although many reasons probably explain all these disparities, scholars are increasingly concluding that the stress of being black is a major factor (Geronimus et al., 2010).
In this way of thinking, African Americans are much more likely than whites to be poor, to live in high-crime neighborhoods, and to live in crowded conditions, among many other problems. As this chapter discussed earlier, they are also more likely, whether or not they are poor, to experience racial slights, refusals to be interviewed for jobs, and other forms of discrimination in their everyday lives. All these problems mean that African Americans from their earliest ages grow up with a great deal of stress, far more than what most whites experience. This stress, in turn, has certain neural and physiological effects, including hypertension (high blood pressure), that impair African Americans’ short-term and long-term health and that ultimately shorten their lives. These effects accumulate over time: black and white hypertension rates are equal for people in their twenties, but the black rate becomes much higher by the time people reach their forties and fifties. As a recent news article on evidence of this “hidden toll” summarized this process, “The long-term stress of living in a white-dominated society ‘weathers’ blacks, making them age faster than their white counterparts” (Blitstein, 2009, p. 48).
Although there is less research on other people of color, many Latinos and Native Americans also experience the various sources of stress that African Americans experience. To the extent this is true, racial and ethnic inequality also takes a hidden toll on members of these two groups. They, too, experience racial slights, live under disadvantaged conditions, and face other problems that result in high levels of stress and shorten their life spans.
• White Privilege: The Benefits of Being White
American whites enjoy certain privileges merely because they are white. For example, they usually do not have to fear that a police officer will stop them simply because they are white, and they also generally do not have to worry about being mistaken for a bellhop, parking valet, or maid. Loren Kerns – Day 73 – CC BY 2.0.
Before we leave this section, it is important to discuss the advantages that US whites enjoy in their daily lives simply because they are white. Social scientists term these advantages and say that whites benefit from being white whether or not they are aware of their advantages (McIntosh, 2007).
This chapter’s discussion of the problems facing people of color points to some of these advantages. For example, whites can usually drive a car at night or walk down a street without having to fear that a police officer will stop them simply because they are white. Recalling the Trayvon Martin tragedy, they can also walk down a street without having to fear they will be confronted and possibly killed by a neighborhood watch volunteer. In addition, whites can count on being able to move into any neighborhood they desire to as long as they can afford the rent or mortgage. They generally do not have to fear being passed up for a promotion simply because of their race. White students can live in college dorms without having to worry that racial slurs will be directed their way. White people, in general, do not have to worry about being the victims of hate crimes based on their race. They can be seated in a restaurant without having to worry that they will be served more slowly or not at all because of their skin color. If they are in a hotel, they do not have to think that someone will mistake them for a bellhop, parking valet, or maid. If they are trying to hail a taxi, they do not have to worry about the taxi driver ignoring them because the driver fears he or she will be robbed.
Social scientist Robert W. Terry (1981, p. 120) once summarized white privilege as follows: “To be white in America is not to have to think about it. Except for hard-core racial supremacists, the meaning of being white is having the choice of attending to or ignoring one’s own whiteness” (emphasis in original). For people of color in the United States, it is not an exaggeration to say that race and ethnicity are a daily fact of their existence. Yet whites do not generally have to think about being white. As all of us go about our daily lives, this basic difference is one of the most important manifestations of racial and ethnic inequality in the United States.
Perhaps because whites do not have to think about being white, many studies find they tend to underestimate the degree of racial inequality in the United States by assuming that African Americans and Latinos are much better off than they really are. As one report summarized these studies’ overall conclusion, “Whites tend to have a relatively rosy impression of what it means to be a black person in America. Whites are more than twice as likely as blacks to believe that the position of African Americans has improved a great deal” (Vedantam, 2008, p. A3). Because whites think African Americans and Latinos fare much better than they really do, that perception probably reduces whites’ sympathy for programs designed to reduce racial and ethnic inequality.
Explaining Racial and Ethnic Inequality
Why does racial and ethnic inequality exist? Why do African Americans, Latinos, Native Americans, and some Asian Americans fare worse than whites? In answering these questions, many people have some very strong opinions.
• Biological Inferiority
One long-standing explanation is that blacks and other people of color are biologically inferior: They are naturally less intelligent and have other innate flaws that keep them from getting a good education and otherwise doing what needs to be done to achieve the American Dream. As discussed earlier, this racist view is no longer common today. However, whites historically used this belief to justify slavery, lynchings, the harsh treatment of Native Americans in the 1800s, and lesser forms of discrimination. In 1994, Richard J. Herrnstein and Charles Murray revived this view in their controversial book, The Bell Curve (Herrnstein & Murray, 1994), in which they argued that the low IQ scores of African Americans, and of poor people more generally, reflect their genetic inferiority in the area of intelligence. African Americans’ low innate intelligence, they said, accounts for their poverty and other problems. Although the news media gave much attention to their book, few scholars agreed with its views, and many condemned the book’s argument as a racist way of “blaming the victim” (Gould, 1994).
• Cultural Deficiencies
Another explanation of racial and ethnic inequality focuses on the supposed cultural deficiencies of African Americans and other people of color (Murray, 1984). These deficiencies include a failure to value hard work and, for African Americans, a lack of strong family ties, and are said to account for the poverty and other problems facing these minorities. This view echoes the culture-of-poverty argument presented in Chapter 2 “Poverty” and is certainly popular today. As we saw earlier, more than half of non-Latino whites think that blacks’ poverty is due to their lack of motivation and willpower. Ironically some scholars find support for this cultural deficiency view in the experience of many Asian Americans, whose success is often attributed to their culture’s emphasis on hard work, educational attainment, and strong family ties (Min, 2005). If that is true, these scholars say, then the lack of success of other people of color stems from the failure of their own cultures to value these attributes.
How accurate is the cultural deficiency argument? Whether people of color have “deficient” cultures remains hotly debated (Bonilla-Silva, 2009). Many social scientists find little or no evidence of cultural problems in minority communities and say the belief in cultural deficiencies is an example of symbolic racism that blames the victim. Citing survey evidence, they say that poor people of color value work and education for themselves and their children at least as much as wealthier white people do (Holland, 2011; Muhammad, 2007). Yet other social scientists, including those sympathetic to the structural problems facing people of color, believe that certain cultural problems do exist, but they are careful to say that these cultural problems arise out of the structural problems. For example, Elijah Anderson (1999) wrote that a “street culture” or “oppositional culture” exists among African Americans in urban areas that contribute to high levels of violent behavior, but he emphasized that this type of culture stems from the segregation, extreme poverty, and other difficulties these citizens face in their daily lives and helps them deal with these difficulties. Thus even if cultural problems do exist, they should not obscure the fact that structural problems are responsible for the cultural ones.
• Structural Problems
A third explanation for US racial and ethnic inequality is based on conflict theory and reflects the blaming-the-system approach outlined in Chapter 1 “Understanding Social Problems”. This view attributes racial and ethnic inequality to structural problems, including institutional and individual discrimination, a lack of opportunity in education and other spheres of life, and the absence of jobs that pay an adequate wage (Feagin, 2006). Segregated housing, for example, prevents African Americans from escaping the inner city and from moving to areas with greater employment opportunities. Employment discrimination keeps the salaries of people of color much lower than they would be otherwise. The schools that many children of color attend every day are typically overcrowded and underfunded. As these problems continue from one generation to the next, it becomes very difficult for people already at the bottom of the socioeconomic ladder to climb up it because of their race and ethnicity (see Note 3.33 “Applying Social Research”).
Applying Social Research
The Poor Neighborhoods of Middle-Class African Americans
• >In a society that values equal opportunity for all, scholars have discovered a troubling trend: African American children from middle-class families are much more likely than white children from middle-class families to move down the socioeconomic ladder by the time they become adults. In fact, almost half of all African American children born during the 1950s and 1960s to middle-class parents ended up with lower incomes than their parents by adulthood. Because these children had parents who had evidently succeeded despite all the obstacles facing them in a society filled with racial inequality, we have to assume they were raised with the values, skills, and aspirations necessary to stay in the middle class and even to rise beyond it. What, then, explains why some end up doing worse than their parents?
• >According to a recent study written by sociologist Patrick Sharkey for the Pew Charitable Trusts, one important answer lies in the neighborhoods in which these children are raised. Because of continuing racial segregation, many middle-class African American families find themselves having to live in poor urban neighborhoods. About half of African American children born between 1955 and 1970 to middle-class parents grew up in poor neighborhoods, but hardly any middle-class white children grew up in such neighborhoods. In Sharkey’s statistical analysis, neighborhood poverty was a much more important factor than variables such as parents’ education and marital status in explaining the huge racial difference in the eventual socioeconomic status of middle-class children. An additional finding of the study underscored the importance of neighborhood poverty for adult socioeconomic status: African American children raised in poor neighborhoods in which the poverty rate declined significantly ended up with higher incomes as adults than those raised in neighborhoods where the poverty rate did not change.
• >Why do poor neighborhoods have this effect? It is difficult to pinpoint the exact causes, but several probable reasons come to mind. In these neighborhoods, middle-class African American children often receive inadequate schooling at run-down schools, and they come under the influence of youths who care much less about schooling and who get into various kinds of trouble. The various problems associated with living in poor neighborhoods also likely cause a good deal of stress, which, as discussed elsewhere in this chapter, can cause health problems and impair learning ability.
• >Even if the exact reasons remain unclear, this study showed that poor neighborhoods make a huge difference. As a Pew official summarized the study, “We’ve known that neighborhood matters…but this does it in a new and powerful way. Neighborhoods become a significant drag not just on the poor, but on those who would otherwise be stable.” Sociologist Sharkey added, “What surprises me is how dramatic the racial differences are in terms of the environments in which children are raised. There’s this perception that after the civil rights period, families have been more able to seek out any neighborhood they choose and that…the racial gap in neighborhoods would whittle away over time, and that hasn’t happened.”
• >Data from the 2010 Census confirm that the racial gap in neighborhoods persists. A study by sociologist John R. Logan for the Russell Sage Foundation found that African American and Latino families with incomes above \$75,000 are more likely to live in poor neighborhoods than non-Latino white families with incomes below \$40,000. More generally, Logan concluded, “The average affluent black or Hispanic household lives in a poorer neighborhood than the average lower-income white household.”
• >One implication of this neighborhood research is clear: to help reduce African American poverty, it is important to do everything possible to improve the quality and economy of the poor neighborhoods in which many African American children, middle-class or poor, grow up.
• >Sources: Logan, 2011; MacGillis, 2009; Sharkey, 2009
• As we assess the importance of structure versus culture in explaining why people of color have higher poverty rates, it is interesting to consider the economic experience of African Americans and Latinos since the 1990s. During that decade, the US economy thrived. Along with this thriving economy, unemployment rates for African Americans and Latinos declined and their poverty rates also declined. Since the early 2000s and especially since 2008, the US economy has faltered. Along with this faltering economy, unemployment and poverty rates for African Americans and Latinos increased.
To explain these trends, does it make sense to assume that African Americans and Latinos somehow had fewer cultural deficiencies during the 1990s and more cultural deficiencies since the early 2000s? Or does it make sense to assume that their economic success or lack of it depended on the opportunities afforded them by the US economy? Economic writer Joshua Holland (2011) provides the logical answer by attacking the idea of cultural deficiencies: “That’s obviously nonsense. It was exogenous economic factors and changes in public policies, not manifestations of ‘black culture’ [or ‘Latino culture’], that resulted in those widely varied outcomes…While economic swings this significant can be explained by economic changes and different public policies, it’s simply impossible to fit them into a cultural narrative.”
Reducing Racial and Ethnic Inequality
Now that we have examined race and ethnicity in the United States, what have we found? Where do we stand in the second decade of the twenty-first century? Did the historic election of Barack Obama as president in 2008 signify a new era of equality between the races, as many observers wrote, or did his election occur despite the continued existence of pervasive racial and ethnic inequality?
On the one hand, there is cause for hope. Legal segregation is gone. The vicious, “old-fashioned” racism that was so rampant in this country into the 1960s has declined dramatically since that tumultuous time. People of color have made important gains in several spheres of life, and African Americans and other people of color occupy some important elected positions in and outside the South, a feat that would have been unimaginable a generation ago. Perhaps most notably, Barack Obama has African ancestry and identifies as an African American, and on his 2008 election night, people across the country wept with joy at the symbolism of his victory. Certainly, progress has been made in US racial and ethnic relations.
On the other hand, there is also cause for despair. Old-fashioned racism has been replaced by modern, symbolic racism that still blames people of color for their problems and reduces public support for government policies to deal with their problems. Institutional discrimination remains pervasive, and hate crimes, such as the cross-burning that began this chapter, remain all too common. So does suspicion of people based solely on the color of their skin, as the Trayvon Martin tragedy again reminds us.
If adequately funded and implemented, several types of programs and policies show a strong promise of reducing racial and ethnic inequality. We turn to these in a moment, but first let’s discuss affirmative action, an issue that has aroused controversy since its inception.
People Making a Difference
College Students and the Southern Civil Rights Movement
• >The first chapter of this book included this famous quotation by anthropologist Margaret Mead: “Never doubt that a small group of thoughtful, committed citizens can change the world. Indeed, it is the only thing that ever has.” The beginnings of the Southern civil rights movement provide an inspirational example of Mead’s wisdom and remind us that young people can make a difference.
• >Although there had been several efforts during the 1950s by African Americans to end legal segregation in the South, the start of the civil rights movement is commonly thought to have begun on February 1, 1960. On that historic day, four brave African American students from the Agricultural and Technical College of North Carolina, dressed in coats and ties, sat down quietly at a segregated lunch counter in a Woolworth’s store in the city of Greensboro and asked to be served. When they were refused service, they stayed until the store closed at the end of the day, and then went home. They returned the next day and were joined by some two dozen other students. They were again refused service and sat quietly for the rest of the day. The next day some sixty students and other people joined them, followed by some three hundred on the fourth day. Within a week, sit-ins were occurring at lunch counters in several other towns and cities inside and outside of North Carolina. In late July 1960, the Greensboro Woolworth’s finally served African Americans, and the entire Woolworth’s chain desegregated its lunch counters a day later. Although no one realized it at the time, the civil rights movement had “officially” begun thanks to the efforts of a small group of college students.
• >During the remaining years of the heyday of the civil rights movement, college students from the South and North joined thousands of other people in sit-ins, marches, and other activities to end legal segregation. Thousands were arrested, and at least forty-one were murdered. By risking their freedom and even their lives, they made a difference for millions of African Americans. And it all began when a small group of college students sat down at a lunch counter in Greensboro and politely refused to leave until they were served.
• >Sources: Branch, 1988; Southern Poverty Law Center, 2011
• Affirmative Action
Affirmative action refers to special consideration for minorities and women in employment and education to compensate for the discrimination and lack of opportunities they experience in the larger society. Affirmative action programs were begun in the 1960s to provide African Americans and, later, other people of color and women access to jobs and education to make up for past discrimination. President John F. Kennedy was the first known official to use the term, when he signed an executive order in 1961 ordering federal contractors to “take affirmative action” in ensuring that applicants are hired and treated without regard to their race and national origin. Six years later, President Lyndon B. Johnson added sex to race and national origin as demographic categories for which affirmative action should be used.
Although many affirmative action programs remain in effect today, court rulings, state legislation, and other efforts have limited their number and scope. Despite this curtailment, affirmative action continues to spark much controversy, with scholars, members of the public, and elected officials all holding strong views on the issue.
One of the major court rulings just mentioned was the US Supreme Court’s decision in Regents of the University of California v. Bakke, 438 US 265 (1978). Allan Bakke was a 35-year-old white man who had twice been rejected for admission into the medical school at the University of California, Davis. At the time he applied, UC–Davis had a policy of reserving sixteen seats in its entering class of one hundred for qualified people of color to make up for their underrepresentation in the medical profession. Bakke’s college grades and scores on the Medical College Admission Test were higher than those of the people of color admitted to UC–Davis either time Bakke applied. He sued for admission on the grounds that his rejection amounted to reverse racial discrimination on the basis of his being white (Stefoff, 2005).
The case eventually reached the Supreme Court, which ruled 5–4 that Bakke must be admitted into the UC–Davis medical school because he had been unfairly denied admission on the basis of his race. As part of its historic but complex decision, the Court thus rejected the use of strict racial quotas in admission, as it declared that no applicant could be excluded based solely on the applicant’s race. At the same time, however, the Court also declared that race may be used as one of the several criteria that admissions committees consider when making their decisions. For example, if an institution desires racial diversity among its students, it may use race as an admissions criterion along with other factors such as grades and test scores.
Two more recent Supreme Court cases both involved the University of Michigan: Gratz v. Bollinger, 539 US 244 (2003), which involved the university’s undergraduate admissions, and Grutter v. Bollinger, 539 US 306 (2003), which involved the university’s law school admissions. In Grutter the Court reaffirmed the right of institutions of higher education to take race into account in the admissions process. In Gratz, however, the Court invalidated the university’s policy of awarding additional points to high school students of color as part of its use of a point system to evaluate applicants; the Court said that consideration of applicants needed to be more individualized than a point system allowed.
Drawing on these Supreme Court rulings, then, affirmative action in higher education admissions on the basis of race/ethnicity is permissible as long as it does not involve a rigid quota system and as long as it does involve an individualized way of evaluating candidates. Race may be used as one of several criteria in such an individualized evaluation process, but it must not be used as the only criterion.
• The Debate over Affirmative Action
Opponents of affirmative action cite several reasons for opposing it (Connors, 2009). Affirmative action, they say, is reverse discrimination and, as such, is both illegal and immoral. The people benefiting from affirmative action are less qualified than many of the whites with whom they compete for employment and college admissions. In addition, opponents say, affirmative action implies that the people benefiting from it need extra help and thus are indeed less qualified. This implication stigmatizes the groups benefiting from affirmative action.
In response, proponents of affirmative action give several reasons for favoring it (Connors, 2009). Many say it is needed to make up not just for past discrimination and a lack of opportunities for people of color but also for ongoing discrimination and a lack of opportunity. For example, because of their social networks, whites are much better able than people of color to find out about and to get jobs (Reskin, 1998). If this is true, people of color are automatically at a disadvantage in the job market, and some form of affirmative action is needed to give them an equal chance at employment. Proponents also say that affirmative action helps add diversity to the workplace and to the campus. Many colleges, they note, give some preference to high school students who live in a distant state in order to add needed diversity to the student body; to “legacy” students—those with a parent who went to the same institution—to reinforce alumni loyalty and to motivate alumni to donate to the institution; and to athletes, musicians, and other applicants with certain specialized talents and skills. If all these forms of preferential admission make sense, proponents say, it also makes sense to take students’ racial and ethnic backgrounds into account as admissions officers strive to have a diverse student body.
Proponents add that affirmative action has indeed succeeded in expanding employment and educational opportunities for people of color and that individuals benefiting from affirmative action have generally fared well in the workplace or on the campus. In this regard, research finds that African American students graduating from selective US colleges and universities after being admitted under affirmative action guidelines are slightly more likely than their white counterparts to obtain professional degrees and to become involved in civic affairs (Bowen & Bok, 1998).
As this brief discussion indicates, several reasons exist for and against affirmative action. A cautious view is that affirmative action may not be perfect but that some form of it is needed to make up for past and ongoing discrimination and lack of opportunity in the workplace and on the campus. Without the extra help that affirmative action programs give disadvantaged people of color, the discrimination and other difficulties they face are certain to continue.
• Other Programs and Policies
As indicated near the beginning of this chapter, one message from DNA evidence and studies of evolution is that we are all part of one human race. If we fail to recognize this lesson, we are doomed to repeat the experiences of the past, when racial and ethnic hostility overtook good reason and subjected people who happened to look different from the white majority to legal, social, and violent oppression. In the democracy that is America, we must try to do better so that there will truly be “liberty and justice for all.”
As the United States attempts, however haltingly, to reduce racial and ethnic inequality, sociology has much insight to offer in its emphasis on the structural basis for this inequality. This emphasis strongly indicates that racial and ethnic inequality has much less to do with any personal faults of people of color than with the structural obstacles they face, including ongoing discrimination and lack of opportunity. Efforts aimed at such obstacles, then, are in the long run essential to reducing racial and ethnic inequality (Danziger, Reed, & Brown, 2004; Syme, 2008; Walsh, 2011). Some of these efforts resemble those for reducing poverty discussed in Chapter 2 “Poverty”, given the greater poverty of many people of color, and include the following:
1. Adopt a national “full employment” policy involving federally funded job training and public works programs.
2. Increase federal aid for the working poor, including earned income credits and child-care subsidies for those with children.
3. Establish and expand well-funded early childhood intervention programs, including home visitation by trained professionals, for poor families, as well as adolescent intervention programs, such as Upward Bound, for low-income teenagers.
4. Improve the schools that poor children attend and the schooling they receive, and expand early childhood education programs for poor children.
5. Provide better nutrition and health services for poor families with young children.
6. Strengthen efforts to reduce teenage pregnancies.
7. Strengthen affirmative action programs within the limits imposed by court rulings.
8. Strengthen legal enforcement of existing laws forbidding racial and ethnic discrimination in hiring and promotion.
9. Strengthen efforts to reduce residential segregation.
Key Takeaways
• Racial and ethnic prejudice and discrimination have been an “American dilemma” in the United States ever since the colonial period. Slavery was only the ugliest manifestation of this dilemma. The urban riots of the 1960s led to warnings about the racial hostility and discrimination confronting African Americans and other groups, and these warnings continue down to the present.
• Social scientists today tend to consider race more of a social category than a biological one for several reasons. Race is thus best considered a social construction and not a fixed biological category.
• Ethnicity refers to a shared cultural heritage and is a term increasingly favored by social scientists over race. Membership in ethnic groups gives many people an important sense of identity and pride but can also lead to hostility toward people in other ethnic groups.
• Prejudice, racism, and stereotypes all refer to negative attitudes about people based on their membership in racial or ethnic categories. Social-psychological explanations of prejudice focus on scapegoating and authoritarian personalities, while sociological explanations focus on conformity and socialization or on economic and political competition. Jim Crow racism has given way to modern or symbolic racism that considers people of color to be culturally inferior.
• Discrimination and prejudice often go hand in hand, but not always. People can discriminate without being prejudiced, and they can be prejudiced without discriminating. Individual and institutional discrimination both continue to exist in the United States.
• Racial and ethnic inequality in the United States is reflected in income, employment, education, and health statistics. In their daily lives, whites enjoy many privileges denied to their counterparts in other racial and ethnic groups.
• On many issues Americans remain sharply divided along racial and ethnic lines. One of the most divisive issues is affirmative action. Its opponents view it among other things as reverse discrimination, while its proponents cite many reasons for its importance, including the need to correct past and present discrimination against racial and ethnic minorities.
What You Can Do
• To help reduce racial and ethnic inequality, you may wish to do any of the following:
1. Contribute money to a local, state, or national organization that tries to help youths of color at their schools, homes, or other venues.
2. Volunteer for an organization that focuses on policy issues related to race and ethnicity.
3. Volunteer for any programs at your campus that aim at enhancing the educational success of new students of color; if no such programs exist, start one.
Attribution
Social Problems by the University of Minnesota under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/04%3A_The_Social_Change_Dimension/4.04%3A_Chapter_8-_Racial_and_Ethnic_Inequality.txt |
Chapter 9 Learning Objectives
• Distinguish between mitosis and meiosis, genotype and phenotype, homozygous and heterozygous, and dominant and recessive.
• Describe some genetic disorders, due to a gene defect, and chromosomal disorders.
• Define behavioral genetics, describe genotype-environment correlations and genotype-environmental interactions, and define epigenetics.
• Describe the changes that occur in the three periods of prenatal development
• Describe what occurs during prenatal brain development
• Define teratogens and describe the factors that influence their effects
• Explain maternal and paternal factors that affect the developing fetus
• Explain the types of prenatal assessment
• Describe both the minor and major complications of pregnancy
• Describe how expectant parents prepare for childbirth
• Describe the stages of vaginal delivery
• Explain why a cesarean or induced birth is necessary
• Describe the two common procedures to assess the condition of the newborn
• Describe problems newborns experience before, during, and after birth
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Prenatal Development
The Germinal Period
zygote.
blastocyst. The blastocyst consists of both an inner and an outer group of cells. The inner group of cells or embryonic disk will become the embryo, while the outer group of cells, or trophoblast, becomes the support system that nourishes the developing organism. This stage ends when the blastocyst fully implants into the uterine wall (U.S. National Library of Medicine, 2015a). Approximately 50-75% of blastocysts do not implant in the uterine wall (Betts et al., 2019).
The Embryonic Period
embryo. Now blood vessels grow forming the placenta. The placenta is a structure connected to the uterus that provides nourishment and oxygen from the mother to the developing embryo via the umbilical cord. During this period, cells continue to differentiate. Growth during prenatal development occurs in two major directions: from head to tail called cephalocaudal development and from the midline outward referred to as proximodistal development. This means that those structures nearest the head develop before those nearest the feet and those structures nearest the torso develop before those away from the center of the body (such as hands and fingers). The head develops in the fourth week and the precursor to the heart begins to pulse. In the early stages of the embryonic period, gills and a tail are apparent. However, by the end of this stage, they disappear and the organism takes on a more human appearance. Some organisms fail during the embryonic period, usually due to gross chromosomal abnormalities. As in the case of the germinal period, often the mother does not yet know that she is pregnant. It is during this stage that the major structures of the body are taking form making the embryonic period the time when the organism is most vulnerable to the greatest amount of damage if exposed to harmful substances. Potential mothers are not often aware of the risks they introduce to the developing embryo during this time. The embryo is approximately 1 inch in length and weighs about 8 grams at the end of eight weeks (Betts et al., 2019). The embryo can move and respond to touch at this time.
The Fetal Period
fetus. During this stage, the major structures are continuing to develop. By the third month, the fetus has all its body parts including external genitalia. In the following weeks, the fetus will develop hair, nails, teeth and the excretory and digestive systems will continue to develop. The fetus is about 3 inches long and weighs about 28 grams.
age of viability is reached at about 24 weeks (Morgan, Goldenberg, & Schulkin, 2008). Many practitioners hesitate to resuscitate before 24 weeks. The majority of the neurons in the brain have developed by 24 weeks, although they are still rudimentary, and the glial or nurse cells that support neurons continue to grow. At 24 weeks the fetus can feel pain (Royal College of Obstetricians and Gynecologists, 1997).
Prenatal Brain Development
neural plate. By the end of the third week, two ridges appear along the neural plate first forming the neural groove and then the neural tube. The open region in the center of the neural tube forms the brain’s ventricles and spinal canal. By the end of the embryonic period, or week eight, the neural tube has further differentiated into the forebrain, midbrain, and hindbrain.
Neurogenesis, or the formation of neurons, is largely completed after five months of gestation. One exception is in the hippocampus, which continues to develop neurons throughout life. Neurons that form the neocortex, or the layer of cells that lie on the surface of the brain, migrate to their location in an orderly way. Neural migration is mostly completed in the cerebral cortex by 24 weeks (Poduri & Volpe, 2018). Once in position, neurons begin to produce dendrites and axons that begin to form the neural networks responsible for information processing. Regions of the brain that contain the cell bodies are referred to as the gray matter because they look gray in appearance. The axons that form the neural pathways make up the white matter because they are covered in myelin, a fatty substance that is white in appearance. Myelin aids in both the insulation and efficiency of neural transmission. Although cell differentiation is complete at birth, the growth of dendrites, axons, and synapses continue for years.
Teratogens
Teratogens are environmental factors that can contribute to birth defects, and include some maternal diseases, pollutants, drugs and alcohol.
Factors influencing prenatal risks: There are several considerations in determining the type and amount of damage that might result from exposure to a particular teratogen (Berger, 2005). These include:
• The timing of the exposure: Structures in the body are vulnerable to the most severe damage when they are forming. If a substance is introduced during a particular structure’s critical period (time of development), the damage to that structure may be greater. For example, the ears and arms reach their critical periods at about 6 weeks after conception. If a mother exposes the embryo to certain substances during this period, the arms and ears may be malformed.
• The amount of exposure: Some substances are not harmful unless the amounts reach a certain level. The critical level depends in part on the size and metabolism of the mother.
• The number of teratogens: Fetuses exposed to multiple teratogens typically have more problems than those exposed to only one.
• Genetics: Genetic make-up also plays a role in the impact a particular teratogen might have on the child. This is suggested by fraternal twins exposed to the same prenatal environment, but they do not experience the same teratogenic effects. The genetic make- up of the mother can also have an effect; some mothers may be more resistant to teratogenic effects than others.
• Being male or female: Males are more likely to experience damage due to teratogens than are females. It is believed that the Y chromosome, which contains fewer genes than the X, may have an impact.
Alcohol: One of the most commonly used teratogens is alcohol, and because half of all pregnancies in the United States are unplanned, it is recommended that women of child-bearing age take great caution against drinking alcohol when not using birth control or when pregnant (CDC, 2005). Alcohol use during pregnancy is the leading preventable cause of intellectual disabilities in children in the United States (Maier & West, 2001). Alcohol consumption, particularly during the second month of prenatal development but at any point during pregnancy, may lead to neurocognitive and behavioral difficulties that can last a lifetime.
Fetal Alcohol Spectrum Disorders (FASD), which is an umbrella term for the range of effects that can occur due to alcohol consumption during pregnancy (March of Dimes, 2016a). The most severe form of FASD is Fetal Alcohol Syndrome (FAS). Children with FAS share certain physical features such as flattened noses, small eye holes, and small heads. Cognitively, these children have poor judgment, poor impulse control, higher rates of ADHD, learning issues, and lower IQ scores. These developmental problems and delays persist into adulthood (Streissguth, Barr, Kogan, & Bookstein, 1996) and can include criminal behavior, psychiatric problems, and unemployment (CDC, 2016a). Based on animal studies, it has been hypothesized that a mother’s alcohol consumption during pregnancy may predispose her child to like alcohol (Youngentob, Molina, Spear, & Youngentob, 2007). Binge drinking, or 4 or more drinks in 2 to 3 hours, during pregnancy increases the chance of having a baby with FASD (March of Dimes, 2016a).
Tobacco: Another widely used teratogen is tobacco as more than 7% of pregnant women smoked in 2016 (Someji & Beltrán-Sánchez, 2019). According to Tong et al. (2013) in conjunction with the Centers for Disease Control and Prevention, data from 27 sites in 2010 representing 52% of live births, showed that among women with recent live births:
• About 23% reported smoking in the 3 months prior to pregnancy.
• Almost 11% reported smoking during pregnancy.
• More than half (54.3%) reported that they quit smoking by the last 3 months of pregnancy.
• Almost 16% reported smoking after delivery.
• Women <20, 13.6% smoked during pregnancy
• Women 20–24,17.6% smoked during pregnancy
• Women 25–34, 8.8% smoked during pregnancy
• Women ≥35, 5.7% smoked during pregnancy
ectopic pregnancy (fertilized egg implants itself outside of the uterus), placenta previa (placenta lies low in the uterus and covers all or part of the cervix), placenta abruption (placenta separates prematurely from the uterine wall), preterm delivery, stillbirth, fetal growth restriction, sudden infant death syndrome (SIDS), birth defects, learning disabilities, and early puberty in girls (Center for Disease Control, 2015d).
thirdhand smoke, or toxins from tobacco smoke that linger on clothing, furniture, and in locations where smoking has occurred, results in a negative impact on infants’ lung development. Rehan, Sakurai, and Torday (2011) found that prenatal exposure to thirdhand smoke played a greater role in altered lung functioning in children than exposure postnatally.
Prescription/Over-the-counter Drugs: About 70% of pregnant women take at least one prescription drug (March of Dimes, 2016e). A woman should not be taking any prescription drug during pregnancy unless it was prescribed by a health care provider who knows she is pregnant. Some prescription drugs can cause birth defects, problems in overall health, and development of the fetus. Over-the-counter drugs are also a concern during the prenatal period because they may cause certain health problems. For example, the pain reliever ibuprofen can cause serious blood flow problems to the fetus during the last three months.
Illicit Drugs: Common illicit drugs include cocaine, ecstasy and other club drugs, heroin, marijuana, and prescription drugs that are abused. It is difficult to completely determine the effects of a particular illicit drug on a developing child because most mothers who use, use more than one substance and have other unhealthy behaviors. These include smoking, drinking alcohol, not eating healthy meals, and being more likely to get a sexually transmitted disease. However, several problems seem clear. The use of cocaine is connected with low birth weight, stillbirths and spontaneous abortion. Heavy marijuana use is associated with problems in brain development (March of Dimes, 2016c). If a baby’s mother used an addictive drug during pregnancy that baby can get addicted to the drug before birth and go through drug withdrawal after birth, also known as neonatal abstinence syndrome (March of Dimes, 2015d). Other complications of illicit drug use include premature birth, smaller than normal head size, birth defects, heart defects, and infections. Additionally, babies born to mothers who use drugs may have problems later in life, including learning and behavior difficulties, slower than normal growth, and die from sudden infant death syndrome. Children of substance abusing parents are also considered at high risk for a range of biological, developmental, academic, and behavioral problems, including developing substance abuse problems of their own (Conners, et al., 2003).
Pollutants: There are more than 83,000 chemicals used in the United States with little information on the effects of them during pregnancy (March of Dimes, 2016b).
• Lead: An environmental pollutant of significant concern is lead poisoning, which has been linked to fertility problems, high blood pressure, low birth weight, prematurity, miscarriage, and slowed neurological development. Grossman and Slutsky (2017) found that babies born in Flint Michigan, an area identified with high lead levels in the drinking water, were premature, weighed less than average, and gained less weight than expected.
• Pesticides: The chemicals in certain pesticides are also potentially damaging and may lead to birth defects, learning problems, low birth weight, miscarriage, and premature birth (March of Dimes, 2014).
• Bisphenol A: Prenatal exposure to bisphenol A (BPA), a chemical commonly used in plastics and food and beverage containers, may disrupt the action of certain genes contributing to certain birth defects (March of Dimes, 2016b).
• Radiation: If a mother is exposed to radiation, it can get into the bloodstream and pass through the umbilical cord to the baby. Radiation can also build up in body areas close to the uterus, such as the bladder. Exposure to radiation can slow the baby’s growth, cause birth defects, affect brain development, cause cancer, and result in a miscarriage.
• Mercury: Mecury, a heavy metal, can cause brain damage and affect the baby’s hearing and vision. This is why women are cautioned about the amount and type of fish they consume during pregnancy.
Toxoplasmosis: The tiny parasite, toxoplasma gondii, causes an infection called toxoplasmosis. According to the March of Dimes (2012d), toxoplasma gondii infects more than 60 million people in the United States. A healthy immune system can keep the parasite at bay producing no symptoms, so most people do not know they are infected. As a routine prenatal screening frequently does not test for the presence of this parasite, pregnant women may want to talk to their health-care provider about being tested.
Toxoplasmosis can cause premature birth, stillbirth, and can result in birth defects to the eyes and brain. While most babies born with this infection show no symptoms, ten percent may experience eye infections, enlarged liver and spleen, jaundice, and pneumonia. To avoid being infected, women should avoid eating undercooked or raw meat and unwashed fruits and vegetables, touching cooking utensils that touched raw meat or unwashed fruits and vegetables, and touching cat feces, soil or sand. If women think they may have been infected during pregnancy, they should have their baby tested.
Sexually Transmitted Diseases: Gonorrhea, syphilis, and chlamydia are sexually transmitted infections that can be passed to the fetus by an infected mother. Mothers should be tested as early as possible to minimize the risk of spreading these infections to their unborn child. Additionally, the earlier the treatment begins, the better the health outcomes for mother and baby (CDC, 2016d). Sexually transmitted diseases (STDs) can cause premature birth, premature rupture of the amniotic sac, an ectopic pregnancy, birth defects, miscarriage, and still births (March of Dimes, 2013). Most babies become infected with STDS while passing through the birth canal during delivery, but some STDs can cross the placenta and infect the developing fetus.
Human Immunodeficiency Virus (HIV): One of the most potentially devastating teratogens is HIV. HIV and Acquired Immune Deficiency Syndrome (AIDS) are leading causes of illness and death in the United States (Health Resources and Services Administration, 2015). One of the main ways children under age 13 become infected with HIV is via mother-to-child transmission of the virus prenatally, during labor, or by breastfeeding (CDC, 2016c). There are some measures that can be taken to lower the chance the child will contract the disease. HIV positive mothers who take antiviral medications during their pregnancy greatly reduce the chance of passing the virus to the fetus. The risk of transmission is less than 2 percent; in contrast, it is 25 percent if the mother does not take antiretroviral drugs (CDC, 2016b). However, the long-term risks of prenatal exposure to the medication are not known. It is recommended that women with HIV deliver the child by c-section, and that after birth they avoid breast feeding.
German measles (or rubella): Rubella, also called German measles, is an infection that causes mild flu-like symptoms and a rash on the skin. However, only about half of children infected have these symptoms, while others have no symptoms (March of Dimes, 2012a). Rubella has been associated with a number of birth defects. If the mother contracts the disease during the first three months of pregnancy, damage can occur in the eyes, ears, heart or brain of the unborn child. Deafness is almost certain if the mother has German measles before the 11th week of prenatal development and can also cause brain damage. Women in the United States are much less likely to be afflicted with rubella, because most women received childhood vaccinations that protect her from the disease.
Maternal Factors
Mothers over 35: Most women over 35 who become pregnant are in good health and have healthy pregnancies. However, according to the March of Dimes (2016d), women over age 35 are more likely to have an increased risk of:
• Fertility problems
• High blood pressure
• Diabetes
• Miscarriages
• Placenta Previa
• Cesarean section
• Premature birth
• Stillbirth
• A baby with a genetic disorder or other birth defects
Teenage Pregnancy: A teenage mother is at a greater risk for having pregnancy complications including anemia, and high blood pressure. These risks are even greater for those under age 15. Infants born to teenage mothers have a higher risk for being premature and having low birthweight or other serious health problems. Premature and low birthweight babies may have organs that are not fully developed which can result in breathing problems, bleeding in the brain, vision loss, and serious intestinal problems. Very low birthweight babies (less than 3 1/3 pounds) are more than 100 times as likely to die, and moderately low birthweight babies (between 3 1/3 and 5 ½ pounds) are more than 5 times as likely to die in their first year, than normal weight babies (March of Dimes, 2012c). Again, the risk is highest for babies of mothers under age 15. Reasons for these health issues include that teenagers are the least likely of all age groups to get early and regular prenatal care. Additionally, they may engage in negative behaviors including eating unhealthy food, smoking, drinking alcohol, and taking drugs. Additional concerns for teenagers are repeat births. About 25% of teen mothers under age 18 have a second baby within 2 years after the first baby’s birth.
Gestational Diabetes: Seven percent of pregnant women develop gestational diabetes (March of Dimes, 2015b). Diabetes is a condition where the body has too much glucose in the bloodstream. Most pregnant women have their glucose level tested at 24 to 28 weeks of pregnancy. Gestational diabetes usually goes away after the mother gives birth, but it might indicate a risk for developing diabetes later in life. If untreated, gestational diabetes can cause premature birth, stillbirth, the baby having breathing problems at birth, jaundice, or low blood sugar. Babies born to mothers with gestational diabetes can also be considerably heavier (more than 9 pounds) making the labor and birth process more difficult. For expectant mothers, untreated gestational diabetes can cause preeclampsia (high blood pressure and signs that the liver and kidneys may not be working properly) discussed later in the chapter. Risk factors for gestational diabetes include age (being over age 25), being overweight or gaining too much weight during pregnancy, family history of diabetes, having had gestational diabetes with a prior pregnancy, and race and ethnicity (African-American, Native American, Hispanic, Asian, or Pacific Islander have a higher risk). Eating healthy and maintaining a healthy weight during pregnancy can reduce the chance of gestational diabetes. Women who already have diabetes and become pregnant need to attend all their prenatal care visits, and follow the same advice as those for women with gestational diabetes as the risk of preeclampsia, premature birth, birth defects, and stillbirth are the same.
High Blood Pressure (Hypertension): Hypertension is a condition in which the pressure against the wall of the arteries becomes too high. There are two types of high blood pressure during pregnancy, gestational and chronic. Gestational hypertension only occurs during pregnancy and goes away after birth. Chronic high blood pressure refers to women who already had hypertension before the pregnancy or to those who developed it during pregnancy and it continued after birth. According to the March of Dimes (2015c) about 8 in every 100 pregnant women have high blood pressure. High blood pressure during pregnancy can cause premature birth and low birth weight (under five and a half pounds), placental abruption, and mothers can develop preeclampsia.
Rh Disease: Rh is a protein found in the blood. Most people are Rh positive, meaning they have this protein. Some people are Rh negative, meaning this protein is absent. Mothers who are Rh negative are at risk of having a baby with a form of anemia called Rh disease (March of Dimes, 2009). A father who is Rh-positive and mother who is Rh-negative can conceive a baby who is Rh-positive. Some of the fetus’s blood cells may get into the mother’s bloodstream and her immune system is unable to recognize the Rh factor. The immune system starts to produce antibodies to fight off what it thinks is a foreign invader. Once her body produces immunity, the antibodies can cross the placenta and start to destroy the red blood cells of the developing fetus. As this process takes time, often the first Rh positive baby is not harmed, but as the mother’s body will continue to produce antibodies to the Rh factor across her lifetime, subsequent pregnancies can pose greater risk for an Rh positive baby. In the newborn, Rh disease can lead to jaundice, anemia, heart failure, brain damage and death.
Weight Gain during Pregnancy: According to March of Dimes (2016f) during pregnancy most women need only an additional 300 calories per day to aid in the growth of the fetus. Gaining too little or too much weight during pregnancy can be harmful. Women who gain too little may have a baby who is low-birth weight, while those who gain too much are likely to have a premature or large baby. There is also a greater risk for the mother developing preeclampsia and diabetes, which can cause further problems during the pregnancy. Putting on the weight slowly is best. Mothers who are concerned about their weight gain should talk to their health care provider.
Stress: Feeling stressed is common during pregnancy, but high levels of stress can cause complications including having a premature baby or a low-birthweight baby. Babies born early or too small are at an increased risk for health problems. Stress-related hormones may cause these complications by affecting a woman’s immune systems resulting in an infection and premature birth. Additionally, some women deal with stress by smoking, drinking alcohol, or taking drugs, which can lead to problems in the pregnancy. High levels of stress in pregnancy have also been correlated with problems in the baby’s brain development and immune system functioning, as well as childhood problems such as trouble paying attention and being afraid (March of Dimes, 2012b).
Depression: Depression is a significant medical condition in which feelings of sadness, worthlessness, guilt, and fatigue interfere with one’s daily functioning. Depression can occur before, during, or after pregnancy, and 1 in 7 women is treated for depression sometime between the year before pregnancy and year after pregnancy (March of Dimes, 2015a). Women who have experienced depression previously are more likely to have depression during pregnancy. Consequences of depression include the baby being born premature, having a low birthweight, being more irritable, less active, less attentive, and having fewer facial expressions. About 13% of pregnant women take an antidepressant during pregnancy. It is important that women taking antidepressants during pregnancy discuss the medication with a health care provider as some medications can cause harm to the developing organism. In fact, birth defects happen about 2 to 3 times more often in women who are prescribed certain Selective Serotonin Reuptake Inhibitors (SSRIs) for their depression.
Paternal Impact: The age of fathers at the time of conception is also an important factor in health risks for children. According to Nippoldt (2015) offspring of men over 40 face an increased risk of miscarriages, autism, birth defects, achondroplasia (bone growth disorder) and schizophrenia. These increased health risks are thought to be due to accumulated chromosomal aberrations and mutations during the maturation of sperm cells in older men (Bray, Gunnell, & Smith, 2006). However, like older women, the overall risks are small.
Prenatal Assessment
Ultrasound is one of the main screening tests done in combination with blood tests. The ultrasound is a test in which sound waves are used to examine the fetus. There are two general types. Transvaginal ultrasounds are used in early pregnancy, while transabdominal ultrasounds are more common and used after 10 weeks of pregnancy (typically, 16 to 20 weeks). Ultrasounds are used to check the fetus for defects or problems. It can also find out the age of the fetus, location of the placenta, fetal position, movement, breathing and heart rate, amount of amniotic fluid, and number of fetuses. Most women have at least one ultra sound during pregnancy, but if problems are noted, additional ultrasounds may be recommended.
Amniocentesis is a procedure in which a needle is used to withdraw a small amount of amniotic fluid and cells from the sac surrounding the fetus and later tested. Chorionic Villus Sampling is a procedure in which a small sample of cells is taken from the placenta and tested. Both amniocentesis and chorionic villus sampling have a risk of miscarriage, and consequently they are not done routinely.
Complications of Pregnancy
Minor complications: There are a number of common side effects of pregnancy. Not everyone experiences all of these, nor to the same degree. And although they are considered “minor” this is not to say that these problems are not potentially very uncomfortable. These side effects include nausea (particularly during the first 3-4 months of pregnancy as a result of higher levels of estrogen in the system), heartburn, gas, hemorrhoids, backache, leg cramps, insomnia, constipation, shortness of breath or varicose veins (as a result of carrying a heavy load on the abdomen).
Major Complications: The following are some serious complications of pregnancy which can pose health risks to mother and child and that often require hospitalization.
Ectopic Pregnancy occurs when the zygote becomes attached to the fallopian tube before reaching the uterus. About 1 in 50 pregnancies in the United States are tubal pregnancies and this number has been increasing because of the higher rates of pelvic inflammatory disease and Chlamydia (Carroll, 2007). Abdominal pain, vaginal bleeding, nausea and fainting are symptoms of ectopic pregnancy.
Preeclampsia, also known as Toxemia, is characterized by a sharp rise in blood pressure, a leakage of protein into the urine as a result of kidney problems, and swelling of the hands, feet, and face during the third trimester of pregnancy. Preeclampsia is the most common complication of pregnancy. It is estimated to affect 5% to 10% of all pregnancies globally and accounts for 40% to 60% of maternal deaths in developing countries (National Institute of Child Health and Human Development, 2013). Rates are lower in the United States and preeclampsia affects about 3% to 5% of pregnant women.
eclampsia, which is the second leading cause of maternal death in the United States. Preeclampsia is also a leading cause of fetal complications, which include low birth weight, premature birth, and stillbirth. Treatment is typically bed rest and sometimes medication. If this treatment is ineffective, labor may be induced.
Maternal Mortality: Acording to the CDC (2019), about 700 American women die from complications related to pregnancy each year, and this number is rising. Further, 60% of those deaths could have been prevented. Bleeding, infections, and heart-related problems are the main causes. Possible contributing factors include the high caesarean section rate and obesity. Compared to other developed nations, this number is considered high. Approximately 1000 women die in childbirth around the world each day (World Health Organization, 2010). Rates are highest in Subsaharan Africa and South Asia, although there has been a substantial decrease in these rates. The campaign to make childbirth safe for everyone has led to the development of clinics accessible to those living in more isolated areas and training more midwives to assist in childbirth.
Spontaneous abortion is experienced in an estimated 20-40 percent of undiagnosed pregnancies and in another 10 percent of diagnosed pregnancies. Usually the body aborts due to chromosomal abnormalities, and this typically happens before the 12th week of pregnancy. Cramping and bleeding result and normal periods return after several months. Some women are more likely to have repeated miscarriages due to chromosomal, amniotic, or hormonal problems, but miscarriage can also be a result of defective sperm (Carrell et. al., 2003).
Birth
Preparation for Childbirth
The Lamaze Method. This method originated in Russia and was brought to the United States in the 1950s by Fernand Lamaze. The emphasis of this method is on teaching the woman to be in control in the process of delivery. It includes learning muscle relaxation, breathing though contractions, having a focal point (usually a picture to look at) during contractions and having a support person who goes through the training process with the mother and serves as a coach during delivery (Eisenberg, Murkoff, & Hathaway, 1996).
Choosing Where to Have the Baby and Who Will Deliver: The vast majority of births occur in a hospital setting. However, one percent of women choose to deliver at home (Martin, Hamilton, Osterman, Curtin, & Mathews, 2015). Women who are at low risk for birth complications can successfully deliver at home. More than half (67%) of home deliveries are by certified nurse midwifes. Midwives are trained and licensed to assist in delivery and are far less expensive than the cost of a hospital delivery. However, because of the potential for a complication during the birth process, most medical professionals recommend that delivery take place in a hospital. Despite the concerns, in the United States women who have had previous children, who are over 25, and who are white are more likely to have out-of-hospital births (MacDorman, Menacker, & Declercq, 2010). In addition to home births, one-third of out-of-hospital births occur in freestanding clinics, birthing centers, in physician’s offices, or other locations.
Stages of Birth for Vaginal Delivery
The First Stage of labor begins with uterine contractions that may initially last about 30 seconds and be spaced 15 to 20 minutes apart. These increase in duration and frequency to more than a minute in length and about 3 to 4 minutes apart. Typically, doctors advise that they be called when contractions are coming about every 5 minutes. Some women experience false labor or Braxton-Hicks contractions, especially with the first child. These may come and go. They tend to diminish when the mother begins walking around. Real labor pains tend to increase with walking. Labor may also be signaled by a bloody discharge being expelled from the cervix. In one out of 8 pregnancies, the amniotic sac or water in which the fetus is suspended may break before labor begins. In such cases, the physician may induce labor with the use of medication if it does not begin on its own in order to reduce the risk of infection. Normally this sac does not rupture until the later stages of labor.
The Second Stage involves the passage of the baby through the birth canal. This stage takes about 10-40 minutes. Contractions usually come about every 2-3 minutes. The mother pushes and relaxes as directed by the medical staff. Normally the head is delivered first. The baby is then rotated so that one shoulder can come through and then the other shoulder. The rest of the baby quickly passes through. At this stage, an episiotomy or incision made in the tissue between the vaginal opening and anus, may be performed to avoid tearing the tissue of the back of the vaginal opening (Mayo Clinic, 2016). The baby’s mouth and nose are suctioned out. The umbilical cord is clamped and cut.
The Third Stage is relatively painless. During this stage, the placenta or afterbirth is delivered. This is typically within 20 minutes after delivery. If an episiotomy was performed it is stitched up during this stage.
epidural block is a regional analgesic that can be used during labor and alleviates most pain in the lower body without slowing labor. The epidural block can be used throughout labor and has little to no effect on the baby. Medication is injected into a small space outside the spinal cord in the lower back. It takes 10 to 20 minutes for the medication to take effect. An epidural block with stronger medications, such as anesthetics, can be used shortly before a C-section or if a vaginal birth requires the use of forceps or vacuum extraction.
Cesarean section (C-section) is surgery to deliver the baby by being removed through the mother’s abdomen. In the United States, about one in three women have their babies delivered this way (Martin et al., 2015). Most C-sections are done when problems occur during delivery unexpectedly. These can include:
• Health problems in the mother
• Signs of distress in the baby
• Not enough room for the baby to go through the vagina
• The position of the baby, such as a breech presentation where the head is not in the downward position
Induced birth: Sometimes a baby’s arrival may need to be induced or delivered before labor begins. Inducing labor may be recommended for a variety of reasons when there is concern for the health of the mother or baby. For example:
• The mother is approaching two weeks beyond her due date and labor has not started naturally
• The mother’s water has broken, but contractions have not begun
• There is an infection in the mother’s uterus
• The baby has stopped growing at the expected pace
• There is not enough amniotic fluid surrounding the baby
• The placenta peels away, either partially or completely, from the inner wall of the uterus before delivery
• The mother has a medical condition that might put her or her baby at risk, such as high blood pressure or diabetes (Mayo Clinic, 2014)
Assessing the Neonate
This is a very quick way to assess the newborn’s overall condition. Five measures are assessed: Heart rate, respiration, muscle tone (assessed by touching the baby’s palm), reflex response (the Babinski reflex is tested), and color. A score of 0 to 2 is given on each feature examined. An Apgar of 5 or less is cause for concern. The second Apgar should indicate improvement with a higher score.
Problems of the Newborn
Anoxia: Anoxia is a temporary lack of oxygen to the brain. Difficulty during delivery may lead to anoxia which can result in brain damage or in severe cases, death. Babies who suffer both low birth weight and anoxia are more likely to suffer learning disabilities later in life as well.
Low Birth weight: We have been discussing a number of teratogens associated with low birth weight such as alcohol, tobacco, etc. A child is considered low birth weight if he or she weighs less than 5 pounds 8 ounces (2500 grams). About 8.2 percent of babies born in the United States are of low birth weight (Center for Disease Control, 2015a). A low birth weight baby has difficulty maintaining adequate body temperature because it lacks the fat that would otherwise provide insulation. Such a baby is also at more risk for infection, and 67 percent of these babies are also preterm which can make them more at risk for respiratory infection. Very low birth weight babies (2 pounds or less) have an increased risk of developing cerebral palsy.
Preterm: A newborn might also have a low birth weight if it is born at less than 37 weeks gestation, which qualifies it as a preterm baby (CDC, 2015c). Early birth can be triggered by anything that disrupts the mother’s system. For instance, vaginal infections can lead to premature birth because such infection causes the mother to release anti-inflammatory chemicals which, in turn, can trigger contractions. Smoking and the use of other teratogens can lead to preterm
birth. The earlier a woman quits smoking, the lower the chance that the baby will be born preterm (Someji & Beltrán-Sánchez, 2019). A significant consequence of preterm birth includes respiratory distress syndrome, which is characterized by weak and irregular breathing (United States National Library of Medicine, 2015b).
Small-for-Date Infants: Infants that have birth weights that are below expectation based on their gestational age are referred to as small-for-date.
These infants may be full term or preterm, but still weigh less than 90 % of all babies of the same gestational age. This is a very serious situation for newborns as their growth was adversely affected. Regev et al. (2003) found that small-for- date infants died at rates more than four times higher than other infants. Remember that many causes of low birth weight and preterm births are preventable with proper prenatal care.
Postpartum Maternal Concerns
baby blues are feelings of sadness that occur 3 to 5 days after having a baby, and typically disappear usually within 10 days of the birth. New mothers may have trouble sleeping, be moody, and feel let-down from the birthing experience. However, postpartum depression is not the same as the baby blues. According to the Diagnostic and Statistical Manual of Mental Disorders-5th edition (DSM-5), (American Psychiatric Association, 2013), peripartum onset of depression, also known as postpartum depression, is a type of depression that occurs during pregnancy or in the 4 weeks following pregnancy. Approximately 1 out of 8 women experience postpartum depression and symptoms can include feelings of sadness, sleeplessness, and difficulty bonding with the newborn.
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/05%3A_Pre-Pregnancy_and_Prenatal_Development/5.01%3A_Chapter_9-_Heredity_Prenatal_Development_and_Birth.txt |
Chapter 10 Learning Objectives
• Summarize overall physical growth during infancy.
• Describe the growth in the brain during infancy.
• Explain infant sleep.
• Identify newborn reflexes.
• Compare gross and fine motor skills.
• Contrast the development of the senses in newborns.
• Describe the habituation procedure.
• Explain the merits of breastfeeding and when to introduce more solid foods.
• Discuss the nutritional concerns of marasmus and kwashiorkor.
The Brain in the First Two Years
where neural connections are reduced thereby making those that are used much stronger. It is thought that pruning causes the brain to function more efficiently, allowing for mastery of more complex skills (Kolb & Whishaw, 2011). The experience will shape which of these connections are maintained and which of these are lost. Ultimately, about 40 percent of these connections will be lost (Webb, Monk, and Nelson, 2001). Blooming occurs during the first few years of life, and pruning continues through childhood and into adolescence in various areas of the brain.
a coating of fatty tissues around the axon of the neuron (Carlson, 2014). Myelin helps insulate the nerve cell and speed the rate of transmission of impulses from one cell to another. This enhances the building of neural pathways and improves coordination and control of movement and thought processes. The development of myelin continues into adolescence but is most dramatic during the first several years of life.
the thin outer covering of the brain involved in voluntary activity and thinking. The cortex is divided into two hemispheres, and each hemisphere is divided into four lobes, each separated by folds known as fissures. If we look at the cortex starting at the front of the brain and moving over the top (see Figure 3.3), we see first the frontal lobe (behind the forehead), which is responsible primarily for thinking, planning, memory, and judgment. Following the frontal lobe is the parietal lobe, which extends from the middle to the back of the skull and which is responsible primarily for processing information about touch. Next is the occipital lobe, at the very back of the skull, which processes visual information. Finally, in front of the occipital lobe, between the ears, is the temporal lobe, which is responsible for hearing and language (Jarrett, 2015).
Although the brain grows rapidly during infancy, specific brain regions do not mature at the same rate. Primary motor areas develop earlier than primary sensory areas, and the prefrontal cortex, that is located behind the forehead, is the least developed (Giedd, 2015). As the prefrontal cortex matures, the child is increasingly able to regulate or control emotions, to plan activities, strategize, and have better judgment. This is not fully accomplished in infancy and toddlerhood but continues throughout childhood, adolescence, and adulthood.
Lateralization is the process in which different functions become localized primarily on one side of the brain. For example, in most adults the left hemisphere is more active than the right during language production, while the reverse pattern is observed during tasks involving visuospatial abilities (Springer & Deutsch, 1993). This process develops over time, however, structural asymmetries between the hemispheres have been reported even in fetuses (Chi, Dooling, & Gilles, 1997; Kasprian et al., 2011) and infants (Dubois et al., 2009).
Lastly, neuroplasticity refers to the brain’s ability to change, both physically and chemically, to enhance its adaptability to environmental change and compensate for an injury. The control of some specific bodily functions, such as movement, vision, and hearing, is performed in specified areas of the cortex, and if these areas are damaged, the individual will likely lose the ability to perform the corresponding function. The brain’s neurons have a remarkable capacity to reorganize and extend themselves to carry out these particular functions in response to the needs of the organism, and to repair any damage. As a result, the brain constantly creates new neural communication routes and rewires existing ones. Both environmental experiences, such as stimulation and events within a person’s body, such as hormones and genes, affect the brain’s plasticity. So too does age. Adult brains demonstrate neuroplasticity, but they are influenced less extensively than those of infants (Kolb & Fantie, 1989; Kolb & Whishaw, 2011).
Infant Sleep
Sudden Unexpected Infant Deaths (SUID): Each year in the United States, there are about 3,500 Sudden Unexpected Infant Deaths (SUID). These deaths occur among infants less than one-year-old and have no immediately obvious cause (CDC, 2019). The three commonly reported types of SUID are:
• Sudden Infant Death Syndrome (SIDS): SIDS is identified when the death of a healthy infant occurs suddenly and unexpectedly, and medical and forensic investigation findings (including an autopsy) are inconclusive. SIDS is the leading cause of death in Figure 3.4 75 infants 1 to 12 months old, and approximately 1,400 infants died of SIDS in 2017 (CDC, 2019). Because SIDS is diagnosed when no other cause of death can be determined, possible causes of SIDS are regularly researched. One leading hypothesis suggests that infants who die from SIDS have abnormalities in the area of the brainstem responsible for regulating breathing (Weekes-Shackelford & Shackelford, 2005).
• Unknown Cause: The sudden death of an infant less than one year of age that cannot be explained because a thorough investigation was not conducted, and the cause of death could not be determined. In 2017, 1300 infants died from unknown causes (CDC, 2019).
• Accidental Suffocation and Strangulation in Bed: Reasons for accidental suffocation include: Suffocation by soft bedding, another person rolling on top of or against the infant while sleeping, an infant being wedged between two objects such as a mattress and wall, and strangulation such as when an infant’s head and neck become caught between crib railings. In 2017, 900 infants died from accidental suffocation and strangulation.
From Reflexes to Voluntary Movements
Table 3.1 Some Common Infant Reflexes
Motor Development
from the floor and placing them in containers. By 9 months, an infant can also watch a moving object, reach for it as it approaches, and grab it.
Sensory Capacities
Vision: The womb is a dark environment void of visual stimulation. Consequently, vision is one of the most poorly developed senses at birth, and time is needed to build those neural pathways between the eyes and the brain (American Optometric Association [AOA], 2019). Newborns typically cannot see further than 8 to 10 inches away from their faces (AOA, 2019). An 8-week old’s vision is 20/300. This means an object 20 feet away from an infant has the same clarity as an object 300 feet away from an adult with normal vision. By 3-months visual acuity has sharpened to 20/200, which would allow them the see the letter E at the top of a standard eye chart (Hamer, 2016). As a result, the world looks blurry to young infants (Johnson & deHaan, 2015).
• One-month-olds have difficulty disengaging their attention and can spend several minutes fixedly gazing at a stimulus (Johnson & deHaan, 2015).
• Aslin (1981) found that when tracking an object visually, the eye movements of newborns and one-month olds are not smooth but saccadic, that is step-like jerky movements. Aslin also found their eye movements lag behind the object’s motion. This means young infants do not anticipate the trajectory of the object. By two months of age, their eye movements are becoming smoother, but they still lag behind the motion of the object and will not achieve this until about three to four months of age (Johnson & deHaan, 2015).
• Newborns also orient more to the visual field toward the side of the head, than to the visual field on either side of the nose (Lewis, Maurer, & Milewski, 1979). By two to three months, stimuli in both fields are now equally attended to (Johnson & deHaan, 2015).
Hearing: The infant’s sense of hearing is very keen at birth, and the ability to hear is evidenced as soon as the seventh month of prenatal development. Newborns prefer their mother’s voices over another female when speaking the same material (DeCasper & Fifer, 1980). Additionally, they will register in utero specific information heard from their mother’s voice.
were 7 months pregnant. The fetuses had been exposed to the stories an average of 67 times or 1.5 hours. When the experimental infants were tested, the target stories (previously heard) were more reinforcing than the novel story as measured by their rate of sucking. However, for control infants, the target stories were not more reinforcing than the novel story indicating that the experimental infants had heard them before.
the sounds that are not in the language around them diminishes rapidly (Cheour-Luhtanen, et al., 1995).
Touch and Pain: Immediately after birth, a newborn is sensitive to touch and temperature, and is also highly sensitive to pain, responding with crying and cardiovascular responses (Balaban & Reisenauer, 2013). Newborns who are circumcised, which is the surgical removal of the foreskin of the penis, without anesthesia experience pain as demonstrated by increased blood pressure, increased heart rate, decreased oxygen in the blood, and a surge of stress hormones (United States National Library of Medicine, 2016). Research has demonstrated that infants who were circumcised without anesthesia experienced more pain and fear during routine childhood vaccines. Fortunately, today many local pain killers are currently used during circumcision.
Taste and Smell: Studies of taste and smell demonstrate that babies respond with different facial expressions, suggesting that certain preferences are innate. Newborns can distinguish between sour, bitter, sweet, and salty flavors and show a preference for sweet flavors. Newborns also prefer the smell of their mothers. An infant only 6 days old is significantly more likely to turn toward its own mother’s breast pad than to the breast pad of another baby’s mother (Porter, Makin, Davis, & Christensen, 1992), and within hours of birth an infant also shows a preference for the face of its own mother (Bushnell, 2001; Bushnell, Sai, & Mullin, 1989).
Intermodality: Infants seem to be born with the ability to perceive the world in an intermodal way; that is, through stimulation from more than one sensory modality. For example, infants who sucked on a pacifier with either a smooth or textured surface preferred to look at a corresponding (smooth or textured) visual model of the pacifier. By 4 months, infants can match lip movements with speech sounds and can match other audiovisual events. Sensory processes are certainly affected by the infant’s developing motor abilities (Hyvärinen, Walthes, Jacob, Nottingham Chapin, & Leonhardt, 2014). Reaching, crawling, and other actions allow the infant to see, touch, and organize his or her experiences in new ways.
How are Infants Tested: Habituation procedures, that is measuring decreased responsiveness to a stimulus after repeated presentations, have increasingly been used to evaluate infants to study the development of perceptual and memory skills. Phelps (2005) describes a habituation procedure used when measuring the rate of the sucking reflex.
Nutrition
rates of childhood leukemia, asthma, obesity, type 1 and 2 diabetes, and a lower risk of SIDS. The USDHHS recommends that mothers breastfeed their infants until at least 6 months of age and that breast milk be used in the diet throughout the first year or two.
HIV are routinely discouraged from breastfeeding as the infection may pass to the infant. Similarly, women who are taking certain medications or undergoing radiation treatment may be told not to breastfeed (USDHHS, 2011).
breastfeeding. Prices for a year’s worth of formula and feeding supplies can cost between \$1,500 and \$3000 per year (Los Angles County Department of Public Health, 2019). In addition to the formula, costs include bottles, nipples, sterilizers, and other supplies.
• can sit up without needing support
• can hold its head up without wobbling
• shows interest in foods others are eating
• is still hungry after being breastfed or formula-fed
• is able to move foods from the front to the back of the mouth
• is able to turn away when they have had enough
For many infants who are 4 to 6 months of age, breast milk or formula can be supplemented with more solid foods. The first semi-solid foods that are introduced are iron-fortified infant cereals mixed with breast milk or formula. Typically rice, oatmeal, and barley cereals are offered as a number of infants are sensitive to more wheat-based cereals. Finger foods such as toast squares, cooked vegetable strips, or peeled soft fruit can be introduced by 10-12 months. New foods should be introduced one at a time, and the new food should be fed for a few days in a row to allow the baby time to adjust to the new food. This also allows parents time to assess if the child has a food allergy. Foods that have multiple ingredients should be avoided until parents have assessed how the child responds to each ingredient separately. Foods that are sticky (such as peanut butter or taffy), cut into large chunks (such as cheese and harder meats), and firm and round (such as hard candies, grapes, or cherry tomatoes) should be avoided as they are a choking hazard. Honey and corn syrup should be avoided as these often contain botulism spores. In children under 12 months, this can lead to death (Clemson University Cooperative Extension, 2014).
Figure 3.12
Global Considerations and Malnutrition
in every 13 children in the world suffers from some form of wasting, and the majority of these children live in Asia (34.3 million) and Africa (13.9 million). Wasting can occur as a result of severe food shortages, regional diets that lack certain proteins and vitamins, or infectious diseases that inhibit appetite (Latham, 1997).
Ainsworth, M. (1979). Infant-mother attachment. American Psychologist, 34(10), 932-937.
Akimoto, S. A., & Sanbinmatsu, D. M. (1999). Differences in self-effacing behavior between European and Japanese Americans: Effect on competence evaluations. Journal of Cross-Cultural Psychology, 30, 159-177.
American Optometric Association. (2019). Infant vision: Birth to 24 months of age. Retrieved from https://www.aoa.org/patients-and-public/good-vision-throughout-life/childrens-vision/infant-vision-birth-to-24- months-of-age
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders, 5th edition (DSM-5).
Washington, DC: Author.
Anglin, J. M. (1993). Vocabulary development: A morphological analysis. Monographs of the Society for Research in Child Development, 58 10), v–165.
Aslin, R. N. (1981). Development of smooth pursuit in human infants. In D. F. Fisher, R. A. Monty, & J. W. Senders (Eds.), Eye movements: Cognition and visual perception (pp. 31– 51). Hillsdale, NJ: Erlbaum.
Atkinson, J., & Braddick, O. (2003). Neurobiological models of normal and abnormal visual development. In M. de Haan & M. H. Johnson (Eds.), The cognitive neuroscience of development (pp. 43– 71). Hove: Psychology Press.
Baillargeon, R. (1987. Object permanence in 3 ½ and 4 ½ year-old infants. Developmental Psychology, 22, 655-664. Baillargeon, R., Li, J., Gertner, Y, & Wu, D. (2011). How do infants reason about physical events? In U. Goswami (Ed.), The Wiley-Blackwell handbook of childhood cognitive development. MA: John Wiley.
Balaban, M. T. & Reisenauer, C. D. (2013). Sensory development. In N. J. Salkind (Ed.), Encyclopedia of human development (pp. 1144-1147). New, York: Sage Publications.
Baldwin, D. A. (1993). Early referential understanding: Infants’ ability to recognize referential acts for what they are. Developmental Psychology, 29(5), 832–843.
Bartrip J, Morton J, & De Schonen S. (2001). Responses to mother’s face in 3-week to 5-month-old infants. British Journal of Developmental Psychology, 19, 219–232
Berk, L. E. (2007). Development through the life span (4th ed.). Boston: Allyn and Bacon.
Berne, S. A. (2006). The primitive reflexes: Considerations in the infant. Optometry & Vision Development, 37(3), 139-145. Bloem, M. (2007). The 2006 WHO child growth standards. BMJ : British Medical Journal, 334(7596), 705–706. doi.org/10.1136/bmj.39155.658843.BE
Blossom, M., & Morgan, J. L. (2006). Does the face say what the mouth says? A study of infants’ sensitivity to visual prosody. In the 30th annual Boston University conference on language development, Somerville, MA.
Bogartz, R. S., Shinskey, J. L., & Schilling, T. (2000). Object permanence in five-and-a-half month old infants. Infancy, 1(4), 403-428.
Bowlby, J. (1969). Attachment and loss. London: Hogarth Press. Bowlby, J. (1982). Attachment (2nd ed.). New York: Basic Books.
Bradshaw, D. (1986). Immediate and prolonged effectiveness of negative emotion expressions in inhibiting infants’ actions (Unpublished doctoral dissertation). Berkeley, CA: University of California, Berkeley.
Braungart-Rieker, J. M., Hill-Soderlund, A. L., &Karrass, J. (2010). Fear, anger reactivity trajectories from 4 to 16 months: The roles of temperament, regulation, and maternal sensitivity. Developmental Psychology, 46, 791-804.
Bushnell, I. W. R. (2001) Mother’s face recognition in newborn infants: Learning and memory. Infant Child Development, 10, 67-94.
Bushnell, I. W. R., Sai, F., Mullin, J. T. (1989). Neonatal recognition of mother’s face. British Journal of Developmental Psychology, 7, 3-15.
Bruer, J. T. (1999). The myth of the first three years: A new understanding of early brain development and lifelong learning. New York: Simon and Schuster.
Campanella, J., & Rovee-Collier, C. (2005). Latent learning and deferred imitation at 3 months. Infancy, 7(3), 243-262. Carlson, N. (2014). Foundations of behavioral neuroscience (9th ed.). Boston, MA: Pearson.
Carpenter, R., McGarvey, C., Mitchell, E. A., Tappin, D. M., Vennemann, M. M., Smuk, M., & Carpenter, J. R. (2013). Bed sharing when parents do not smoke: Is there a risk of SIDS? An individual level analysis of five major case–control studies. BMJ Open, 3:e002299. doi:10.1136/bmjopen-2012-002299
Centers for Disease Control and Prevention. (2018). Breastfeeding facts. Retrieved from https://www.cdc.gov/breastfeeding/data/facts.html
Centers for Disease Control and Prevention. (2019). Sudden unexpected infant death and sudden infant death syndrome. Retrieved from http://www.cdc.gov/sids/data.htm
Cheour-Luhtanen, M., Alho. K., Kujala, T., Reinikainen, K., Renlund, M., Aaltonen, O., … & Näätänen R. (1995). Mismatch negativity indicates vowel discrimination in newborns. Hearing Research, 82, 53–58.
Chess, S., & Thomas, A. (1996). Temperament: Theory and practice. New York: Brunner/Mazel.
Chi, J. G., Dooling, E. C., & Gilles, F. H. (1977). Left-right asymmetries of the temporal speech areas of the human fetus. Archives of Neurology, 34, 346–8.
Chien S. (2011). No more top-heavy bias: Infants and adults prefer upright faces but not top-heavy geometric or face-like patterns. Journal of Vision, 11(6):1–14.
Chomsky, N. (1965). Aspects of the theory of syntax. Cambridge, MA: MIT Press. Chomsky, N. (1972). Language and mind. NY: Harcourt Brace.
Clark, E. V. (2009). What shapes children’s language? Child-directed speech and the process of acquisition. In V. C. M. Gathercole (Ed.), Routes to language: Essays in honor of Melissa Bowerman. NY: Psychology Press.
Clark, L. A., Kochanska, G., & Ready, R. (2000). Mothers’ personality and its interaction with child temperament as predictors of parenting behavior. Journal of Personality and Social Psychology, 79, 274–285.
Clemson University Cooperative Extension. (2014). Introducing solid foods to infants. Retrieved from http://www.clemson.edu/extension/hgic/food/nutrition/nutrition/life_stages/hgic4102.html
Cole, P. M., Armstrong, L. M., & Pemberton, C. K. (2010). The role of language in the development of emotional regulation. In S. D. Calkins & M. A. Bell (Eds.). Child development at intersection of emotion and cognition (pp. 59-77). Washington D.C.: American Psychological Association.
Colvin, J.D., Collie-Akers, V., Schunn, C., & Moon, R.Y. (2014). Sleep environment risks for younger and older infants. Pediatrics Online. Retrieved from pediatrics.aappublications.org/content/pediatrics/early/2014/07/09/peds. 2014-0401.full.pdf
de Boysson-Bardies, B., Sagart, L., & Durand, C. (1984). Discernible differences in the babbling of infants according to target language. Journal of Child Language, 11(1), 1–15.
DeCasper, A. J., & Fifer, W. P. (1980). Of human bonding: Newborns prefer their mother’s voices. Science, 208, 1174-1176. DeCasper, A. J., & Spence, M. J. (1986). Prenatal maternal speech influences newborns’ perception of speech sounds. Infant Behavior and Development, 9, 133-150.
Diamond, A. (1985). Development of the ability to use recall to guide actions, as indicated by infants’ performance on AB. Child Development, 56, 868-883.
Dobrich, W., & Scarborough, H. S. (1992). Phonological characteristics of words young children try to say. Journal of Child Language, 19(3), 597–616.
Dubois, J., Hertz-Pannier, L., Cachia, A., Mangin, J. F., Le Bihan, D., & Dehaene-Lambertz, G. (2009). Structural asymmetries in the infant language and sensori-motor networks. Cerebral Cortex, 19, 414–423.
Eisenberg, A., Murkoff, H. E., & Hathaway, S. E. (1989). What to expect the first year. New York: Workman Publishing.
Eisenberg, N., Fabes, R. A., Shepard, S. A., Guthrie, I.K., Murphy, B.C., & Reiser, M. (1999). Parental reactions to children’s negative emotions: Longitudinal relations to quality of children’s social functioning. Child Development, 70, 513-534.
Eisenberg, N., Hofer, C., Spinrad, T., Gershoff, E., Valiente, C., Losoya, S. L., Zhou, Q., Cumberland, A., Liew, J., Reiser, M., & Maxon, E. (2008). Understanding parent-adolescent conflict discussions: Concurrent and across-time prediction from youths’ dispositions and parenting. Monographs of the Society for Research in Child Development, 73, (Serial No. 290, No. 2), 1-160.
El-Dib, M., Massaro, A. N., Glass, P., & Aly, H. (2012). Neurobehavioral assessment as a predictor of neurodevelopmental outcome in preterm infants. Journal of Perinatology, 32, 299-303.
Eliot, L. (1999). What’s going on in there? New York: Bantam. Erikson, E. (1982). The life cycle completed. NY: Norton & Company.
Evans, N., & Levinson, S. C. (2009). The myth of language universals: Language diversity and its importance for cognitive science. Behavioral and Brain Sciences, 32(5), 429–448.
Farroni, T., Johnson, M.H. Menon, E., Zulian, L. Faraguna, D., Csibra, G. (2005). Newborns’ preference for face-relevant stimuli: Effects of contrast polarity. Proceedings of the National Academy of Sciences of the United States of America, 102(47), 17245-17250.
Fergusson, D. M., & Woodward, L. J. (1999). Breastfeeding and later psychosocial adjustment. Paediatric and Perinatal Epidemiology, 13, 144-157.
Fitzpatrick, E.M., Crawford, L., Ni, A., & Durieux-Smith, A. (2011). A descriptive analysis of language and speech skills in 4-to- 5-yr-old children with hearing loss. Ear and Hearing, 32(2), 605-616.
Freud, S. (1938). An outline of psychoanalysis. London: Hogarth.
Galler J. R., & Ramsey F. (1989). A follow-up study of the influence of early malnutrition on development: Behavior at home and at school. American Academy of Child and Adolescence Psychiatry, 28 (2), 254-61.
Galler, J. R., Ramsey, F. C., Morely, D. S., Archer, E., & Salt, P. (1990). The long-term effects of early kwashiorkor compared with marasmus. IV. Performance on the national high school entrance examination. Pediatric Research, 28(3), 235- 239.
Galler, J. R., Ramsey, F. C., Salt, P. & Archer, E. (1987). The long-term effect of early kwashiorkor compared with marasmus. III. Fine motor skills. Journal of Pediatric Gastroenterology Nutrition, 6, 855-859.
Giedd, J. N. (2015). The amazing teen brain. Scientific American, 312(6), 32-37.
Giles, A., & Rovee-Collier, C. (2011). Infant long-term memory for associations formed during mere exposure. Infant Behavior and Development, 34 (2), 327-338.
Gillath, O., Shaver, P. R., Baek, J. M., & Chun, D. S. (2008). Genetic correlates of adult attachment style. Personality & Social Psychology Bulletin, 34, 1396–1405.
Gleitman, L. R., & Newport, E. L. (1995). The invention of language by children: Environmental and biological influences on the acquisition of language. An Invitation to Cognitive Science, 1, 1-24.
Goldin-Meadow, S., & Mylander, C. (1998). Spontaneous sign systems created by deaf children in two cultures. Nature, 391(6664), 279–281.
Grosse, G., Behne, T., Carpenter, M., & Tomasello, M. (2010). Infants communicate in order to be understood. Developmental Psychology, 46(6), 1710-1722.
Gunderson, E. P., Hurston, S. R., Ning, X., Lo, J. C., Crites, Y., Walton, D…. & Quesenberry, C. P. Jr. (2015). Lactation and progression to type 2 diabetes mellitus after gestational diabetes mellitus: A prospective cohort study. American Journal of Medicine, 163, 889-898. Doi: 10.7326/m 15-0807.
Hainline L. (1978). Developmental changes in visual scanning of face and nonface patterns by infants. Journal of Experimental Child Psychology, 25, 90–115.
Hamer, R. (2016). The visual world of infants. Scientific American, 104, 98-101. Harlow, H. F. (1958). The nature of love. American Psychologist, 13, 673-685.
Harris, Y. R. (2005). Cognitive development. In N. J. Salkind (Ed.), Encyclopedia of human development (pp. 276-281). New, York: Sage Publications.
Hart, S., & Carrington, H. (2002). Jealousy in 6-month-old infants. Infancy, 3(3), 395-402.
Hatch, E. M. (1983). Psycholinguistics: A second language perspective. Rowley, MA: Newbury House Publishers. Hertenstein, M. J., & Campos, J. J. (2004). The retention effects of an adult’s emotional displays on infant behavior. Child Development, 75(2), 595–613.
Holland, D., Chang, L., Ernst, T., Curan, M Dale, A. (2014). Structural growth trajectories and rates of change in the first 3 months of infant brain development. JAMA Neurology, 71(10), 1266-1274.
Huttenlocher, P. R., & Dabholkar, A. S. (1997). Regional differences in synaptogenesis in human cerebral cortex. The Journal of Comparative Neurology, 387(2), 167-178.
Hyde, J. S., Else-Quest, N. M., & Goldsmith, H. H. (2004). Children’s temperament and behavior problems predict their employed mothers’ work functioning. Child Development, 75, 580–594.
Hyvärinen, L., Walthes, R., Jacob, N., Nottingham Chaplin, K., & Leonhardt, M. (2014). Current understanding of what infants see. Current Opthalmological Report, 2, 142-149. doi:10.1007/s40135-014-0056-2
Imai, M., Li, L., Haryu, E., Hirsh-Pasek, K., Golinkoff, R. M., & Shigematsu, J. (2008). Novel noun and verb learning in Chinese, English, and Japanese children: Universality and language-specificity in novel noun and verb learning. Child Development, 79, 979-1000.
Islami, F., Liu, Y., Jemal, A., Zhou, J., Weiderpass, E., Colditz, G…Weiss, M. (2015). Breastfeeding and breast cancer risk by receptor status – a systematic review and meta-analysis. Annals of Oncology, 26, 2398-2407.
Iverson, J. M., & Goldin-Meadow, S. (2005). Gesture paves the way for language development. Psychological science, 16(5), 367-371.
Jarrett, C. (2015). Great myths of the brain. West Sussex, UK: Wiley.
Johnson, M. H., & deHaan, M. (2015). Developmental cognitive neuroscience: An introduction. Chichester, West Sussex: UK, Wiley & Sons
Jusczyk, P.W., Cutler, A., & Redanz, N.J. (1993). Infants’ preference for the predominant stress patterns of English words. Child Development, 64, 675–687.
Karlson, E.W., Mandl, L.A., Hankison, S. E., & Grodstein, F. (2004). Do breast-feeding and other reproductive factors influence future risk of rheumatoid arthritis? Arthritis & Rheumatism, 50 (11), 3458-3467.
Kasprian, G., Langs, G., Brugger, P. C., Bittner, M., Weber, M., Arantes, M., & Prayer, D. (2011). The prenatal origin of hemispheric asymmetry: an in utero neuroimaging study. Cerebral Cortex, 21, 1076–1083.
Kiff, C. J., Lengua, L. J., & Zalewski, M. (2011). Nature and nurturing: Parenting in the context of child temperament. Clinical Child and Family Psychology Review, 14, 251–301. doi: 10.1007/s10567-011-0093-4
Klein, P. J., & Meltzoff, A. N. (1999). Long-term memory, forgetting, and deferred imitation in 12-month-old infants. Developmental Science, 2(1), 102-113.
Klinnert, M. D., Campos, J. J., & Sorce, J. F. (1983). Emotions as behavior regulators: Social referencing in infancy. In R. Plutchik & H. Kellerman (Eds.), Emotion: Theory, research, and experience (pp. 57–86). New York, NY: Academic Press.
Kolb, B., & Fantie, B. (1989). Development of the child’s brain and behavior. In C. R. Reynolds & E. Fletcher-Janzen (Eds.),
Handbook of clinical child neuropsychology (pp. 17–39). New York, NY: Plenum Press.
Kolb, B. & Whishaw, I. Q. (2011). An introduction to brain and behavior (3rd ed.). New York: Worth Publishers.
Kopp, C. B. (2011). Development in the early years: Socialization, motor development, and consciousness. Annual Review of Psychology, 62, 165-187.
Latham, M. C. (1997). Human nutrition in the developing world. Rome, IT: Food and Agriculture Organization of the United Nations.
Lavelli, M., & Fogel, A. (2005). Developmental changes in the relationships between infant attention and emotion during early face-to-face communications: The 2 month transition. Developmental Psychology, 41, 265-280.
Lenneberg, E. (1967). Biological foundations of language. New York, NY: John Wiley & Sons.
LeVine, R. A., Dixon, S., LeVine, S., Richman, A., Leiderman, P. H., Keefer, C. H., & Brazelton, T. B. (1994). Child care and culture: Lessons from Africa. New York: Cambridge University Press.
Lewis, M., & Brooks, J. (1978). Self-knowledge and emotional development. In M. Lewis & L. A. Rosenblum (Eds.), Genesis of behavior (Vol. 1, pp. 205-226). New York: Plenum Press.
Lewis, T. L., Maurer, D., & Milewski, A. (1979). The development of nasal detection in young infants. Investigative Ophthalmology and Visual Science Supplement, 19, 271.
Li, Y., & Ding, Y. (2017). Human visual development. In Y. Liu., & W. Chen (Eds.), Pediatric lens diseases (pp. 11-20). Singapore: Springer.
Los Angles County Department of Public Health. (2019). Breastfeeding vs. formula feeding. Retrieved from publichealth.lacounty.gov/LAmoms/lessons/Breastfeeding/6_BreastfeedingvsFormulaFeeding.pdf
Main, M., & Solomon, J. (1990). Procedures for identifying infants as disorganized/disoriented during the Ainsworth Strange Situation. In M. T. Greenberg, D. Cicchetti, & E. M. Cummings (Eds.), Attachment inthe Preschool Years (pp.121– 160).Chicago,IL: UniversityofChicagoPress.
Mandel, D. R., Jusczyk, P. W., & Pisoni, D. B. (1995). Infants’ recognition of the sound patterns of their own names. Psychological Science, 6(5), 314–317.
Mayberry, R. I., Lock, E., & Kazmi, H. (2002). Development: Linguistic ability and early language exposure. Nature, 417(6884), 38.
Moeller, M.P., & Tomblin, J.B. (2015). An introduction to the outcomes of children with hearing loss study. Ear and Hearing, 36 Suppl (0-1), 4S-13S
Morelli, G., Rogoff, B., Oppenheim, D., & Goldsmith, D. (1992). Cultural variations in infants’ sleeping arrangements: Questions of independence. Developmental Psychology, 28, 604-613.
Nelson, E. A., Schiefenhoevel, W., & Haimerl, F. (2000). Child care practices in nonindustrialized societies. Pediatrics, 105, e75.
O’Connor, T. G., Marvin, R. S., Rotter, M., Olrich, J. T., Britner, P. A., & The English and Romanian Adoptees Study Team. (2003). Child-parent attachment following early institutional deprivation. Development and Psychopathology, 15, 19- 38.
Papousek, M. (2007). Communication in early infancy: An arena of intersubjective learning. Infant Behavior and Development, 30, 258-266.
Pearson Education. (2016). Bayley Scales of Infant Development, Third Edition. New York: Pearson. Retrieved from http://www.pearsonclinical.com/childhood/products/100000123/bayley-scales-of-infant-and-toddler-development- third-edition-bayley-iii.html#tab-details
Penfield, W., & Roberts, L. (1959). Speech and brain mechanisms. Princeton, NJ: Princeton University Press.
Petitto, L. A., & Marentette, P. F. (1991). Babbling in the manual mode: Evidence for the ontogeny of language. Science, 251(5000), 1493–1496.
Phelps, B. J. (2005). Habituation. In N. J. Salkind (Ed.), Encyclopedia of human development (pp. 597-600). New York: Sage Publications.
Piaget, J. (1954). The construction of reality in the child. New York: Basic Books.
Pickens, J., Field, T., Nawrocki, T., Martinez, A., Soutullo, D., & Gonzalez, J. (1994). Full-term and preterm infants’ perception of face-voice synchrony. Infant Behavior and Development, 17(4), 447-455.
Porter, R. H., Makin, J. W., Davis, L. M., Christensen, K. (1992). Responsiveness of infants to olfactory cues from lactating females. Infant Behavior and Development, 15, 85-93.
Redondo, C. M., Gago-Dominguez, M., Ponte, S. M., Castelo, M. E., Jiang, X., Garcia, A.A… Castelao, J. E. (2012). Breast feeding, parity and breast cancer subtypes in a Spanish cohort. PLoS One, 7(7): e40543 doi: 10.1371/journal.pone.00040543
Richardson, B. D. (1980). Malnutrition and nutritional anthropometry. Journal of Tropical Pediatrics, 26(3), 80-84. Rothbart, M. K., & Bates, J. E. (2006). Temperament. In N. Eisenberg (Ed.). Handbook of child psychology: Vol. 3: Social, emotional, and personality development (6th ed., pp. 99-116). Hoboken, NJ: Wiley.
Rothbart, M. K., Posner, M. I. & Kieras, J. (2006). Temperament, attention, and the development of self-regulation. In M. McCartney & D. Phillips (Eds.) Blackwell handbook of early childhood development (pp. 3338-357). Malden, MA: Blackwell.
Rothbaum, F., Weisz, J., Pott, M., Miyake, K., & Morelli, G. (2010). Attachment and culture: Security in the United States and Japan. American Psychologist, 55, 1093-1104.
Rovee-Collier, C. (1987). Learning and memory in infancy. In J. D. Osofsky (Ed.), Handbook of infant development, (2nd, ed., pp. 98-148). New York: Wiley.
Rovee-Collier, C. (1990). The “memory system” of prelinguistic infants. Annuals of the New York Academy of Sciences, 608, 517-542. doi: 10.1111/j.1749-66231990.tb48908.
Rovee-Collier, C., & Hayne, H. (1987). Reactivation of infant memory: Implications for cognitive development. In H. W. Reese (Ed.), Advances in child development and behavior. (Vol. 20, pp. 185-238). London, UK: Academic Press.
Rymer, R. (1993). Genie: A scientific tragedy. Harmondsworth: Penguin.
Salkind, N. J. (2005). Encyclopedia of human development. New York: Sage Publications.
Schwarz, E. B., Brown, J. S., Creasman, J. M. Stuebe, A., McClure, C. K., Van Den Eeden, S. K., & Thom, D. (2010). Lactation and maternal risk of type-2 diabetes: A population-based study. American Journal of Medicine, 123, 863.e1-863.e6. doi: 10.1016/j.amjmed.2010.03.016.
Seifer, R., Schiller, M., Sameroff, A., Resnick, S., & Riordan, K. (1996). Attachment, maternal sensitivity, and infant temperament during the first year of life. Developmental Psychology, 32, 12-25.
Sen, M. G., Yonas, A., & Knill, D. C. (2001). Development of infants’ sensitivity to surface contour information for spatial layout. Perception, 30, 167-176.
Senghas, R. J., Senghas, A., & Pyers, J. E. (2005). The emergence of Nicaraguan Sign Language: Questions of development, acquisition, and evolution. In S. T. Parker, J. Langer, & C. Milbrath (Eds.), Biology and knowledge revisited: From neurogenesis to psychogenesis (pp. 287–306). Mahwah, NJ: Lawrence Erlbaum Associates.
Shaffer, D. R. (1985). Developmental psychology: Theory, research, and applications. Belmont, CA: Wadsworth, Inc. Skinner, B. F. (1953). Science and human behavior. NY: Free Press.
Sorce, J. F., Emde, J. J., Campos, J. J., & Klinnert, M. D. (1985). Maternal emotional signaling: Its effect on the visual cliff behavior of 1-year-olds. Developmental Psychology, 21, 195–200.
Spelke, E. S., & Cortelyou, A. (1981). Perceptual aspects of social knowing: Looking and listening in infancy. Infant social cognition, 61-84.
Springer, S. P. & Deutsch, G. (1993). Left brain, right brain (4th ed.). New York: W. H. Freeman.
Stika, C.J., Eisenberg, L.S., Johnson, K.C. Henning, S.C., Colson, B.G., Ganguly, D.H., & DesJardin, J.L. (2015). Developmental outcomes of early-identified children who are hard of hearing at 12 to 18 months of age. Early Human Development, 9(1), 47-55.
Stork, F. & Widdowson, J. (1974). Learning about Linguistics. London: Hutchinson.
Thomas, R. M. (1979). Comparing theories of child development. Santa Barbara, CA: Wadsworth.
Thompson, R. A. (2006). The development of the person. In W. Damon & R. Lerner (Eds.), Handbook of child psychology (6th Ed.). New York: Wiley.
Thompson, R. A., & Goodvin, R. (2007). Taming the tempest in the teapot. In C. A. Brownell & C. B. Kopp (Eds.). Socioemotional development in the toddler years: Transitions and transformations (pp. 320-342). New York: Guilford.
Thompson, R. A., Winer, A. C., & Goodvin, R. (2010). The individual child: Temperament, emotion, self, and personality. In M. Bornstein & M. E. Lamb (Eds.), Developmental science: An advanced textbook (6th ed., pp. 423–464). New York, NY: Psychology Press/Taylor & Francis.
Titus-Ernstoff, L., Rees, J. R., Terry, K. L., & Cramer, D. W. (2010). Breast-feeding the last-born child and risk of ovarian cancer. Cancer Causes Control, 21(2), 201-207. doi: 10.1007/s10552-009-9450-8
Tomblin, J. B., Harrison, M., Ambrose, S. E., Walker, E. A., Oleson, J. J., & Moeller, M. P. (2015). Language outcomes in young children with mild to severe hearing loss. Ear and hearing, 36 Suppl 1(0 1), 76S–91S.
United Nations Children’s Fund. (2015). Levels and trends in child mortality: Report 2015. United Nations Children’s Fund. New York: NY.
United States Department of Health and Human Services, Office of Women’s Health. (2011). Your guide to breast feeding. Washington D.C.
United States National Library of Medicine. (2016). Circumcision. Retrieved from https://medlineplus.gov/circumcision.html
Van den Boom, D. C. (1994). The influence of temperament and mothering on attachment and exploration: An experimental manipulation of sensitive responsiveness among lower-class mothers with irritable infants. Child Development, 65, 1457–1477.
Van Ijzendoorn, M. H., & Sagi, A. (1999). Cross-cultural patterns of attachment. In J. Cassidy & P. R. Shaver (Eds.), Handbook of attachment: Theory, research, and clinical applications (pp. 713-734). New York: Guilford.
Webb, S. J., Monk, C. S., & Nelson, C. A. (2001). Mechanisms of postnatal neurobiological development: Implications for human development. Developmental Neuropsychology, 19, 147-171.
Weekes-Shackelford, V. A. & Shackelford, T. K. (2005). Sudden Infant Death Syndrome (SIDS). In N. J. Salkind (Ed.), Encyclopedia of human development (pp. 1238-1239). New York: Sage Publications.
Werker, J. F., Pegg, J. E., & McLeod, P. J. (1994). A cross-language investigation of infant preference for infant-directed communication. Infant Behavior and Development, 17, 323-333.
Werker, J. F., & Tees, R. C. (2002). Cross-language speech perception: Evidence for perceptual reorganization during the first year of life. Infant Behavior and Development, 25, 121-133.
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/06%3A_Development_in_Infancy_and_Toddlerhood/6.01%3A_Chapter_10-_Physical_Development_in_Infancy_and_Toddlerhood.txt |
Chapter 11 Learning Objectives
• Compare the Piagetian concepts of schema, assimilation, and accommodation
• List and describe the six substages of sensorimotor intelligence
• Describe the characteristics of infant memory
• Describe components and developmental progression of language
• Identify and compare the theories of language
Figure 3.14
Table 3.2
Figure 3.17
Components of Language
Phoneme: A phoneme is the smallest unit of sound that makes a meaningful difference in a language. The word “bit” has three phonemes. In spoken languages, phonemes are produced by the positions and movements of the vocal tract, including our lips, teeth, tongue, vocal cords, and throat, whereas in sign language phonemes are defined by the shapes and movement of the hands.
Morpheme: Whereas phonemes are the smallest units of sound in language, a morpheme is a string of one or more phonemes that makes up the smallest units of meaning in a language. Some morphemes are prefixes and suffixes used to modify other words. For example, the syllable “re-” as in “rewrite” or “repay” means “to do again,” and the suffix “-est” as in “happiest” or “coolest” means “to the maximum.”
Semantics: Semantics refers to the set of rules we use to obtain meaning from morphemes. For example, adding “ed” to the end of a verb makes it past tense.
Syntax: Syntax is the set of rules of a language by which we construct sentences. Each language has a different syntax. The syntax of the English language requires that each sentence has a noun and a verb, each of which may be modified by adjectives and adverbs. Some syntaxes make use of the order in which words appear. For example, in English, the meaning of the sentence “The man bites the dog” is different from “The dog bites the man.”
Pragmatics: The social side of language is expressed through pragmatics, or how we communicate effectively and appropriately with others. Examples of pragmatics include turn taking, staying on topic, volume and tone of voice, and appropriate eye contact.
Language Developmental Progression
Do newborns communicate? Of course, they do. They do not, however, communicate with the use of oral language. Instead, they communicate their thoughts and needs with body posture (being relaxed or still), gestures, cries, and facial expressions. A person who spends adequate time with an infant can learn which cries indicate pain and which ones indicate hunger, discomfort, or frustration.
Intentional Vocalizations: In terms of producing spoken language, babies begin to coo almost immediately. Cooing is a one-syllable combination of a consonant and a vowel sound (e.g., coo or ba). Interestingly, babies replicate sounds from their own languages. A baby whose parents speak French will coo in a different tone than a baby whose parents speak Spanish or Urdu. These gurgling, musical vocalizations can serve as a source of entertainment to an infant who has been laid down for a nap or seated in a carrier on a car ride. Cooing serves as practice for vocalization, as well as the infant hears the sound of his or her own voice and tries to repeat sounds that are entertaining. Infants also begin to learn the pace and pause of conversation as they alternate their vocalization with that of someone else and then take their turn again when the other person’s vocalization has stopped.
Gesturing: Children communicate information through gesturing long before they speak, and there is some evidence that gesture usage predicts subsequent language development (Iverson & Goldin-Meadow, 2005). Deaf babies also use gestures to communicate wants, reactions, and feelings. Because gesturing seems to be easier than vocalization for some toddlers, sign language is sometimes taught to enhance one’s ability to communicate by making use of the ease of gesturing. The rhythm and pattern of language are used when deaf babies sign, just as it is when hearing babies babble.
Understanding: At around ten months of age, the infant can understand more than he or she can say, which is referred to as receptive language. You may have experienced this phenomenon as well if you have ever tried to learn a second language. You may have been able to follow a conversation more easily than contribute to it. One of the first words that children understand is their own name, usually by about 6 months, followed by commonly used words like “bottle,” “mama,” and “doggie” by 10 to 12 months (Mandel, Jusczyk, & Pisoni, 1995).
Holophrastic Speech: Children begin using their first words at about 12 or 13 months of age and may use partial words to convey thoughts at even younger ages. These one-word expressions are referred to as holophrasic speech. For example, the child may say “ju” for the word “juice” and use this sound when referring to a bottle. The listener must interpret the meaning of the holophrase, and when this is someone who has spent time with the child, interpretation is not too difficult. But, someone who has not been around the child will have trouble knowing what is meant. Imagine the parent who to a friend exclaims, “Ezra’s talking all the time now!” The friend hears only “ju da ga” to which the parent explains means, “I want some milk when I go with Daddy.”
Language Errors: The early utterances of children contain many errors, for instance, confusing /b/ and /d/, or /c/ and /z/. The words children create are often simplified, in part because they are not yet able to make the more complex sounds of the real language (Dobrich & Scarborough, 1992). Children may say “keekee” for kitty, “nana” for banana, and “vesketti” for spaghetti because it is easier. Often these early words are accompanied by gestures that may also be easier to produce than the words themselves. Children’s pronunciations become increasingly accurate between 1 and 3 years, but some problems may persist until school age.
First words and cultural influences: If the child is using English, first words tend to be nouns. The child labels objects such as a cup, ball, or other items that they regularly interact with. In a verb-friendly language such as Chinese, however, children may learn more verbs. This may also be due to the different emphasis given to objects based on culture. Chinese children may be taught to notice action and relationships between objects, while children from the United States may be taught to name an object and its qualities (color, texture, size, etc.). These differences can be seen when comparing interpretations of art by older students from China and the United States (Imai et al., 2008).
Two-word sentences and telegraphic (text message) speech: By the time they become toddlers, children have a vocabulary of about 50-200 words and begin putting those words together in telegraphic speech, such as “baby bye-bye” or “doggie pretty”. Words needed to convey messages are used, but the articles and other parts of speech necessary for grammatical correctness are not yet used. These expressions sound like a telegraph, or perhaps a better analogy today would be that they read like a text message. Telegraphic speech/text message speech occurs when unnecessary words are not used. “Give baby ball” is used rather than “Give the baby the ball.”
Infant-directed Speech: Why is a horse a “horsie”? Have you ever wondered why adults tend to use “baby talk” or that sing-song type of intonation and exaggeration used when talking to children? This represents a universal tendency and is known as infant-directed speech. It involves exaggerating the vowel and consonant sounds, using a high-pitched voice, and delivering the phrase with great facial expression (Clark, 2009). Why is this done? Infants are frequently more attuned to the tone of voice of the person speaking than to the content of the words themselves and are aware of the target of speech. Werker, Pegg, and McLeod (1994) found that infants listened longer to a woman who was speaking to a baby than to a woman who was speaking to another adult. Adults may use this form of speech in order to clearly articulate the sounds of a word so that the child can hear the sounds involved. It may also be because when this type of speech is used, the infant pays more attention to the speaker and this sets up a pattern of interaction in which the speaker and listener are in tune with one another.
Theories of Language Development
Nativism: The linguist Noam Chomsky is a believer in the natural approach to language, arguing that human brains contain a language acquisition device (LAD) that includes a universal grammar that underlies all human language (Chomsky, 1965, 1972). According to this approach, each of the many languages spoken around the world (there are between 6,000 and 8,000) is an individual example of the same underlying set of procedures that are hardwired into human brains. Chomsky’s account proposes that children are born with a knowledge of general rules of syntax that determine how sentences are constructed. Language develops as long as the infant is exposed to it. No teaching, training, or reinforcement is required for language to develop as proposed by Skinner.
Chomsky differentiates between the deep structure of an idea; that is, how the idea is represented in the fundamental universal grammar that is common to all languages, and the surface structure of the idea or how it is expressed in any one language. Once we hear or express a thought in surface structure, we generally forget exactly how it happened. At the end of a lecture, you will remember a lot of the deep structure (i.e., the ideas expressed by the instructor), but you cannot reproduce the surface structure (the exact words that the instructor used to communicate the ideas).
Brain Areas for Language: For the 90% of people who are right-handed, language is stored and controlled by the left cerebral cortex, although for some left-handers this pattern is reversed. These differences can easily be seen in the results of neuroimaging studies that show that listening to and producing language creates greater activity in the left hemisphere than in the right. Broca’s area, an area in front of the left hemisphere near the motor cortex, is responsible for language production (Figure 3.20).
Figure 3.20 Drawing of Brain Showing Broca’s and Wernicke’s Area
responsible for language comprehension.
will likely never grasp the grammatical and communication nuances of language. Case studies, including Victor the “Wild Child,” who has abandoned as a baby in 18th century France and not discovered until he was 12, and Genie, a child whose parents kept her locked away from 18 months until 13 years of age, are two examples of children who were deprived of language. Both children made some progress in socialization after they were rescued, but neither of them ever developed a working understanding of language (Rymer, 1993). Yet, such case studies are fraught with many confounds. How much did the years of social isolation and malnutrition contribute to their problems in language development?
hearing impairment and receive treatment, the better the child’s long-term language development. For instance, Stika et al. (2015) reported that when children’s hearing loss was identified during newborn screening, and subsequently addressed, the majority showed normal language development when later tested at 12-18 months. Fitzpatrick, Crawford, Ni, and Durieux-Smith (2011) reported that early language intervention in children who were moderately to severely hard of hearing, demonstrated normal outcomes in language proficiency by 4 to 5 years of age. Tomblin et al. (2015) reported that children who were fit with hearing aids by 6 months of age showed good levels of language development by age 2. Those whose hearing was not corrected until after 18 months showed lower language performance, even in the early preschool years. However, this study did reveal that those whose hearing was corrected by toddlerhood had greatly improved language skills by age 6. The research with hearing impaired children reveals that this critical period for language development is not exclusive to infancy, and that the brain is still receptive to language development in early childhood. Fortunately, it is has become routine to screen hearing in newborns, because when hearing loss is not treated early, it can delay spoken language, literacy, and impact children’s social skills (Moeller & Tomblin, 2015).
Learning Theory: Perhaps the most straightforward explanation of language development is that it occurs through the principles of learning, including association and reinforcement (Skinner, 1953). Additionally, Bandura (1977) described the importance of observation and imitation of others in learning language. There must be at least some truth to the idea that language is learned through environmental interactions or nurture. Children learn the language that they hear spoken around them rather than some other language. Also supporting this idea is the gradual improvement of language skills with time. It seems that children modify their language through imitation and reinforcement, such as parental praise and being understood. For example, when a two-year-old child asks for juice, he might say, “me juice,” to which his mother might respond by giving him a cup of apple juice.
Figure 3.22 Three Theorists who provide explanations for language development
need them, but rather a system of rules and procedures that allows us to create an infinite number of statements, thoughts, and ideas, including those that have never previously occurred. When a child says that she “swimmed” in the pool, for instance, she is showing generativity. No adult speaker of English would ever say “swimmed,” yet it is easily generated from the normal system of producing language.
Social pragmatics: Another view emphasizes the very social nature of human language. Language from this view is not only a cognitive skill but also a social one. A language is a tool humans use to communicate, connect to, influence and inform others. Most of all, language comes out of a need to cooperate. The social nature of language has been demonstrated by a number of studies that have shown that children use several pre-linguistic skills (such as pointing and other gestures) to communicate not only their own needs but what others may need. So, a child watching her mother search for an object may point to the object to help her mother find it. Eighteen-month to 30-month-olds have been shown to make linguistic repairs when it is clear that another person does not understand them (Grosse, Behne, Carpenter & Tomasello, 2010). Grosse et al. (2010) found that even when the child was given the desired object if there had been any misunderstanding along the way (such as a delay in being handed the object, or the experimenter calling the object by the wrong name), children would make linguistic repairs. This would suggest that children are using language not only as a means of achieving some material goal, but to make themselves understood in the mind of another person.
References
Ainsworth, M. (1979). Infant-mother attachment. American Psychologist, 34(10), 932-937.
Akimoto, S. A., & Sanbinmatsu, D. M. (1999). Differences in self-effacing behavior between European and Japanese Americans: Effect on competence evaluations. Journal of Cross-Cultural Psychology, 30, 159-177.
American Optometric Association. (2019). Infant vision: Birth to 24 months of age. Retrieved from https://www.aoa.org/patients-and-public/good-vision-throughout-life/childrens-vision/infant-vision-birth-to-24- months-of-age
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders, 5th edition (DSM-5).
Washington, DC: Author.
Anglin, J. M. (1993). Vocabulary development: A morphological analysis. Monographs of the Society for Research in Child Development, 58 10), v–165.
Aslin, R. N. (1981). Development of smooth pursuit in human infants. In D. F. Fisher, R. A. Monty, & J. W. Senders (Eds.), Eye movements: Cognition and visual perception (pp. 31– 51). Hillsdale, NJ: Erlbaum.
Atkinson, J., & Braddick, O. (2003). Neurobiological models of normal and abnormal visual development. In M. de Haan & M. H. Johnson (Eds.), The cognitive neuroscience of development (pp. 43– 71). Hove: Psychology Press.
Baillargeon, R. (1987. Object permanence in 3 ½ and 4 ½ year-old infants. Developmental Psychology, 22, 655-664. Baillargeon, R., Li, J., Gertner, Y, & Wu, D. (2011). How do infants reason about physical events? In U. Goswami (Ed.), The Wiley-Blackwell handbook of childhood cognitive development. MA: John Wiley.
Balaban, M. T. & Reisenauer, C. D. (2013). Sensory development. In N. J. Salkind (Ed.), Encyclopedia of human development (pp. 1144-1147). New, York: Sage Publications.
Baldwin, D. A. (1993). Early referential understanding: Infants’ ability to recognize referential acts for what they are. Developmental Psychology, 29(5), 832–843.
Bartrip J, Morton J, & De Schonen S. (2001). Responses to mother’s face in 3-week to 5-month-old infants. British Journal of Developmental Psychology, 19, 219–232
Berk, L. E. (2007). Development through the life span (4th ed.). Boston: Allyn and Bacon.
Berne, S. A. (2006). The primitive reflexes: Considerations in the infant. Optometry & Vision Development, 37(3), 139-145. Bloem, M. (2007). The 2006 WHO child growth standards. BMJ : British Medical Journal, 334(7596), 705–706. doi.org/10.1136/bmj.39155.658843.BE
Blossom, M., & Morgan, J. L. (2006). Does the face say what the mouth says? A study of infants’ sensitivity to visual prosody. In the 30th annual Boston University conference on language development, Somerville, MA.
Bogartz, R. S., Shinskey, J. L., & Schilling, T. (2000). Object permanence in five-and-a-half month old infants. Infancy, 1(4), 403-428.
Bowlby, J. (1969). Attachment and loss. London: Hogarth Press. Bowlby, J. (1982). Attachment (2nd ed.). New York: Basic Books.
Bradshaw, D. (1986). Immediate and prolonged effectiveness of negative emotion expressions in inhibiting infants’ actions (Unpublished doctoral dissertation). Berkeley, CA: University of California, Berkeley.
Braungart-Rieker, J. M., Hill-Soderlund, A. L., &Karrass, J. (2010). Fear, anger reactivity trajectories from 4 to 16 months: The roles of temperament, regulation, and maternal sensitivity. Developmental Psychology, 46, 791-804.
Bushnell, I. W. R. (2001) Mother’s face recognition in newborn infants: Learning and memory. Infant Child Development, 10, 67-94.
Bushnell, I. W. R., Sai, F., Mullin, J. T. (1989). Neonatal recognition of mother’s face. British Journal of Developmental Psychology, 7, 3-15.
Bruer, J. T. (1999). The myth of the first three years: A new understanding of early brain development and lifelong learning. New York: Simon and Schuster.
Campanella, J., & Rovee-Collier, C. (2005). Latent learning and deferred imitation at 3 months. Infancy, 7(3), 243-262. Carlson, N. (2014). Foundations of behavioral neuroscience (9th ed.). Boston, MA: Pearson.
Carpenter, R., McGarvey, C., Mitchell, E. A., Tappin, D. M., Vennemann, M. M., Smuk, M., & Carpenter, J. R. (2013). Bed sharing when parents do not smoke: Is there a risk of SIDS? An individual level analysis of five major case–control studies. BMJ Open, 3:e002299. doi:10.1136/bmjopen-2012-002299
Centers for Disease Control and Prevention. (2018). Breastfeeding facts. Retrieved from https://www.cdc.gov/breastfeeding/data/facts.html
Centers for Disease Control and Prevention. (2019). Sudden unexpected infant death and sudden infant death syndrome. Retrieved from http://www.cdc.gov/sids/data.htm
Cheour-Luhtanen, M., Alho. K., Kujala, T., Reinikainen, K., Renlund, M., Aaltonen, O., … & Näätänen R. (1995). Mismatch negativity indicates vowel discrimination in newborns. Hearing Research, 82, 53–58.
Chess, S., & Thomas, A. (1996). Temperament: Theory and practice. New York: Brunner/Mazel.
Chi, J. G., Dooling, E. C., & Gilles, F. H. (1977). Left-right asymmetries of the temporal speech areas of the human fetus. Archives of Neurology, 34, 346–8.
Chien S. (2011). No more top-heavy bias: Infants and adults prefer upright faces but not top-heavy geometric or face-like patterns. Journal of Vision, 11(6):1–14.
Chomsky, N. (1965). Aspects of the theory of syntax. Cambridge, MA: MIT Press. Chomsky, N. (1972). Language and mind. NY: Harcourt Brace.
Clark, E. V. (2009). What shapes children’s language? Child-directed speech and the process of acquisition. In V. C. M. Gathercole (Ed.), Routes to language: Essays in honor of Melissa Bowerman. NY: Psychology Press.
Clark, L. A., Kochanska, G., & Ready, R. (2000). Mothers’ personality and its interaction with child temperament as predictors of parenting behavior. Journal of Personality and Social Psychology, 79, 274–285.
Clemson University Cooperative Extension. (2014). Introducing solid foods to infants. Retrieved from http://www.clemson.edu/extension/hgic/food/nutrition/nutrition/life_stages/hgic4102.html
Cole, P. M., Armstrong, L. M., & Pemberton, C. K. (2010). The role of language in the development of emotional regulation. In S. D. Calkins & M. A. Bell (Eds.). Child development at intersection of emotion and cognition (pp. 59-77). Washington D.C.: American Psychological Association.
Colvin, J.D., Collie-Akers, V., Schunn, C., & Moon, R.Y. (2014). Sleep environment risks for younger and older infants. Pediatrics Online. Retrieved from pediatrics.aappublications.org/content/pediatrics/early/2014/07/09/peds. 2014-0401.full.pdf
de Boysson-Bardies, B., Sagart, L., & Durand, C. (1984). Discernible differences in the babbling of infants according to target language. Journal of Child Language, 11(1), 1–15.
DeCasper, A. J., & Fifer, W. P. (1980). Of human bonding: Newborns prefer their mother’s voices. Science, 208, 1174-1176. DeCasper, A. J., & Spence, M. J. (1986). Prenatal maternal speech influences newborns’ perception of speech sounds. Infant Behavior and Development, 9, 133-150.
Diamond, A. (1985). Development of the ability to use recall to guide actions, as indicated by infants’ performance on AB. Child Development, 56, 868-883.
Dobrich, W., & Scarborough, H. S. (1992). Phonological characteristics of words young children try to say. Journal of Child Language, 19(3), 597–616.
Dubois, J., Hertz-Pannier, L., Cachia, A., Mangin, J. F., Le Bihan, D., & Dehaene-Lambertz, G. (2009). Structural asymmetries in the infant language and sensori-motor networks. Cerebral Cortex, 19, 414–423.
Eisenberg, A., Murkoff, H. E., & Hathaway, S. E. (1989). What to expect the first year. New York: Workman Publishing.
Eisenberg, N., Fabes, R. A., Shepard, S. A., Guthrie, I.K., Murphy, B.C., & Reiser, M. (1999). Parental reactions to children’s negative emotions: Longitudinal relations to quality of children’s social functioning. Child Development, 70, 513-534.
Eisenberg, N., Hofer, C., Spinrad, T., Gershoff, E., Valiente, C., Losoya, S. L., Zhou, Q., Cumberland, A., Liew, J., Reiser, M., & Maxon, E. (2008). Understanding parent-adolescent conflict discussions: Concurrent and across-time prediction from youths’ dispositions and parenting. Monographs of the Society for Research in Child Development, 73, (Serial No. 290, No. 2), 1-160.
El-Dib, M., Massaro, A. N., Glass, P., & Aly, H. (2012). Neurobehavioral assessment as a predictor of neurodevelopmental outcome in preterm infants. Journal of Perinatology, 32, 299-303.
Eliot, L. (1999). What’s going on in there? New York: Bantam. Erikson, E. (1982). The life cycle completed. NY: Norton & Company.
Evans, N., & Levinson, S. C. (2009). The myth of language universals: Language diversity and its importance for cognitive science. Behavioral and Brain Sciences, 32(5), 429–448.
Farroni, T., Johnson, M.H. Menon, E., Zulian, L. Faraguna, D., Csibra, G. (2005). Newborns’ preference for face-relevant stimuli: Effects of contrast polarity. Proceedings of the National Academy of Sciences of the United States of America, 102(47), 17245-17250.
Fergusson, D. M., & Woodward, L. J. (1999). Breastfeeding and later psychosocial adjustment. Paediatric and Perinatal Epidemiology, 13, 144-157.
Fitzpatrick, E.M., Crawford, L., Ni, A., & Durieux-Smith, A. (2011). A descriptive analysis of language and speech skills in 4-to- 5-yr-old children with hearing loss. Ear and Hearing, 32(2), 605-616.
Freud, S. (1938). An outline of psychoanalysis. London: Hogarth.
Galler J. R., & Ramsey F. (1989). A follow-up study of the influence of early malnutrition on development: Behavior at home and at school. American Academy of Child and Adolescence Psychiatry, 28 (2), 254-61.
Galler, J. R., Ramsey, F. C., Morely, D. S., Archer, E., & Salt, P. (1990). The long-term effects of early kwashiorkor compared with marasmus. IV. Performance on the national high school entrance examination. Pediatric Research, 28(3), 235- 239.
Galler, J. R., Ramsey, F. C., Salt, P. & Archer, E. (1987). The long-term effect of early kwashiorkor compared with marasmus. III. Fine motor skills. Journal of Pediatric Gastroenterology Nutrition, 6, 855-859.
Giedd, J. N. (2015). The amazing teen brain. Scientific American, 312(6), 32-37.
Giles, A., & Rovee-Collier, C. (2011). Infant long-term memory for associations formed during mere exposure. Infant Behavior and Development, 34 (2), 327-338.
Gillath, O., Shaver, P. R., Baek, J. M., & Chun, D. S. (2008). Genetic correlates of adult attachment style. Personality & Social Psychology Bulletin, 34, 1396–1405.
Gleitman, L. R., & Newport, E. L. (1995). The invention of language by children: Environmental and biological influences on the acquisition of language. An Invitation to Cognitive Science, 1, 1-24.
Goldin-Meadow, S., & Mylander, C. (1998). Spontaneous sign systems created by deaf children in two cultures. Nature, 391(6664), 279–281.
Grosse, G., Behne, T., Carpenter, M., & Tomasello, M. (2010). Infants communicate in order to be understood. Developmental Psychology, 46(6), 1710-1722.
Gunderson, E. P., Hurston, S. R., Ning, X., Lo, J. C., Crites, Y., Walton, D…. & Quesenberry, C. P. Jr. (2015). Lactation and progression to type 2 diabetes mellitus after gestational diabetes mellitus: A prospective cohort study. American Journal of Medicine, 163, 889-898. Doi: 10.7326/m 15-0807.
Hainline L. (1978). Developmental changes in visual scanning of face and nonface patterns by infants. Journal of Experimental Child Psychology, 25, 90–115.
Hamer, R. (2016). The visual world of infants. Scientific American, 104, 98-101. Harlow, H. F. (1958). The nature of love. American Psychologist, 13, 673-685.
Harris, Y. R. (2005). Cognitive development. In N. J. Salkind (Ed.), Encyclopedia of human development (pp. 276-281). New, York: Sage Publications.
Hart, S., & Carrington, H. (2002). Jealousy in 6-month-old infants. Infancy, 3(3), 395-402.
Hatch, E. M. (1983). Psycholinguistics: A second language perspective. Rowley, MA: Newbury House Publishers. Hertenstein, M. J., & Campos, J. J. (2004). The retention effects of an adult’s emotional displays on infant behavior. Child Development, 75(2), 595–613.
Holland, D., Chang, L., Ernst, T., Curan, M Dale, A. (2014). Structural growth trajectories and rates of change in the first 3 months of infant brain development. JAMA Neurology, 71(10), 1266-1274.
Huttenlocher, P. R., & Dabholkar, A. S. (1997). Regional differences in synaptogenesis in human cerebral cortex. The Journal of Comparative Neurology, 387(2), 167-178.
Hyde, J. S., Else-Quest, N. M., & Goldsmith, H. H. (2004). Children’s temperament and behavior problems predict their employed mothers’ work functioning. Child Development, 75, 580–594.
Hyvärinen, L., Walthes, R., Jacob, N., Nottingham Chaplin, K., & Leonhardt, M. (2014). Current understanding of what infants see. Current Opthalmological Report, 2, 142-149. doi:10.1007/s40135-014-0056-2
Imai, M., Li, L., Haryu, E., Hirsh-Pasek, K., Golinkoff, R. M., & Shigematsu, J. (2008). Novel noun and verb learning in Chinese, English, and Japanese children: Universality and language-specificity in novel noun and verb learning. Child Development, 79, 979-1000.
Islami, F., Liu, Y., Jemal, A., Zhou, J., Weiderpass, E., Colditz, G…Weiss, M. (2015). Breastfeeding and breast cancer risk by receptor status – a systematic review and meta-analysis. Annals of Oncology, 26, 2398-2407.
Iverson, J. M., & Goldin-Meadow, S. (2005). Gesture paves the way for language development. Psychological science, 16(5), 367-371.
Jarrett, C. (2015). Great myths of the brain. West Sussex, UK: Wiley.
Johnson, M. H., & deHaan, M. (2015). Developmental cognitive neuroscience: An introduction. Chichester, West Sussex: UK, Wiley & Sons
Jusczyk, P.W., Cutler, A., & Redanz, N.J. (1993). Infants’ preference for the predominant stress patterns of English words. Child Development, 64, 675–687.
Karlson, E.W., Mandl, L.A., Hankison, S. E., & Grodstein, F. (2004). Do breast-feeding and other reproductive factors influence future risk of rheumatoid arthritis? Arthritis & Rheumatism, 50 (11), 3458-3467.
Kasprian, G., Langs, G., Brugger, P. C., Bittner, M., Weber, M., Arantes, M., & Prayer, D. (2011). The prenatal origin of hemispheric asymmetry: an in utero neuroimaging study. Cerebral Cortex, 21, 1076–1083.
Kiff, C. J., Lengua, L. J., & Zalewski, M. (2011). Nature and nurturing: Parenting in the context of child temperament. Clinical Child and Family Psychology Review, 14, 251–301. doi: 10.1007/s10567-011-0093-4
Klein, P. J., & Meltzoff, A. N. (1999). Long-term memory, forgetting, and deferred imitation in 12-month-old infants. Developmental Science, 2(1), 102-113.
Klinnert, M. D., Campos, J. J., & Sorce, J. F. (1983). Emotions as behavior regulators: Social referencing in infancy. In R. Plutchik & H. Kellerman (Eds.), Emotion: Theory, research, and experience (pp. 57–86). New York, NY: Academic Press.
Kolb, B., & Fantie, B. (1989). Development of the child’s brain and behavior. In C. R. Reynolds & E. Fletcher-Janzen (Eds.),
Handbook of clinical child neuropsychology (pp. 17–39). New York, NY: Plenum Press.
Kolb, B. & Whishaw, I. Q. (2011). An introduction to brain and behavior (3rd ed.). New York: Worth Publishers.
Kopp, C. B. (2011). Development in the early years: Socialization, motor development, and consciousness. Annual Review of Psychology, 62, 165-187.
Latham, M. C. (1997). Human nutrition in the developing world. Rome, IT: Food and Agriculture Organization of the United Nations.
Lavelli, M., & Fogel, A. (2005). Developmental changes in the relationships between infant attention and emotion during early face-to-face communications: The 2 month transition. Developmental Psychology, 41, 265-280.
Lenneberg, E. (1967). Biological foundations of language. New York, NY: John Wiley & Sons.
LeVine, R. A., Dixon, S., LeVine, S., Richman, A., Leiderman, P. H., Keefer, C. H., & Brazelton, T. B. (1994). Child care and culture: Lessons from Africa. New York: Cambridge University Press.
Lewis, M., & Brooks, J. (1978). Self-knowledge and emotional development. In M. Lewis & L. A. Rosenblum (Eds.), Genesis of behavior (Vol. 1, pp. 205-226). New York: Plenum Press.
Lewis, T. L., Maurer, D., & Milewski, A. (1979). The development of nasal detection in young infants. Investigative Ophthalmology and Visual Science Supplement, 19, 271.
Li, Y., & Ding, Y. (2017). Human visual development. In Y. Liu., & W. Chen (Eds.), Pediatric lens diseases (pp. 11-20). Singapore: Springer.
Los Angles County Department of Public Health. (2019). Breastfeeding vs. formula feeding. Retrieved from publichealth.lacounty.gov/LAmoms/lessons/Breastfeeding/6_BreastfeedingvsFormulaFeeding.pdf
Main, M., & Solomon, J. (1990). Procedures for identifying infants as disorganized/disoriented during the Ainsworth Strange Situation. In M. T. Greenberg, D. Cicchetti, & E. M. Cummings (Eds.), Attachment inthe Preschool Years (pp.121– 160).Chicago,IL: UniversityofChicagoPress.
Mandel, D. R., Jusczyk, P. W., & Pisoni, D. B. (1995). Infants’ recognition of the sound patterns of their own names. Psychological Science, 6(5), 314–317.
Mayberry, R. I., Lock, E., & Kazmi, H. (2002). Development: Linguistic ability and early language exposure. Nature, 417(6884), 38.
Moeller, M.P., & Tomblin, J.B. (2015). An introduction to the outcomes of children with hearing loss study. Ear and Hearing, 36 Suppl (0-1), 4S-13S
Morelli, G., Rogoff, B., Oppenheim, D., & Goldsmith, D. (1992). Cultural variations in infants’ sleeping arrangements: Questions of independence. Developmental Psychology, 28, 604-613.
Nelson, E. A., Schiefenhoevel, W., & Haimerl, F. (2000). Child care practices in nonindustrialized societies. Pediatrics, 105, e75.
O’Connor, T. G., Marvin, R. S., Rotter, M., Olrich, J. T., Britner, P. A., & The English and Romanian Adoptees Study Team. (2003). Child-parent attachment following early institutional deprivation. Development and Psychopathology, 15, 19- 38.
Papousek, M. (2007). Communication in early infancy: An arena of intersubjective learning. Infant Behavior and Development, 30, 258-266.
Pearson Education. (2016). Bayley Scales of Infant Development, Third Edition. New York: Pearson. Retrieved from http://www.pearsonclinical.com/childhood/products/100000123/bayley-scales-of-infant-and-toddler-development- third-edition-bayley-iii.html#tab-details
Penfield, W., & Roberts, L. (1959). Speech and brain mechanisms. Princeton, NJ: Princeton University Press.
Petitto, L. A., & Marentette, P. F. (1991). Babbling in the manual mode: Evidence for the ontogeny of language. Science, 251(5000), 1493–1496.
Phelps, B. J. (2005). Habituation. In N. J. Salkind (Ed.), Encyclopedia of human development (pp. 597-600). New York: Sage Publications.
Piaget, J. (1954). The construction of reality in the child. New York: Basic Books.
Pickens, J., Field, T., Nawrocki, T., Martinez, A., Soutullo, D., & Gonzalez, J. (1994). Full-term and preterm infants’ perception of face-voice synchrony. Infant Behavior and Development, 17(4), 447-455.
Porter, R. H., Makin, J. W., Davis, L. M., Christensen, K. (1992). Responsiveness of infants to olfactory cues from lactating females. Infant Behavior and Development, 15, 85-93.
Redondo, C. M., Gago-Dominguez, M., Ponte, S. M., Castelo, M. E., Jiang, X., Garcia, A.A… Castelao, J. E. (2012). Breast feeding, parity and breast cancer subtypes in a Spanish cohort. PLoS One, 7(7): e40543 doi: 10.1371/journal.pone.00040543
Richardson, B. D. (1980). Malnutrition and nutritional anthropometry. Journal of Tropical Pediatrics, 26(3), 80-84. Rothbart, M. K., & Bates, J. E. (2006). Temperament. In N. Eisenberg (Ed.). Handbook of child psychology: Vol. 3: Social, emotional, and personality development (6th ed., pp. 99-116). Hoboken, NJ: Wiley.
Rothbart, M. K., Posner, M. I. & Kieras, J. (2006). Temperament, attention, and the development of self-regulation. In M. McCartney & D. Phillips (Eds.) Blackwell handbook of early childhood development (pp. 3338-357). Malden, MA: Blackwell.
Rothbaum, F., Weisz, J., Pott, M., Miyake, K., & Morelli, G. (2010). Attachment and culture: Security in the United States and Japan. American Psychologist, 55, 1093-1104.
Rovee-Collier, C. (1987). Learning and memory in infancy. In J. D. Osofsky (Ed.), Handbook of infant development, (2nd, ed., pp. 98-148). New York: Wiley.
Rovee-Collier, C. (1990). The “memory system” of prelinguistic infants. Annuals of the New York Academy of Sciences, 608, 517-542. doi: 10.1111/j.1749-66231990.tb48908.
Rovee-Collier, C., & Hayne, H. (1987). Reactivation of infant memory: Implications for cognitive development. In H. W. Reese (Ed.), Advances in child development and behavior. (Vol. 20, pp. 185-238). London, UK: Academic Press.
Rymer, R. (1993). Genie: A scientific tragedy. Harmondsworth: Penguin.
Salkind, N. J. (2005). Encyclopedia of human development. New York: Sage Publications.
Schwarz, E. B., Brown, J. S., Creasman, J. M. Stuebe, A., McClure, C. K., Van Den Eeden, S. K., & Thom, D. (2010). Lactation and maternal risk of type-2 diabetes: A population-based study. American Journal of Medicine, 123, 863.e1-863.e6. doi: 10.1016/j.amjmed.2010.03.016.
Seifer, R., Schiller, M., Sameroff, A., Resnick, S., & Riordan, K. (1996). Attachment, maternal sensitivity, and infant temperament during the first year of life. Developmental Psychology, 32, 12-25.
Sen, M. G., Yonas, A., & Knill, D. C. (2001). Development of infants’ sensitivity to surface contour information for spatial layout. Perception, 30, 167-176.
Senghas, R. J., Senghas, A., & Pyers, J. E. (2005). The emergence of Nicaraguan Sign Language: Questions of development, acquisition, and evolution. In S. T. Parker, J. Langer, & C. Milbrath (Eds.), Biology and knowledge revisited: From neurogenesis to psychogenesis (pp. 287–306). Mahwah, NJ: Lawrence Erlbaum Associates.
Shaffer, D. R. (1985). Developmental psychology: Theory, research, and applications. Belmont, CA: Wadsworth, Inc. Skinner, B. F. (1953). Science and human behavior. NY: Free Press.
Sorce, J. F., Emde, J. J., Campos, J. J., & Klinnert, M. D. (1985). Maternal emotional signaling: Its effect on the visual cliff behavior of 1-year-olds. Developmental Psychology, 21, 195–200.
Spelke, E. S., & Cortelyou, A. (1981). Perceptual aspects of social knowing: Looking and listening in infancy. Infant social cognition, 61-84.
Springer, S. P. & Deutsch, G. (1993). Left brain, right brain (4th ed.). New York: W. H. Freeman.
Stika, C.J., Eisenberg, L.S., Johnson, K.C. Henning, S.C., Colson, B.G., Ganguly, D.H., & DesJardin, J.L. (2015). Developmental outcomes of early-identified children who are hard of hearing at 12 to 18 months of age. Early Human Development, 9(1), 47-55.
Stork, F. & Widdowson, J. (1974). Learning about Linguistics. London: Hutchinson.
Thomas, R. M. (1979). Comparing theories of child development. Santa Barbara, CA: Wadsworth.
Thompson, R. A. (2006). The development of the person. In W. Damon & R. Lerner (Eds.), Handbook of child psychology (6th Ed.). New York: Wiley.
Thompson, R. A., & Goodvin, R. (2007). Taming the tempest in the teapot. In C. A. Brownell & C. B. Kopp (Eds.). Socioemotional development in the toddler years: Transitions and transformations (pp. 320-342). New York: Guilford.
Thompson, R. A., Winer, A. C., & Goodvin, R. (2010). The individual child: Temperament, emotion, self, and personality. In M. Bornstein & M. E. Lamb (Eds.), Developmental science: An advanced textbook (6th ed., pp. 423–464). New York, NY: Psychology Press/Taylor & Francis.
Titus-Ernstoff, L., Rees, J. R., Terry, K. L., & Cramer, D. W. (2010). Breast-feeding the last-born child and risk of ovarian cancer. Cancer Causes Control, 21(2), 201-207. doi: 10.1007/s10552-009-9450-8
Tomblin, J. B., Harrison, M., Ambrose, S. E., Walker, E. A., Oleson, J. J., & Moeller, M. P. (2015). Language outcomes in young children with mild to severe hearing loss. Ear and hearing, 36 Suppl 1(0 1), 76S–91S.
United Nations Children’s Fund. (2015). Levels and trends in child mortality: Report 2015. United Nations Children’s Fund. New York: NY.
United States Department of Health and Human Services, Office of Women’s Health. (2011). Your guide to breast feeding. Washington D.C.
United States National Library of Medicine. (2016). Circumcision. Retrieved from https://medlineplus.gov/circumcision.html
Van den Boom, D. C. (1994). The influence of temperament and mothering on attachment and exploration: An experimental manipulation of sensitive responsiveness among lower-class mothers with irritable infants. Child Development, 65, 1457–1477.
Van Ijzendoorn, M. H., & Sagi, A. (1999). Cross-cultural patterns of attachment. In J. Cassidy & P. R. Shaver (Eds.), Handbook of attachment: Theory, research, and clinical applications (pp. 713-734). New York: Guilford.
Webb, S. J., Monk, C. S., & Nelson, C. A. (2001). Mechanisms of postnatal neurobiological development: Implications for human development. Developmental Neuropsychology, 19, 147-171.
Weekes-Shackelford, V. A. & Shackelford, T. K. (2005). Sudden Infant Death Syndrome (SIDS). In N. J. Salkind (Ed.), Encyclopedia of human development (pp. 1238-1239). New York: Sage Publications.
Werker, J. F., Pegg, J. E., & McLeod, P. J. (1994). A cross-language investigation of infant preference for infant-directed communication. Infant Behavior and Development, 17, 323-333.
Werker, J. F., & Tees, R. C. (2002). Cross-language speech perception: Evidence for perceptual reorganization during the first year of life. Infant Behavior and Development, 25, 121-133.
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/06%3A_Development_in_Infancy_and_Toddlerhood/6.02%3A_Chapter_11-_Cognitive_Development_in_Infancy_and_Toddlerhood.txt |
Chapter 12 Learning Objectives
• Identify styles of temperament and explore goodness-of-fit
• Describe the infant emotions, self-awareness, stranger wariness, and separation anxiety
• Describe the early theories of attachment
• Contrast styles of attachment according to the Strange Situation Technique
• Explain the factors that influence attachment
• Use Erikson’s theory to characterize psychosocial development during infancy
Temperament
• Easy Child (40%) who is able to quickly adapt to routine and new situations, remains calm, is easy to soothe, and usually is in a positive mood.
• Difficult Child (10%) who reacts negatively to new situations, has trouble adapting to routine, is usually negative in mood, and cries frequently.
• Slow-to-Warm-Up Child (15%) has a low activity level, adjusts slowly to new situations and is often negative in mood.
References
Ainsworth, M. (1979). Infant-mother attachment. American Psychologist, 34(10), 932-937.
Akimoto, S. A., & Sanbinmatsu, D. M. (1999). Differences in self-effacing behavior between European and Japanese Americans: Effect on competence evaluations. Journal of Cross-Cultural Psychology, 30, 159-177.
American Optometric Association. (2019). Infant vision: Birth to 24 months of age. Retrieved from https://www.aoa.org/patients-and-public/good-vision-throughout-life/childrens-vision/infant-vision-birth-to-24- months-of-age
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders, 5th edition (DSM-5).
Washington, DC: Author.
Anglin, J. M. (1993). Vocabulary development: A morphological analysis. Monographs of the Society for Research in Child Development, 58 10), v–165.
Aslin, R. N. (1981). Development of smooth pursuit in human infants. In D. F. Fisher, R. A. Monty, & J. W. Senders (Eds.), Eye movements: Cognition and visual perception (pp. 31– 51). Hillsdale, NJ: Erlbaum.
Atkinson, J., & Braddick, O. (2003). Neurobiological models of normal and abnormal visual development. In M. de Haan & M. H. Johnson (Eds.), The cognitive neuroscience of development (pp. 43– 71). Hove: Psychology Press.
Baillargeon, R. (1987. Object permanence in 3 ½ and 4 ½ year-old infants. Developmental Psychology, 22, 655-664. Baillargeon, R., Li, J., Gertner, Y, & Wu, D. (2011). How do infants reason about physical events? In U. Goswami (Ed.), The Wiley-Blackwell handbook of childhood cognitive development. MA: John Wiley.
Balaban, M. T. & Reisenauer, C. D. (2013). Sensory development. In N. J. Salkind (Ed.), Encyclopedia of human development (pp. 1144-1147). New, York: Sage Publications.
Baldwin, D. A. (1993). Early referential understanding: Infants’ ability to recognize referential acts for what they are. Developmental Psychology, 29(5), 832–843.
Bartrip J, Morton J, & De Schonen S. (2001). Responses to mother’s face in 3-week to 5-month-old infants. British Journal of Developmental Psychology, 19, 219–232
Berk, L. E. (2007). Development through the life span (4th ed.). Boston: Allyn and Bacon.
Berne, S. A. (2006). The primitive reflexes: Considerations in the infant. Optometry & Vision Development, 37(3), 139-145. Bloem, M. (2007). The 2006 WHO child growth standards. BMJ : British Medical Journal, 334(7596), 705–706. doi.org/10.1136/bmj.39155.658843.BE
Blossom, M., & Morgan, J. L. (2006). Does the face say what the mouth says? A study of infants’ sensitivity to visual prosody. In the 30th annual Boston University conference on language development, Somerville, MA.
Bogartz, R. S., Shinskey, J. L., & Schilling, T. (2000). Object permanence in five-and-a-half month old infants. Infancy, 1(4), 403-428.
Bowlby, J. (1969). Attachment and loss. London: Hogarth Press. Bowlby, J. (1982). Attachment (2nd ed.). New York: Basic Books.
Bradshaw, D. (1986). Immediate and prolonged effectiveness of negative emotion expressions in inhibiting infants’ actions (Unpublished doctoral dissertation). Berkeley, CA: University of California, Berkeley.
Braungart-Rieker, J. M., Hill-Soderlund, A. L., &Karrass, J. (2010). Fear, anger reactivity trajectories from 4 to 16 months: The roles of temperament, regulation, and maternal sensitivity. Developmental Psychology, 46, 791-804.
Bushnell, I. W. R. (2001) Mother’s face recognition in newborn infants: Learning and memory. Infant Child Development, 10, 67-94.
Bushnell, I. W. R., Sai, F., Mullin, J. T. (1989). Neonatal recognition of mother’s face. British Journal of Developmental Psychology, 7, 3-15.
Bruer, J. T. (1999). The myth of the first three years: A new understanding of early brain development and lifelong learning. New York: Simon and Schuster.
Campanella, J., & Rovee-Collier, C. (2005). Latent learning and deferred imitation at 3 months. Infancy, 7(3), 243-262. Carlson, N. (2014). Foundations of behavioral neuroscience (9th ed.). Boston, MA: Pearson.
Carpenter, R., McGarvey, C., Mitchell, E. A., Tappin, D. M., Vennemann, M. M., Smuk, M., & Carpenter, J. R. (2013). Bed sharing when parents do not smoke: Is there a risk of SIDS? An individual level analysis of five major case–control studies. BMJ Open, 3:e002299. doi:10.1136/bmjopen-2012-002299
Centers for Disease Control and Prevention. (2018). Breastfeeding facts. Retrieved from https://www.cdc.gov/breastfeeding/data/facts.html
Centers for Disease Control and Prevention. (2019). Sudden unexpected infant death and sudden infant death syndrome. Retrieved from http://www.cdc.gov/sids/data.htm
Cheour-Luhtanen, M., Alho. K., Kujala, T., Reinikainen, K., Renlund, M., Aaltonen, O., … & Näätänen R. (1995). Mismatch negativity indicates vowel discrimination in newborns. Hearing Research, 82, 53–58.
Chess, S., & Thomas, A. (1996). Temperament: Theory and practice. New York: Brunner/Mazel.
Chi, J. G., Dooling, E. C., & Gilles, F. H. (1977). Left-right asymmetries of the temporal speech areas of the human fetus. Archives of Neurology, 34, 346–8.
Chien S. (2011). No more top-heavy bias: Infants and adults prefer upright faces but not top-heavy geometric or face-like patterns. Journal of Vision, 11(6):1–14.
Chomsky, N. (1965). Aspects of the theory of syntax. Cambridge, MA: MIT Press. Chomsky, N. (1972). Language and mind. NY: Harcourt Brace.
Clark, E. V. (2009). What shapes children’s language? Child-directed speech and the process of acquisition. In V. C. M. Gathercole (Ed.), Routes to language: Essays in honor of Melissa Bowerman. NY: Psychology Press.
Clark, L. A., Kochanska, G., & Ready, R. (2000). Mothers’ personality and its interaction with child temperament as predictors of parenting behavior. Journal of Personality and Social Psychology, 79, 274–285.
Clemson University Cooperative Extension. (2014). Introducing solid foods to infants. Retrieved from http://www.clemson.edu/extension/hgic/food/nutrition/nutrition/life_stages/hgic4102.html
Cole, P. M., Armstrong, L. M., & Pemberton, C. K. (2010). The role of language in the development of emotional regulation. In S. D. Calkins & M. A. Bell (Eds.). Child development at intersection of emotion and cognition (pp. 59-77). Washington D.C.: American Psychological Association.
Colvin, J.D., Collie-Akers, V., Schunn, C., & Moon, R.Y. (2014). Sleep environment risks for younger and older infants. Pediatrics Online. Retrieved from pediatrics.aappublications.org/content/pediatrics/early/2014/07/09/peds. 2014-0401.full.pdf
de Boysson-Bardies, B., Sagart, L., & Durand, C. (1984). Discernible differences in the babbling of infants according to target language. Journal of Child Language, 11(1), 1–15.
DeCasper, A. J., & Fifer, W. P. (1980). Of human bonding: Newborns prefer their mother’s voices. Science, 208, 1174-1176. DeCasper, A. J., & Spence, M. J. (1986). Prenatal maternal speech influences newborns’ perception of speech sounds. Infant Behavior and Development, 9, 133-150.
Diamond, A. (1985). Development of the ability to use recall to guide actions, as indicated by infants’ performance on AB. Child Development, 56, 868-883.
Dobrich, W., & Scarborough, H. S. (1992). Phonological characteristics of words young children try to say. Journal of Child Language, 19(3), 597–616.
Dubois, J., Hertz-Pannier, L., Cachia, A., Mangin, J. F., Le Bihan, D., & Dehaene-Lambertz, G. (2009). Structural asymmetries in the infant language and sensori-motor networks. Cerebral Cortex, 19, 414–423.
Eisenberg, A., Murkoff, H. E., & Hathaway, S. E. (1989). What to expect the first year. New York: Workman Publishing.
Eisenberg, N., Fabes, R. A., Shepard, S. A., Guthrie, I.K., Murphy, B.C., & Reiser, M. (1999). Parental reactions to children’s negative emotions: Longitudinal relations to quality of children’s social functioning. Child Development, 70, 513-534.
Eisenberg, N., Hofer, C., Spinrad, T., Gershoff, E., Valiente, C., Losoya, S. L., Zhou, Q., Cumberland, A., Liew, J., Reiser, M., & Maxon, E. (2008). Understanding parent-adolescent conflict discussions: Concurrent and across-time prediction from youths’ dispositions and parenting. Monographs of the Society for Research in Child Development, 73, (Serial No. 290, No. 2), 1-160.
El-Dib, M., Massaro, A. N., Glass, P., & Aly, H. (2012). Neurobehavioral assessment as a predictor of neurodevelopmental outcome in preterm infants. Journal of Perinatology, 32, 299-303.
Eliot, L. (1999). What’s going on in there? New York: Bantam. Erikson, E. (1982). The life cycle completed. NY: Norton & Company.
Evans, N., & Levinson, S. C. (2009). The myth of language universals: Language diversity and its importance for cognitive science. Behavioral and Brain Sciences, 32(5), 429–448.
Farroni, T., Johnson, M.H. Menon, E., Zulian, L. Faraguna, D., Csibra, G. (2005). Newborns’ preference for face-relevant stimuli: Effects of contrast polarity. Proceedings of the National Academy of Sciences of the United States of America, 102(47), 17245-17250.
Fergusson, D. M., & Woodward, L. J. (1999). Breastfeeding and later psychosocial adjustment. Paediatric and Perinatal Epidemiology, 13, 144-157.
Fitzpatrick, E.M., Crawford, L., Ni, A., & Durieux-Smith, A. (2011). A descriptive analysis of language and speech skills in 4-to- 5-yr-old children with hearing loss. Ear and Hearing, 32(2), 605-616.
Freud, S. (1938). An outline of psychoanalysis. London: Hogarth.
Galler J. R., & Ramsey F. (1989). A follow-up study of the influence of early malnutrition on development: Behavior at home and at school. American Academy of Child and Adolescence Psychiatry, 28 (2), 254-61.
Galler, J. R., Ramsey, F. C., Morely, D. S., Archer, E., & Salt, P. (1990). The long-term effects of early kwashiorkor compared with marasmus. IV. Performance on the national high school entrance examination. Pediatric Research, 28(3), 235- 239.
Galler, J. R., Ramsey, F. C., Salt, P. & Archer, E. (1987). The long-term effect of early kwashiorkor compared with marasmus. III. Fine motor skills. Journal of Pediatric Gastroenterology Nutrition, 6, 855-859.
Giedd, J. N. (2015). The amazing teen brain. Scientific American, 312(6), 32-37.
Giles, A., & Rovee-Collier, C. (2011). Infant long-term memory for associations formed during mere exposure. Infant Behavior and Development, 34 (2), 327-338.
Gillath, O., Shaver, P. R., Baek, J. M., & Chun, D. S. (2008). Genetic correlates of adult attachment style. Personality & Social Psychology Bulletin, 34, 1396–1405.
Gleitman, L. R., & Newport, E. L. (1995). The invention of language by children: Environmental and biological influences on the acquisition of language. An Invitation to Cognitive Science, 1, 1-24.
Goldin-Meadow, S., & Mylander, C. (1998). Spontaneous sign systems created by deaf children in two cultures. Nature, 391(6664), 279–281.
Grosse, G., Behne, T., Carpenter, M., & Tomasello, M. (2010). Infants communicate in order to be understood. Developmental Psychology, 46(6), 1710-1722.
Gunderson, E. P., Hurston, S. R., Ning, X., Lo, J. C., Crites, Y., Walton, D…. & Quesenberry, C. P. Jr. (2015). Lactation and progression to type 2 diabetes mellitus after gestational diabetes mellitus: A prospective cohort study. American Journal of Medicine, 163, 889-898. Doi: 10.7326/m 15-0807.
Hainline L. (1978). Developmental changes in visual scanning of face and nonface patterns by infants. Journal of Experimental Child Psychology, 25, 90–115.
Hamer, R. (2016). The visual world of infants. Scientific American, 104, 98-101. Harlow, H. F. (1958). The nature of love. American Psychologist, 13, 673-685.
Harris, Y. R. (2005). Cognitive development. In N. J. Salkind (Ed.), Encyclopedia of human development (pp. 276-281). New, York: Sage Publications.
Hart, S., & Carrington, H. (2002). Jealousy in 6-month-old infants. Infancy, 3(3), 395-402.
Hatch, E. M. (1983). Psycholinguistics: A second language perspective. Rowley, MA: Newbury House Publishers. Hertenstein, M. J., & Campos, J. J. (2004). The retention effects of an adult’s emotional displays on infant behavior. Child Development, 75(2), 595–613.
Holland, D., Chang, L., Ernst, T., Curan, M Dale, A. (2014). Structural growth trajectories and rates of change in the first 3 months of infant brain development. JAMA Neurology, 71(10), 1266-1274.
Huttenlocher, P. R., & Dabholkar, A. S. (1997). Regional differences in synaptogenesis in human cerebral cortex. The Journal of Comparative Neurology, 387(2), 167-178.
Hyde, J. S., Else-Quest, N. M., & Goldsmith, H. H. (2004). Children’s temperament and behavior problems predict their employed mothers’ work functioning. Child Development, 75, 580–594.
Hyvärinen, L., Walthes, R., Jacob, N., Nottingham Chaplin, K., & Leonhardt, M. (2014). Current understanding of what infants see. Current Opthalmological Report, 2, 142-149. doi:10.1007/s40135-014-0056-2
Imai, M., Li, L., Haryu, E., Hirsh-Pasek, K., Golinkoff, R. M., & Shigematsu, J. (2008). Novel noun and verb learning in Chinese, English, and Japanese children: Universality and language-specificity in novel noun and verb learning. Child Development, 79, 979-1000.
Islami, F., Liu, Y., Jemal, A., Zhou, J., Weiderpass, E., Colditz, G…Weiss, M. (2015). Breastfeeding and breast cancer risk by receptor status – a systematic review and meta-analysis. Annals of Oncology, 26, 2398-2407.
Iverson, J. M., & Goldin-Meadow, S. (2005). Gesture paves the way for language development. Psychological science, 16(5), 367-371.
Jarrett, C. (2015). Great myths of the brain. West Sussex, UK: Wiley.
Johnson, M. H., & deHaan, M. (2015). Developmental cognitive neuroscience: An introduction. Chichester, West Sussex: UK, Wiley & Sons
Jusczyk, P.W., Cutler, A., & Redanz, N.J. (1993). Infants’ preference for the predominant stress patterns of English words. Child Development, 64, 675–687.
Karlson, E.W., Mandl, L.A., Hankison, S. E., & Grodstein, F. (2004). Do breast-feeding and other reproductive factors influence future risk of rheumatoid arthritis? Arthritis & Rheumatism, 50 (11), 3458-3467.
Kasprian, G., Langs, G., Brugger, P. C., Bittner, M., Weber, M., Arantes, M., & Prayer, D. (2011). The prenatal origin of hemispheric asymmetry: an in utero neuroimaging study. Cerebral Cortex, 21, 1076–1083.
Kiff, C. J., Lengua, L. J., & Zalewski, M. (2011). Nature and nurturing: Parenting in the context of child temperament. Clinical Child and Family Psychology Review, 14, 251–301. doi: 10.1007/s10567-011-0093-4
Klein, P. J., & Meltzoff, A. N. (1999). Long-term memory, forgetting, and deferred imitation in 12-month-old infants. Developmental Science, 2(1), 102-113.
Klinnert, M. D., Campos, J. J., & Sorce, J. F. (1983). Emotions as behavior regulators: Social referencing in infancy. In R. Plutchik & H. Kellerman (Eds.), Emotion: Theory, research, and experience (pp. 57–86). New York, NY: Academic Press.
Kolb, B., & Fantie, B. (1989). Development of the child’s brain and behavior. In C. R. Reynolds & E. Fletcher-Janzen (Eds.),
Handbook of clinical child neuropsychology (pp. 17–39). New York, NY: Plenum Press.
Kolb, B. & Whishaw, I. Q. (2011). An introduction to brain and behavior (3rd ed.). New York: Worth Publishers.
Kopp, C. B. (2011). Development in the early years: Socialization, motor development, and consciousness. Annual Review of Psychology, 62, 165-187.
Latham, M. C. (1997). Human nutrition in the developing world. Rome, IT: Food and Agriculture Organization of the United Nations.
Lavelli, M., & Fogel, A. (2005). Developmental changes in the relationships between infant attention and emotion during early face-to-face communications: The 2 month transition. Developmental Psychology, 41, 265-280.
Lenneberg, E. (1967). Biological foundations of language. New York, NY: John Wiley & Sons.
LeVine, R. A., Dixon, S., LeVine, S., Richman, A., Leiderman, P. H., Keefer, C. H., & Brazelton, T. B. (1994). Child care and culture: Lessons from Africa. New York: Cambridge University Press.
Lewis, M., & Brooks, J. (1978). Self-knowledge and emotional development. In M. Lewis & L. A. Rosenblum (Eds.), Genesis of behavior (Vol. 1, pp. 205-226). New York: Plenum Press.
Lewis, T. L., Maurer, D., & Milewski, A. (1979). The development of nasal detection in young infants. Investigative Ophthalmology and Visual Science Supplement, 19, 271.
Li, Y., & Ding, Y. (2017). Human visual development. In Y. Liu., & W. Chen (Eds.), Pediatric lens diseases (pp. 11-20). Singapore: Springer.
Los Angles County Department of Public Health. (2019). Breastfeeding vs. formula feeding. Retrieved from publichealth.lacounty.gov/LAmoms/lessons/Breastfeeding/6_BreastfeedingvsFormulaFeeding.pdf
Main, M., & Solomon, J. (1990). Procedures for identifying infants as disorganized/disoriented during the Ainsworth Strange Situation. In M. T. Greenberg, D. Cicchetti, & E. M. Cummings (Eds.), Attachment inthe Preschool Years (pp.121– 160).Chicago,IL: UniversityofChicagoPress.
Mandel, D. R., Jusczyk, P. W., & Pisoni, D. B. (1995). Infants’ recognition of the sound patterns of their own names. Psychological Science, 6(5), 314–317.
Mayberry, R. I., Lock, E., & Kazmi, H. (2002). Development: Linguistic ability and early language exposure. Nature, 417(6884), 38.
Moeller, M.P., & Tomblin, J.B. (2015). An introduction to the outcomes of children with hearing loss study. Ear and Hearing, 36 Suppl (0-1), 4S-13S
Morelli, G., Rogoff, B., Oppenheim, D., & Goldsmith, D. (1992). Cultural variations in infants’ sleeping arrangements: Questions of independence. Developmental Psychology, 28, 604-613.
Nelson, E. A., Schiefenhoevel, W., & Haimerl, F. (2000). Child care practices in nonindustrialized societies. Pediatrics, 105, e75.
O’Connor, T. G., Marvin, R. S., Rotter, M., Olrich, J. T., Britner, P. A., & The English and Romanian Adoptees Study Team. (2003). Child-parent attachment following early institutional deprivation. Development and Psychopathology, 15, 19- 38.
Papousek, M. (2007). Communication in early infancy: An arena of intersubjective learning. Infant Behavior and Development, 30, 258-266.
Pearson Education. (2016). Bayley Scales of Infant Development, Third Edition. New York: Pearson. Retrieved from http://www.pearsonclinical.com/childhood/products/100000123/bayley-scales-of-infant-and-toddler-development- third-edition-bayley-iii.html#tab-details
Penfield, W., & Roberts, L. (1959). Speech and brain mechanisms. Princeton, NJ: Princeton University Press.
Petitto, L. A., & Marentette, P. F. (1991). Babbling in the manual mode: Evidence for the ontogeny of language. Science, 251(5000), 1493–1496.
Phelps, B. J. (2005). Habituation. In N. J. Salkind (Ed.), Encyclopedia of human development (pp. 597-600). New York: Sage Publications.
Piaget, J. (1954). The construction of reality in the child. New York: Basic Books.
Pickens, J., Field, T., Nawrocki, T., Martinez, A., Soutullo, D., & Gonzalez, J. (1994). Full-term and preterm infants’ perception of face-voice synchrony. Infant Behavior and Development, 17(4), 447-455.
Porter, R. H., Makin, J. W., Davis, L. M., Christensen, K. (1992). Responsiveness of infants to olfactory cues from lactating females. Infant Behavior and Development, 15, 85-93.
Redondo, C. M., Gago-Dominguez, M., Ponte, S. M., Castelo, M. E., Jiang, X., Garcia, A.A… Castelao, J. E. (2012). Breast feeding, parity and breast cancer subtypes in a Spanish cohort. PLoS One, 7(7): e40543 doi: 10.1371/journal.pone.00040543
Richardson, B. D. (1980). Malnutrition and nutritional anthropometry. Journal of Tropical Pediatrics, 26(3), 80-84. Rothbart, M. K., & Bates, J. E. (2006). Temperament. In N. Eisenberg (Ed.). Handbook of child psychology: Vol. 3: Social, emotional, and personality development (6th ed., pp. 99-116). Hoboken, NJ: Wiley.
Rothbart, M. K., Posner, M. I. & Kieras, J. (2006). Temperament, attention, and the development of self-regulation. In M. McCartney & D. Phillips (Eds.) Blackwell handbook of early childhood development (pp. 3338-357). Malden, MA: Blackwell.
Rothbaum, F., Weisz, J., Pott, M., Miyake, K., & Morelli, G. (2010). Attachment and culture: Security in the United States and Japan. American Psychologist, 55, 1093-1104.
Rovee-Collier, C. (1987). Learning and memory in infancy. In J. D. Osofsky (Ed.), Handbook of infant development, (2nd, ed., pp. 98-148). New York: Wiley.
Rovee-Collier, C. (1990). The “memory system” of prelinguistic infants. Annuals of the New York Academy of Sciences, 608, 517-542. doi: 10.1111/j.1749-66231990.tb48908.
Rovee-Collier, C., & Hayne, H. (1987). Reactivation of infant memory: Implications for cognitive development. In H. W. Reese (Ed.), Advances in child development and behavior. (Vol. 20, pp. 185-238). London, UK: Academic Press.
Rymer, R. (1993). Genie: A scientific tragedy. Harmondsworth: Penguin.
Salkind, N. J. (2005). Encyclopedia of human development. New York: Sage Publications.
Schwarz, E. B., Brown, J. S., Creasman, J. M. Stuebe, A., McClure, C. K., Van Den Eeden, S. K., & Thom, D. (2010). Lactation and maternal risk of type-2 diabetes: A population-based study. American Journal of Medicine, 123, 863.e1-863.e6. doi: 10.1016/j.amjmed.2010.03.016.
Seifer, R., Schiller, M., Sameroff, A., Resnick, S., & Riordan, K. (1996). Attachment, maternal sensitivity, and infant temperament during the first year of life. Developmental Psychology, 32, 12-25.
Sen, M. G., Yonas, A., & Knill, D. C. (2001). Development of infants’ sensitivity to surface contour information for spatial layout. Perception, 30, 167-176.
Senghas, R. J., Senghas, A., & Pyers, J. E. (2005). The emergence of Nicaraguan Sign Language: Questions of development, acquisition, and evolution. In S. T. Parker, J. Langer, & C. Milbrath (Eds.), Biology and knowledge revisited: From neurogenesis to psychogenesis (pp. 287–306). Mahwah, NJ: Lawrence Erlbaum Associates.
Shaffer, D. R. (1985). Developmental psychology: Theory, research, and applications. Belmont, CA: Wadsworth, Inc. Skinner, B. F. (1953). Science and human behavior. NY: Free Press.
Sorce, J. F., Emde, J. J., Campos, J. J., & Klinnert, M. D. (1985). Maternal emotional signaling: Its effect on the visual cliff behavior of 1-year-olds. Developmental Psychology, 21, 195–200.
Spelke, E. S., & Cortelyou, A. (1981). Perceptual aspects of social knowing: Looking and listening in infancy. Infant social cognition, 61-84.
Springer, S. P. & Deutsch, G. (1993). Left brain, right brain (4th ed.). New York: W. H. Freeman.
Stika, C.J., Eisenberg, L.S., Johnson, K.C. Henning, S.C., Colson, B.G., Ganguly, D.H., & DesJardin, J.L. (2015). Developmental outcomes of early-identified children who are hard of hearing at 12 to 18 months of age. Early Human Development, 9(1), 47-55.
Stork, F. & Widdowson, J. (1974). Learning about Linguistics. London: Hutchinson.
Thomas, R. M. (1979). Comparing theories of child development. Santa Barbara, CA: Wadsworth.
Thompson, R. A. (2006). The development of the person. In W. Damon & R. Lerner (Eds.), Handbook of child psychology (6th Ed.). New York: Wiley.
Thompson, R. A., & Goodvin, R. (2007). Taming the tempest in the teapot. In C. A. Brownell & C. B. Kopp (Eds.). Socioemotional development in the toddler years: Transitions and transformations (pp. 320-342). New York: Guilford.
Thompson, R. A., Winer, A. C., & Goodvin, R. (2010). The individual child: Temperament, emotion, self, and personality. In M. Bornstein & M. E. Lamb (Eds.), Developmental science: An advanced textbook (6th ed., pp. 423–464). New York, NY: Psychology Press/Taylor & Francis.
Titus-Ernstoff, L., Rees, J. R., Terry, K. L., & Cramer, D. W. (2010). Breast-feeding the last-born child and risk of ovarian cancer. Cancer Causes Control, 21(2), 201-207. doi: 10.1007/s10552-009-9450-8
Tomblin, J. B., Harrison, M., Ambrose, S. E., Walker, E. A., Oleson, J. J., & Moeller, M. P. (2015). Language outcomes in young children with mild to severe hearing loss. Ear and hearing, 36 Suppl 1(0 1), 76S–91S.
United Nations Children’s Fund. (2015). Levels and trends in child mortality: Report 2015. United Nations Children’s Fund. New York: NY.
United States Department of Health and Human Services, Office of Women’s Health. (2011). Your guide to breast feeding. Washington D.C.
United States National Library of Medicine. (2016). Circumcision. Retrieved from https://medlineplus.gov/circumcision.html
Van den Boom, D. C. (1994). The influence of temperament and mothering on attachment and exploration: An experimental manipulation of sensitive responsiveness among lower-class mothers with irritable infants. Child Development, 65, 1457–1477.
Van Ijzendoorn, M. H., & Sagi, A. (1999). Cross-cultural patterns of attachment. In J. Cassidy & P. R. Shaver (Eds.), Handbook of attachment: Theory, research, and clinical applications (pp. 713-734). New York: Guilford.
Webb, S. J., Monk, C. S., & Nelson, C. A. (2001). Mechanisms of postnatal neurobiological development: Implications for human development. Developmental Neuropsychology, 19, 147-171.
Weekes-Shackelford, V. A. & Shackelford, T. K. (2005). Sudden Infant Death Syndrome (SIDS). In N. J. Salkind (Ed.), Encyclopedia of human development (pp. 1238-1239). New York: Sage Publications.
Werker, J. F., Pegg, J. E., & McLeod, P. J. (1994). A cross-language investigation of infant preference for infant-directed communication. Infant Behavior and Development, 17, 323-333.
Werker, J. F., & Tees, R. C. (2002). Cross-language speech perception: Evidence for perceptual reorganization during the first year of life. Infant Behavior and Development, 25, 121-133.
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/06%3A_Development_in_Infancy_and_Toddlerhood/6.03%3A_Chapter_12-_Psychosocial_Development_in_Infancy_and_Toddlerhood.txt |
Chapter 13 Learning Objectives
• Summarize the overall physical growth
• Describe the changes in brain maturation
• Describe the changes in sleep
• Summarize the changes in gross and motor skills
• Describe when a child is ready for toilet training
• Describe sexual development
• Identify nutritional concerns
Overall Physical Growth
the ages of 4 and 8 need 1,200 to 2,000 calories (Mayo Clinic, 2016a).
Brain Maturation
Brain weight: The brain is about 75 percent of its adult weight by three years of age. By age 6, it is at 95 percent of its adult weight (Lenroot & Giedd, 2006). Myelination and the development of dendrites continue to occur in the cortex and as it does, we see a corresponding change in what the child is capable of doing. Greater development in the prefrontal cortex, the area of the brain behind the forehead that helps us to think, strategize, and control attention and emotion, makes it increasingly possible to inhibit emotional outbursts and understand how to play games.
Growth in the Hemispheres and Corpus Callosum: Between ages 3 and 6, the left hemisphere of the brain grows dramatically. This side of the brain or hemisphere is typically involved in language skills. The right hemisphere continues to grow throughout early childhood and is involved in tasks that require spatial skills, such as recognizing shapes and patterns. The corpus callosum, a dense band of fibers that connects the two hemispheres of the brain, contains approximately 200 million nerve fibers that connect the hemispheres (Kolb & Whishaw, 2011). The corpus callosum is illustrated in Figure 4.2.
Figure 4.2
The corpus callosum is located a couple of inches below the longitudinal fissure, which runs the length of the brain and separates the two cerebral hemispheres (Garrett, 2015). Because the two hemispheres carry out different functions, they communicate with each other and integrate their activities through the corpus callosum. Additionally, because incoming information is directed toward one hemisphere, such as visual information from the left eye being directed to the right hemisphere, the corpus callosum shares this information with the other hemisphere.
Motor Skill Development
highlights some of the changes in motor skills during early childhood between 2 and 5 years of age. The development of greater coordination of muscle groups and finer precision can be seen during this time period. Thus, average 2-year-olds may be able to run with slightly better coordination than they managed as a toddler, yet they would have difficulty peddling a tricycle, something the typical 3-year-old can do. We see similar changes in fine motor skills with 4-year-olds who no longer struggle to put on their clothes, something they may have had problems with two years earlier. Motor skills continue to develop into middle childhood, but for those in early childhood, a play that deliberately involves these skills is emphasized.
Children’s Art: Children’s art highlights many developmental changes. Kellogg (1969) noted that children’s drawings underwent several transformations. Starting with about 20 different types of scribbles at age 2, children move on to experimenting with the placement of scribbles on the page. By age 3 they are using the basic structure of scribbles to create shapes and are beginning to combine these shapes to create more complex images. By 4 or 5 children are creating images that are more recognizable representations of the world. These changes are a function of improvement in motor skills, perceptual development, and cognitive understanding of the world (Cote & Golbeck, 2007).
expressions, while those from non-Western rural contexts (i.e., rural areas of Cameroon and India) depicted themselves as smaller, with less facial details and a more neutral emotional expression. The authors suggest that cultural norms of non-Western traditionally rural cultures, which emphasize the social group rather than the individual, maybe one of the factors for the smaller size of the figures compared to the larger figures from children in the Western cultures which emphasize the individual.
Table 4.1
Toilet Training
• Does your child seem interested in the potty chair or toilet, or in wearing underwear?
• Can your child understand and follow basic directions?
• Does your child complain about wet or dirty diapers?
• Does your child tell you through words, facial expressions or posture when he or she needs to go?
• Does your child stay dry for periods of two hours or longer during the day?
• Can your child pull down his or her pants and pull them up again?
• Can your child sit on and rise from a potty chair? (p. 1)
Some children experience elimination disorders that may require intervention by the child’s pediatrician or a trained mental health practitioner. Elimination disorders include enuresis, or the repeated voiding of urine into bed or clothes (involuntary or intentional) and encopresis, the repeated passage of feces into inappropriate places (involuntary or intentional) (American Psychiatric Association, 2013). The prevalence of enuresis is 5%-10% for 5-year-olds, 3%-5% for 10-year-olds and approximately 1% for those 15 years of age or older. Around 1% of 5-year- olds have encopresis, and it is more common in males than females.
Figure 4.6
Sexual Development in Early Childhood
Infancy: Boys and girls are capable of erections and vaginal lubrication even before birth (Martinson, 1981). Arousal can signal overall physical contentment and stimulation that accompanies feeding or warmth. Infants begin to explore their bodies and touch their genitals as soon as they have sufficient motor skills. This stimulation is for comfort or to relieve tension rather than to reach orgasm (Carroll, 2007).
Early Childhood: Self-stimulation is common in early childhood for both boys and girls. Curiosity about the body and about others’ bodies is a natural part of early childhood as well. As children grow, they are more likely to show their genitals to siblings or peers, and to take off their clothes and touch each other (Okami, Olmstead, & Abramson, 1997). Masturbation is common for both boys and girls. Boys are often shown by other boys how to masturbate, but girls tend to find out accidentally. Additionally, boys masturbate more often and touch themselves more openly than do girls (Schwartz, 1999).
Nutritional Concerns
vegetables. Consider the following advice (See Box 4.1) about establishing eating patterns for years to come (Rice, 1997). Notice that keeping mealtime pleasant, providing sound nutrition and not engaging in power struggles over food are the main goals:
Tips for Establishing Healthy Eating Patterns
• Recognize that appetite varies. Children may eat well at one meal and have no appetite at another. Rather than seeing this as a problem, it may help to realize that appetites do vary. Continue to provide good nutrition, but do not worry excessively if the child does not eat at a particular meal.
• Keep it pleasant. This tip is designed to help caregivers create a positive atmosphere during mealtime. Mealtimes should not be the time for arguments or expressing tensions. You do not want the child to have painful memories of mealtimes together or have nervous stomachs and problems eating and digesting food due to stress.
• No short-order chefs. While it is fine to prepare foods that children enjoy, preparing a different meal for each child or family member sets up an unrealistic expectation from others. Children probably do best when they are hungry, and a meal is ready. Limiting snacks rather than allowing children to “graze” can help create an appetite for what is being served.
• Limit choices. If you give your young child choices, make sure that you give them one or two specific choices rather than asking “What would you like for lunch?” If given an open choice, children may change their minds or ask for something that is not available or appropriate.
• Serve balanced meals. This tip encourages caregivers to serve balanced meals. A box of macaroni and cheese is not a balanced meal. Meals prepared at home tend to have better nutritional value than fast food or frozen dinners. Prepared foods tend to be higher in fat and sugar content, as these ingredients enhance taste and profit margin because fresh food is often costlier and less profitable. However, preparing fresh food at home is not costly. It does, however, require more activity. Preparing meals and including the children in kitchen chores can provide a fun and memorable experience.
• Do not bribe. Bribing a child to eat vegetables by promising desert is not a good idea. The child will likely find a way to get the desert without eating the vegetables (by whining or fidgeting, perhaps, until the caregiver gives in). In addition, bribery teaches the child that some foods are better than others. Children tend to naturally enjoy a variety of foods until they are taught that some are considered less desirable than others. Most important is not to force your child to eat or fight overeating food.
References
Abuhatoum, S., & Howe, N. (2013). Power in sibling conflict during early and middle childhood. Social Development, 22, 738- 754.
Al-Haddad, B., Jacobsson, B., Chabra, S., Modzelewska, D., Olson, E……. Sengpiel, V. (2019). Long-term risk of neuropsychiatric disease after exposure to infection in utero. JAMA Psychiatry, 76(6), 594-602.
American Academy of Pediatrics. (2015). Gender identity development in children. Retrieved from https://www.healthychildren.org/English/ages-stages/ gradeschool/Pages/Gender-Identity-and-Gender-Confusion-In- Children.aspx
American Academy of Pediatrics. (2016). Media and young minds. Retrieved from https://pediatrics.aappublications.org/content/138/5/e20162591
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders, 5th edition (DSM-5). Washington, DC: Author.
American Psychological Association. (2019). Immigration. Retrieved from https://www.apa.org/advocacy/immigration
Armor, D. J. (2015). Head Start or false start. USA Today Magazine. Retrieved from https://www.questia.com/magazine/1G1-429736352/head-start-or-false-start
Autism Genome Project Consortium. (2007). Mapping autism risk loci using genetic linkage and chromosomal rearrangements. Nature Genetics, 39, 319–328.
Baio, J., Wiggins, L., Christensen, D., Maenner, M., ……. Dowling, N. (2018). Prevalence of autism spectrum disorder among children aged 8 years-autism and developmental disabilities monitoring network, 11 sites, United States, 2014. MMWR Surveillance Summary, 67(No. SS-6), 1-23. doi : dx.doi.org/a0.15585/mmwr.ss6706a1External
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.
Barshay, J. (2015). Report: Scant scientific evidence for Head Start programs’ effectiveness. U.S. News and World Report. Retrieved from www.usnews.com/news/articles/ 2015/08/03/report-scant-scientific-evidence-for-head-start- programs-effectiveness
Baumrind, D. (1971). Current patterns of parental authority. Developmental Psychology Monograph, 4(1), part 2.
Baumrind, D. (2013). Authoritative parenting revisited: History and current status. In R. E. Larzelere, A. Sheffield, & A. W. Harrist (Eds.). Authoritative parenting: Synthesizing nurturance and discipline for optimal child development (pp. 11- 34). Washington, DC: American Psychological Association.
Bem, S. L. (1981). Gender schema theory: A cognitive account of sex typing. Psychological Review, 88, 354-364. Berk, L. E. (2007). Development through the life span (4th ed.). Boston: Allyn and Bacon.
Berwid, O., Curko-Kera, E. A., Marks, D. J., & Halperin, J. M. (2005). Sustained attention and response inhibition in young children at risk for attention deficit hyperactivity disorder. Journal of Child Psychology and Psychiatry, 46(11), 1219- 1229.
Bialystok, E. (2011). Coordination of executive functions in monolingual and bilingual children. Journal of Experimental Child Psychology, 110, 461–468.
Bialystok, E., Martin, M.M., & Viswanathan, M. (2005). Bilingualism across the lifespan: The rise and fall of inhibitory control. International Journal of Bilingualism, 9, 103–119.
Bibok, M.B., Carpendale, J.I.M., & Muller, U. (2009). Parental scaffolding and the development of executive function. New Directions for Child and Adolescent Development, 123, 17-34.
Bigler, R. S., & Liben, L. S. (2007). Developmental intergroup theory: Exploring and reducing children’s social stereotyping and prejudice. Current Directions in Psychological Science, 16, 162-166.
Birch, S., & Bloom, P. (2003). Children are cursed: An asymmetric bias in mental-state attribution. Psychological Science, 14(3), 283-286.
Blackless, M., Charuvastra, A., Derryck, A., Fausto-Sterling, A., Lauzanne, K., & Lee, E. (2000). How sexually dimorphic are we? Review and synthesis. American Journal of Human Biology, 12, 151-166.
Bonifacci, P., Giombini, L., Beloocchi, S., & Conteno, S. (2011). Speed of processing, anticipation, inhibition and working memory in bilinguals. Developmental Science, 14, 256–269.
Boyse, K. & Fitgerald, K. (2010). Toilet training. University of Michigan Health System. Retrieved from http://www.med.umich.edu/yourchild/topics/toilet.htm
Brody, G. H., Stoneman, Z., & McCoy, J. K. (1994). Forecasting sibling relationships in early adolescence from child temperament and family processes in middle childhood. Child development, 65, 771-784.
Brown, G.L., Mangelsdork, S.C., Agathen, J.M., & Ho, M. (2008). Young children’s psychological selves: Convergence with maternal reports of child personality. Social Development, 17, 161-182.
Bureau of Labor Statistics. (2019). Employment characteristics of families-2018. Retrieved from https://www.bls.gov/news.release/pdf/famee.pdf
Bussey, K., & Bandura, A. (1999). Social cognitive theory of gender development and differentiation. Psychological Review, 106(4), 676-713.
Byrd, R. (2002). Report to the legislature on the principal findings from the epidemiology of autism in California: A comprehensive pilot study. Retrieved from www.dds.ca.gov/Autism/MindReport.cfm
Camarota, S. A., & Zeigler, K. (2015). One in five U. S. residents speaks foreign language at home. Retrieved from https://cis.org/sites/default/files/camarota-language-15.pdf
Carroll, J. L. (2007). Sexuality now: Embracing diversity (2nd ed.). Belmont, CA: Thomson.
Centers for Disease Control and Prevention. (2000). 2000 CDC Growth Charts for the United States: Methods and Development. Retrieved from http://www.cdc.gov/nchs/data/series/sr_11/sr11_246.pdf
Centers for Disease Control and Prevention. (2012). Prevalence of autism spectrum disorders, autism and developmental disabilities monitoring network, 14 sites, United States, 2008. Morbidity and Mortality Weekly Report: Surveillance Summaries, 61(3), 1–19. Retrieved from http://www.cdc.gov/mmwr/pdf/ss/ss6103.pdf
Centers for Disease Control and Prevention. (2015). Nutrition and health of young people. Retrieved from http://www.cdc.gov/healthyschools/nutrition/facts.htm
Centers for Disease Control and Prevention. (2019). About adverse childhood experiences. Retrived from www.cdc.gov/violenceprevention/childabuseandneglect/acestudy/aboutace.html
Chang, A., Sandhofer, C., & Brown, C. S. (2011). Gender biases in early number exposure to preschool-aged children. Journal of Language and Social Psychology, 30(4), 440-450.
Chiong, C., & Shuler, C. (2010). Learning: Is there an app for that? Investigations of young children’s usage and learning with mobile devices and apps. New York: The Joan Ganz Cooney Center at Sesame Workshop. Retrieved from: https://clalliance.org/wp-content/uploads/files/learningapps_final_110410.pdf
Christakis, D.A. (2009). The effects of infant media usage: What do we know and what should we learn? Acta Paediatrica, 98, 8–16.
Clark, J. (1994). Motor development. In V. S. Ramachandran (Ed.), Encyclopedia of human behavior (pp. 245–255). San Diego: Academic Press.
Colwell, M.J., & Lindsey, E.W. (2003). Teacher-child interactions and preschool children’s perceptions of self and peers. Early Childhood Development & Care, 173, 249-258.
Coté, C. A., & Golbeck, S. (2007). Preschoolers’ feature placement on own and others’ person drawings. International Journal of Early Years Education, 15(3), 231-243.
Courage, M.L., Murphy, A.N., & Goulding, S. (2010). When the television is on: The impact of infant-directed video on 6- and 18-month-olds’ attention during toy play and on parent-infant interaction. Infant Behavior and Development, 33, 176- 188.
Crain, W. (2005). Theories of development concepts and applications (5th ed.). New Jersey: Pearson.
De Houwer, A. (2007). Parental language input patterns and children’s bilingual use. Applied Psycholinguistics, 28, 411–422
DeStefano, F., Price, C. S., & Weintraub, E. S. (2013). Increasing exposures to antibody-stimulating proteins and polysaccharides in vaccines is not associated with risk of autism. The Journal of Pediatrics, 163, 561–567.
Dougherty, D.M., Marsh, D.M., Mathias, C.W., & Swann, A.C. (2005). The conceptualization of impulsivity: Bipolar disorder and substance abuse. Psychiatric Times, 22(8), 32-35.
Dunn, J., & Munn, P. (1987). Development of justification in disputes with mother and sibling. Developmental Psychology, 23, 791-798.
Dyer, S., & Moneta, G. B. (2006). Frequency of parallel, associative, and cooperative play in British children of different socio- economic status. Social Behavior and Personality, 34(5), 587-592.
Economist Data Team. (2017). Parents now spend twice as much time with their children as 50 years ago. Retrieved from https://www.economist.com/graphic-detail/2017/11/27/parents-now-spend-twice-as-much-time-with-their-children-as- 50-years-ago
Epley, N., Morewedge, C. K., & Keysar, B. (2004). Perspective taking in children and adults: Equivalent egocentrism but differential correction. Journal of Experimental Social Psychology, 40, 760–768.
Erikson, E. (1982). The life cycle completed. NY: Norton & Company.
Evans, D. W., Gray, F. L., & Leckman, J. F. (1999). The rituals, fears and phobias of young children: Insights from development, psychopathology and neurobiology. Child Psychiatry and Human Development, 29(4), 261-276. doi:10.1023/A:1021392931450
Evans, D. W. & Leckman, J. F. (2015) Origins of obsessive-compulsive disorder: Developmental and evolutionary perspectives. In D. Cicchetti and D. J. Cohen (Eds.), Developmental psychopathology (2nd edition). Hoboken, NJ: Wiley & Sons. doi: 10.1002/9780470939406.ch10
Fay-Stammbach, T., Hawes, D. J., & Meredith, P. (2014). Parenting influences on executive function in early childhood: A review. Child Development Perspectives, 8(4), 258-264.
Felitti, V. J., Anda, R.F., Nordenberg, D., Williamson, D. F., Spitz, A., Edwards, V., Koss, M. P., & Marks, J. S. (1998).
Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The Adverse Childhood Experiences (ACE) Study. American Journal of Preventive Medicine, 14(4), 245-258. doi:10.1016/S0749-3797(98)00017-8
Finkelhorn, D., Hotaling, G., Lewis, I. A., & Smith, C. (1990). Sexual abuse in a national survey of adult men and women: Prevalence, characteristics, and risk factors. Child Abuse and Neglect, 14(1), 19-28.
Frank, G., Plunkett, S. W., & Otten, M. P. (2010). Perceived parenting, self-esteem, and general self-efficacy of Iranian American adolescents. Journal of Child & Family Studies, 19, 738-746.
Galotti, K. M. (2018). Cognitive psychology: In and out of the laboratory (6th Ed.). Thousand Oaks, CA: Sage. Garrett, B. (2015). Brain and behavior: An introduction to biological psychology (4th Ed.). Thousand Oaks, CA: Sage.
Gauthier, J., Siddiqui, T. J., Huashan, P., Yokomaku, D., Hamdan, F. F., Champagne, N., . . . Rouleau, G.A. (2011). Truncating mutations in NRXN2 and NRXN1 in autism spectrum disorders and schizophrenia. Human Genetics, 130, 563–573.
Gecas, V., & Seff, M. (1991). Families and adolescents. In A. Booth (Ed.), Contemporary families: Looking forward, looking back. Minneapolis, MN: National Council on Family Relations.
Gentile, D.A., & Walsh, D.A. (2002). A normative study of family media habits. Applied Developmental Psychology, 23, 157- 178.
Gernhardt, A., Rubeling, H., & Keller, H. (2015). Cultural perspectives on children’s tadpole drawings: At the interface between representation and production. Frontiers in Psychology, 6, Article 812. doi: 0.3389/fpsyg.2015.00812.
Gershoff, E. T. (2008). Report on physical punishment in the United States: What research tell us about its effects on children. Columbus, OH: Center for Effective Discipline.
Glass, E., Sachse, S., & von Suchodoletz, W. (2008). Development of auditory sensory memory from 2 to 6 years: An MMN study. Journal of Neural Transmission, 115(8), 1221-1229.doi:10.1007/s00702-008-0088-6
Gleason, T. R. (2002). Social provisions of real and imaginary relationships in early childhood. Developmental Psychology, 38, 979-992.
Gleason, T. R., & Hohmann, L. M. (2006). Concepts of real and imaginary friendships in early childhood. Social Development, 15, 128-144.
Gleason, T. R., Sebanc, A. M., & Hartup, W. W. (2000). Imaginary companions of preschool children. Developmental Psychology, 36(4), 419-428.
Gomes, G. Sussman, E., Ritter, W., Kurtzberg, D., Vaughan, H. D. Jr., & Cowen, N. (1999). Electrophysiological evidence of development changes in the duration of auditory sensory memory. Developmental Psychology, 35, 294-302.
Goodvin, R., Meyer, S. Thompson, R.A., & Hayes, R. (2008). Self-understanding in early childhood: Associations with child attachment security and maternal negative affect. Attachment & Human Development, 10(4), 433-450.
Gopnik, A., & Wellman, H.M. (2012). Reconstructing constructivism: Causal models, Bayesian learning mechanisms, and the theory theory. Psychological Bulletin, 138(6), 1085-1108.
Guy, J., Rogers, M., & Cornish, K. (2013). Age-related changes in visual and auditory sustained attention in preschool-aged children. Child Neuropsychology, 19(6), 601–614. Retrieved from http://dx.doi.org/10.1080/09297049.2012.710321
Hammer C. S., Hoff, E., Uchikosh1, Y., Gillanders, C., Castro, D., & Sandilos, L. E. (2014). The language literacy development of young dual language learners: A critical review. Early Child Research Quarterly, 29(4), 715-733.
Harter, S., & Pike, R. (1984). The pictorial scale of Perceived Competence and Social Acceptance for Young Children. Child Development, 55, 1969-1982.
Harvard University. (2019). Center on the developing child: Toxic stress. Retrieved from https://developingchild.harvard.edu/science/key-concepts/toxic-stress/
Herrmann, E., Misch, A., Hernandez-Lloreda, V., & Tomasello, M. (2015). Uniquely human self-control begins at school age. Developmental Science, 18(6), 979-993. doi:10.1111/desc.12272.
Herrmann, E., & Tomasello, M. (2015). Focusing and shifting attention in human children (homo sapiens) and chimpanzees (pan troglodytes). Journal of Comparative Psychology, 129(3), 268–274. Retrieved from dx.doi.org/10.1037/a0039384
Hoff, E. (2018). Bilingual development in children of immigrant families. Child Development Perspectives, 12(2), 80-86.
Howe, N., Rinaldi, C. M., Jennings, M., & Petrakos, H. (2002). “No! The lambs can stay out because they got cozies”: Constructive and destructive sibling conflict, pretend play, and social understanding. Child Development, 73, 1406- 1473.
Hughes, V. (2007). Mercury rising. Nature Medicine, 13, 896-897.
Imai, M., Li, L., Haryu, E., Hirsh-Pasek, K., Golinkoff, R. M., & Shigematsu, J. (2008). Novel noun and verb learning in Chinese, English, and Japanese children: Universality and language-specificity in novel noun and verb learning. Child Development, 79, 979-1000.
Jarne, P., & Auld, J. R. (2006). Animals mix it up too: The distribution of self-fertilization among hermaphroditic animals. Evolution, 60, 1816–1824.
Jones, P.R., Moore, D.R., & Amitay, S. (2015). Development of auditory selective attention: Why children struggle to hear in noisy environments. Developmental Psychology, 51(3), 353–369. Retrieved from dx.doi.org/10.1037/a0038570
Kalat, J. W. (2016). Biological Psychology (12th Ed.). Boston, MA: Cengage.
Kaushanskaya, M., Gross, M., & Buac, M. (2014). Effects of classroom bilingualism on task-shifting, verbal memory, and word learning in children. Developmental Science, 17(4), 564-583.
Kellogg, R. (1969). Handbook for Rhoda Kellogg: Child art collection. Washington D. C.: NCR/Microcard Editions.
Kemple, K.M., (1995). Shyness and self-esteem in early childhood. Journal of Humanistic Education and Development, 33(4), 173-182.
Kimmel, M. S. (2008). The gendered society (3rd ed.). Oxford: Oxford University Press.
Kinney, D. K., Barch, D. H., Chayka, B., Napoleon, S., & Munir, K. M. (2009). Environmental risk factors for autism: Do they help or cause de novo genetic mutations that contribute to the disorder? Medical Hypotheses, 74, 102–106.
Kirkorian, H.L., Choi, K., & Pempek, T.A. (2016). Toddlers’ word learning from contingent and noncontingent video on touch screens. Child Development, 87(2), 405–413.
Kirkorian, H.L., Pempek, T.A., & Murphy, L.A. (2009). The impact of background television on parent-child interaction. Child Development, 80, 1350-1359.
Knorr, C. (2017). Gender stereotypes are messing with your kid. Retrieved from https://www.commonsensemedia.org/blog/gender-stereotypes-are-messing-with-your-kid
Kohn, M. L. (1977). Class and conformity. (2nd ed.). Chicago: University of Chicago Press.
Kolb, B. & Whishaw, I. Q. (2011). An introduction to brain and behavior (3rd ed.). New York: Worth Publishers.
Kramer, L., & Gottman, J. M. (1992). Becoming a sibling: “With a little help from my friends.” Developmental Psychology, 28, 685-699.
Lenroot, R. K., & Giedd, J. N. (2006). Brain development in children and adolescents: Insights from anatomical magnetic resonance imaging. Neuroscience and Biobehavioral Reviews, 30, 718-729.
Maccoby, E., & Jacklin, C. (1987). Gender segregation in childhood. Advances in Child Development and Behavior, 20, 239-287.
MacKenzie, M. J., Nicklas, E., Waldfogel, J., & Brooks-Gunn, J. (2013). Spanking and child development across the first decade of life. Pediatrics, 132(5), e1118-e1125.
Madigan, S., Browne, D., Racine, N., Mori, C., & Tough, S. (2019). Association between screen time and children’s performance on a developmental screening test. JAMA Pediatrics, 173(3), 244-250.
Manosevitz, M., Prentice, N. M., & Wilson, F. (1973). Individual and family correlates of imaginary companions in preschool children. Developmental Psychology, 8, 72-79.
Martinson, F. M. (1981). Eroticism in infancy and childhood. In L. L. Constantine & F. M. Martinson (Eds.), Children and sex: New findings, new perspectives. (pp. 23-35). Boston: Little, Brown.
Masih, V. (1978). Imaginary play companions of children. In R. Weizman, R. Brown, P. Levinson, & P. Taylor (Eds.). Piagetian theory and the helping profession (pp. 136-144). Los Angeles: University of Southern California Press.
Mauro, J. (1991). The friend that only I can see: A longitudinal investigation of children’s imaginary companions. Dissertation, University of Oregon.
Mayo Clinic Staff. (2016a). Nutrition for kids: Guidelines for a healthy diet. Retrieved from www.mayoclinic.org/healthy- lifestyle/childrens-health/in-depth/nutrition-for-kids/art-20049335
Mayo Clinic Staff. (2016b). Potty training: How to get the job done. Retrieved from www.mayoclinic.org/healthy- lifestyle/infant-and-toddler-health/indepth/potty-training/art-20045230
McAlister, A. R., & Peterson, C. C. (2007). A longitudinal study of siblings and theory of mind development. Cognitive Development, 22, 258-270.
Meek, S. E., Lemery-Chalfant, K., Jahromi, L. D., & Valiente, C. (2013). A review of gene-environment correlations and their implications for autism: A conceptual model. Psychological Review, 120, 497–521.
Merrick, M. T., Ford, D. C., Ports, K. A., & Guinn, A. S. (2018). Prevalence of adverse childhood experiences from the 2011- 2014 Behavioral Risk Factor Surveillance System in 23 States. Early JAMA Pediatrics, 172(11), 1038-1044.
Meyers-Sutton, C. (2005). Multiple voices: An introduction ot bilingualism. Malden, MA: Blackwell Publishers.
Middlebrooks, J. S., & Audage, N. C. (2008). The effects of childhood stress on health across the lifespan. (United States, Center for Disease Control, National Center for Injury Prevention and Control). Atlanta, GA.
Mischel, W., Ayduk, O., Berman, M. G., Casey, B. J., Gotlib, I. H., Jonides, J., & … Shoda, Y. (2011). ‘Willpower’ over the life span: Decomposing self-regulation. Social Cognitive & Affective Neuroscience, 6(2), 252-256. doi:10.1093/scan/nsq081
Mischel, W., Ebbesen, E. B., & Zeiss, A. R. (1972). Cognitive and attentional mechanisms in delay of gratification. Journal of Personality and Social Psychology, 21, 204–218.
Morra, S., Gobbo, C., Marini, Z., & Sheese, R. (2008). Cognitive development: Neo-Piagetian perspectives. New York: Lawrence Erlbaum Associates.
National Association for the Education of Young Children. (2016). The 10 NAEYC program standards. Retrieved from http://families.naeyc.org/accredited-article/10-naeyc-program-standards
National Institute of Child Health and Human Development. (2006). The NICHD study of early child care (NIH Pub. No. 05- 4318). Washington, DC: Government Printing Office.
Nelson, K., & Fivush, R. (2004). The emergence of autobiographical memory: A social cultural developmental theory. Psychological Review, 111(2), 468-511.
Nelson, K., & Ross, G. (1980). The generalities and specifics of long-term memory in infants and young children. In M. Perlmutter (Ed.), Children’s memory: New directions in child development (Vol. 10, pp. 87-101). San Francisco: Jossey-Bass.
Nielsen Company. (2009). Television audience 2008-2009. Retrieved from blog.nielsen.com/nielsenwire/wp-content/uploads/2009/07/tva_2008_071709.pdf
Novella, S. (2008). The increase in autism diagnoses: Two hypotheses [Web log post]. Retrieved from http://www.sciencebasedmedicine.org/the-increase-in-autism-diagnoses-two-hypotheses/
Okami, P., Olmstead, R., & Abramson, P. R. (1997). Sexual experiences in early childhood: 18-year longitudinal data from UCLA Family Lifestyles Project. Journal of Sex Research, 34(4), 339-347.
Olson, K. R., & Gülgöz, S. (2018). Early findings from the TransYouth Project: Gender development in transgender children. Child Development Perspectives, 12(2), 93-97.
Parten, M. B. (1932). Social participation among preschool children. Journal of Abnormal and Social Psychology, 27, 243-269. Perner, J., Ruffman, T., & Leekam, S. R. (1994). Theory of mind is contagious: You catch from your sibs. Child Development, 65, 1228-1238.
Pike, A., Coldwell, J., & Dunn, J. F. (2005). Sibling relationships in early/middle childhood: Links with individual adjustment. Journal of Family Psychology, 19(4), 523-532.
Place, S., & Hoff, E. (2016). Effects and non-effects of input in bilingual environments on dual language skills in 2 1/2-year-olds. Bilingualism: Language and Cognition, 19, 1023–1041.
Porporino, M., Shore, D.I., Iarocci, G., & Burack, J.A. (2004). A developmental change in selective attention and global form perception. International Journal of Behavioral Development, 28 (4), 358–364 doi:10.1080/01650250444000063
Posner, M.I., & Rothbart, M.K. (2007). Research on attention networks as a model for the integration of psychological science. Annual Review in Psychology, 58, 1–23
Price-Williams, D.R., Gordon, W., & Ramirez, M. (1969). Skill and conservation: A study of pottery making children. Developmental Psychology, 1, 769.
Ram, A., & Ross, H. (2008). “We got to figure it out”: Information-sharing and siblings’ negotiations of conflicts of interest. Social Development, 17, 512-527.
Rice, F. P. (1997). Human development: A life-span approach. Upper Saddle River, NJ: Prentice Hall. Rideout, V.J., & Hamel E. (2006). The media family: Electronic media in the lives of infants, toddlers, preschoolers and their parents. Retrieved from www.kff.org/entmedia/upload/7500.pdf
Robinson, T.N., Wilde, M.L., & Navracruz, L.C. (2001). Effects of reducing children’s television and video game use on aggressive behavior: A randomized controlled trial. Archives of Pediatrics and Adolescent Medicine, 155, 17-23.
Rothbart, M.K., & Rueda, M.R. (2005). The development of effortful control. In U. Mayr, E. Awh, & S.W. Keele (Eds.), Developing individuality in the human brain: A festschrift honoring Michael I. Posner (pp. 167–88). Washington, DC: American Psychological Association
Ruble, D.N., Boggiano, A.K., Feldman, N.S., & Loeble, J.H. (1980). Developmental analysis of the role of social comparison in self-evaluation. Developmental Psychology, 16, 105-115.
Ruble, D. N., Martin, C., & Berenbaum, S. (2006). Gender development. In W. Damon & R. M. Lerner (Series Eds.) & N. Eisenberg (Vol. Ed.), Handbook of child psychology: Vol. 3. Social, emotional, and personality development (6th ed., pp. 858–932). New York, NY: Wiley.
Russo, F. (2016). Debate growing about how to meet the urgent needs of transgender kids. Scientific American Mind, 27(1), 27- 35.
Ryan, C. (2013). Language use in the United States: 2011. Retrieved from https://www2.census.gov/library/publications/2013/acs/acs-22/acs-22.pdf
Save the Children. (2019). Child protection. Retrived from https://www.savethechildren.net/what-we-do/child-protection
Schmidt, M.E., Pempek, T.A., & Kirkorian, H.L. (2008). The effects of background television on the toy play behavior of very young children. Child Development, 79, 1137-1151.
Schneider, W., Kron-Sperl, V., & Hunnerkopf, M. (2009). The development of young children’s memory strategies: Evidence from the Würzburg longitudinal memory study. European Journal of Developmental Psychology, 6(1), 70-99.
Schwartz, I. M. (1999). Sexual activity prior to coitus initiation: A comparison between males and females. Archives of Sexual Behavior, 28(1), 63-69.
Shahaeian, A., Peterson, C. C., Slaughter, V., & Wellman, H. M. (2011). Culture and the sequence of steps in theory of mind development. Developmental Psychology, 47(5), 1239-1247.
Singer, D., & Singer, J. (1990). The house of make-believe. Cambridge, MA: Harvard University Press.
Society for Research in Child Development. (2018). The Science is clear: Separating families has long-term damaging psychological and health consequences for children, families, and communities. Retrieved from https://www.srcd.org/policy-media/statements-evidence
Spears Brown, C., & Jewell, J. A. (2018). Gender. Retrieved from https://nobaproject.com/modules/gender
Steele, B.F. (1986). Notes on the lasting effects of early child abuse throughout the life cycle. Child Abuse & Neglect 10(3), 283-291.
Tamana, S.K., Ezeugwu, E., Chikuma, J., Lefebvre, D.L., Azad, M.B., Moraes, T.J.,… & Mandhane, P. J. (2019). Screen-time is associated with inattention problems in preschoolers: Results from the CHILD birth cohort study. PLOS ONE, 14(4), e0213995. Retrieved from https://journals.plos.org/plosone/ar...l.pone.0213995
Thomas, R. M. (1979). Comparing theories of child development. Santa Barbara, CA: Wadsworth.
Traverso, L., Viterbori, P., & Usai, M. C. (2015). Improving executive function in childhood: Evaluation of a training intervention for 5-year-old children. Frontiers in Psychology, 6, 1-14. doi:10.3389/fpsyg.2015.00525
United Nations. (2014). Committee on the rights of the child. Retrieved from http://tbinternet.ohchr.org/Treaties/CRC/Shared%20Documents/VAT/CRC_C_VAT_CO_2_16302_E.pdf
United States Department of Health and Human Services. (2019). Child Maltreatment 2017. Retrieved from https://www.acf.hhs.gov/cb/resource/child-maltreatment-2017
United States Department of Health and Human Services. (2015). Head Start program facts fiscal year 2013. Retrieved from eclkc.ohs.acf.hhs.gov/hslc/data/factsheets/docs/hs-program-fact-sheet-2013.pdf
Valente, S. M. (2005). Sexual abuse of boys. Journal of Child and Adolescent Psychiatric Nursing, 18, 10–16. doi:10.1111/j.1744-6171.2005.00005.x
Wellman, H.M., Cross, D., & Watson, J. (2001). Meta-analysis of theory of mind development: The truth about false belief. Child Development, 72(3), 655-684.
Wellman, H. M., Fang, F., Liu, D., Zhu, L, & Liu, L. (2006). Scaling theory of mind understandings in Chinese children. Psychological Science, 17, 1075-1081.
White House Press Secretary. (2014). Fact Sheet: Invest in US: The White House Summit on Early Childhood Education. Retrieved from https://www.whitehouse.gov/the-press-office/2014/12/10/fact-sheet-invest-us-white-house-summit-early-childhood-education
Wimmer, H., & Perner, J. (1983). Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children’s understanding of deception. Cognition, 13, 103–128.
Wing, L., Gould, J., & Gillberg, C. (2011). Autism spectrum disorders in the DSM-5: Better or worse than the DSM IV? Research in Developmental Disabilities, 32, 768–773.
Wu, X., Tao, S., Rutayisirel, E., Chen, Y., Huang, K., & Tao, F. (2017). The relationship between screen time, nighttime sleep duration, and behavioral problems in preschool children in China. European Child and Adolescent Psychiatry, 26, 541– 548.
Yoo, J., & Kaushanskaya, M. (2012). Phonological memory in bilinguals and monolinguals. Memory & Cognition, 40, 1314– 1330.
Zachry, A. (2013). 6 Types of Preschool Programs. Retrieved from www.parents.com/toddlers-preschoolers/starting – preschool/preparing/types-of-preschool-programs/
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/07%3A_Development_in_Early_Childhood/7.01%3A_Chapter_13-_Physical_Development_in_Early_Childhood.txt |
Chapter 14 Learning Objectives
• Describe Piaget’s preoperational stage and the characteristics of preoperational thought
• Summarize the challenges to Piaget’s theory
• Describe Vygotsky’s theory of cognitive development
• Describe Information processing research on attention and memory
• Describe the views of the neo-Piagetians
• Describe theory-theory and the development of theory of mind
• Describe the developmental changes in language
• Describe the various types of early childhood education
• Describe the characteristics of autism
Piaget’s Preoperational Stage
Pretend Play: Pretending is a favorite activity at this time. A toy has qualities beyond the way it was designed to function and can now be used to stand for a character or object unlike anything originally intended. A teddy bear, for example, can be a baby or the queen of a faraway land. Piaget believed that children’s pretend play helped children solidify new schemata they were developing cognitively. This play, then, reflected changes in their conceptions or thoughts. However, children also learn as they pretend and experiment. Their play does not simply represent what they have learned (Berk, 2007).
Egocentrism: Egocentrism in early childhood refers to the tendency of young children not to be able to take the perspective of others, and instead the child thinks that everyone sees, thinks, and feels just as they do. Egocentric children are not able to infer the perspective of other people and instead attribute their own perspective to situations. For example, ten-year-old Keiko’s birthday is coming up, so her mom takes 3-year-old Kenny to the toy store to choose a present for his sister. He selects an Iron Man action figure for her, thinking that if he likes the toy, his sister will too.
Figure 4.9
Conservation Errors: Conservation refers to the ability to recognize that moving or rearranging matter does not change the quantity. Using Kenny and Keiko again, dad gave a slice of pizza to 10-year-old Keiko and another slice to 3-year-old Kenny. Kenny’s pizza slice was cut into five pieces, so Kenny told his sister that he got more pizza than she did. Kenny did not understand that cutting the pizza into smaller pieces did not increase the overall amount. This was because Kenny exhibited centration or focused on only one characteristic of an object to the exclusion of others. Kenny focused on the five pieces of pizza to his sister’s one piece even though the total amount was the same. Keiko was able to consider several characteristics of an object than just one. Because children have not developed this understanding of conservation, they cannot perform mental operations.
Figure 4.10
Classification Errors: Preoperational children have difficulty understanding that an object can be classified in more than one way. For example, if shown three white buttons and four black buttons and asked whether there are more black buttons or buttons, the child is likely to respond that there are more black buttons. They do not consider the general class of buttons. Because young children lack these general classes, their reasoning is typically transductive, that is, making faulty inferences from one specific example to another. For example, Piaget’s daughter Lucienne stated she had not had her nap, therefore it was not afternoon. She did not understand that the afternoon is a time period and her nap was just one of many events that occurred in the afternoon (Crain, 2005). As the child’s vocabulary improves and more schemata are developed, the ability to classify objects improves.
Animism: Animism refers to attributing life-like qualities to objects. The cup is alive, the chair that falls down and hits the child’s ankle is mean, and the toys need to stay home because they are tired. Cartoons frequently show objects that appear alive and take on lifelike qualities.
Critique of Piaget: Similar to the critique of the sensorimotor period, several psychologists have attempted to show that Piaget also underestimated the intellectual capabilities of the preoperational child. For example, children’s specific experiences can influence when they are able to conserve. Children of pottery makers in Mexican villages know that reshaping clay does not change the amount of clay at much younger ages than children who do not have similar experiences (Price-Williams, Gordon, & Ramirez, 1969). Crain (2005) indicated that preoperational children can think rationally on mathematical and scientific tasks, and they are not as egocentric as Piaget implied. Research on Theory of Mind (discussed later in the chapter) has demonstrated that children overcome egocentrism by 4 or 5 years of age, which is sooner than Piaget indicated.
Vygotsky’s Sociocultural Theory of Cognitive Development
Zone of Proximal Development and Scaffolding: Vygotsky’s best-known concept is the zone of proximal development (ZPD). Vygotsky stated that children should be taught in the ZPD, which occurs when they can almost perform a task, but not quite on their own without assistance. With the right kind of teaching, however, they can accomplish it successfully. A good teacher identifies a child’s ZPD and helps the child stretch beyond it. Then the adult (teacher) gradually withdraws support until the child can then perform the task unaided. Researchers have applied the metaphor of scaffolds (the temporary platforms on which construction workers stand) to this way of teaching. Scaffolding is the temporary support that parents or teachers give a child to do a task.
Private Speech: Do you ever talk to yourself? Why? Chances are, this occurs when you are struggling with a problem, trying to remember something or feel very emotional about a situation. Children talk to themselves too. Piaget interpreted this as egocentric speech or speech that is focused on the child and does not include another’s point of view.
something. This inner speech is not as elaborate as the speech we use when communicating with others (Vygotsky, 1962).
Contrast with Piaget: Piaget was highly critical of teacher-directed instruction believing that teachers who take control of the child’s learning place the child into a passive role (Crain, 2005). Further, teachers may present abstract ideas without the child’s true understanding, and instead, they just repeat back what they heard. Piaget believed children must be given opportunities to discover concepts on their own. As previously stated, Vygotsky did not believe children could reach a higher cognitive level without instruction from more learned individuals. Who is correct? Both theories certainly contribute to our understanding of how children learn.
Attention
Divided Attention: Young children (age 3-4) have considerable difficulties in dividing their attention between two tasks, and often perform at levels equivalent to our closest relative, the chimpanzee, but by age five they have surpassed the chimp (Hermann, Misch, Hernandez-Lloreda & Tomasello, 2015; Hermann & Tomasello, 2015). Despite these improvements, 5-year- olds continue to perform below the level of school-age children, adolescents, and adults.
Selective Attention: Children’s ability with selective attention tasks improves as they age. However, this ability is also greatly influenced by the child’s temperament (Rothbart & Rueda, 2005), the complexity of the stimulus or task (Porporino, Shore, Iarocci & Burack, 2004), and along with whether the stimuli are visual or auditory (Guy, Rogers & Cornish, 2013). Guy et al. found that children’s ability to selectively attend to visual information outpaced that of auditory stimuli. This may explain why young children are not able to hear the voice of the teacher over the cacophony of sounds in the typical preschool classroom (Jones, Moore & Amitay, 2015). Jones and his colleagues found that 4 to 7-year-olds could not filter out background noise, especially when its frequencies were close in sound to the target sound. In comparison, 8 to 11-year-old older children often performed similarly to adults.
Sustained Attention: Most measures of sustained attention typically ask children to spend several minutes focusing on one task, while waiting for an infrequent event, while there are multiple distractors for several minutes. Berwid, Curko-Kera, Marks and Halperin (2005) asked children between the ages of 3 and 7 to push a button whenever a “target” image was displayed, but they had to refrain from pushing the button when a non-target image was shown. The younger the child, the more difficulty he or she had maintaining their attention.
Figure 4.14
Children’s Understanding of the World
encounter new experiences (Gopnik & Wellman, 2012). One of the theories they start to generate in early childhood centers on the mental states; both their own and those of others.
Language Development
Vocabulary growth: A child’s vocabulary expands between the ages of two to six from about 200 words to over 10,000 words. This “vocabulary spurt” typically involves 10-20 new words per week and is accomplished through a process called fast-mapping. Words are easily learned by making connections between new words and concepts already known. The parts of speech that are learned depend on the language and what is emphasized. Children speaking verb-friendly languages, such as Chinese and Japanese, learn verbs more readily, while those speaking English tend to learn nouns more readily. However, those learning less verb-friendly languages, such as English, seem to need assistance in grammar to master the use of verbs (Imai et al., 2008).
Literal meanings: Children can repeat words and phrases after having heard them only once or twice, but they do not always understand the meaning of the words or phrases. This is especially true of expressions or figures of speech which are taken literally. For example, a classroom full of preschoolers hears the teacher say, “Wow! That was a piece of cake!” The children began asking “Cake? Where is my cake? I want cake!”
Overregularization: Children learn rules of grammar as they learn language but may apply these rules inappropriately at first. For instance, a child learns to add “ed” to the end of a word to indicate past tense. Then form a sentence such as “I goed there. I doed that.” This is typical at ages two and three. They will soon learn new words such as “went” and “did” to be used in those situations.
the adult responds, “You went there? Say, ‘I went there.’ Where did you go?” Children may be ripe for language as Chomsky suggests, but active participation in helping them learn is important for language development as well. The process of scaffolding is one in which the guide provides needed assistance to the child as a new skill is learned.
Bilingualism
new name for a previously labelled object. In contrast, bilingual children and adults show little difficulty with either task (Kaushanskaya & Marian, 2009). This finding may be explained by the experience bilinguals have in translating between languages when referring to familiar objects.
Preschool
• Positive relationships among all children and adults are promoted.
• A curriculum that supports learning and development in social, emotional, physical, language, and cognitive areas.
• Teaching approaches that are developmentally, culturally and linguistically appropriate.
• Assessment of children’s progress to provide information on learning and development.
• The health and nutrition of children are promoted, while they are protected from illness and injury.
• Teachers possess the educational qualifications, knowledge, and commitment to promote children’s learning.
• Collaborative relationships with families are established and maintained.
• Relationships with agencies and institutions in the children’s communities are established to support the program’s goals.
• The indoor and outdoor physical environments are safe and well-maintained.
• Leadership and management personnel are well qualified, effective, and maintain licensure status with the applicable state agency.
Head Start: For children who live in poverty, Head Start has been providing preschool education since 1965 when it was begun by President Lyndon Johnson as part of his war on poverty. It currently serves nearly one million children and annually costs approximately 7.5 billion dollars (United States Department of Health and Human Services, 2015). However, concerns about the effectiveness of Head Start have been ongoing since the program began.
learned more than children who did not receive preschool education.
Autism Spectrum Disorder
communication, and (c) repetitive patterns of behavior or interests. These disturbances appear early in life and cause serious impairments in functioning (APA, 2013). The child with autism spectrum disorder might exhibit deficits in social interaction by not initiating conversations with other children or turning their head away when spoken to. These children do not make eye contact with others and seem to prefer playing alone rather than with others. In a certain sense, it is almost as though these individuals live in a personal and isolated social world which others are simply not privy to or able to penetrate. Communication deficits can range from a complete lack of speech, to one-word responses (e.g., saying “Yes” or “No” when replying to questions or statements that require additional elaboration), to echoed speech (e.g., parroting what another person says, either immediately or several hours or even days later), and to difficulty maintaining a conversation because of an inability to reciprocate others’ comments. These deficits can also include problems in using and understanding nonverbal cues (e.g., facial expressions, gestures, and postures) that facilitate normal communication.
individuals with autism spectrum disorder, particularly those with better language and intellectual skills, can live and work independently as adults. However, most do not because the symptoms cause serious impairment in many aspects of life (APA, 2013).
A recent Swedish study looking at the records of over one million children born between 1973 and 2014 found that exposure to prenatal infections increased the risk for autism spectrum disorders (al-Haddad et al., 2019). Children born to mothers with an infection during pregnancy has a 79% increased risk of autism. Infections included: sepsis, flu, pneumonia, meningitis, encephalitis, an infection of the placental tissues or kidneys, or a urinary tract infection. One possible reason for the autism diagnosis is that the fetal brain is extremely vulnerable to damage from infections and inflammation. These results highlighted the importance of pregnant women receiving a flu vaccination and avoiding any infections during pregnancy.
(substances that fight infections), the investigators examined medical records to see how many immunogens children received to determine if those children who received more immunogens were at greater risk for developing autism spectrum disorder. The results of this study clearly demonstrated that the quantity of immunogens from vaccines received during the first two years of life were not at all related to the development of autism spectrum disorder.
References
Abuhatoum, S., & Howe, N. (2013). Power in sibling conflict during early and middle childhood. Social Development, 22, 738- 754.
Al-Haddad, B., Jacobsson, B., Chabra, S., Modzelewska, D., Olson, E……. Sengpiel, V. (2019). Long-term risk of neuropsychiatric disease after exposure to infection in utero. JAMA Psychiatry, 76(6), 594-602.
American Academy of Pediatrics. (2015). Gender identity development in children. Retrieved from https://www.healthychildren.org/English/ages-stages/ gradeschool/Pages/Gender-Identity-and-Gender-Confusion-In- Children.aspx
American Academy of Pediatrics. (2016). Media and young minds. Retrieved from https://pediatrics.aappublications.org/content/138/5/e20162591
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders, 5th edition (DSM-5). Washington, DC: Author.
American Psychological Association. (2019). Immigration. Retrieved from https://www.apa.org/advocacy/immigration
Armor, D. J. (2015). Head Start or false start. USA Today Magazine. Retrieved from https://www.questia.com/magazine/1G1-429736352/head-start-or-false-start
Autism Genome Project Consortium. (2007). Mapping autism risk loci using genetic linkage and chromosomal rearrangements. Nature Genetics, 39, 319–328.
Baio, J., Wiggins, L., Christensen, D., Maenner, M., ……. Dowling, N. (2018). Prevalence of autism spectrum disorder among children aged 8 years-autism and developmental disabilities monitoring network, 11 sites, United States, 2014. MMWR Surveillance Summary, 67(No. SS-6), 1-23. doi : dx.doi.org/a0.15585/mmwr.ss6706a1External
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.
Barshay, J. (2015). Report: Scant scientific evidence for Head Start programs’ effectiveness. U.S. News and World Report. Retrieved from www.usnews.com/news/articles/ 2015/08/03/report-scant-scientific-evidence-for-head-start- programs-effectiveness
Baumrind, D. (1971). Current patterns of parental authority. Developmental Psychology Monograph, 4(1), part 2.
Baumrind, D. (2013). Authoritative parenting revisited: History and current status. In R. E. Larzelere, A. Sheffield, & A. W. Harrist (Eds.). Authoritative parenting: Synthesizing nurturance and discipline for optimal child development (pp. 11- 34). Washington, DC: American Psychological Association.
Bem, S. L. (1981). Gender schema theory: A cognitive account of sex typing. Psychological Review, 88, 354-364. Berk, L. E. (2007). Development through the life span (4th ed.). Boston: Allyn and Bacon.
Berwid, O., Curko-Kera, E. A., Marks, D. J., & Halperin, J. M. (2005). Sustained attention and response inhibition in young children at risk for attention deficit hyperactivity disorder. Journal of Child Psychology and Psychiatry, 46(11), 1219- 1229.
Bialystok, E. (2011). Coordination of executive functions in monolingual and bilingual children. Journal of Experimental Child Psychology, 110, 461–468.
Bialystok, E., Martin, M.M., & Viswanathan, M. (2005). Bilingualism across the lifespan: The rise and fall of inhibitory control. International Journal of Bilingualism, 9, 103–119.
Bibok, M.B., Carpendale, J.I.M., & Muller, U. (2009). Parental scaffolding and the development of executive function. New Directions for Child and Adolescent Development, 123, 17-34.
Bigler, R. S., & Liben, L. S. (2007). Developmental intergroup theory: Exploring and reducing children’s social stereotyping and prejudice. Current Directions in Psychological Science, 16, 162-166.
Birch, S., & Bloom, P. (2003). Children are cursed: An asymmetric bias in mental-state attribution. Psychological Science, 14(3), 283-286.
Blackless, M., Charuvastra, A., Derryck, A., Fausto-Sterling, A., Lauzanne, K., & Lee, E. (2000). How sexually dimorphic are we? Review and synthesis. American Journal of Human Biology, 12, 151-166.
Bonifacci, P., Giombini, L., Beloocchi, S., & Conteno, S. (2011). Speed of processing, anticipation, inhibition and working memory in bilinguals. Developmental Science, 14, 256–269.
Boyse, K. & Fitgerald, K. (2010). Toilet training. University of Michigan Health System. Retrieved from http://www.med.umich.edu/yourchild/topics/toilet.htm
Brody, G. H., Stoneman, Z., & McCoy, J. K. (1994). Forecasting sibling relationships in early adolescence from child temperament and family processes in middle childhood. Child development, 65, 771-784.
Brown, G.L., Mangelsdork, S.C., Agathen, J.M., & Ho, M. (2008). Young children’s psychological selves: Convergence with maternal reports of child personality. Social Development, 17, 161-182.
Bureau of Labor Statistics. (2019). Employment characteristics of families-2018. Retrieved from https://www.bls.gov/news.release/pdf/famee.pdf
Bussey, K., & Bandura, A. (1999). Social cognitive theory of gender development and differentiation. Psychological Review, 106(4), 676-713.
Byrd, R. (2002). Report to the legislature on the principal findings from the epidemiology of autism in California: A comprehensive pilot study. Retrieved from www.dds.ca.gov/Autism/MindReport.cfm
Camarota, S. A., & Zeigler, K. (2015). One in five U. S. residents speaks foreign language at home. Retrieved from https://cis.org/sites/default/files/camarota-language-15.pdf
Carroll, J. L. (2007). Sexuality now: Embracing diversity (2nd ed.). Belmont, CA: Thomson.
Centers for Disease Control and Prevention. (2000). 2000 CDC Growth Charts for the United States: Methods and Development. Retrieved from http://www.cdc.gov/nchs/data/series/sr_11/sr11_246.pdf
Centers for Disease Control and Prevention. (2012). Prevalence of autism spectrum disorders, autism and developmental disabilities monitoring network, 14 sites, United States, 2008. Morbidity and Mortality Weekly Report: Surveillance Summaries, 61(3), 1–19. Retrieved from http://www.cdc.gov/mmwr/pdf/ss/ss6103.pdf
Centers for Disease Control and Prevention. (2015). Nutrition and health of young people. Retrieved from http://www.cdc.gov/healthyschools/nutrition/facts.htm
Centers for Disease Control and Prevention. (2019). About adverse childhood experiences. Retrived from www.cdc.gov/violenceprevention/childabuseandneglect/acestudy/aboutace.html
Chang, A., Sandhofer, C., & Brown, C. S. (2011). Gender biases in early number exposure to preschool-aged children. Journal of Language and Social Psychology, 30(4), 440-450.
Chiong, C., & Shuler, C. (2010). Learning: Is there an app for that? Investigations of young children’s usage and learning with mobile devices and apps. New York: The Joan Ganz Cooney Center at Sesame Workshop. Retrieved from: https://clalliance.org/wp-content/uploads/files/learningapps_final_110410.pdf
Christakis, D.A. (2009). The effects of infant media usage: What do we know and what should we learn? Acta Paediatrica, 98, 8–16.
Clark, J. (1994). Motor development. In V. S. Ramachandran (Ed.), Encyclopedia of human behavior (pp. 245–255). San Diego: Academic Press.
Colwell, M.J., & Lindsey, E.W. (2003). Teacher-child interactions and preschool children’s perceptions of self and peers. Early Childhood Development & Care, 173, 249-258.
Coté, C. A., & Golbeck, S. (2007). Preschoolers’ feature placement on own and others’ person drawings. International Journal of Early Years Education, 15(3), 231-243.
Courage, M.L., Murphy, A.N., & Goulding, S. (2010). When the television is on: The impact of infant-directed video on 6- and 18-month-olds’ attention during toy play and on parent-infant interaction. Infant Behavior and Development, 33, 176- 188.
Crain, W. (2005). Theories of development concepts and applications (5th ed.). New Jersey: Pearson.
De Houwer, A. (2007). Parental language input patterns and children’s bilingual use. Applied Psycholinguistics, 28, 411–422
DeStefano, F., Price, C. S., & Weintraub, E. S. (2013). Increasing exposures to antibody-stimulating proteins and polysaccharides in vaccines is not associated with risk of autism. The Journal of Pediatrics, 163, 561–567.
Dougherty, D.M., Marsh, D.M., Mathias, C.W., & Swann, A.C. (2005). The conceptualization of impulsivity: Bipolar disorder and substance abuse. Psychiatric Times, 22(8), 32-35.
Dunn, J., & Munn, P. (1987). Development of justification in disputes with mother and sibling. Developmental Psychology, 23, 791-798.
Dyer, S., & Moneta, G. B. (2006). Frequency of parallel, associative, and cooperative play in British children of different socio- economic status. Social Behavior and Personality, 34(5), 587-592.
Economist Data Team. (2017). Parents now spend twice as much time with their children as 50 years ago. Retrieved from https://www.economist.com/graphic-detail/2017/11/27/parents-now-spend-twice-as-much-time-with-their-children-as- 50-years-ago
Epley, N., Morewedge, C. K., & Keysar, B. (2004). Perspective taking in children and adults: Equivalent egocentrism but differential correction. Journal of Experimental Social Psychology, 40, 760–768.
Erikson, E. (1982). The life cycle completed. NY: Norton & Company.
Evans, D. W., Gray, F. L., & Leckman, J. F. (1999). The rituals, fears and phobias of young children: Insights from development, psychopathology and neurobiology. Child Psychiatry and Human Development, 29(4), 261-276. doi:10.1023/A:1021392931450
Evans, D. W. & Leckman, J. F. (2015) Origins of obsessive-compulsive disorder: Developmental and evolutionary perspectives. In D. Cicchetti and D. J. Cohen (Eds.), Developmental psychopathology (2nd edition). Hoboken, NJ: Wiley & Sons. doi: 10.1002/9780470939406.ch10
Fay-Stammbach, T., Hawes, D. J., & Meredith, P. (2014). Parenting influences on executive function in early childhood: A review. Child Development Perspectives, 8(4), 258-264.
Felitti, V. J., Anda, R.F., Nordenberg, D., Williamson, D. F., Spitz, A., Edwards, V., Koss, M. P., & Marks, J. S. (1998).
Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The Adverse Childhood Experiences (ACE) Study. American Journal of Preventive Medicine, 14(4), 245-258. doi:10.1016/S0749-3797(98)00017-8
Finkelhorn, D., Hotaling, G., Lewis, I. A., & Smith, C. (1990). Sexual abuse in a national survey of adult men and women: Prevalence, characteristics, and risk factors. Child Abuse and Neglect, 14(1), 19-28.
Frank, G., Plunkett, S. W., & Otten, M. P. (2010). Perceived parenting, self-esteem, and general self-efficacy of Iranian American adolescents. Journal of Child & Family Studies, 19, 738-746.
Galotti, K. M. (2018). Cognitive psychology: In and out of the laboratory (6th Ed.). Thousand Oaks, CA: Sage. Garrett, B. (2015). Brain and behavior: An introduction to biological psychology (4th Ed.). Thousand Oaks, CA: Sage.
Gauthier, J., Siddiqui, T. J., Huashan, P., Yokomaku, D., Hamdan, F. F., Champagne, N., . . . Rouleau, G.A. (2011). Truncating mutations in NRXN2 and NRXN1 in autism spectrum disorders and schizophrenia. Human Genetics, 130, 563–573.
Gecas, V., & Seff, M. (1991). Families and adolescents. In A. Booth (Ed.), Contemporary families: Looking forward, looking back. Minneapolis, MN: National Council on Family Relations.
Gentile, D.A., & Walsh, D.A. (2002). A normative study of family media habits. Applied Developmental Psychology, 23, 157- 178.
Gernhardt, A., Rubeling, H., & Keller, H. (2015). Cultural perspectives on children’s tadpole drawings: At the interface between representation and production. Frontiers in Psychology, 6, Article 812. doi: 0.3389/fpsyg.2015.00812.
Gershoff, E. T. (2008). Report on physical punishment in the United States: What research tell us about its effects on children. Columbus, OH: Center for Effective Discipline.
Glass, E., Sachse, S., & von Suchodoletz, W. (2008). Development of auditory sensory memory from 2 to 6 years: An MMN study. Journal of Neural Transmission, 115(8), 1221-1229.doi:10.1007/s00702-008-0088-6
Gleason, T. R. (2002). Social provisions of real and imaginary relationships in early childhood. Developmental Psychology, 38, 979-992.
Gleason, T. R., & Hohmann, L. M. (2006). Concepts of real and imaginary friendships in early childhood. Social Development, 15, 128-144.
Gleason, T. R., Sebanc, A. M., & Hartup, W. W. (2000). Imaginary companions of preschool children. Developmental Psychology, 36(4), 419-428.
Gomes, G. Sussman, E., Ritter, W., Kurtzberg, D., Vaughan, H. D. Jr., & Cowen, N. (1999). Electrophysiological evidence of development changes in the duration of auditory sensory memory. Developmental Psychology, 35, 294-302.
Goodvin, R., Meyer, S. Thompson, R.A., & Hayes, R. (2008). Self-understanding in early childhood: Associations with child attachment security and maternal negative affect. Attachment & Human Development, 10(4), 433-450.
Gopnik, A., & Wellman, H.M. (2012). Reconstructing constructivism: Causal models, Bayesian learning mechanisms, and the theory theory. Psychological Bulletin, 138(6), 1085-1108.
Guy, J., Rogers, M., & Cornish, K. (2013). Age-related changes in visual and auditory sustained attention in preschool-aged children. Child Neuropsychology, 19(6), 601–614. Retrieved from http://dx.doi.org/10.1080/09297049.2012.710321
Hammer C. S., Hoff, E., Uchikosh1, Y., Gillanders, C., Castro, D., & Sandilos, L. E. (2014). The language literacy development of young dual language learners: A critical review. Early Child Research Quarterly, 29(4), 715-733.
Harter, S., & Pike, R. (1984). The pictorial scale of Perceived Competence and Social Acceptance for Young Children. Child Development, 55, 1969-1982.
Harvard University. (2019). Center on the developing child: Toxic stress. Retrieved from https://developingchild.harvard.edu/science/key-concepts/toxic-stress/
Herrmann, E., Misch, A., Hernandez-Lloreda, V., & Tomasello, M. (2015). Uniquely human self-control begins at school age. Developmental Science, 18(6), 979-993. doi:10.1111/desc.12272.
Herrmann, E., & Tomasello, M. (2015). Focusing and shifting attention in human children (homo sapiens) and chimpanzees (pan troglodytes). Journal of Comparative Psychology, 129(3), 268–274. Retrieved from dx.doi.org/10.1037/a0039384
Hoff, E. (2018). Bilingual development in children of immigrant families. Child Development Perspectives, 12(2), 80-86.
Howe, N., Rinaldi, C. M., Jennings, M., & Petrakos, H. (2002). “No! The lambs can stay out because they got cozies”: Constructive and destructive sibling conflict, pretend play, and social understanding. Child Development, 73, 1406- 1473.
Hughes, V. (2007). Mercury rising. Nature Medicine, 13, 896-897.
Imai, M., Li, L., Haryu, E., Hirsh-Pasek, K., Golinkoff, R. M., & Shigematsu, J. (2008). Novel noun and verb learning in Chinese, English, and Japanese children: Universality and language-specificity in novel noun and verb learning. Child Development, 79, 979-1000.
Jarne, P., & Auld, J. R. (2006). Animals mix it up too: The distribution of self-fertilization among hermaphroditic animals. Evolution, 60, 1816–1824.
Jones, P.R., Moore, D.R., & Amitay, S. (2015). Development of auditory selective attention: Why children struggle to hear in noisy environments. Developmental Psychology, 51(3), 353–369. Retrieved from dx.doi.org/10.1037/a0038570
Kalat, J. W. (2016). Biological Psychology (12th Ed.). Boston, MA: Cengage.
Kaushanskaya, M., Gross, M., & Buac, M. (2014). Effects of classroom bilingualism on task-shifting, verbal memory, and word learning in children. Developmental Science, 17(4), 564-583.
Kellogg, R. (1969). Handbook for Rhoda Kellogg: Child art collection. Washington D. C.: NCR/Microcard Editions.
Kemple, K.M., (1995). Shyness and self-esteem in early childhood. Journal of Humanistic Education and Development, 33(4), 173-182.
Kimmel, M. S. (2008). The gendered society (3rd ed.). Oxford: Oxford University Press.
Kinney, D. K., Barch, D. H., Chayka, B., Napoleon, S., & Munir, K. M. (2009). Environmental risk factors for autism: Do they help or cause de novo genetic mutations that contribute to the disorder? Medical Hypotheses, 74, 102–106.
Kirkorian, H.L., Choi, K., & Pempek, T.A. (2016). Toddlers’ word learning from contingent and noncontingent video on touch screens. Child Development, 87(2), 405–413.
Kirkorian, H.L., Pempek, T.A., & Murphy, L.A. (2009). The impact of background television on parent-child interaction. Child Development, 80, 1350-1359.
Knorr, C. (2017). Gender stereotypes are messing with your kid. Retrieved from https://www.commonsensemedia.org/blog/gender-stereotypes-are-messing-with-your-kid
Kohn, M. L. (1977). Class and conformity. (2nd ed.). Chicago: University of Chicago Press.
Kolb, B. & Whishaw, I. Q. (2011). An introduction to brain and behavior (3rd ed.). New York: Worth Publishers.
Kramer, L., & Gottman, J. M. (1992). Becoming a sibling: “With a little help from my friends.” Developmental Psychology, 28, 685-699.
Lenroot, R. K., & Giedd, J. N. (2006). Brain development in children and adolescents: Insights from anatomical magnetic resonance imaging. Neuroscience and Biobehavioral Reviews, 30, 718-729.
Maccoby, E., & Jacklin, C. (1987). Gender segregation in childhood. Advances in Child Development and Behavior, 20, 239-287.
MacKenzie, M. J., Nicklas, E., Waldfogel, J., & Brooks-Gunn, J. (2013). Spanking and child development across the first decade of life. Pediatrics, 132(5), e1118-e1125.
Madigan, S., Browne, D., Racine, N., Mori, C., & Tough, S. (2019). Association between screen time and children’s performance on a developmental screening test. JAMA Pediatrics, 173(3), 244-250.
Manosevitz, M., Prentice, N. M., & Wilson, F. (1973). Individual and family correlates of imaginary companions in preschool children. Developmental Psychology, 8, 72-79.
Martinson, F. M. (1981). Eroticism in infancy and childhood. In L. L. Constantine & F. M. Martinson (Eds.), Children and sex: New findings, new perspectives. (pp. 23-35). Boston: Little, Brown.
Masih, V. (1978). Imaginary play companions of children. In R. Weizman, R. Brown, P. Levinson, & P. Taylor (Eds.). Piagetian theory and the helping profession (pp. 136-144). Los Angeles: University of Southern California Press.
Mauro, J. (1991). The friend that only I can see: A longitudinal investigation of children’s imaginary companions. Dissertation, University of Oregon.
Mayo Clinic Staff. (2016a). Nutrition for kids: Guidelines for a healthy diet. Retrieved from www.mayoclinic.org/healthy- lifestyle/childrens-health/in-depth/nutrition-for-kids/art-20049335
Mayo Clinic Staff. (2016b). Potty training: How to get the job done. Retrieved from www.mayoclinic.org/healthy- lifestyle/infant-and-toddler-health/indepth/potty-training/art-20045230
McAlister, A. R., & Peterson, C. C. (2007). A longitudinal study of siblings and theory of mind development. Cognitive Development, 22, 258-270.
Meek, S. E., Lemery-Chalfant, K., Jahromi, L. D., & Valiente, C. (2013). A review of gene-environment correlations and their implications for autism: A conceptual model. Psychological Review, 120, 497–521.
Merrick, M. T., Ford, D. C., Ports, K. A., & Guinn, A. S. (2018). Prevalence of adverse childhood experiences from the 2011- 2014 Behavioral Risk Factor Surveillance System in 23 States. Early JAMA Pediatrics, 172(11), 1038-1044.
Meyers-Sutton, C. (2005). Multiple voices: An introduction ot bilingualism. Malden, MA: Blackwell Publishers.
Middlebrooks, J. S., & Audage, N. C. (2008). The effects of childhood stress on health across the lifespan. (United States, Center for Disease Control, National Center for Injury Prevention and Control). Atlanta, GA.
Mischel, W., Ayduk, O., Berman, M. G., Casey, B. J., Gotlib, I. H., Jonides, J., & … Shoda, Y. (2011). ‘Willpower’ over the life span: Decomposing self-regulation. Social Cognitive & Affective Neuroscience, 6(2), 252-256. doi:10.1093/scan/nsq081
Mischel, W., Ebbesen, E. B., & Zeiss, A. R. (1972). Cognitive and attentional mechanisms in delay of gratification. Journal of Personality and Social Psychology, 21, 204–218.
Morra, S., Gobbo, C., Marini, Z., & Sheese, R. (2008). Cognitive development: Neo-Piagetian perspectives. New York: Lawrence Erlbaum Associates.
National Association for the Education of Young Children. (2016). The 10 NAEYC program standards. Retrieved from http://families.naeyc.org/accredited-article/10-naeyc-program-standards
National Institute of Child Health and Human Development. (2006). The NICHD study of early child care (NIH Pub. No. 05- 4318). Washington, DC: Government Printing Office.
Nelson, K., & Fivush, R. (2004). The emergence of autobiographical memory: A social cultural developmental theory. Psychological Review, 111(2), 468-511.
Nelson, K., & Ross, G. (1980). The generalities and specifics of long-term memory in infants and young children. In M. Perlmutter (Ed.), Children’s memory: New directions in child development (Vol. 10, pp. 87-101). San Francisco: Jossey-Bass.
Nielsen Company. (2009). Television audience 2008-2009. Retrieved from blog.nielsen.com/nielsenwire/wp-content/uploads/2009/07/tva_2008_071709.pdf
Novella, S. (2008). The increase in autism diagnoses: Two hypotheses [Web log post]. Retrieved from http://www.sciencebasedmedicine.org/the-increase-in-autism-diagnoses-two-hypotheses/
Okami, P., Olmstead, R., & Abramson, P. R. (1997). Sexual experiences in early childhood: 18-year longitudinal data from UCLA Family Lifestyles Project. Journal of Sex Research, 34(4), 339-347.
Olson, K. R., & Gülgöz, S. (2018). Early findings from the TransYouth Project: Gender development in transgender children. Child Development Perspectives, 12(2), 93-97.
Parten, M. B. (1932). Social participation among preschool children. Journal of Abnormal and Social Psychology, 27, 243-269. Perner, J., Ruffman, T., & Leekam, S. R. (1994). Theory of mind is contagious: You catch from your sibs. Child Development, 65, 1228-1238.
Pike, A., Coldwell, J., & Dunn, J. F. (2005). Sibling relationships in early/middle childhood: Links with individual adjustment. Journal of Family Psychology, 19(4), 523-532.
Place, S., & Hoff, E. (2016). Effects and non-effects of input in bilingual environments on dual language skills in 2 1/2-year-olds. Bilingualism: Language and Cognition, 19, 1023–1041.
Porporino, M., Shore, D.I., Iarocci, G., & Burack, J.A. (2004). A developmental change in selective attention and global form perception. International Journal of Behavioral Development, 28 (4), 358–364 doi:10.1080/01650250444000063
Posner, M.I., & Rothbart, M.K. (2007). Research on attention networks as a model for the integration of psychological science. Annual Review in Psychology, 58, 1–23
Price-Williams, D.R., Gordon, W., & Ramirez, M. (1969). Skill and conservation: A study of pottery making children. Developmental Psychology, 1, 769.
Ram, A., & Ross, H. (2008). “We got to figure it out”: Information-sharing and siblings’ negotiations of conflicts of interest. Social Development, 17, 512-527.
Rice, F. P. (1997). Human development: A life-span approach. Upper Saddle River, NJ: Prentice Hall. Rideout, V.J., & Hamel E. (2006). The media family: Electronic media in the lives of infants, toddlers, preschoolers and their parents. Retrieved from www.kff.org/entmedia/upload/7500.pdf
Robinson, T.N., Wilde, M.L., & Navracruz, L.C. (2001). Effects of reducing children’s television and video game use on aggressive behavior: A randomized controlled trial. Archives of Pediatrics and Adolescent Medicine, 155, 17-23.
Rothbart, M.K., & Rueda, M.R. (2005). The development of effortful control. In U. Mayr, E. Awh, & S.W. Keele (Eds.), Developing individuality in the human brain: A festschrift honoring Michael I. Posner (pp. 167–88). Washington, DC: American Psychological Association
Ruble, D.N., Boggiano, A.K., Feldman, N.S., & Loeble, J.H. (1980). Developmental analysis of the role of social comparison in self-evaluation. Developmental Psychology, 16, 105-115.
Ruble, D. N., Martin, C., & Berenbaum, S. (2006). Gender development. In W. Damon & R. M. Lerner (Series Eds.) & N. Eisenberg (Vol. Ed.), Handbook of child psychology: Vol. 3. Social, emotional, and personality development (6th ed., pp. 858–932). New York, NY: Wiley.
Russo, F. (2016). Debate growing about how to meet the urgent needs of transgender kids. Scientific American Mind, 27(1), 27- 35.
Ryan, C. (2013). Language use in the United States: 2011. Retrieved from https://www2.census.gov/library/publications/2013/acs/acs-22/acs-22.pdf
Save the Children. (2019). Child protection. Retrived from https://www.savethechildren.net/what-we-do/child-protection
Schmidt, M.E., Pempek, T.A., & Kirkorian, H.L. (2008). The effects of background television on the toy play behavior of very young children. Child Development, 79, 1137-1151.
Schneider, W., Kron-Sperl, V., & Hunnerkopf, M. (2009). The development of young children’s memory strategies: Evidence from the Würzburg longitudinal memory study. European Journal of Developmental Psychology, 6(1), 70-99.
Schwartz, I. M. (1999). Sexual activity prior to coitus initiation: A comparison between males and females. Archives of Sexual Behavior, 28(1), 63-69.
Shahaeian, A., Peterson, C. C., Slaughter, V., & Wellman, H. M. (2011). Culture and the sequence of steps in theory of mind development. Developmental Psychology, 47(5), 1239-1247.
Singer, D., & Singer, J. (1990). The house of make-believe. Cambridge, MA: Harvard University Press.
Society for Research in Child Development. (2018). The Science is clear: Separating families has long-term damaging psychological and health consequences for children, families, and communities. Retrieved from https://www.srcd.org/policy-media/statements-evidence
Spears Brown, C., & Jewell, J. A. (2018). Gender. Retrieved from https://nobaproject.com/modules/gender
Steele, B.F. (1986). Notes on the lasting effects of early child abuse throughout the life cycle. Child Abuse & Neglect 10(3), 283-291.
Tamana, S.K., Ezeugwu, E., Chikuma, J., Lefebvre, D.L., Azad, M.B., Moraes, T.J.,… & Mandhane, P. J. (2019). Screen-time is associated with inattention problems in preschoolers: Results from the CHILD birth cohort study. PLOS ONE, 14(4), e0213995. Retrieved from https://journals.plos.org/plosone/ar...l.pone.0213995
Thomas, R. M. (1979). Comparing theories of child development. Santa Barbara, CA: Wadsworth.
Traverso, L., Viterbori, P., & Usai, M. C. (2015). Improving executive function in childhood: Evaluation of a training intervention for 5-year-old children. Frontiers in Psychology, 6, 1-14. doi:10.3389/fpsyg.2015.00525
United Nations. (2014). Committee on the rights of the child. Retrieved from http://tbinternet.ohchr.org/Treaties/CRC/Shared%20Documents/VAT/CRC_C_VAT_CO_2_16302_E.pdf
United States Department of Health and Human Services. (2019). Child Maltreatment 2017. Retrieved from https://www.acf.hhs.gov/cb/resource/child-maltreatment-2017
United States Department of Health and Human Services. (2015). Head Start program facts fiscal year 2013. Retrieved from eclkc.ohs.acf.hhs.gov/hslc/data/factsheets/docs/hs-program-fact-sheet-2013.pdf
Valente, S. M. (2005). Sexual abuse of boys. Journal of Child and Adolescent Psychiatric Nursing, 18, 10–16. doi:10.1111/j.1744-6171.2005.00005.x
Wellman, H.M., Cross, D., & Watson, J. (2001). Meta-analysis of theory of mind development: The truth about false belief. Child Development, 72(3), 655-684.
Wellman, H. M., Fang, F., Liu, D., Zhu, L, & Liu, L. (2006). Scaling theory of mind understandings in Chinese children. Psychological Science, 17, 1075-1081.
White House Press Secretary. (2014). Fact Sheet: Invest in US: The White House Summit on Early Childhood Education. Retrieved from https://www.whitehouse.gov/the-press-office/2014/12/10/fact-sheet-invest-us-white-house-summit-early-childhood-education
Wimmer, H., & Perner, J. (1983). Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children’s understanding of deception. Cognition, 13, 103–128.
Wing, L., Gould, J., & Gillberg, C. (2011). Autism spectrum disorders in the DSM-5: Better or worse than the DSM IV? Research in Developmental Disabilities, 32, 768–773.
Wu, X., Tao, S., Rutayisirel, E., Chen, Y., Huang, K., & Tao, F. (2017). The relationship between screen time, nighttime sleep duration, and behavioral problems in preschool children in China. European Child and Adolescent Psychiatry, 26, 541– 548.
Yoo, J., & Kaushanskaya, M. (2012). Phonological memory in bilinguals and monolinguals. Memory & Cognition, 40, 1314– 1330.
Zachry, A. (2013). 6 Types of Preschool Programs. Retrieved from www.parents.com/toddlers-preschoolers/starting – preschool/preparing/types-of-preschool-programs/
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/07%3A_Development_in_Early_Childhood/7.02%3A_Chapter_14-_Cognitive_Development_in_Early_Childhood.txt |
Chapter 15 Learning Objectives
• Describe Erikson’s third stage of initiative vs. guilt
• Describe the changes in self-concept and self-esteem
• Describe children’s understanding of others
• Describe emotional regulation and delayed gratification
• Describe young children’s understanding of morality
• Summarize the main theories of gender development
• Explain the terms transgender, gender dysphoria, and intersex
• Describe the major parenting styles and their consequences for children
• Describe the role of siblings in children’s development
• Summarize the types of play in which children engage
• Describe the influence of the media on young children’s social development
Gender
identify some differences and learn whether they are boys or girls, preschoolers become more interested in what it means to be male or female. Gender is the cultural, social and psychological meanings associated with masculinity and feminity (Spears Brown & Jewell, 2018). A person’s sense of self as a member of a particular gender is known as gender identity. The development of gender identity appears to be due to an interaction among biological, social and representational influences (Ruble, Martin, & Berenbaum, 2006). Gender roles, or the expectations associated with being male or female, are learned in one’s culture throughout childhood and into adulthood.
way. Knowing the sex of the child can conjure up images of the child’s behavior, appearance, and potential on the part of a parent, and this stereotyping continues to guide perception through life. Consider parents of newborns, shown a 7-pound, 20-inch baby, wrapped in blue (a color designating males) describe the child as tough, strong, and angry when crying. Shown the same infant in pink (a color used in the United States for baby girls), these parents are likely to describe the baby as pretty, delicate, and frustrated when crying (Maccoby & Jacklin, 1987). Female infants are held more, talked to more frequently and given direct eye contact, while male infant interactions are often mediated through a toy or activity.
Theories of Gender Development
appropriate for each gender. Cognitive social learning theory also emphasizes reinforcement, punishment, and imitation, but adds cognitive processes. These processes include attention, self- regulation, and self-efficacy. Once children learn the significance of gender, they regulate their own behavior based on internalized gender norms (Bussey & Bandura, 1999).
Transgender Children
about two percent of the world’s population (Blackless et al., 2000). There are dozens of intersex conditions, and intersex individuals demonstrate the diverse variations of biological sex. Some examples of intersex conditions include:
• Turner syndrome or the absence of, or an imperfect, second X chromosome
• Congenital adrenal hyperplasia or a genetic disorder caused by an increased production of androgens
• Androgen insensitivity syndrome or when a person has one X and one Y chromosome, but is resistant to the male hormones or androgens
How much does gender matter for children: Starting at birth, children learn the social meanings of gender from adults and their culture. Gender roles and expectations are especially portrayed in children’s toys, books, commercials, video games, movies, television shows and music (Khorr, 2017). Therefore, when children make choices regarding their gender identification, expression, and behavior that may be contrary to gender stereotypes, it is important that they feel supported by the caring adults in their lives. This support allows children to feel valued, resilient, and develop a secure sense of self (American Academy of Pediatricians, 2015).
Parenting Styles
overbearing and allow them to make constructive mistakes. Parents allow negotiation where appropriate, and consequently this type of parenting is considered more democratic.
distant. Consequently, children reared in this way may fear rather than respect their parents and, because their parents do not allow discussion, may take out their frustrations on safer targets- perhaps as bullies toward peers.
Table 4.3 Comparison of Four Parenting Styles
Culture: The impact of culture and class cannot be ignored when examining parenting styles. The model of parenting described above assumes that the authoritative style is the best because this style is designed to help the parent raise a child who is independent, self-reliant and responsible. These are qualities favored in “individualistic” cultures such as the United States, particularly by the middle class. However, in “collectivistic” cultures such as China or Korea, being obedient and compliant are favored behaviors. Authoritarian parenting has been used historically and reflects cultural need for children to do as they are told. African-American, Hispanic and Asian parents tend to be more authoritarian than non-Hispanic whites. In societies where family members’ cooperation is necessary for survival, rearing children who are independent and who strive to be on their own makes no sense. However, in an economy based on being mobile in order to find jobs and where one’s earnings are based on education, raising a child to be independent is very important.
Spanking
• Praising and modeling appropriate behavior
• Providing time-outs for inappropriate behavior
• Giving choices
• Helping the child identify emotions and learning to calm down
• Ignoring small annoyances
• Withdrawing privileges
Sibling Relationships
more negative interactions between siblings have been reported in families where parents had poor patterns of communication with their children (Brody, Stoneman, & McCoy, 1994).
While parents want positive interactions between their children, conflicts are going to arise, and some confrontations can be the impetus for growth in children’s social and cognitive skills. The sources of conflict between siblings often depend on their respective ages. Dunn and Munn (1987) revealed that over half of all sibling conflicts in early childhood were disputes about property rights. By middle childhood this starts shifting toward control over social situation, such as what games to play, disagreements about facts or opinions, or rude behavior (Howe, Rinaldi, Jennings, & Petrakos, 2002). Researchers have also found that the strategies children use to deal with conflict change with age, but this is also tempered by the nature of the conflict. Abuhatoum and Howe (2013) found that coercive strategies (e.g., threats) were preferred when the dispute centered on property rights, while reasoning was more likely to be used by older siblings and in disputes regarding control over the social situation. However, younger siblings also use reasoning, frequently bringing up the concern of legitimacy (e.g., “You’re not the boss”) when in conflict with an older sibling. This is a very common strategy used by younger siblings and is possibly an adaptive strategy in order for younger siblings to assert their autonomy (Abuhatoum & Howe, 2013). A number of researchers have found that children who can use non-coercive strategies are more likely to have a successful resolution, whereby a compromise is reached and neither child feels slighted (Ram & Ross, 2008; Abuhatoum & Howe, 2013). Not surprisingly, friendly relationships with siblings often lead to more positive interactions with peers. The reverse is also true. A child can also learn to get along with a sibling, with, as the song says, “a little help from my friends” (Kramer & Gottman, 1992).
Play
than those older; by age five associative and cooperative play are the most common forms of play (Dyer & Moneta, 2006).
they engaging in similar activities as the children around them.
on the activities and even make suggestions but will not directly join the play.
companions have no obvious trigger in the child’s life (Masih, 1978). Imaginary companions are sometimes based on real people, characters from stories, or simply names the child has heard (Gleason, et. al., 2000). Imaginary companions often change over time. In their study, Gleason et al. (2000) found that 40% of the imaginary companions of the children they studied changed, such as developing superpowers, switching age, gender, or even dying, and 68% of the characteristics of the companion were acquired over time. This could reflect greater complexity in the child’s “creation” over time and/or a greater willingness to talk about their imaginary playmates.
Do children treat real friends differently? The answer appears to be not really. Young children view their relationship with their imaginary companion to be as supportive and nurturing as with their real friends. Gleason has suggested that this might suggest that children form a schema of what is a friend and use this same schema in their interactions with both types of friends (Gleason, et al., 2000; Gleason, 2002; Gleason & Hohmann, 2006).
Children and the Media
cognitive and language development as well as be linked to attention problems later in childhood (Schmidt, Pempek, & Kirkorian, 2008; Courage, Murphy, & Goulding, 2010).
Child Care
mothers. In 1965 mothers with and without a university education spent about the same amount of time on child care. By 2012 the more educated ones were spending half an hour more per day. See Figure 4.27 for the difference between mothers in the United States who were university educated (dark blue line) and those who were non-university educated (light blue line).
Figure 4.27 U.S. Mothers’ Time Spent in Child Care
facility. The physical environment should be colorful, stimulating, clean, and safe. The philosophy of the organization and the curriculum available should be child-centered, positive, and stimulating. Providers should be trained in early childhood education as well. A majority of states do not require training for their child care providers. While formal education is not required for a person to provide a warm, loving relationship to a child, knowledge of a child’s development is useful for addressing their social, emotional, and cognitive needs in an effective way.
Child Abuse
Victims of Child Abuse: According to the United States Department of Health and Human Services (HHS) (2019), during 2017 (the most recent year data has been collected) Child Protective Services (CPS) agencies received an estimated 4.1 million referrals for abuse involving approximately 7.5 million children. This is a rate of 31.8 per 1,000 children in the national population. Professionals made 65.7% of alleged child abuse and neglect reports, and they included law enforcement (18.3%), educational (19.4%) and social services personnel (11.7%). Nonprofessionals, such as friends, neighbors, and relatives, submitted 17.3% of the reports. Approximately 3.5 million children were the subjects of at least one report.
Sexual Abuse: Childhood sexual abuse is defined as any sexual contact between a child and an adult or a much older child. Incest refers to sexual contact between a child and family members. In each of these cases, the child is exploited by an older person without regard for the child’s developmental immaturity and inability to understand the sexual behavior (Steele, 1986). Research estimates that 1 out of 4 girls and 1 out of 10 boys have been sexually abused (Valente, 2005). The median age for sexual abuse is 8 or 9 years for both boys and girls (Finkelhorn, Hotaling, Lewis, & Smith, 1990). Most boys and girls are sexually abused by a male. Although rates of sexual abuse are higher for girls than for boys, boys may be less likely to report abuse because of the cultural expectation that boys should be able to take care of themselves and because of the stigma attached to homosexual encounters (Finkelhorn et al., 1990). Girls are more likely to be abused by family member and boys by strangers. Sexual abuse can create feelings of self-blame, betrayal, shame and guilt (Valente, 2005). Sexual abuse is particularly damaging when the perpetrator is someone the child trusts and may lead to depression, anxiety, problems with intimacy, and suicide (Valente, 2005).
Stress on Young Children: Children experience different types of stressors. Normal, everyday stress can provide an opportunity for young children to build coping skills and poses little risk to development. Even more long-lasting stressful events, such as changing schools or losing a loved one, can be managed fairly well. Children who experience toxic stress or who live in extremely stressful situations of abuse over long periods of time can suffer long-lasting effects. The structures in the midbrain or limbic system, such as the hippocampus and amygdala, can be vulnerable to prolonged stress during early childhood (Middlebrooks & Audage, 2008). High levels of the stress hormone cortisol can reduce the size of the hippocampus and affect the child’s memory abilities. Stress hormones can also reduce immunity to disease. The brain exposed to long periods of severe stress can develop a low threshold making the child hypersensitive to stress in the future.
Adverse Childhood Experiences (ACEs)
Figure 4.29
Figure 4.30 How ACES Affect Children and Adults
skills, emotional processing, and physiological health. When exposed to stress, children typically look to their parents for support and care, and parents can reduce children’s stress. These separated children were already under extreme stress escaping their previous homes, and then were separated from the individuals who could support them through this process.
References
Abuhatoum, S., & Howe, N. (2013). Power in sibling conflict during early and middle childhood. Social Development, 22, 738- 754.
Al-Haddad, B., Jacobsson, B., Chabra, S., Modzelewska, D., Olson, E……. Sengpiel, V. (2019). Long-term risk of neuropsychiatric disease after exposure to infection in utero. JAMA Psychiatry, 76(6), 594-602.
American Academy of Pediatrics. (2015). Gender identity development in children. Retrieved from https://www.healthychildren.org/English/ages-stages/ gradeschool/Pages/Gender-Identity-and-Gender-Confusion-In- Children.aspx
American Academy of Pediatrics. (2016). Media and young minds. Retrieved from https://pediatrics.aappublications.org/content/138/5/e20162591
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders, 5th edition (DSM-5). Washington, DC: Author.
American Psychological Association. (2019). Immigration. Retrieved from https://www.apa.org/advocacy/immigration
Armor, D. J. (2015). Head Start or false start. USA Today Magazine. Retrieved from https://www.questia.com/magazine/1G1-429736352/head-start-or-false-start
Autism Genome Project Consortium. (2007). Mapping autism risk loci using genetic linkage and chromosomal rearrangements. Nature Genetics, 39, 319–328.
Baio, J., Wiggins, L., Christensen, D., Maenner, M., ……. Dowling, N. (2018). Prevalence of autism spectrum disorder among children aged 8 years-autism and developmental disabilities monitoring network, 11 sites, United States, 2014. MMWR Surveillance Summary, 67(No. SS-6), 1-23. doi : dx.doi.org/a0.15585/mmwr.ss6706a1External
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.
Barshay, J. (2015). Report: Scant scientific evidence for Head Start programs’ effectiveness. U.S. News and World Report. Retrieved from www.usnews.com/news/articles/ 2015/08/03/report-scant-scientific-evidence-for-head-start- programs-effectiveness
Baumrind, D. (1971). Current patterns of parental authority. Developmental Psychology Monograph, 4(1), part 2.
Baumrind, D. (2013). Authoritative parenting revisited: History and current status. In R. E. Larzelere, A. Sheffield, & A. W. Harrist (Eds.). Authoritative parenting: Synthesizing nurturance and discipline for optimal child development (pp. 11- 34). Washington, DC: American Psychological Association.
Bem, S. L. (1981). Gender schema theory: A cognitive account of sex typing. Psychological Review, 88, 354-364. Berk, L. E. (2007). Development through the life span (4th ed.). Boston: Allyn and Bacon.
Berwid, O., Curko-Kera, E. A., Marks, D. J., & Halperin, J. M. (2005). Sustained attention and response inhibition in young children at risk for attention deficit hyperactivity disorder. Journal of Child Psychology and Psychiatry, 46(11), 1219- 1229.
Bialystok, E. (2011). Coordination of executive functions in monolingual and bilingual children. Journal of Experimental Child Psychology, 110, 461–468.
Bialystok, E., Martin, M.M., & Viswanathan, M. (2005). Bilingualism across the lifespan: The rise and fall of inhibitory control. International Journal of Bilingualism, 9, 103–119.
Bibok, M.B., Carpendale, J.I.M., & Muller, U. (2009). Parental scaffolding and the development of executive function. New Directions for Child and Adolescent Development, 123, 17-34.
Bigler, R. S., & Liben, L. S. (2007). Developmental intergroup theory: Exploring and reducing children’s social stereotyping and prejudice. Current Directions in Psychological Science, 16, 162-166.
Birch, S., & Bloom, P. (2003). Children are cursed: An asymmetric bias in mental-state attribution. Psychological Science, 14(3), 283-286.
Blackless, M., Charuvastra, A., Derryck, A., Fausto-Sterling, A., Lauzanne, K., & Lee, E. (2000). How sexually dimorphic are we? Review and synthesis. American Journal of Human Biology, 12, 151-166.
Bonifacci, P., Giombini, L., Beloocchi, S., & Conteno, S. (2011). Speed of processing, anticipation, inhibition and working memory in bilinguals. Developmental Science, 14, 256–269.
Boyse, K. & Fitgerald, K. (2010). Toilet training. University of Michigan Health System. Retrieved from http://www.med.umich.edu/yourchild/topics/toilet.htm
Brody, G. H., Stoneman, Z., & McCoy, J. K. (1994). Forecasting sibling relationships in early adolescence from child temperament and family processes in middle childhood. Child development, 65, 771-784.
Brown, G.L., Mangelsdork, S.C., Agathen, J.M., & Ho, M. (2008). Young children’s psychological selves: Convergence with maternal reports of child personality. Social Development, 17, 161-182.
Bureau of Labor Statistics. (2019). Employment characteristics of families-2018. Retrieved from https://www.bls.gov/news.release/pdf/famee.pdf
Bussey, K., & Bandura, A. (1999). Social cognitive theory of gender development and differentiation. Psychological Review, 106(4), 676-713.
Byrd, R. (2002). Report to the legislature on the principal findings from the epidemiology of autism in California: A comprehensive pilot study. Retrieved from www.dds.ca.gov/Autism/MindReport.cfm
Camarota, S. A., & Zeigler, K. (2015). One in five U. S. residents speaks foreign language at home. Retrieved from https://cis.org/sites/default/files/camarota-language-15.pdf
Carroll, J. L. (2007). Sexuality now: Embracing diversity (2nd ed.). Belmont, CA: Thomson.
Centers for Disease Control and Prevention. (2000). 2000 CDC Growth Charts for the United States: Methods and Development. Retrieved from http://www.cdc.gov/nchs/data/series/sr_11/sr11_246.pdf
Centers for Disease Control and Prevention. (2012). Prevalence of autism spectrum disorders, autism and developmental disabilities monitoring network, 14 sites, United States, 2008. Morbidity and Mortality Weekly Report: Surveillance Summaries, 61(3), 1–19. Retrieved from http://www.cdc.gov/mmwr/pdf/ss/ss6103.pdf
Centers for Disease Control and Prevention. (2015). Nutrition and health of young people. Retrieved from http://www.cdc.gov/healthyschools/nutrition/facts.htm
Centers for Disease Control and Prevention. (2019). About adverse childhood experiences. Retrived from www.cdc.gov/violenceprevention/childabuseandneglect/acestudy/aboutace.html
Chang, A., Sandhofer, C., & Brown, C. S. (2011). Gender biases in early number exposure to preschool-aged children. Journal of Language and Social Psychology, 30(4), 440-450.
Chiong, C., & Shuler, C. (2010). Learning: Is there an app for that? Investigations of young children’s usage and learning with mobile devices and apps. New York: The Joan Ganz Cooney Center at Sesame Workshop. Retrieved from: https://clalliance.org/wp-content/uploads/files/learningapps_final_110410.pdf
Christakis, D.A. (2009). The effects of infant media usage: What do we know and what should we learn? Acta Paediatrica, 98, 8–16.
Clark, J. (1994). Motor development. In V. S. Ramachandran (Ed.), Encyclopedia of human behavior (pp. 245–255). San Diego: Academic Press.
Colwell, M.J., & Lindsey, E.W. (2003). Teacher-child interactions and preschool children’s perceptions of self and peers. Early Childhood Development & Care, 173, 249-258.
Coté, C. A., & Golbeck, S. (2007). Preschoolers’ feature placement on own and others’ person drawings. International Journal of Early Years Education, 15(3), 231-243.
Courage, M.L., Murphy, A.N., & Goulding, S. (2010). When the television is on: The impact of infant-directed video on 6- and 18-month-olds’ attention during toy play and on parent-infant interaction. Infant Behavior and Development, 33, 176- 188.
Crain, W. (2005). Theories of development concepts and applications (5th ed.). New Jersey: Pearson.
De Houwer, A. (2007). Parental language input patterns and children’s bilingual use. Applied Psycholinguistics, 28, 411–422
DeStefano, F., Price, C. S., & Weintraub, E. S. (2013). Increasing exposures to antibody-stimulating proteins and polysaccharides in vaccines is not associated with risk of autism. The Journal of Pediatrics, 163, 561–567.
Dougherty, D.M., Marsh, D.M., Mathias, C.W., & Swann, A.C. (2005). The conceptualization of impulsivity: Bipolar disorder and substance abuse. Psychiatric Times, 22(8), 32-35.
Dunn, J., & Munn, P. (1987). Development of justification in disputes with mother and sibling. Developmental Psychology, 23, 791-798.
Dyer, S., & Moneta, G. B. (2006). Frequency of parallel, associative, and cooperative play in British children of different socio- economic status. Social Behavior and Personality, 34(5), 587-592.
Economist Data Team. (2017). Parents now spend twice as much time with their children as 50 years ago. Retrieved from https://www.economist.com/graphic-detail/2017/11/27/parents-now-spend-twice-as-much-time-with-their-children-as- 50-years-ago
Epley, N., Morewedge, C. K., & Keysar, B. (2004). Perspective taking in children and adults: Equivalent egocentrism but differential correction. Journal of Experimental Social Psychology, 40, 760–768.
Erikson, E. (1982). The life cycle completed. NY: Norton & Company.
Evans, D. W., Gray, F. L., & Leckman, J. F. (1999). The rituals, fears and phobias of young children: Insights from development, psychopathology and neurobiology. Child Psychiatry and Human Development, 29(4), 261-276. doi:10.1023/A:1021392931450
Evans, D. W. & Leckman, J. F. (2015) Origins of obsessive-compulsive disorder: Developmental and evolutionary perspectives. In D. Cicchetti and D. J. Cohen (Eds.), Developmental psychopathology (2nd edition). Hoboken, NJ: Wiley & Sons. doi: 10.1002/9780470939406.ch10
Fay-Stammbach, T., Hawes, D. J., & Meredith, P. (2014). Parenting influences on executive function in early childhood: A review. Child Development Perspectives, 8(4), 258-264.
Felitti, V. J., Anda, R.F., Nordenberg, D., Williamson, D. F., Spitz, A., Edwards, V., Koss, M. P., & Marks, J. S. (1998).
Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The Adverse Childhood Experiences (ACE) Study. American Journal of Preventive Medicine, 14(4), 245-258. doi:10.1016/S0749-3797(98)00017-8
Finkelhorn, D., Hotaling, G., Lewis, I. A., & Smith, C. (1990). Sexual abuse in a national survey of adult men and women: Prevalence, characteristics, and risk factors. Child Abuse and Neglect, 14(1), 19-28.
Frank, G., Plunkett, S. W., & Otten, M. P. (2010). Perceived parenting, self-esteem, and general self-efficacy of Iranian American adolescents. Journal of Child & Family Studies, 19, 738-746.
Galotti, K. M. (2018). Cognitive psychology: In and out of the laboratory (6th Ed.). Thousand Oaks, CA: Sage. Garrett, B. (2015). Brain and behavior: An introduction to biological psychology (4th Ed.). Thousand Oaks, CA: Sage.
Gauthier, J., Siddiqui, T. J., Huashan, P., Yokomaku, D., Hamdan, F. F., Champagne, N., . . . Rouleau, G.A. (2011). Truncating mutations in NRXN2 and NRXN1 in autism spectrum disorders and schizophrenia. Human Genetics, 130, 563–573.
Gecas, V., & Seff, M. (1991). Families and adolescents. In A. Booth (Ed.), Contemporary families: Looking forward, looking back. Minneapolis, MN: National Council on Family Relations.
Gentile, D.A., & Walsh, D.A. (2002). A normative study of family media habits. Applied Developmental Psychology, 23, 157- 178.
Gernhardt, A., Rubeling, H., & Keller, H. (2015). Cultural perspectives on children’s tadpole drawings: At the interface between representation and production. Frontiers in Psychology, 6, Article 812. doi: 0.3389/fpsyg.2015.00812.
Gershoff, E. T. (2008). Report on physical punishment in the United States: What research tell us about its effects on children. Columbus, OH: Center for Effective Discipline.
Glass, E., Sachse, S., & von Suchodoletz, W. (2008). Development of auditory sensory memory from 2 to 6 years: An MMN study. Journal of Neural Transmission, 115(8), 1221-1229.doi:10.1007/s00702-008-0088-6
Gleason, T. R. (2002). Social provisions of real and imaginary relationships in early childhood. Developmental Psychology, 38, 979-992.
Gleason, T. R., & Hohmann, L. M. (2006). Concepts of real and imaginary friendships in early childhood. Social Development, 15, 128-144.
Gleason, T. R., Sebanc, A. M., & Hartup, W. W. (2000). Imaginary companions of preschool children. Developmental Psychology, 36(4), 419-428.
Gomes, G. Sussman, E., Ritter, W., Kurtzberg, D., Vaughan, H. D. Jr., & Cowen, N. (1999). Electrophysiological evidence of development changes in the duration of auditory sensory memory. Developmental Psychology, 35, 294-302.
Goodvin, R., Meyer, S. Thompson, R.A., & Hayes, R. (2008). Self-understanding in early childhood: Associations with child attachment security and maternal negative affect. Attachment & Human Development, 10(4), 433-450.
Gopnik, A., & Wellman, H.M. (2012). Reconstructing constructivism: Causal models, Bayesian learning mechanisms, and the theory theory. Psychological Bulletin, 138(6), 1085-1108.
Guy, J., Rogers, M., & Cornish, K. (2013). Age-related changes in visual and auditory sustained attention in preschool-aged children. Child Neuropsychology, 19(6), 601–614. Retrieved from http://dx.doi.org/10.1080/09297049.2012.710321
Hammer C. S., Hoff, E., Uchikosh1, Y., Gillanders, C., Castro, D., & Sandilos, L. E. (2014). The language literacy development of young dual language learners: A critical review. Early Child Research Quarterly, 29(4), 715-733.
Harter, S., & Pike, R. (1984). The pictorial scale of Perceived Competence and Social Acceptance for Young Children. Child Development, 55, 1969-1982.
Harvard University. (2019). Center on the developing child: Toxic stress. Retrieved from https://developingchild.harvard.edu/science/key-concepts/toxic-stress/
Herrmann, E., Misch, A., Hernandez-Lloreda, V., & Tomasello, M. (2015). Uniquely human self-control begins at school age. Developmental Science, 18(6), 979-993. doi:10.1111/desc.12272.
Herrmann, E., & Tomasello, M. (2015). Focusing and shifting attention in human children (homo sapiens) and chimpanzees (pan troglodytes). Journal of Comparative Psychology, 129(3), 268–274. Retrieved from dx.doi.org/10.1037/a0039384
Hoff, E. (2018). Bilingual development in children of immigrant families. Child Development Perspectives, 12(2), 80-86.
Howe, N., Rinaldi, C. M., Jennings, M., & Petrakos, H. (2002). “No! The lambs can stay out because they got cozies”: Constructive and destructive sibling conflict, pretend play, and social understanding. Child Development, 73, 1406- 1473.
Hughes, V. (2007). Mercury rising. Nature Medicine, 13, 896-897.
Imai, M., Li, L., Haryu, E., Hirsh-Pasek, K., Golinkoff, R. M., & Shigematsu, J. (2008). Novel noun and verb learning in Chinese, English, and Japanese children: Universality and language-specificity in novel noun and verb learning. Child Development, 79, 979-1000.
Jarne, P., & Auld, J. R. (2006). Animals mix it up too: The distribution of self-fertilization among hermaphroditic animals. Evolution, 60, 1816–1824.
Jones, P.R., Moore, D.R., & Amitay, S. (2015). Development of auditory selective attention: Why children struggle to hear in noisy environments. Developmental Psychology, 51(3), 353–369. Retrieved from dx.doi.org/10.1037/a0038570
Kalat, J. W. (2016). Biological Psychology (12th Ed.). Boston, MA: Cengage.
Kaushanskaya, M., Gross, M., & Buac, M. (2014). Effects of classroom bilingualism on task-shifting, verbal memory, and word learning in children. Developmental Science, 17(4), 564-583.
Kellogg, R. (1969). Handbook for Rhoda Kellogg: Child art collection. Washington D. C.: NCR/Microcard Editions.
Kemple, K.M., (1995). Shyness and self-esteem in early childhood. Journal of Humanistic Education and Development, 33(4), 173-182.
Kimmel, M. S. (2008). The gendered society (3rd ed.). Oxford: Oxford University Press.
Kinney, D. K., Barch, D. H., Chayka, B., Napoleon, S., & Munir, K. M. (2009). Environmental risk factors for autism: Do they help or cause de novo genetic mutations that contribute to the disorder? Medical Hypotheses, 74, 102–106.
Kirkorian, H.L., Choi, K., & Pempek, T.A. (2016). Toddlers’ word learning from contingent and noncontingent video on touch screens. Child Development, 87(2), 405–413.
Kirkorian, H.L., Pempek, T.A., & Murphy, L.A. (2009). The impact of background television on parent-child interaction. Child Development, 80, 1350-1359.
Knorr, C. (2017). Gender stereotypes are messing with your kid. Retrieved from https://www.commonsensemedia.org/blog/gender-stereotypes-are-messing-with-your-kid
Kohn, M. L. (1977). Class and conformity. (2nd ed.). Chicago: University of Chicago Press.
Kolb, B. & Whishaw, I. Q. (2011). An introduction to brain and behavior (3rd ed.). New York: Worth Publishers.
Kramer, L., & Gottman, J. M. (1992). Becoming a sibling: “With a little help from my friends.” Developmental Psychology, 28, 685-699.
Lenroot, R. K., & Giedd, J. N. (2006). Brain development in children and adolescents: Insights from anatomical magnetic resonance imaging. Neuroscience and Biobehavioral Reviews, 30, 718-729.
Maccoby, E., & Jacklin, C. (1987). Gender segregation in childhood. Advances in Child Development and Behavior, 20, 239-287.
MacKenzie, M. J., Nicklas, E., Waldfogel, J., & Brooks-Gunn, J. (2013). Spanking and child development across the first decade of life. Pediatrics, 132(5), e1118-e1125.
Madigan, S., Browne, D., Racine, N., Mori, C., & Tough, S. (2019). Association between screen time and children’s performance on a developmental screening test. JAMA Pediatrics, 173(3), 244-250.
Manosevitz, M., Prentice, N. M., & Wilson, F. (1973). Individual and family correlates of imaginary companions in preschool children. Developmental Psychology, 8, 72-79.
Martinson, F. M. (1981). Eroticism in infancy and childhood. In L. L. Constantine & F. M. Martinson (Eds.), Children and sex: New findings, new perspectives. (pp. 23-35). Boston: Little, Brown.
Masih, V. (1978). Imaginary play companions of children. In R. Weizman, R. Brown, P. Levinson, & P. Taylor (Eds.). Piagetian theory and the helping profession (pp. 136-144). Los Angeles: University of Southern California Press.
Mauro, J. (1991). The friend that only I can see: A longitudinal investigation of children’s imaginary companions. Dissertation, University of Oregon.
Mayo Clinic Staff. (2016a). Nutrition for kids: Guidelines for a healthy diet. Retrieved from www.mayoclinic.org/healthy- lifestyle/childrens-health/in-depth/nutrition-for-kids/art-20049335
Mayo Clinic Staff. (2016b). Potty training: How to get the job done. Retrieved from www.mayoclinic.org/healthy- lifestyle/infant-and-toddler-health/indepth/potty-training/art-20045230
McAlister, A. R., & Peterson, C. C. (2007). A longitudinal study of siblings and theory of mind development. Cognitive Development, 22, 258-270.
Meek, S. E., Lemery-Chalfant, K., Jahromi, L. D., & Valiente, C. (2013). A review of gene-environment correlations and their implications for autism: A conceptual model. Psychological Review, 120, 497–521.
Merrick, M. T., Ford, D. C., Ports, K. A., & Guinn, A. S. (2018). Prevalence of adverse childhood experiences from the 2011- 2014 Behavioral Risk Factor Surveillance System in 23 States. Early JAMA Pediatrics, 172(11), 1038-1044.
Meyers-Sutton, C. (2005). Multiple voices: An introduction ot bilingualism. Malden, MA: Blackwell Publishers.
Middlebrooks, J. S., & Audage, N. C. (2008). The effects of childhood stress on health across the lifespan. (United States, Center for Disease Control, National Center for Injury Prevention and Control). Atlanta, GA.
Mischel, W., Ayduk, O., Berman, M. G., Casey, B. J., Gotlib, I. H., Jonides, J., & … Shoda, Y. (2011). ‘Willpower’ over the life span: Decomposing self-regulation. Social Cognitive & Affective Neuroscience, 6(2), 252-256. doi:10.1093/scan/nsq081
Mischel, W., Ebbesen, E. B., & Zeiss, A. R. (1972). Cognitive and attentional mechanisms in delay of gratification. Journal of Personality and Social Psychology, 21, 204–218.
Morra, S., Gobbo, C., Marini, Z., & Sheese, R. (2008). Cognitive development: Neo-Piagetian perspectives. New York: Lawrence Erlbaum Associates.
National Association for the Education of Young Children. (2016). The 10 NAEYC program standards. Retrieved from http://families.naeyc.org/accredited-article/10-naeyc-program-standards
National Institute of Child Health and Human Development. (2006). The NICHD study of early child care (NIH Pub. No. 05- 4318). Washington, DC: Government Printing Office.
Nelson, K., & Fivush, R. (2004). The emergence of autobiographical memory: A social cultural developmental theory. Psychological Review, 111(2), 468-511.
Nelson, K., & Ross, G. (1980). The generalities and specifics of long-term memory in infants and young children. In M. Perlmutter (Ed.), Children’s memory: New directions in child development (Vol. 10, pp. 87-101). San Francisco: Jossey-Bass.
Nielsen Company. (2009). Television audience 2008-2009. Retrieved from blog.nielsen.com/nielsenwire/wp-content/uploads/2009/07/tva_2008_071709.pdf
Novella, S. (2008). The increase in autism diagnoses: Two hypotheses [Web log post]. Retrieved from http://www.sciencebasedmedicine.org/the-increase-in-autism-diagnoses-two-hypotheses/
Okami, P., Olmstead, R., & Abramson, P. R. (1997). Sexual experiences in early childhood: 18-year longitudinal data from UCLA Family Lifestyles Project. Journal of Sex Research, 34(4), 339-347.
Olson, K. R., & Gülgöz, S. (2018). Early findings from the TransYouth Project: Gender development in transgender children. Child Development Perspectives, 12(2), 93-97.
Parten, M. B. (1932). Social participation among preschool children. Journal of Abnormal and Social Psychology, 27, 243-269. Perner, J., Ruffman, T., & Leekam, S. R. (1994). Theory of mind is contagious: You catch from your sibs. Child Development, 65, 1228-1238.
Pike, A., Coldwell, J., & Dunn, J. F. (2005). Sibling relationships in early/middle childhood: Links with individual adjustment. Journal of Family Psychology, 19(4), 523-532.
Place, S., & Hoff, E. (2016). Effects and non-effects of input in bilingual environments on dual language skills in 2 1/2-year-olds. Bilingualism: Language and Cognition, 19, 1023–1041.
Porporino, M., Shore, D.I., Iarocci, G., & Burack, J.A. (2004). A developmental change in selective attention and global form perception. International Journal of Behavioral Development, 28 (4), 358–364 doi:10.1080/01650250444000063
Posner, M.I., & Rothbart, M.K. (2007). Research on attention networks as a model for the integration of psychological science. Annual Review in Psychology, 58, 1–23
Price-Williams, D.R., Gordon, W., & Ramirez, M. (1969). Skill and conservation: A study of pottery making children. Developmental Psychology, 1, 769.
Ram, A., & Ross, H. (2008). “We got to figure it out”: Information-sharing and siblings’ negotiations of conflicts of interest. Social Development, 17, 512-527.
Rice, F. P. (1997). Human development: A life-span approach. Upper Saddle River, NJ: Prentice Hall. Rideout, V.J., & Hamel E. (2006). The media family: Electronic media in the lives of infants, toddlers, preschoolers and their parents. Retrieved from www.kff.org/entmedia/upload/7500.pdf
Robinson, T.N., Wilde, M.L., & Navracruz, L.C. (2001). Effects of reducing children’s television and video game use on aggressive behavior: A randomized controlled trial. Archives of Pediatrics and Adolescent Medicine, 155, 17-23.
Rothbart, M.K., & Rueda, M.R. (2005). The development of effortful control. In U. Mayr, E. Awh, & S.W. Keele (Eds.), Developing individuality in the human brain: A festschrift honoring Michael I. Posner (pp. 167–88). Washington, DC: American Psychological Association
Ruble, D.N., Boggiano, A.K., Feldman, N.S., & Loeble, J.H. (1980). Developmental analysis of the role of social comparison in self-evaluation. Developmental Psychology, 16, 105-115.
Ruble, D. N., Martin, C., & Berenbaum, S. (2006). Gender development. In W. Damon & R. M. Lerner (Series Eds.) & N. Eisenberg (Vol. Ed.), Handbook of child psychology: Vol. 3. Social, emotional, and personality development (6th ed., pp. 858–932). New York, NY: Wiley.
Russo, F. (2016). Debate growing about how to meet the urgent needs of transgender kids. Scientific American Mind, 27(1), 27- 35.
Ryan, C. (2013). Language use in the United States: 2011. Retrieved from https://www2.census.gov/library/publications/2013/acs/acs-22/acs-22.pdf
Save the Children. (2019). Child protection. Retrived from https://www.savethechildren.net/what-we-do/child-protection
Schmidt, M.E., Pempek, T.A., & Kirkorian, H.L. (2008). The effects of background television on the toy play behavior of very young children. Child Development, 79, 1137-1151.
Schneider, W., Kron-Sperl, V., & Hunnerkopf, M. (2009). The development of young children’s memory strategies: Evidence from the Würzburg longitudinal memory study. European Journal of Developmental Psychology, 6(1), 70-99.
Schwartz, I. M. (1999). Sexual activity prior to coitus initiation: A comparison between males and females. Archives of Sexual Behavior, 28(1), 63-69.
Shahaeian, A., Peterson, C. C., Slaughter, V., & Wellman, H. M. (2011). Culture and the sequence of steps in theory of mind development. Developmental Psychology, 47(5), 1239-1247.
Singer, D., & Singer, J. (1990). The house of make-believe. Cambridge, MA: Harvard University Press.
Society for Research in Child Development. (2018). The Science is clear: Separating families has long-term damaging psychological and health consequences for children, families, and communities. Retrieved from https://www.srcd.org/policy-media/statements-evidence
Spears Brown, C., & Jewell, J. A. (2018). Gender. Retrieved from https://nobaproject.com/modules/gender
Steele, B.F. (1986). Notes on the lasting effects of early child abuse throughout the life cycle. Child Abuse & Neglect 10(3), 283-291.
Tamana, S.K., Ezeugwu, E., Chikuma, J., Lefebvre, D.L., Azad, M.B., Moraes, T.J.,… & Mandhane, P. J. (2019). Screen-time is associated with inattention problems in preschoolers: Results from the CHILD birth cohort study. PLOS ONE, 14(4), e0213995. Retrieved from https://journals.plos.org/plosone/ar...l.pone.0213995
Thomas, R. M. (1979). Comparing theories of child development. Santa Barbara, CA: Wadsworth.
Traverso, L., Viterbori, P., & Usai, M. C. (2015). Improving executive function in childhood: Evaluation of a training intervention for 5-year-old children. Frontiers in Psychology, 6, 1-14. doi:10.3389/fpsyg.2015.00525
United Nations. (2014). Committee on the rights of the child. Retrieved from http://tbinternet.ohchr.org/Treaties/CRC/Shared%20Documents/VAT/CRC_C_VAT_CO_2_16302_E.pdf
United States Department of Health and Human Services. (2019). Child Maltreatment 2017. Retrieved from https://www.acf.hhs.gov/cb/resource/child-maltreatment-2017
United States Department of Health and Human Services. (2015). Head Start program facts fiscal year 2013. Retrieved from eclkc.ohs.acf.hhs.gov/hslc/data/factsheets/docs/hs-program-fact-sheet-2013.pdf
Valente, S. M. (2005). Sexual abuse of boys. Journal of Child and Adolescent Psychiatric Nursing, 18, 10–16. doi:10.1111/j.1744-6171.2005.00005.x
Wellman, H.M., Cross, D., & Watson, J. (2001). Meta-analysis of theory of mind development: The truth about false belief. Child Development, 72(3), 655-684.
Wellman, H. M., Fang, F., Liu, D., Zhu, L, & Liu, L. (2006). Scaling theory of mind understandings in Chinese children. Psychological Science, 17, 1075-1081.
White House Press Secretary. (2014). Fact Sheet: Invest in US: The White House Summit on Early Childhood Education. Retrieved from https://www.whitehouse.gov/the-press-office/2014/12/10/fact-sheet-invest-us-white-house-summit-early-childhood-education
Wimmer, H., & Perner, J. (1983). Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children’s understanding of deception. Cognition, 13, 103–128.
Wing, L., Gould, J., & Gillberg, C. (2011). Autism spectrum disorders in the DSM-5: Better or worse than the DSM IV? Research in Developmental Disabilities, 32, 768–773.
Wu, X., Tao, S., Rutayisirel, E., Chen, Y., Huang, K., & Tao, F. (2017). The relationship between screen time, nighttime sleep duration, and behavioral problems in preschool children in China. European Child and Adolescent Psychiatry, 26, 541– 548.
Yoo, J., & Kaushanskaya, M. (2012). Phonological memory in bilinguals and monolinguals. Memory & Cognition, 40, 1314– 1330.
Zachry, A. (2013). 6 Types of Preschool Programs. Retrieved from www.parents.com/toddlers-preschoolers/starting – preschool/preparing/types-of-preschool-programs/
Attribution
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Chapter 16 Learning Objectives
• Summarize the overall physical growth
• Describe the changes in brain maturation
• Describe the positive effects of sports
• Describe reasons for a lack of participation in youth sports
• Explain current trends regarding being overweight in childhood, the negative consequences of excess weight, the lack of recognition of being overweight, and interventions to normalize weight
Overall Physical Growth: Rates of growth generally slow during these years. Typically, a child will gain about 5-7 pounds a year and grow about 2-3 inches per year (CDC, 2000). They also tend to slim down and gain muscle strength and lung capacity making it possible to engage in strenuous physical activity for long periods of time. The beginning of the growth spurt, which occurs prior to puberty, begins two years earlier for females than males. The mean age for the beginning of the growth spurt for girls is nine, while for boys it is eleven. Children of this age tend to sharpen their abilities to perform both gross motor skills, such as riding a bike, and fine motor skills, such as cutting their fingernails. In gross motor skills (involving large muscles) boys typically outperform girls, while with fine motor skills (small muscles) girls outperform the boys. These improvements in motor skills are related to brain growth and experience during this developmental period.
Brain Growth: Two major brain growth spurts occur during middle/late childhood (Spreen, Riser, & Edgell, 1995). Between ages 6 and 8, significant improvements in fine motor skills and eye-hand coordination are noted. Then between 10 and 12 years of age, the frontal lobes become more developed and improvements in logic, planning, and memory are evident (van der Molen & Molenaar, 1994). Myelination is one factor responsible for these growths. From age 6 to 12, the nerve cells in the association areas of the brain, that is those areas where sensory, motor, and intellectual functioning connect, become almost completely myelinated (Johnson, 2005). This myelination contributes to increases in information processing speed and the child’s reaction time. The hippocampus, responsible for transferring information from the short-term to long- term memory, also show increases in myelination resulting in improvements in memory functioning (Rolls, 2000). Children in middle to late childhood are also better able to plan, coordinate activity using both left and right hemispheres of the brain, and to control emotional outbursts. Paying attention is also improved as the prefrontal cortex matures (Markant & Thomas, 2013).
Sports
children. The U. S. Soccer Federation recently advised coaches to reduce the amount of drilling engaged in during practice and to allow children to play more freely and to choose their own positions. The hope is that this will build on their love of the game and foster their natural talents.
• Higher levels of satisfaction with family and overall quality of life in children
• Improved physical and emotional development
• Better academic performance
Figure 5.2
Figure 5.3 Percent of Students Participating in Organized Sports, by Gender, Race, and Ethnicity
Finally, Sabo and Veliz asked children who had dropped out of organized sports why they left. For both girls and boys, the number one answer was that it was no longer any fun (see Table 5.1). According to the Sport Policy and Research Collaborative (SPARC) (2013), almost 1 in 3 children drop out of organized sports, and while there are many factors involved in the decisions to drop out, one suggestion has been the lack of training that coaches of children’s sports receive may be contributing to this attrition (Barnett, Smoll & Smith, 1992). Several studies have found that when coaches receive proper training, the drop-out rate is about 5% instead of the usual 30% (Fraser-Thomas, Côté , & Deakin, 2005; SPARC, 2013).
Table 5.1 Top Reasons Dropped Out or Stopped Playing Organized/Team Sports
Welcome to the world of esports: According to Discover Esports (2017), esports is a form of competition with the medium being video games. Players use computers or specific video game consoles to play video games against each other. In addition to playing themselves, children my just watch others play the video games. The recent SPARC (2016) report on the “State of Play” in the United States highlights a disturbing trend. One in four children between the ages of 5 and 16 rate playing computer games with their friends as a form of exercise. Over half of males and about 20% of females, aged 12-19, say they are fans of esports.
Physical Education: For many children, physical education in school is a key component in introducing children to sports. After years of schools cutting back on physical education programs, there has been a turn around, prompted by concerns over childhood obesity and the related health issues. Despite these changes, currently only the state of Oregon and the District of Columbia meet PE guidelines of a minimum of 150 minutes per week of physical activity in elementary school and 225 minutes in middle school (SPARC, 2016).
Childhood Obesity
harmful substances that can impair its functioning. Another important executive functioning skill is controlling impulses and delaying gratification. Children who are overweight show less inhibitory control than normal weight children, which may make it more difficult for them to avoid unhealthy foods (Lu, 2016). Overall, being overweight as a child increases the risk for cognitive decline as one ages.
Figure 5.4 Being Overweight can be a Lifelong Struggle
children (Lu, 2016). Parents should take caution against emphasizing diet alone to avoid the development of any obsession about dieting that can lead to eating disorders. Instead, increasing a child’s activity level is most helpful.
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/08%3A_Development_in_Middle_Childhood/8.01%3A_Chapter_16-_Physical_Development_in_Middle_Childhood.txt |
Chapter 17 Learning Objectives
• Describe Piaget’s concrete operational stage and the characteristics of concrete thought
• Describe information processing research on memory, attention, knowledgebase, metacognition, and critical thinking
• Describe language development and explain the three types of communication disorders
• Describe the theories of intelligence, including general “g”, triarchic theory, and Gardner’s multiple intelligences
• Explain how intelligence is measured, the tests used to assess intelligence, the extremes in intelligence, and the concern of bias
• Describe how language and culture influence the typical classroom
• Identify common disabilities in childhood and the legislation that protects them educationally
Additionally, they can process complex ideas such as addition and subtraction and cause-and-effect relationships.
Concrete Operational Thought
Classification: As children’s experiences and vocabularies grow, they build schemata and are able to organize objects in many different ways. They also understand classification hierarchies and can arrange objects into a variety of classes and subclasses.
Identity: One feature of concrete operational thought is the understanding that objects have qualities that do not change even if the object is altered in some way. For instance, the mass of an object does not change by rearranging it. A piece of chalk is still chalked even when the piece is broken in two.
Reversibility: The child learns that some things that have been changed can be returned to their original state. Water can be frozen and then thawed to become liquid again, but eggs cannot be unscrambled. Arithmetic operations are reversible as well: 2 + 3 = 5 and 5 – 3 = 2. Many of these cognitive skills are incorporated into the school’s curriculum through mathematical problems and in worksheets about which situations are reversible or irreversible.
Conservation: Remember the example in our last chapter of preoperational children thinking that a tall beaker filled with 8 ounces of water was “more” than a short, wide bowl filled with 8 ounces of water? Concrete operational children can understand the concept of conservation which means that changing one quality (in this example, height or water level) can be compensated for by changes in another quality (width). Consequently, there is the same amount of water in each container, although one is taller and narrower and the other is shorter and wider.
Decentration: Concrete operational children no longer focus on only one dimension of any object (such as the height of the glass) and instead consider the changes in other dimensions too (such as the width of the glass). This allows for conservation to occur.
Seriation: Arranging items along a quantitative dimension, such as length or weight, in a methodical way is now demonstrated by the concrete operational child. For example, they can methodically arrange a series of different-sized sticks in order by length, while younger children approach a similar task in a haphazard way.
experiments, most children younger than 12 perform biased experiments from which no conclusions can be drawn (Inhelder & Piaget, 1958).
Information Processing
Working Memory: The capacity of working memory expands during middle and late childhood, and research has suggested that both an increase in processing speed and the ability to inhibit irrelevant information from entering memory are contributing to the greater efficiency of working memory during this age (de Ribaupierre, 2002). Changes in myelination and synaptic pruning in the cortex are likely behind the increase in processing speed and ability to filter out irrelevant stimuli (Kail, McBride-Chang, Ferrer, Cho, & Shu, 2013).
Attention: As noted above, the ability to inhibit irrelevant information improves during this age group, with there being a sharp improvement in selective attention from age six into adolescence (Vakil, Blachstein, Sheinman, & Greenstein, 2009). Children also improve in their ability to shift their attention between tasks or different features of a task (Carlson, Zelazo, & Faja, 2013). A younger child who is asked to sort objects into piles based on type of object, car versus animal, or color of object, red versus blue, may have difficulty if you switch from asking them to sort based on type to now having them sort based on color. This requires them to suppress the prior sorting rule. An older child has less difficulty making the switch, meaning there is greater flexibility in their attentional skills. These changes in attention and working memory contribute to children having more strategic approaches to challenging tasks.
Memory Strategies: Bjorklund (2005) describes a developmental progression in the acquisition and use of memory strategies. Such strategies are often lacking in younger children but increase in frequency as children progress through elementary school. Examples of memory strategies include rehearsing information you wish to recall, visualizing and organizing information, creating rhymes, such “i” before “e” except after “c”, or inventing acronyms, such as “roygbiv” to remember the colors of the rainbow. Schneider, Kron-Sperl, and Hünnerkopf (2009) reported a steady increase in the use of memory strategies from ages six to ten in their longitudinal study (see Table 5.2). Moreover, by age ten many children were using two or more memory strategies to help them recall information. Schneider and colleagues found that there were considerable individual differences at each age in the use of strategies, and that children who utilized more strategies had better memory performance than their same aged peers.
Knowledge Base: During middle and late childhood, children are able to learn and remember due to an improvement in the ways they attend to and store information. As children enter school and learn more about the world, they develop more categories for concepts and learn more efficient strategies for storing and retrieving information. One significant reason is that they continue to have more experiences on which to tie new information. In other words, their knowledge base, knowledge in particular areas that makes learning new information easier, expands (Berger, 2014).
Metacognition: Children in middle and late childhood also have a better understanding of how well they are performing a task, and the level of difficulty of a task. As they become more realistic about their abilities, they can adapt studying strategies to meet those needs. Young children spend as much time on an unimportant aspect of a problem as they do on the main point, while older children start to learn to prioritize and gauge what is significant and what is not. As a result, they develop metacognition. Metacognition refers to the knowledge we have about our own thinking and our ability to use this awareness to regulate our own cognitive processes (Bruning, Schraw, Norby, & Ronning, 2004).
Critical Thinking: According to Bruning et al. (2004) there is a debate in U.S. education as to whether schools should teach students what to think or how to think. Critical thinking, or a detailed examination of beliefs, courses of action, and evidence, involves teaching children how to think. The purpose of critical thinking is to evaluate information in ways that help us make informed decisions. Critical thinking involves better understanding a problem through gathering, evaluating, and selecting information, and also by considering many possible solutions. Ennis (1987) identified several skills useful in critical thinking. These include: Analyzing arguments, clarifying information, judging the credibility of a source, making value judgements, and deciding on an action. Metacognition is essential to critical thinking because it allows us to reflect on the information as we make decisions.
Language Development
Vocabulary: One of the reasons that children can classify objects in so many ways is that they have acquired a vocabulary to do so. By fifth grade, a child’s vocabulary has grown to 40,000 words. It grows at a rate that exceeds that of those in early childhood. This language explosion, however, differs from that of younger children because it is facilitated by being able to associate new words with those already known, and because it is accompanied by a more sophisticated understanding of the meanings of a word.
New Understanding: Those in middle and late childhood are also able to think of objects in less literal ways. For example, if asked for the first word that comes to mind when one hears the word “pizza”, the younger child is likely to say “eat” or some word that describes what is done with a pizza. However, the older child is more likely to place pizza in the appropriate category and say “food”. This sophistication of vocabulary is also evidenced by the fact that older children tell jokes and delight in doing do. They may use jokes that involve plays on words such as “knock- knock” jokes or jokes with punch lines. Young children do not understand play on words and tell “jokes” that are literal or slapstick, such as “A man fell down in the mud! Isn’t that funny?”
Grammar and Flexibility: Older children are also able to learn new rules of grammar with more flexibility. While younger children are likely to be reluctant to give up saying “I goed there”, older children will learn this rather quickly along with other rules of grammar.
Communication Disorders
At the end of early childhood, children are often assessed in terms of their ability to speak properly. By first grade, about 5% of children have a notable speech disorder (Medline Plus, 2016c).
persist as a lifelong communication disorder (National Institute on Deafness and other Communication Disorders, NIDCD, 2016). This is called developmental stuttering and is the most common form of stuttering. Brain injury, and in very rare instances, emotional trauma may be other triggers for developing problems with stuttering. In most cases of developmental stuttering, other family members share the same communication disorder. Researchers have recently identified variants in four genes that are more commonly found in those who stutter (NIDCD, 2016).
Articulation disorder: An articulation disorder refers to the inability to correctly produce speech sounds (phonemes) because of imprecise placement, timing, pressure, speed, or flow of movement of the lips, tongue, or throat (NIDCD, 2016). Sounds can be substituted, left off, added or changed. These errors may make it hard for people to understand the speaker. They can range from problems with specific sounds, such as lisping to severe impairment in the phonological system. Most children have problems pronouncing words early on while their speech is developing. However, by age three, at least half of what a child says should be understood by a stranger. By age five, a child’s speech should be mostly intelligible. Parents should seek help if by age six the child is still having trouble producing certain sounds. It should be noted that accents are not articulation disorders (Medline Plus, 2016a).
Voice disorders: Disorders of the voice involve problems with pitch, loudness, and quality of the voice (American Speech-Language and Hearing Association, 2016). It only becomes a disorder when problems with the voice makes the child unintelligible. In children, voice disorders are significantly more prevalent in males than in females. Between 1.4% and 6% of children experience problems with the quality of their voice. Causes can be due to structural abnormalities in the vocal cords and/or larynx, functional factors, such as vocal fatigue from overuse, and in rarer cases psychological factors, such as chronic stress and anxiety.
Theories of Intelligence
General (g) versus Specific (s) Intelligences: From 1904-1905 the French psychologist Alfred Binet (1857–1914) and his colleague Théodore Simon (1872–1961) began working on behalf of the French government to develop a measure that would identify children who would not be successful with the regular school curriculum. The goal was to help teachers better educate these students (Aiken, 1994). Binet and Simon developed what most psychologists today regard as the first intelligence test, which consisted of a wide variety of questions that included the ability to name objects, define words, draw pictures, complete sentences, compare items, and construct sentences.
Triarchic Theory: One advocate of the idea of multiple intelligences is the psychologist Robert Sternberg. Sternberg has proposed a triarchic (three-part) theory of intelligence that proposes that people may display more or less analytical intelligence, creative intelligence, and practical intelligence. Sternberg (1985, 2003) argued that traditional intelligence tests assess analytical intelligence, academic problem solving and performing calculations, but that they do not typically assess creative intelligence, the ability to adapt to new situations and create new ideas, and/or practical intelligence, the ability to demonstrate common sense and street-smarts.
As Sternberg proposed, research has found that creativity is not highly correlated with analytical intelligence (Furnham & Bachtiar, 2008) and exceptionally creative scientists, artists, mathematicians, and engineers do not score higher on intelligence than do their less, creative peers (Simonton, 2000).
Table 5.3
Theory of Multiple Intelligences: Another champion of the idea of specific types of intelligences rather than one overall intelligence is the psychologist Howard Gardner (1983, 1999). Gardner argued that it would be evolutionarily functional for different people to have different talents and skills and proposed that there are eight intelligences that can be differentiated from each other. A potential ninth intelligence; that is, existential still needs empirical support. Gardner investigated intelligences by focusing on children who were talented in one or more areas and adults who suffered from strokes that compromised some capacities, but not others. Gardner also noted that some evidence for multiple intelligences comes from the abilities of autistic savants, people who score low on intelligence tests overall, but who nevertheless may have exceptional skills in a given domain, such as math, music, art, or in being able to recite statistics in a given sport (Treffert & Wallace, 2004). In addition to brain damage and the existence of savants, Gardner identified these 8 intelligences based on other criteria including a set developmental history and psychometric findings. See Table 5.4 for a list of Gardner’s eight specific intelligences.
Table 5.4
and so forth also separate intelligences? Furthermore, and again demonstrating the underlying power of a single intelligence, the many different intelligences are, in fact, correlated and thus represent, in part, “g” (Brody, 2003).
Measuring Intelligence: Standardization and the Intelligence Quotient
IQ = mental age ÷ chronological age × 100.
Thus a 10-year-old child who does as well as the average 10-year-old child has an IQ of 100 (10 ÷ 10 × 100), whereas an 8-year-old child who does as well as the average 10-year-old child would have an IQ of 125 (10 ÷ 8 × 100). Most modern intelligence tests are based on the relative position of a person’s score among people of the same age, rather than on the basis of this formula, but the idea of an intelligence “ratio” or “quotient” provides a good description of the score’s meaning.
Wechsler Scales: A number of scales are based on the IQ. The Wechsler Adult lntelligence Scale (WAIS) is the most widely used intelligence test for adults (Watkins, Campbell, Nieberding, & Hallmark, 1995). The current version of the WAIS, the WAIS-IV, was standardized on 2,200 people ranging from 16 to 90 years of age. It consists of 15 different tasks, each designed to assess intelligence, including working memory, arithmetic ability, spatial ability, and general knowledge about the world. The WAIS-IV yield scores on four domains: verbal, perceptual, working memory, and processing speed. The reliability of the test is high (more than 0.95), and it shows substantial construct validity. The WAIS-IV is correlated highly with other IQ tests such as the Stanford-Binet, as well as with criteria of academic and life success, including college grades, measures of work performance, and occupational level. It also shows significant correlations with measures of everyday functioning among people with intellectual disabilities.
Figure 5.11
Bias: Intelligence tests and psychological definitions of intelligence have been heavily criticized since the 1970s for being biased in favor of Anglo-American, middle-class respondents and for being inadequate tools for measuring non-academic types of intelligence or talent. Intelligence changes with experience, and intelligence quotients or scores do not reflect that ability to change. What is considered smart varies culturally as well, and most intelligence tests do not take this variation into account. For example, in the West, being smart is associated with being quick. A person who answers a question the fastest is seen as the smartest, but in some cultures being smart is associated with considering an idea thoroughly before giving an answer. A well- thought out, the contemplative answer is the best answer.
Extremes of Intelligence: Intellectual Disability and Giftedness
Figure 5.12
Stanford-Binet and similar IQ tests (i.e., who had IQs of about 135 or higher), and tracked them for more than seven decades (the children became known as the “termites” and are still being studied today). This study found that these students were not unhealthy or poorly adjusted, but rather were above average in physical health and were taller and heavier than individuals in the general population. The students also had above-average social relationships and were less likely to divorce than the average person (Seagoe, 1975).
Education
Gender: The stereotypes held by parents and teachers can influence children’s self-efficacy in various domains. For example, teachers who hold the view that girls are better at reading (Retelsdorf, Schwartz, & Asbrock, 2015) or boys are better at math (Plante, de la Sablonnière, Aronson, & Théorêt, 2013) often find that their students’ performance in these areas mirror these stereotypes, despite the children’s actual ability, or the ability of children in the classrooms of teachers who do not hold such stereotypes. While not all children will internalize the views of others, those who do are more likely to show declines in their performance consistent with the stereotypes (Plante, et al., 2013; Retelsdorf et al., 2015).
Parental Involvement in School: Parents vary in their level of involvement with their children’s schools. Teachers often complain that they have difficulty getting parents to participate in their child’s education and devise a variety of techniques to keep parents in touch with daily and overall progress. For example, parents may be required to sign a behavior chart each evening to be returned to school or may be given information about the school’s events through websites and newsletters. There are other factors that need to be considered when looking at parental involvement. To explore these, first ask yourself if all parents who enter the school with concerns about their child be received in the same way?
ability to dialogue with parents about school policies in more open ways. Any efforts to improve effective parental involvement should address these concerns.
Cultural Differences in the Classroom
Bilingualism: In 2013, approximately 20% of school aged children and adolescents spoke a language other than English in the home (Camarota & Zeigler, 2014). The majority of bilingual students speak Spanish, but the rest represent more than three hundred different language groups from around the world. In larger communities throughout the United States, it is therefore common for a single classroom to contain students from several language backgrounds at once. In classrooms, as in other social settings, bilingualism exists in different forms and degrees. At one extreme are students who speak both English and another language fluently; at the other extreme are those who speak only limited versions of both languages. In between are students who speak their home (or heritage) language much better than English, as well as others who have partially lost their heritage language in the process of learning English (Tse, 2001). Commonly, a student may speak a language satisfactorily, but be challenged by reading or writing it. Whatever the case, each bilingual student poses unique challenges to teachers.
• In some cultures, it is considered polite or even intelligent not to speak unless you have something truly important to say. Chitchat, or talk that simply affirms a personal tie between people, is considered immature or intrusive (Minami, 2002). In a classroom, this habit can make it easier for a child to learn not to interrupt others, but it can also make the child seem unfriendly.
• Eye contact varies by culture. In many African American and Latin American communities, it is considered appropriate and respectful for a child not to look directly at an adult who is speaking to them (Torres-Guzman, 1998). In classrooms, however, teachers often expect a lot of eye contact (as in “I want all eyes on me!”) and may be tempted to construe lack of eye contact as a sign of indifference or disrespect.
• Social distance varies by culture. In some cultures, it is common to stand relatively close when having a conversation; in others, it is more customary to stand relatively far apart (Beaulieu, 2004). Problems may happen when a teacher and a student prefer different social distances. A student who expects a closer distance than does the teacher may seem overly familiar or intrusive, whereas one who expects a longer distance may seem overly formal or hesitant.
• Wait time varies by culture. Wait time is the gap between the end of one person’s comment or question and the next person’s reply or answer. In some cultures wait time is relatively long, as long as three or four seconds (Tharp & Gallimore, 1989). In others it is a negative gap, meaning that it is acceptable, even expected, for a person to interrupt before the end of the previous comment. In classrooms the wait time is customarily about one second; after that, the teacher is likely to move on to another question or to another student. A student who habitually expects a wait time longer than one second may seem hesitant, and not be given many chances to speak. A student who expects a negative wait time, on the other hand, may seem overeager or even rude.
• In most non-Anglo cultures, questions are intended to gain information, and it is assumed that a person asking the question truly does not have the information requested (Rogoff, 2003). In most classrooms, however, teachers regularly ask test questions, which are questions to which the teacher already knows the answer and that simply assess whether a student knows the answer as well (Macbeth, 2003). The question: “How much is 2 + 2?” for example, is a test question. If the student is not aware of this purpose, he or she may become confused, or think that the teacher is surprisingly ignorant. Worse yet, the student may feel that the teacher is trying deliberately to shame the student by revealing the student’s ignorance or incompetence to others.
• Preference for activities that are cooperative rather than competitive. Many activities in school are competitive, even when teachers try to de-emphasize the competition. Once past the first year or second year of school, students often become attentive to who receives the highest marks on an assignment, for example, or who is the best athlete at various sports or whose contributions to class discussions gets the most verbal recognition from the teacher (Johnson & Johnson, 1998). A teacher deliberately organizes important activities or assignments competitively, as in “Let’s see who finishes the math sheet first”. Classroom life can then become explicitly competitive, and the competitive atmosphere can interfere with cultivating supportive relationships among students or between students and the teacher (Cohen, 2004). For students who give priority to these relationships, competition can seem confusing at best and threatening at worst. A student may wonder, “What sort of sharing or helping with answers is allowed?” The answer to this question may be different depending on the cultural background of the student and teacher. What the student views as cooperative sharing may be seen by the teacher as laziness, freeloading, or even cheating.
Figure 5.1
Children with Disabilities
essential in that person’s life (as when they are working rather than going to school) these disabilities may no longer be noticed or relevant, depending on the person’s job and the extent of the disability.
Dyslexia is one of the most commonly diagnosed disabilities and involves having difficulty in the area of reading. This diagnosis is used for a number of reading difficulties. Common characteristics are difficulty with phonological processing, which includes the manipulation of sounds, spelling, and rapid visual/verbal processing. Additionally, the child may reverse letters, have difficulty reading from left to right, or may have problems associating letters with sounds. It appears to be rooted in neurological problems involving the parts of the brain active in recognizing letters, verbally responding, or being able to manipulate sounds. Recent studies have identified a number of genes that are linked to developing dyslexia (National Institute of Neurological Disorders and Stroke, 2016). Treatment typically involves altering teaching methods to accommodate the person’s particular problematic area.
Dysgraphia refers to a writing disability that is often associated with dyslexia (Carlson, 2013). There are different types of dysgraphia, including phonological dysgraphia when the person cannot sound out words and write them phonetically. Orthographic dysgraphia is demonstrated by those individuals who can spell regularly spelled words, but not irregularly spelled ones. Some individuals with dysgraphia experience difficulties in motor control and experience trouble forming letters when using a pen or pencil.
Dyscalculia refers to problems in math. Cowan and Powell (2014) identified several terms used when describing difficulties in mathematics including dyscalculia, mathematical learning disability, and mathematics disorder. All three terms refer to students with average intelligence who exhibit poor academic performance in mathematics. When evaluating a group of third graders, Cowan and Powell (2014) found that children with dyscalculia demonstrated problems with working memory, reasoning, processing speed and oral language, all of which are referred to as domain-general factors. Additionally, problems with multi-digit skills, including number system knowledge, were also exhibited.
movement and includes fidgeting or squirming, leaving one’s seat in situations when remaining seated is expected, having trouble sitting still (e.g., in a restaurant), running about and climbing on things, blurting out responses before another person’s question or statement has been completed, difficulty waiting for one’s turn for something, and interrupting and intruding on others. Frequently, the hyperactive child comes across as noisy and boisterous. The child’s behavior is hasty, impulsive, and seems to occur without much forethought; these characteristics may explain why adolescents and young adults diagnosed with ADHD receive more traffic tickets and have more automobile accidents than do others their age (Thompson, Molina, Pelham, & Gnagy, 2007).
Children with ADHD face severe academic and social challenges. Compared to their non-ADHD counterparts, children with ADHD have lower grades and standardized test scores and higher rates of expulsion, grade retention, and dropping out. They also are less well-liked and more often rejected by their peers (Hoza et al., 2005).
Additional concerns when an adult has ADHD include Worse educational attainment, lower socioeconomic status, less likely to be employed, more likely to be divorced, and more likely to have non-alcohol-related substance abuse problems (Klein et al., 2012).
Etiology of ADHD: Family and twin studies indicate that genetics play a significant role in the development of ADHD. Burt (2009), in a review of 26 studies, reported that the median rate of concordance for identical twins was .66, whereas the median concordance rate for fraternal twins was .20. The specific genes involved in ADHD are thought to include at least two that are important in the regulation of the neurotransmitter dopamine (Gizer, Ficks, & Waldman, 2009), suggesting that dopamine may be important in ADHD. Indeed, medications used in the treatment of ADHD, such as methylphenidate (Ritalin) and amphetamine with dextroamphetamine (Adderall), have stimulant qualities and elevate dopamine activity. People with ADHD show less dopamine activity in key regions of the brain, especially those associated with motivation and reward (Volkow et al., 2009), which provides support to the theory that dopamine deficits may be a vital factor in the development this disorder (Swanson et al., 2007).
Treatment for ADHD: Recommended treatment for ADHD includes behavioral interventions, cognitive behavioral therapy, parent and teacher education, recreational programs, and lifestyle changes, such as getting more sleep (Clay, 2013). For some children, medication is prescribed. Parents are often concerned that stimulant medication may result in their child acquiring a substance use disorder. However, research using longitudinal studies has demonstrated that children diagnosed with ADHD who received pharmacological treatment had a lower risk for substance abuse problems than those children who did not receive medication (Wilens, Fararone, Biederman, & Gunawardene, 2003). The risk of substance abuse problems appears to be even greater for those with ADHD who are un-medicated and also exhibit antisocial tendencies (Marshal & Molina, 2006).
Is the prevalence rate of ADHD increasing? Many people believe that the rates of ADHD have increased in recent years, and there is evidence to support this contention. In a recent study, investigators found that the parent-reported prevalence of ADHD among children (4–17 years old) in the United States increased by 22% during a 4-year period, from 7.8% in 2003 to 9.5% in 2007 (CDC, 2010). ADHD may be over-diagnosed by doctors who are too quick to medicate children as behavior treatment. There is also greater awareness of ADHD now than in the past. Nearly everyone has heard of ADHD, and most parents and teachers are aware of its key symptoms. Thus, parents may be quick to take their children to a doctor if they believe their child possesses these symptoms, or teachers may be more likely now than in the past to notice the symptoms and refer the child for evaluation. Further, the use of computers, video games, iPhones, and other electronic devices has become pervasive among children in the early 21st century, and these devices could potentially shorten children’s attention spans.
Children with Disabilities: Legislation
Rehabilitation Act of 1973, Section 504: This law, the first of its kind, required that individuals with disabilities be accommodated in any program or activity that receives Federal funding (PL 93-112, 1973). Although this law was not intended specifically for education, in practice it has protected students’ rights in some extra-curricular activities (for older students) and in some child care or after-school care programs (for younger students). If those programs receive Federal funding of any kind, the programs are not allowed to exclude children or youths with disabilities, and they have to find reasonable ways to accommodate the individuals’ disabilities.
Americans with Disabilities Act of 1990 (or ADA): This legislation also prohibited discrimination on the basis of disability, just as Section 504 of the Rehabilitation Act had done (PL 101-336, 1990). Although the ADA also applies to all people (not just to students), its provisions are more specific and “stronger” than those of Section 504. In particular, ADA extends to all employment and jobs, not just those receiving Federal funding. It also specifically requires accommodations to be made in public facilities such as with buses, restrooms, and telephones. ADA legislation is therefore responsible for some of the “minor” renovations in schools that you may have noticed in recent years, like wheelchair-accessible doors, ramps, and restrooms, and public telephones with volume controls.
Individuals with Disabilities Education Act (or IDEA): As its name implied, this legislation was more focused on education than either Section 504 or ADA. It was first passed in 1975, reauthorized in 2004 (PL 108-446, 2004), and most recently amended in 2015 through Public Law 114-95, as the Every Student Succeeds Act (United States Department of Education, 2017). In its current form, the law guarantees the following rights related to education for anyone with a disability from birth to age 21. The first two influence schooling in general, but the last three affect the work of classroom teachers rather directly:
• Free, appropriate education: An individual or an individual’s family should not have to pay for education simply because the individual has a disability, and the educational program should be truly educational; i.e., not merely care-taking or babysitting the person.
• Due process: In case of disagreements between an individual with a disability and the schools or other professionals, there must be procedures for resolving the disagreements that are fair and accessible to all parties, including the person himself or herself or the person’s representative.
• A fair evaluation of performance in spite of disability: Tests or other evaluations should not assume test-taking skills that a person with a disability cannot reasonably be expected to have, such as holding a pencil, hearing or seeing questions, working quickly, or understanding and speaking orally. Evaluation procedures should be modified to allow for these differences. This provision of the law applies both to evaluations made by teachers and to school-wide or “high-stakes” testing programs.
• Education in the “least restrictive environment”: Education for someone with a disability should provide as many educational opportunities and options for the person as possible, both in the short term and in the long term. In practice, this requirement has meant including students in regular classrooms and school activities as much as possible, though often not totally.
• An individualized educational program (IEP): Given that every disability is unique, instructional planning for a person with a disability should be unique or individualized as well. In practice this provision has led to classroom teachers planning individualized programs jointly with other professionals (like reading specialists, psychologists, or medical personnel) as part of a team.
• Attribution
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Chapter 18 Learning Objectives
• Describe Erikson’s fourth stage of industry vs. inferiority
• Describe the changes in self-concept, self-esteem, and self-efficacy
• Explain Kohlberg’s stages of moral development
• Describe the importance of peers, the stages of friendships, peer acceptance, and the consequences of peer acceptance
• Describe bullying, cyberbullying and the consequences of bullying
• Identify the types of families where children reside
• Identify the five family tasks
• Explain the consequences of divorce on children
• Describe the effects of cohabitation and remarriage on children
• Describe the characteristics and developmental stages of blended families
Kohlberg’s Stages of Moral Development
A man’s wife is dying of cancer and there is only one drug that can save her. The only place to get the drug is at the store of a pharmacist who is known to overcharge people for drugs. The man can only pay \$1,000, but the pharmacist wants \$2,000, and refuses to sell it to him for less, or to let him pay later. Desperate, the man later breaks into the pharmacy and steals the medicine. Should he have done that? Was it right or wrong? Why? (Kohlberg, 1984)
Level One-Preconventional Morality: In stage one, moral reasoning is based on concepts of punishment. The child believes that if the consequence for an action is punishment, then the action was wrong. In the second stage, the child bases his or her thinking on self-interest and reward. “You scratch my back, I’ll scratch yours.” The youngest subjects seemed to answer based on what would happen to the man as a result of the act. For example, they might say the man should not break into the pharmacy because the pharmacist might find him and beat him. Or they might say that the man should break in and steal the drug and his wife will give him a big kiss. Right or wrong, both decisions were based on what would physically happen to the man as a result of the act. This is a self-centered approach to moral decision-making. He called this most superficial understanding of right and wrong pre-conventional morality. Preconventional morality focuses on self-interest. Punishment is avoided, and rewards are sought. Adults can also fall into these stages, particularly when they are under pressure.
Level Two-Conventional Morality: Those tested who based their answers on what other people would think of the man as a result of his act, were placed in Level Two. For instance, they might say he should break into the store, and then everyone would think he was a good husband, or he should not because it is against the law. In either case, right and wrong is determined by what other people think. In stage three, the person wants to please others. At stage four, the person acknowledges the importance of social norms or laws and wants to be a good member of the group or society. A good decision is one that gains the approval of others or one that complies with the law. This he called conventional morality, people care about the effect of their actions on others. Some older children, adolescents, and adults use this reasoning.
Level Three-Postconventional Morality: Right and wrong are based on social contracts established for the good of everyone and that can transcend the self and social convention. For example, the man should break into the store because, even if it is against the law, the wife needs the drug and her life is more important than the consequences the man might face for breaking the law. Alternatively, the man should not violate the principle of the right of property because this rule is essential for social order. In either case, the person’s judgment goes beyond what happens to the self. It is based on a concern for others; for society as a whole, or for an ethical standard rather than a legal standard. This level is called post-conventional moral development because it goes beyond convention or what other people think to a higher, universal ethical principle of conduct that may or may not be reflected in the law. Notice that such thinking is the kind Supreme Court justices do all day when deliberating whether a law is moral or ethical, which requires being able to think abstractly. Often this is not accomplished until a person reaches adolescence or adulthood. In the fifth stage, laws are recognized as social contracts. The reasons for the laws, like justice, equality, and dignity, are used to evaluate decisions and interpret laws. In the sixth stage, individually determined universal ethical principles are weighed to make moral decisions. Kohlberg said that few people ever reach this stage. The six stages can be reviewed in Table 5.6.
Table 5.6
Friends and Peers
• Momentary physical interaction, a friend is someone who you are playing with at this point in time. Selman notes that this is typical of children between the ages of three and six. These early friendships are based more on circumstances (e.g., a neighbor) than on genuine similarities.
• One-way assistance, a friend is someone who does nice things for you, such as saving you a seat on the school bus or sharing a toy. However, children in this stage, do not always think about what they are contributing to the relationships. Nonetheless, having a friend is important and children will sometimes put up with a not so nice friend, just to have a friend. Children as young as five and as old as nine may be in this stage.
• Fair-weather cooperation, children are very concerned with fairness and reciprocity, and thus, a friend is someone returns a favor. In this stage, if a child does something Figure 5.21 Source Source 198 nice for a friend there is an expectation that the friend will do something nice for them at the first available opportunity. When this fails to happen, a child may break off the friendship. Selman found that some children as young as seven and as old as twelve are in this stage.
• Intimate and mutual sharing, typically between the ages of eight and fifteen, a friend is someone who you can tell them things you would tell no one else. Children and teens in this stage no longer “keep score” and do things for a friend because they genuinely care for the person. If a friendship dissolves in the stage it is usually due to a violation of trust. However, children in this stage do expect their friend to share similar interests and viewpoints and may take it as a betrayal if a friend likes someone that they do not.
• Autonomous interdependence, a friend is someone who accepts you and that you accept as they are. In this stage children, teens, and adults accept and even appreciate differences between themselves and their friends. They are also not as possessive, so they are less likely to feel threatened if their friends have other relationships or interests. Children are typically twelve or older in this stage.
Peer Relationships: Sociometric assessment measures attraction between members of a group, such as a classroom of students. In sociometric research children are asked to mention the three children they like to play with the most, and those they do not like to play with. The number of times a child is nominated for each of the two categories (like, do not like) is tabulated. Popular children receive many votes in the “like” category, and very few in the “do not like” category. In contrast, rejected children receive more unfavorable votes, and few favorable ones. Controversial children are mentioned frequently in each category, with several children liking them and several children placing them in the do not like category. Neglected children are rarely mentioned in either category, and the average child has a few positive votes with very few negative ones (Asher & Hymel, 1981).
Long-Term Consequences of Popularity: Childhood popularity researcher Mitch Prinstein has found that likability in childhood leads to positive outcomes throughout one’s life (as cited in Reid, 2017). Adults who were accepted in childhood have stronger marriages and work relationships, earn more money, and have better health outcomes than those who were unpopular. Further, those who were unpopular as children, experienced greater anxiety, depression, substance use, obesity, physical health problems and suicide. Prinstein found that a significant consequence of unpopularity was that children were denied opportunities to build their social skills and negotiate complex interactions, thus contributing to their continued unpopularity. Further, biological effects can occur due to unpopularity, as social rejection can activate genes that lead to an inflammatory response.
Bullying
Those at risk for bullying: Bullying can happen to anyone, but some students are at an increased risk for being bullied including lesbian, gay, bisexual, transgendered (LGBT) youth, those with disabilities, and those who are socially isolated. Additionally, those who are perceived as different, weak, less popular, overweight, or having low self-esteem, have a higher likelihood of being bullied. 200 Those who are more likely to bully: Bullies are often thought of as having low self-esteem, and then bully others to feel better about themselves. Although this can occur, many bullies in fact have high levels of self-esteem. They possess considerable popularity and social power and have well-connected peer relationships. They do not lack self-esteem, and instead lack empathy for others. They like to dominate or be in charge of others.
Those who are more likely to bully: Bullies are often thought of as having low self-esteem, and then bully others to feel better about themselves. Although this can occur, many bullies in fact have high levels of self-esteem. They possess considerable popularity and social power and have well-connected peer relationships. They do not lack self-esteem, and instead lack empathy for others. They like to dominate or be in charge of others.
Bullied children often do not ask for help: Unfortunately, most children do not let adults know that they are being bullied. Some fear retaliation from the bully, while others are too embarrassed to ask for help. Those who are socially isolated may not know who to ask for help or believe that no one would care or assist them if they did ask for assistance. Consequently, it is important for parents and teacher to know the warning signs that may indicate a child is being bullied. These include: unexplainable injuries, lost or destroyed possessions, changes in eating or sleeping patterns, declining school grades, not wanting to go to school, loss of friends, decreased selfesteem and/or self-destructive behaviors.
Family Life
Family Tasks: One of the ways to assess the quality of family life is to consider the tasks of families. Berger (2014) lists five family functions:
1. Providing food, clothing and shelter
2. Encouraging learning
3. Developing self-esteem
4. Nurturing friendships with peers
5. Providing harmony and stability
Parenting Styles: As discussed in the previous chapter, parenting styles affect the relationship parents have with their children. During middle and late childhood, children spend less time with parents and more time with peers, and consequently parents may have to modify their approach to parenting to accommodate the child’s growing independence. The authoritative style, which incorporates reason and engaging in joint decision-making whenever possible may be the most effective approach (Berk, 2007). However, Asian-American, African-American, and Mexican-American parents are more likely than European-Americans to use an authoritarian style of parenting. This authoritarian style of parenting that uses strict discipline and focuses on obedience is also tempered with acceptance and warmth on the part of the parents. Children raised in this manner tend to be confident, successful and happy (Chao, 2001; Stewart & Bond, 2002).
Living Arrangements: Certainly, the living arrangements of children have changed significantly over the years. In 1960, 92% of children resided with married parents, while only 5% had parents who were divorced or separated and 1% resided with parents who had never been married. By 2008, 70% of children resided with married parents, 15% had parent who were divorced or separated, and 14% resided with parents who had never married (Pew Research Center, 2010). In 2017, only 65% of children lived with two married parents, while 32% (24 million children younger than 18) lived with an unmarried parent (Livingston, 2018). Some 3% of children were not living with any parents, according to the U.S. Census Bureau data.
Figure 5.24
Lesbian and Gay Parenting: Research has consistently shown that the children of lesbian and gay parents are as successful as those of heterosexual parents, and consequently efforts are being made to ensure that gay and lesbian couples are provided with the same legal rights as heterosexual couples when adopting children (American Civil Liberties Union, 2016).
Divorce: Using families in the National Institute of Child Health and Human Development (NICHD) Study of Early Child Care and Youth Development, Weaver and Schofield (2015) found that children from divorced families had significantly more behavior problems than those from a matched sample of children from non-divorced families. These problems were evident immediately after the separation and also in early and middle adolescence. An analysis of divorce factors indicated that children exhibited more externalizing behaviors if the family had fewer financial resources before the separation. It was hypothesized that the lower income and lack of educational and community resources contributed to the stress involved in the divorce. Additional factors contributing to children’s behavior problems included a post-divorce home that was less supportive and stimulating, and a mother that was less sensitive and more depressed.
Is cohabitation and remarriage more difficult than divorce for the child? The remarriage of a parent may be a more difficult adjustment for a child than the divorce of a parent (Seccombe & Warner, 2004). Parents and children typically have different ideas of how the stepparent should act. Parents and stepparents are more likely to see the stepparent’s role as that of parent. A more democratic style of parenting may become more authoritarian after a parent remarries. Biological parents are more likely to continue to be involved with their children jointly when neither parent has remarried. They are least likely to jointly be involved if the father has remarried and the mother has not. Cohabitation can be difficult for children to adjust to because cohabiting relationships in the United States tend to be short-lived. About 50 percent last less than 2 years (Brown, 2000). The child who starts a relationship with the parent’s live-in partner may have to sever this relationship later. Even in long-term cohabiting relationships, once it is over, continued contact with the child is rare.
Blended Families: One in six children (16%) live in blended families (Pew Research Center, 2015). As can be seen in Figure 5.27, Hispanic, black and white children are equally likely to be living in a blended family. In contrast, children of Asian descent are more likely to be living with two married parents, often in their first marriage. Blended families are not new. In the 1700-1800s there were many blended families, but they were created because someone died and remarried. Most blended families today are a result of divorce and remarriage, and such origins lead to new considerations. Blended families are different from intact families and more complex in a number of ways that can pose unique challenges to those who seek to form successful blended family relationships (Visher & Visher, 1985). Children may be a part of two households, each with different rules that can be confusing.
Figure 5.27
Attribution
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Chapter 19 Learning Objectives
• Summarize the overall physical growth
• Describe the changes that occur during puberty
• Describe the changes in brain maturation
• Describe the changes in sleep
• Describe gender intensification
• Identify nutritional concerns
• Describe eating disorders
• Explain the prevalence, risk factors, and consequences of adolescent pregnancy
Sexual Development
Male Anatomy: Males have both internal and external genitalia that are responsible for procreation and sexual intercourse. Males produce their sperm on a cycle, and unlike the female’s ovulation cycle, the male sperm production cycle is constantly producing millions of sperm daily. The main male sex organs are the penis and the testicles, the latter of which produce semen and sperm. The semen and sperm, as a result of sexual intercourse, can fertilize an ovum in the female’s body; the fertilized ovum (zygote) develops into a fetus which is later born as a child.
Figure 6.1
Figure 6.2
Female Anatomy: Female external genitalia is collectively known as the vulva, which includes the mons veneris, labia majora, labia minora, clitoris, vaginal opening, and urethral opening. Female internal reproductive organs consist of the vagina, uterus, fallopian tubes, and ovaries. The uterus hosts the developing fetus, produces vaginal and uterine secretions, and passes the male’s sperm through to the fallopian tubes while the ovaries release the eggs. A female is born with all her eggs already produced. The vagina is attached to the uterus through the cervix, while the uterus is attached to the ovaries via the fallopian tubes. Females have a monthly reproductive cycle; at certain intervals the ovaries release an egg, which passes through the fallopian tube into the uterus. If, in this transit, it meets with sperm, the sperm might penetrate and merge with the egg, fertilizing it. If not fertilized, the egg is flushed out of the system through menstruation.
Gender Role Intensification: At about the same time that puberty accentuates gender, role differences also accentuate for at least some teenagers. Some girls who excelled at math or science in elementary school, may curb their enthusiasm and displays of success at these subjects for fear of limiting their popularity or attractiveness as girls (Taylor, Gilligan, & Sullivan, 1995; Sadker, 2004). Some boys who were not especially interested in sports previously may begin dedicating themselves to athletics to affirm their masculinity in the eyes of others. Some boys and girls who once worked together successfully on class projects may no longer feel comfortable doing so, or alternatively may now seek to be working partners, but for social rather than academic reasons. Such changes do not affect all youngsters equally, nor affect any one youngster equally on all occasions. An individual may act like a young adult on one day, but more like a child the next.
Adolescent Sleep
Why do adolescents not get adequate sleep? In addition to known environmental and social factors, including work, homework, media, technology, and socializing, the adolescent brain is also a factor. As adolescent go through puberty, their circadian rhythms change and push back their sleep time until later in the evening (Weintraub, 2016). This biological change not only keeps adolescents awake at night, it makes it difficult for them to wake up. When they are awake too early, their brains do not function optimally. Impairments are noted in attention, academic achievement, and behavior while increases in tardiness and absenteeism are also seen.
Adolescent Sexual Activity
Adolescent Pregnancy: As can be seen in Figure 6.8, in 2018 females aged 15–19 years experienced a birth rate (live births) of 17.4 per 1,000 women. The birth rate for teenagers has declined by 58% since 2007 and 72% since 1991, the most recent peak (Hamilton, Joyce, Martin, & Osterman, 2019). It appears that adolescents seem to be less sexually active than in previous years, and those who are sexually active seem to be using birth control (CDC, 2016).
Risk Factors for Adolescent Pregnancy: Miller, Benson, and Galbraith (2001) found that parent/child closeness, parental supervision, and parents’ values against teen intercourse (or unprotected intercourse) decreased the risk of adolescent pregnancy. In contrast, residing in disorganized/dangerous neighborhoods, living in a lower SES family, living with a single parent, having older sexually active siblings or pregnant/parenting teenage sisters, early puberty, and being a victim of sexual abuse place adolescents at an increased risk of adolescent pregnancy.
Figure 6.8
Consequences of Adolescent Pregnancy: After the child is born life can be difficult for a teenage mother. Only 40% of teenagers who have children before age 18 graduate from high school. Without a high school degree her job prospects are limited, and economic independence is difficult. Teen mothers are more likely to live in poverty, and more than 75% of all unmarried teen mother receive public assistance within 5 years of the birth of their first child. Approximately, 64% of children born to an unmarried teenage high-school dropout live in poverty. Further, a child born to a teenage mother is 50% more likely to repeat a grade in school and is more likely to perform poorly on standardized tests and drop out before finishing high school (March of Dimes, 2012).
Eating Disorders
Risk Factors for Eating Disorders: Because of the high mortality rate, researchers are looking into the etiology of the disorder and associated risk factors. Researchers are finding that eating disorders are caused by a complex interaction of genetic, biological, behavioral, psychological, and social factors (NIMH, 2016). Eating disorders appear to run in families, and researchers are working to identify DNA variations that are linked to the increased risk of developing eating disorders. Researchers from King’s College London (2019) found that the genetic basis of anorexia overlaps with both metabolic and body measurement traits. The genetic factors also influence physical activity, which may explain the high activity level of those with anorexia. Further, the genetic basis of anorexia overlaps with other psychiatric disorders. Researchers have also found differences in patterns of brain activity in women with eating disorders in comparison with healthy women.
Table 6.1
Health Consequences of Eating Disorders: For those suffering from anorexia, health consequences include an abnormally slow heart rate and low blood pressure, which increases the risk for heart failure. Additionally, there is a reduction in bone density (osteoporosis), muscle loss and weakness, severe dehydration, fainting, fatigue, and overall weakness. Anorexia nervosa has the highest mortality rate of any psychiatric disorder (Arcelus, Mitchell, Wales, & Nielsen, 2011). Individuals with this disorder may die from complications associated with starvation, while others die of suicide. In women, suicide is much more common in those with anorexia than with most other mental disorders.
Eating Disorders Treatment: To treat eating disorders, adequate nutrition and stopping inappropriate behaviors, such as purging, are the foundations of treatment. Treatment plans are tailored to individual needs and include medical care, nutritional counseling, medications (such as antidepressants), and individual, group, and/or family psychotherapy (NIMH, 2016). For example, the Maudsley Approach has parents of adolescents with anorexia nervosa be actively involved in their child’s treatment, such as assuming responsibility for feeding the child. To eliminate binge-eating and purging behaviors, cognitive behavioral therapy (CBT) assists sufferers by identifying distorted thinking patterns and changing inaccurate beliefs.
Attribution
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Chapter 21 Learning Objectives
• Describe the changes in self-concept and self-esteem in adolescence
• Summarize Erikson’s fifth psychosocial task of identity versus role confusion
• Describe Marcia’s four identity statuses
• Summarize the three stages of ethnic identity development
• Describe the parent-teen relationship
• Describe the role of peers
• Describe dating relationships
Erikson: Identity vs. Role Confusion
Table 6.2
Religious identity: The religious views of teens are often similar to that of their families (KimSpoon, Longo, & McCullough, 2012). Most teens may question specific customs, practices, or ideas in the faith of their parents, but few completely reject the religion of their families.
Political identity: The political ideology of teens is also influenced by their parents’ political beliefs. A new trend in the 21st century is a decrease in party affiliation among adults. Many adults do not align themselves with either the democratic or republican party but view themselves as more of an “independent”. Their teenage children are often following suit or become more apolitical (Côtè, 2006).
Vocational identity: While adolescents in earlier generations envisioned themselves as working in a particular job, and often worked as an apprentice or part-time in such occupations as teenagers, this is rarely the case today. Vocational identity takes longer to develop, as most of today’s occupations require specific skills and knowledge that will require additional education or are acquired on the job itself. In addition, many of the jobs held by teens are not in occupations that most teens will seek as adults.
Gender identity: Acquiring a gender identity is becoming an increasingly prolonged task as attitudes and norms regarding gender keep changing. The roles appropriate for males and females are evolving, and the lack of a gender binary allow adolescents more freedom to explore various aspects of gender. Some teens may foreclose on a gender identity as a way of dealing with this uncertainty, and they may adopt more stereotypic male or female roles (Sinclair & Carlsson, 2013).
Sexual identity: According to Carroll (2016), by age 14 most adolescents become interested in intimate relationships, and they may begin sexual experimentation. Many adolescent feel pressure to express interest in opposite-sex relationships, even if they are not ready to do so. This pressure can be especially stressful for those adolescents who are gay, lesbian, bisexual or questioning their sexual identity. Many non-heterosexual adolescents struggle with negative peer and family reactions during their exploration. A lack of parental acceptance, especially, can adversely affect the gay, lesbian or bisexual adolescent’s emerging sexual identity and can result in feelings of depression. In contrast, adolescents whose familes support their sexual identity have better health outcomes.
1. Unexamined Ethnic Identity: Adolescents and adults who have not been exposed to ethnic identity issues may be in the first stage, unexamined ethnic identity. This is often characterized with a preference for the dominant culture, or where the individual has given little thought to the question of their ethnic heritage. This is similar to diffusion in Marcia’s model of identity. Included in this group are also those who have adopted the ethnicity of their parents and other family members with little thought about the issues themselves, similar to Marcia’s foreclosure status (Phinney, 1990).
2. Ethnic Identity Search: Adolescents and adults who are exploring the customs, culture, and history of their ethnic group are in the ethnic identity search stage, similar to Marcia’s moratorium status (Phinney, 1990). Often some event “awakens” a teen or adult to their ethnic group; either a personal experience with prejudice, a highly profiled case in the media, or even a more positive event that recognizes the contribution of someone from the individual’s ethnic group. Teens and adults in this stage will immerse themselves in their ethnic culture. For some, “it may lead to a rejection of the values of the dominant culture” (Phinney, 1990, p. 503).
3. Achieved Ethnic Identity: Those who have actively explored their culture are likely to have a deeper appreciation and understanding of their ethnic heritage, leading to progress toward an achieved ethnic identity (Phinney, 1990). An achieved ethnic identity does not necessarily imply that the individual is highly involved in the customs and values of their ethnic culture. One can be confident in their ethnic identity without wanting to maintain the language or other customs.
Bicultural/Multiracial Identity: Ethnic minorities must wrestle with the question of how, and to what extent, they will identify with the culture of the surrounding society and with the culture of their family. Phinney (2006) suggests that people may handle it in different ways. Some may keep the identities separate, others may combine them in some way, while others may reject some of them. Bicultural identity means the individual sees himself or herself as part of both the ethnic minority group and the larger society. Those who are multiracial, that is whose parents come from two or more ethnic or racial groups, have a more challenging task. In some cases, their appearance may be ambiguous. This can lead to others constantly asking them to categorize themselves. Phinney (2006) notes that the process of identity formation may start earlier and take longer to accomplish in those who are not mono-racial.
Negative Identity: A negative identity is the adoption of norms and values that are the opposite of one’s family and culture, and it is assumed to be one of the more problematic outcomes of identity development in young people (Hihara, Umemura, & Sigimura, 2019). Those with a negative identity hold dichotomous beliefs, and consequently divide the world into two categories (e.g., friend or foe, good or bad). Hihara et al. suggest that this may be because teens with a negative identity cannot integrate information and beliefs that exist in both their inner and outer worlds. In addition, those with a negative identity are generally hostile and cynical toward society, often because they do not trust the world around them. These beliefs may lead teens to engage in delinquent and criminal behavior and prevent them from engaging in more positive acts that could be beneficial to society.
Attribution
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Chapter 22 Learning Objectives
• Summarize the overall physical growth in early adulthood
• Describe statistics, possible causes, and consequences of obesity
• Explain how early adulthood is a healthy, yet risky time of life
• Identify the risk factors for substance use
• Describe the changes in brain maturation
• Describe gender in adulthood, including gender minorities and stress
• Define sexuality and explain the female and male reproductive systems
• Describe the brain areas and hormones responsible for sexual behavior
• Identify sexually transmitted infections
• Describe cultural views related to sexuality
• Describe research on sexual orientation
Obesity
Body mass index (BMI), expressed as weight in kilograms divided by height in meters squared (kg/m2), is commonly used to classify overweight (BMI 25.0–29.9), obesity (BMI greater than or equal to 30.0), and extreme obesity (BMI greater than or equal to 40.0). The current statistics are an increase from the 2013-2014 statistics that indicated that an estimated 35.1% were obese, and 6.4% extremely obese (Fryar, Carroll, & Ogden, 2014). The CDC also indicated that one’s 20s are the prime time to gain weight as the average person gains one to two pounds per year from early adulthood into middle adulthood. The average man in his 20s weighs around 185 pounds and by his 30s weighs approximately 200 pounds. The average American woman weighs 162 pounds in her 20s and 170 pounds in her 30s.
Figure 7. 6
Causes of Obesity: According to the Centers for Disease Control and Prevention (CDC) (2016), obesity originates from a complex set of contributing factors, including one’s environment, behavior, and genetics. Societal factors include culture, education, food marketing and promotion, the quality of food, and the physical activity environment available. Behaviors leading to obesity include diet, the amount of physical activity, and medication use. Lastly, there does not appear to be a single gene responsible for obesity. Rather, research has identified variants in several genes that may contribute to obesity by increasing hunger and food intake. Another genetic explanation is the mismatch between today’s environment and “energy-thrifty genes” that multiplied in the distant past when food sources were unpredictable. The genes that helped our ancestors survive occasional famines are now being challenged by environments in which food is plentiful all the time. Overall, obesity most likely results from complex interactions among the environment and multiple genes.
Figure 7.7
ObesityHealth Consequences: Obesity is considered to be one of the leading causes of death in the United States and worldwide. Additionally, the medical care costs of obesity in the United States were estimated to be \$147 billion in 2008. According to the CDC (2016) compared to those with a normal or healthy weight, people who are obese are at increased risk for many serious diseases and health conditions including:
• All-causes of death (mortality)
• High blood pressure (Hypertension)
• High LDL cholesterol, low HDL cholesterol, or high levels of triglycerides (Dyslipidemia)
• Type 2 diabetes
• Coronary heart disease
• Stroke
• Gallbladder disease
• Osteoarthritis (a breakdown of cartilage and bone within a joint)
• Sleep apnea and breathing problems
• Some cancers (endometrial, breast, colon, kidney, gallbladder, and liver)
• Low quality of life
• Mental illness, such as clinical depression, anxiety, and other mental disorders
• Body pain and difficulty with physical functioning
A Healthy, But Risky Time
Alcohol Abuse: A significant contributing factor to risky behavior is alcohol. According to 2014, National Survey on Drug Use and Health (National Institute on Alcohol Abuse and Alcoholism (NIAAA), 2016) 88% of people ages 18 or older reported that they drank alcohol at some point in their lifetime; 71% reported that they drank in the past year, and 57% reported drinking in the past month. Additionally, 6.7% reported that they engaged in heavy drinking in the past month. Heavy drinking is defined as drinking five or more drinks on the same occasion on each of five or more days in the past 30 days. Nearly 88,000 people (approximately 62,000 men and 26,000 women) die from alcohol-related causes annually, making it the fourth leading preventable cause of death in the United States. In 2014, alcohol-impaired driving fatalities accounted for 9,967 deaths (31% of overall driving fatalities).
Alcohol and College Students: Results from the 2014 survey demonstrated a difference between the amount of alcohol consumed by college students and those of the same age who are not in college (NIAAA, 2016). Specifically, 60% of full-time college students ages 18–22 drank alcohol in the past month compared with 51.5% of other persons of the same age not in college. In addition, 38% of college students ages 18–22 engaged in binge drinking; that is, five or more drinks on one occasion in the past month, compared with 33.5% of other persons of the same age. Lastly, 12% of college students’ (ages 18–22) engaged in heavy drinking; that is, binge drinking on five or more occasions per month, in the past month. This compares with 9.5% of other emerging adults not in college.
• 1,825 college students between the ages of 18 and 24 die from alcohol-related unintentional injuries, including motor-vehicle crashes.
• 696,000 students between the ages of 18 and 24 are assaulted by another student who has been drinking.
• Roughly 1 in 5 college students meet the criteria for an Alcohol Use Disorder.
• About 1 in 4 college students report academic consequences from drinking, including missing class, falling behind in class, doing poorly on exams or papers, and receiving lower grades overall. (p. 1)
• 97,000 students between the ages of 18 and 24 report experiencing alcohol-related sexual assault or date rape.
Factors Affecting College Students’ Drinking: Several factors associated with college life affect a student’s involvement with alcohol (NIAAA, 2015).
College Strategies to Curb Drinking: Strategies to address college drinking involve the individual-level and campus community as a whole. Identifying at-risk groups, such as first-year students, members of fraternities and sororities, and athletes have proven helpful in changing students’ knowledge, attitudes, and behavior regarding alcohol (NIAAA, 2015).
Non-Alcohol Substance Use: Illicit drug use peaks between the ages of 19 and 22 and then begins to decline. Additionally, 25% of those who smoke cigarettes, 33% of those who smoke marijuana, and 70% of those who abuse cocaine began using after age 17 (Volkow, 2004).
Figure 7.10
Gender
gender is the cultural, social and psychological meanings associated with masculinity and feminity. A person’s sense of self as a member of a particular gender is known as gender identity. Because gender is considered a social construct, meaning that it does not exist naturally, but is instead a concept that is created by cultural and societal norms, there are cultural variations on how people express their gender identity. For example, in American culture, it is considered feminine to wear a dress or skirt. However, in many Middle Eastern, Asian, and African cultures, dresses or skirts (often referred to as sarongs, robes, or gowns) can be considered masculine. Similarly, the kilt worn by a Scottish male does not make him appear feminine in his culture.
gender roles, or the societal expectations associated with being male or female, continues throughout life. In American culture, masculine roles have traditionally been associated with strength, aggression, and dominance, while feminine roles have traditionally been associated with passivity, nurturing, and subordination. Men tend to outnumber women in professions such as law enforcement, the military, and politics, while women tend to outnumber men in care-related occupations such as childcare, healthcare, and social work. These occupational roles are examples of stereotypical American male and female behavior, derived not from biology or genetics, but from our culture’s traditions. Adherence to these roles may demonstrate fulfillment of social expectations, however, not necessarily personal preferences (Diamond, 2002).
gender binary; that is, categorizing humans as only female and male, has been undermined by current psychological research (Hyde, Bigler, Joel, Tate, & van Anders, 2019). The term gender now encompasses a wide range of possible identities, including cisgender, transgender, agender, genderfluid, genderqueer, gender nonconforming, bigender, pangender, ambigender, non- gendered, intergender, and Two-spirit which is a modern umbrella term used by some indigenous North Americans to describe gender-variant individuals in their communities (Carroll, 2016). Hyde et al. (2019) advocate for a conception of gender that stresses multiplicity and diversity and uses multiple categories that are not mutually exclusive.
Gender Minority Discrimination: Gender nonconforming people are much more likely to experience harassment, bullying, and violence based on their gender identity; they also experience much higher rates of discrimination in housing, employment, healthcare, and education (Borgogna, McDermott, Aita, & Kridel, 2019; National Center for Transgender Equality, 2015). Transgender individuals of color face additional financial, social, and interpersonal challenges, in comparison to the transgender community as a whole, as a result of structural racism. Black transgender people reported the highest level of discrimination among all transgender individuals of color. As members of several intersecting minority groups, transgender people of color, and transgender women of color, in particular, are especially vulnerable to employment discrimination, poor health outcomes, harassment, and violence. Consequently, they face even greater obstacles than white transgender individuals and cisgender members of their own race.
Gender Minority Status and Mental Health: Using data from over 43,000 college students, Borgona et al. (2019) examined mental health differences among several gender groups, including those identifying as cisgender, transgender and gender nonconforming. Results indicated that participants who identified as transgender and gender nonconforming had significantly higher levels of anxiety and depression than those identifying as cisgender. Bargona et al. explained the higher rates of anxiety and depression using the minority stress model, which states that an unaccepting social environment results in both external and internal stress which contributes to poorer mental health. External stressors include discrimination, harassment, and prejudice, while internal stressors include negative thoughts, feelings, and emotions resulting from one’s identity. Bargona et al. recommend that mental health services that are sensitive to both gender minority and sexual minority status be available.
transvestite, which is the practice of dressing and acting in a style or manner traditionally associated with another sex (APA, 2013) with transgender. Cross-dressing is typically a form of self-expression, entertainment, or personal style, and not necessarily an expression about one’s gender identity.
Sexuality
Human sexuality refers to people’s sexual interest in and attraction to others, as well as their capacity to have erotic experiences and responses. Sexuality may be experienced and expressed in a variety of ways, including thoughts, fantasies, desires, beliefs, attitudes, values, behaviors, practices, roles, and relationships. These may manifest themselves in biological, physical, emotional, social, or spiritual aspects. The biological and physical aspects of sexuality largely concern the human reproductive functions, including the human sexual response cycle and the basic biological drive that exists in all species. Emotional aspects of sexuality include bonds between individuals that are expressed through profound feelings or physical manifestations of love, trust, and care. Social aspects deal with the effects of human society on one’s sexuality, while spirituality concerns an individual’s spiritual connection with others through sexuality. Sexuality also impacts and is impacted by cultural, political, legal, philosophical, moral, ethical, and religious aspects of life.
The Sexual Response Cycle: Sexual motivation, often referred to as libido, is a person’s overall sexual drive or desire for sexual activity. This motivation is determined by biological, psychological, and social factors. In most mammalian species, sex hormones control the ability to engage in sexual behaviors. However, sex hormones do not directly regulate the ability to copulate in primates (including humans); rather, they are only one influence on the motivation to engage in sexual behaviors. Social factors, such as work and family, also have an impact, as do internal psychological factors like personality and stress. Sex drive may also be affected by hormones, medical conditions, medications, lifestyle stress, pregnancy, and relationship issues.
sexual response cycle is a model that describes the physiological responses that take place during sexual activity. According to Kinsey, Pomeroy, and Martin (1948), the cycle consists of four phases: excitement, plateau, orgasm, and resolution. The excitement phase is the phase in which the intrinsic (inner) motivation to pursue sex arises. The plateau phase is the period of sexual excitement with increased heart rate and circulation that sets the stage for orgasm. Orgasm is the release of tension, and the resolution period is the unaroused state before the cycle begins again.
The Brain and Sex: The brain is the structure that translates the nerve impulses from the skin into pleasurable sensations. It controls the nerves and muscles used during sexual behavior. The brain regulates the release of hormones, which are believed to be the physiological origin of sexual desire. The cerebral cortex, which is the outer layer of the brain that allows for thinking and reasoning, is believed to be the origin of sexual thoughts and fantasies. Beneath the cortex is the limbic system, which consists of the amygdala, hippocampus, cingulate gyrus, and septal area. These structures are where emotions and feelings are believed to originate, and they are important for sexual behavior.
hypothalamus is the most important part of the brain for sexual functioning. This is the small area at the base of the brain consisting of several groups of nerve-cell bodies that receives input from the limbic system. Studies with lab animals have shown that the destruction of certain areas of the hypothalamus causes the complete elimination of sexual behavior. One of the reasons for the importance of the hypothalamus is that it controls the pituitary gland, which secretes hormones that control the other glands of the body.
Figure 7.13
Hormones: Several important sexual hormones are secreted by the pituitary gland. Oxytocin, also known as the hormone of love, is released during sexual intercourse when an orgasm is achieved. Oxytocin is also released in females when they give birth or are breastfeeding; it is believed that oxytocin is involved with maintaining close relationships. Both prolactin and oxytocin stimulate milk production in females. Follicle-stimulating hormone (FSH) is responsible for ovulation in females by triggering egg maturity; it also stimulates sperm production in males. Luteinizing hormone (LH) triggers the release of a mature egg in females during the process of ovulation. In males, testosterone appears to be a major contributing factor to sexual motivation. Vasopressin is involved in the male arousal phase, and the increase of vasopressin during erectile response may be directly associated with increased motivation to engage in sexual behavior.
Estrogen and progesterone typically regulate motivation to engage in sexual behavior for females, with estrogen increasing motivation and progesterone decreasing it. The levels of these hormones rise and fall throughout a woman’s menstrual cycle. Research suggests that testosterone, oxytocin, and vasopressin are also implicated in female sexual motivation in similar ways as they are in males, but more research is needed to understand these relationships.
Sexual Responsiveness Peak: Men and women tend to reach their peak of sexual responsiveness at different ages. For men, sexual responsiveness tends to peak in the late teens and early twenties. Sexual arousal can easily occur in response to physical stimulation or fantasizing. Sexual responsiveness begins a slow decline in the late twenties and into the thirties, although a man may continue to be sexually active. Through time, a man may require more intense stimulation in order to become aroused. Women often find that they become more sexually responsive throughout their 20s and 30s and may peak in the late 30s or early 40s. This is likely due to greater self-confidence and reduced inhibitions about sexuality.
Sexually Transmitted Infections: Sexually transmitted infections (STIs), also referred to as sexually transmitted diseases (STDs) or venereal diseases (VDs) are illnesses that have a significant probability of transmission by means of sexual behavior, including vaginal intercourse, anal sex, and oral sex. Some STIs can also be contracted by sharing intravenous drug needles with an infected person, as well as through childbirth or breastfeeding.
Common STIs include:
• chlamydia;
• herpes (HSV-1 and HSV-2);
• human papillomavirus (HPV);
• gonorrhea;
• syphilis;
• trichomoniasis;
• HIV (human immunodeficiency virus) and AIDS (acquired immunodeficiency syndrome).
Societal Views on Sexuality: Society’s views on sexuality are influenced by everything from religion to philosophy, and they have changed throughout history and are continuously evolving. Historically, religion has been the greatest influence on sexual behavior in the United States; however, in more recent years, peers and the media have emerged as two of the strongest influences, particularly among American teens (Potard, Courtois, & Rusch, 2008).
Cultural Differences: In the West, premarital sex is normative by the late teens, more than a decade before most people enter marriage. In the United States and Canada, and in northern and eastern Europe, cohabitation is also normative; most people have at least one cohabiting partnership before marriage. In southern Europe, cohabiting is still taboo, but premarital sex is tolerated in emerging adulthood. In contrast, both premarital sex and cohabitation remain rare and forbidden throughout Asia. Even dating is discouraged until the late twenties when it would be a prelude to a serious relationship leading to marriage. In cross-cultural comparisons, about three-fourths of emerging adults in the United States and Europe report having had premarital sexual relations by age 20, versus less than one fifth in Japan and South Korea (Hatfield & Rapson, 2006).
Sexual Orientation: A person’s sexual orientation is their emotional and sexual attraction to a particular gender. It is a personal quality that inclines people to feel romantic or sexual attraction (or a combination of these) to persons of a given sex or gender. According to the American Psychological Association (APA) (2016), sexual orientation also refers to a person’s sense of identity-based on those attractions, related behaviors, and membership in a community of others who share those attractions. Sexual orientation is independent of gender; for example, a transgender person may identify as heterosexual, homosexual, bisexual, pansexual, polysexual, asexual, or any other kind of sexuality, just like a cisgender person.
Sexual Orientation on a Continuum: Sexuality researcher Alfred Kinsey was among the first to conceptualize sexuality as a continuum rather than a strict dichotomy of gay or straight. To classify this continuum of heterosexuality and homosexuality, Kinsey et al. (1948) created a seven-point rating scale that ranged from exclusively heterosexual to exclusively homosexual. Research done over several decades has supported this idea that sexual orientation ranges along a continuum, from exclusive attraction to the opposite sex/gender to exclusive attraction to the same sex/gender (Carroll, 2016).
Heterosexuality, which is often referred to as being straight, is attraction to individuals of the opposite sex/gender, while homosexuality, being gay or lesbian, is attraction to individuals of one’s own sex/gender. Bisexuality was a term traditionally used to refer to attraction to individuals of either male or female sex, but it has recently been used in nonbinary models of sex and gender (i.e., models that do not assume there are only two sexes or two genders) to refer to attraction to any sex or gender. Alternative terms such as pansexuality and polysexuality have also been developed, referring to attraction to all sexes/genders and attraction to multiple sexes/genders, respectively (Carroll, 2016).
Asexuality refers to having no sexual attraction to any sex/gender. According to Bogaert (2015), about one percent of the population is asexual. Being asexual is not due to any physical problems, and the lack of interest in sex does not cause the individual any distress. Asexuality is being researched as a distinct sexual orientation.
Development of Sexual Orientation: According to current scientific understanding, individuals are usually aware of their sexual orientation between middle childhood and early adolescence. However, this is not always the case, and some do not become aware of their sexual orientation until much later in life. It is not necessary to participate in sexual activity to be aware of these emotional, romantic, and physical attractions; people can be celibate and still recognize their sexual orientation. Some researchers argue that sexual orientation is not static and inborn but is instead fluid and changeable throughout the lifespan.
Genetics: Using both twin and familial studies, heredity provides one biological explanation for same-sex orientation. Bailey and Pillard (1991) studied pairs of male twins and found that the concordance rate for identical twins was 52%, while the rate for fraternal twins was only 22%. Bailey, Pillard, Neale, and Agyei (1993) studied female twins and found a similar difference with a concordance rate of 48% for identical twins and 16% for fraternal twins. Schwartz, Kim, Kolundzija, Rieger, & Sanders (2010) found that gay men had more gay male relatives than straight men, and sisters of gay men were more likely to be lesbians than sisters of straight men.
Fraternal Birth Order: The fraternal birth order effect indicates that the probability of a boy identifying as gay increases for each older brother born to the same mother (Balthazart, 2018; Blanchard, 2001). According to Bogaret et al. “the increased incidence of homosexuality in males with older brothers results from a progressive immunization of the mother against a male-specific cell-adhesion protein that plays a key role in cell-cell interactions, specifically in the process of synapse formation,” (as cited in Balthazart, 2018, p. 234). A meta-analysis indicated that the fraternal birth order effect explains the sexual orientation of between 15% and 29% of gay men.
Hormones: Excess or deficient exposure to hormones during prenatal development has also been theorized as an explanation for sexual orientation. One-third of females exposed to abnormal amounts of prenatal androgens, a condition called congenital adrenal hyperplasia (CAH), identify as bisexual or lesbian (Cohen-Bendahan, van de Beek, & Berenbaum, 2005). In contrast, too little exposure to prenatal androgens may affect male sexual orientation by not masculinizing the male brain (Carlson, 2011).
Sexual Orientation Discrimination: The United States is heteronormative, meaning that society supports heterosexuality as the norm. Consider, for example, that homosexuals are often asked, “When did you know you were gay?” but heterosexuals are rarely asked, “When did you know you were straight?” (Ryle, 2011). Living in a culture that privileges heterosexuality has a significant impact on the ways in which non-heterosexual people are able to develop and express their sexuality.
homophobia which encompasses a range of negative attitudes and feelings toward homosexuality or people who are identified or perceived as being lesbian, gay, bisexual, or transgender (LGBT). It can be expressed as antipathy, contempt, prejudice, aversion, or hatred; it may be based on irrational fear and is sometimes related to religious beliefs (Carroll, 2016). Homophobia is observable in critical and hostile behavior, such as discrimination and violence on the basis of sexual orientations that are non- heterosexual. Recognized types of homophobia include institutionalized homophobia, such as religious and state-sponsored homophobia, and internalized homophobia in which people with same-sex attractions internalize, or believe, society’s negative views and/or hatred of themselves.
marginalized sub-populations that are also affected by racism, classism, and other forms of oppression. In the United States, non-Caucasian LGBT individuals may find themselves in a double minority, in which they are not fully accepted or understood by Caucasian LGBT communities and are also not accepted by their own ethnic group (Tye, 2006). Many people experience racism in the dominant LGBT community where racial stereotypes merge with gender stereotypes.
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/10%3A_Development_in_Early_Adulthood/10.01%3A_Chapter_22-_Physical_Development_in_Early_Adulthood.txt |
Chapter 23 Learning Objectives
• Distinguish between formal and post formal thought
• Describe dialectical thought
• Describe the changes in educational attainment and the costs of education
• Describe the benefits of education beyond high school
• Describe the stages in career development, millennial employment, and NEETS
• Describe sexism and how it affects pay, hiring, employment, and education
Education
• 84% of 18 to 24-year-olds and 88% of those 25 and older have a high school diploma or its equivalent
• 36% of 18 to 24-year-olds and 7% of 25 to 49-year-olds attend college
• 59% of those 25 and older have completed some college
• 32.5% of those 25 and older have a bachelor’s degree or higher, with slightly more women (33%) than men (32%) holding a college degree (Ryan & Bauman, 2016).
Figure 7.17
Table 7.1
Graduate School: Larger amounts of student debt actually occur at the graduate level (Kreighbaum, 2019). In 2019, the highest average debts were concentrated in the medical fields. Average median debt for graduate programs including:
• \$42,335 for a master’s degree
• \$95,715 for a doctoral degree
• \$141,000 for a professional degree
Is college worth the time and investment? College is certainly a substantial investment each year, with the financial burden falling on students and their families in the U.S., and mainly by the government in many other nations. Nonetheless, the benefits both to the individual and society outweigh the initial costs. As can be seen in Figure 7.18, those in America with the most advanced degrees earn the highest income and have the lowest unemployment.
Figure 7.18
Career Development and Employment
Stage One: As children, we may select careers based on what appears glamorous or exciting to us (Patton & McMahon, 1999). There is little regard in this stage for whether we are suited for our occupational choices.
Stage Two: In the second stage, teens include their abilities and limitations, in addition to the glamour of the occupation when narrowing their choices.
Stage Three: Older teens and emerging adults narrow their choices further and begin to weigh more objectively the requirements, rewards, and downsides to careers, along with comparing possible careers with their own interests, values, and future goals (Patton & McMahon, 1999). However, some young people in this stage “fall-into” careers simply because these were what was available at the time, because of family pressures to pursue particular paths, or because these were high paying jobs, rather than from an intrinsic interest in that career path (Patton & McMahon, 1999).
Stage Four: Super (1980) suggests that by our mid to late thirties, many adults settle in their careers. Even though they might change companies or move up in their position, there is a sense of continuity and forward motion in their career. However, some people at this point in their working life may feel trapped, especially if there is little opportunity for advancement in a more dead-end job.
How have things changed for Millennials compared with previous generations of early adults? In recent years, young adults are more likely to find themselves job-hopping, and periodically returning to school for further education and retraining than in prior generations. However, researchers find that occupational interests remain fairly stable. Thus, despite the more frequent change in jobs, most people are generally seeking jobs with similar interests rather than entirely new careers (Rottinghaus, Coon, Gaffey & Zytowski, 2007). As of 2016, millennials became the largest generation in the labor force (Fry, 2018) (See Figure 7.19).
Figure 7.19
NEETs: Around the world, teens and young adults were some of the hardest hit by the economic downturn in recent years (Desilver, 2016). Consequently, a number of young people have become NEETs, neither employed nor in education or training. While the number of young people who are NEETs has declined more recently, there is concern that “without assistance, economically inactive young people won’t gain critical job skills and will never fully integrate into the wider economy or achieve their full earning potential” (Desilver, 2016, para. 3). In parts of the world where the rates of NEETs are persistently high, there is also concern that having such large numbers of young adults with little opportunity may increase the chances of social unrest.
In the United States, in 2017 over 13% of 15 to 29 year-olds were neither employed nor in school, (Organisation for Economic Cooperation and Development, (OECD), 2019). This is down from 2013 when approximately 18.5% of this age group fit the category (Desilver, 2016). More young women than men in the United States find themselves unemployed and not in school or training for a job. Additionally, most NEETs have a high school or less education, and Asians are less likely to be NEETs than any other ethnic group in the US (Desilver, 2016).
The rate of NEETs varies around the world, with higher rates found in nations that have been the hardest hit by economic recessions, and government austerity measures. The number of NEETs also varies widely between the genders, although females are more likely to be NEETs in all nations (see Table 7.2).
Table 7.2
What role does gender play in career and employment? Gender also has an impact on career choices. Despite the rise in the number of women who work outside of the home, there are some career fields that are still pursued more by men than women. Jobs held by women still tend to cluster in the service sector, such as education, nursing, and child-care worker. While in more technical and scientific careers, women are greatly outnumbered by men. Jobs that have been traditionally held by women tend to have lower status, pay, benefits, and job security (Bosson, et al., 2019). In recent years, women have made inroads into fields once dominated by males, and today women are almost as likely as men to become medical doctors or lawyers. Despite these changes, women are more likely to have lower-status, and thus less pay than men in these professions. For instance, women are more likely to be a family practice doctor than a surgeon or are less likely to make partner in a law firm (Ceci & Williams, 2007).
Sexism
Sexism or gender discrimination is prejudice or discrimination based on a person’s sex or gender (Bosson, Vandello, & Buckner, 2019). Sexism can affect any sex that is marginalized or oppressed in society; however, it is particularly documented as affecting females. It has been linked to stereotypes and gender roles and includes the belief that males are intrinsically superior to other sexes and genders. Extreme sexism may foster sexual harassment, rape, and other forms of sexual violence.
Occupational sexism involves discriminatory practices, statements, or actions, based on a person’s sex, that occur in the workplace. One form of occupational sexism is wage discrimination. In 2008, the Organisation for Economic Co-operation and Development (OECD) found that while female employment rates have expanded, and gender employment and wage gaps have narrowed nearly everywhere, on average women still have a 20 percent less chance to have a job. The Council of Economic Advisors (2015) found that despite women holding 49.3% of the jobs, they are paid only 78 cents for every \$1.00 a man earns. It also found that despite the fact that many countries, including the U.S., have established anti-discrimination laws, these laws are difficult to enforce. A recent example of significant wage inequality occurred among athletes.
2019 Women’s World Cup: The world witnessed the tremendous athleticism and soccer skills demonstrated by female players from 24 different countries during the 2019 Women’s World Cup. Amid the cheering at the end of the final match between the United States and the Netherlands, were chants of “equal pay” (Channick, 2019). Throughout the tournament, attention was focused on the discrepancy between what male soccer players earned compared to the female players. In winning the World Cup, the American women’s team earned \$4 million as part of a \$30 million prize pool (Peterson, 2019). In contrast, the French men’s team, who won the Men’s World Cup in 2018, earned \$38 million as part of the \$400 million prize pool. The Federation of Association Football (FIFA) promised to double the prize money to \$60 million for the 2023 Women’s World Cup, but that still lags far behind the \$440 million that will be given out for the Men’s World Cup in 2022. In the United States, the women’s soccer team generates more revenue and receives higher TV ratings than the men’s team, yet the women get paid significantly less. By winning the 2019 Women’s World Cup, each woman should receive \$200,000, yet if the American men had won the 2018 Men’s World Cup, each would have received \$1.1 million (Hess, 2019). Because of this discrepancy, in March 2019, 28 members of the women’s team filed a lawsuit against the United States Soccer Federation for gender discrimination and unequal pay (Channick, 2019).
Factors Affecting Wage Inequality: There are many possible explanations for the wage gap. It has been argued in the past that education may account for the wage gap. However, the wage gap exists at every education level (Bosson et al., 2019). Men with less than high school to men with graduate degrees earn more than women with the same level of education. In addition, women now attain more associates, bachelor’s, and master’s degrees than men, and very similar levels of professional degrees and doctorates, according to a recent Census survey (U.S. Census Bureau, 2019). As the wage gap still exists in most occupations it cannot be the explanation. Instead, occupational segregation is a likely contributor to the overall wage gap, as women tend to work in very different occupations than men, and those jobs tend to have lower wages. In addition, the entry of women into a field tends to reduce the wages and prestige of the job. Mandel (2013) found that jobs typically held by men who saw the biggest influx of women into those careers also saw the biggest drop in wages.
Sticky floors, which keep low-wage workers, who are more likely to be women and minorities, from being promoted contribute to lower wages (Bosson, et al. 2019). Women are disproportionately in low-paid occupations, such as clerical, childcare, and service workers (Hegewisch & Ellis, 2015). They also get paid less than men in the same jobs, as can be seen in Table 7.3 women paid more than men on average; stock clerk. Men are not only being paid more in more masculine jobs but also in jobs typically held by women.
Table 7.3
Barriers to Positions of Power: There are a few barriers to women achieving positions of power. The glass ceiling is the invisible barrier that keeps women and minorities from rising to higher positions regardless of their qualifications (Bosson et al., 2019). Women hold only 4.5% of CEO positions and 14% of top executive positions around the world (Noland, Moran, & Kotschwar, 2016). In addition, Noland and colleagues found that in a study of nearly 22,000 companies worldwide, in 77% of those firms only 30% of women held an executive position or board seat. There were only 11 companies, or 0.05% of all the firms studied, where women held all the executive positions and board seats. Some researchers see the root cause of this situation in the tacit discrimination based on gender, conducted by current top executives and corporate directors, who are primarily male.
glass cliff, and it refers to women and minorities being placed in leadership positions when the risk of failure is high. For instance, female lawyers are more likely than their male counterparts to lead high-risk cases, and female politicians are more likely to be recommended to run in unwinnable seats (Bruckmuller, Ryan, Floor, & Haslam, 2014).
Worldwide Gender Parity: The World Economic Forum (2017) introduced The Global Gender Gap Report in 2006 as a way of tracking gender-based disparities between men and women in the world. The most recent report in 2017 analyzed 144 countries on gender equality in the areas of economic participation and opportunity, educational attainment, health and survival, and political empowerment. Countries are then ranked to create global awareness of the challenges posed by gender gaps in different areas of the world. A parity rating of 100% would mean that females and males achieved equality on these measures. Results indicated:
• 68% of gender parity was found worldwide across the four areas. Specifically, there was 96% parity in health outcomes, 95% parity in educational attainment, 58% parity in economic participation, and only 23% parity in political empowerment.
• The top spots were held by smaller Western European countries, particularly the Nordic countries as Iceland (88% parity), Norway (83% parity) and Finland (82% parity) occupied the top three positions.
• The United States ranked 49th with 72% gender parity.
• Following the current trends, it will take 100 years for global gender parity.
• Improving gender parity is expected to provide significant economic gains for a country and closing the occupational gender gaps would be one way to achieve this.
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/10%3A_Development_in_Early_Adulthood/10.02%3A_Chapter_23-_Cognitive_Development_in_Early_Adulthood.txt |
Chapter 24 Learning Objectives
• Describe the relationship between infant and adult temperament
• Explain personality in early adulthood
• Explain the five factor model of personality
• Describe adult attachment styles
• Describe Erikson’s stage of intimacy vs. isolation
• Identify the factors affecting attraction
• Differentiate among the types of love
• Describe adult lifestyles, including singlehood, cohabitation, and marriage
• Describe the factors that influence parenting
Attachment in Young Adulthood
Table 7.5
Attachment-related anxiety refers to the extent to which an adult worries about whether their partner really loves them. Those who score high on this dimension fear that their partner will reject or abandon them (Fraley, Hudson, Heffernan, & Segal, 2015). Attachment-related avoidance refers to whether an adult can open up to others, and whether they trust and feel they can depend on others. Those who score high on attachment-related avoidance are uncomfortable with opening up and may fear that such dependency may limit their sense of autonomy (Fraley et al., 2015). According to Bartholomew (1990) this would yield four possible attachment styles in adults; secure, dismissing, preoccupied, and fearful-avoidant (see Figure 7.22)
Figure 7.22
• Adults with insecure attachments report lower satisfaction in their relationships (Butzer, & Campbell, 2008; Holland, Fraley, & Roisman, 2012).
• Those high in attachment-related anxiety report more daily conflict in their relationships (Campbell, Simpson, Boldry, & Kashy, 2005).
• Those with avoidant attachment exhibit less support to their partners (Simpson, Rholes, Oriña, & Grich, 2002).
• Young adults show greater attachment-related anxiety than do middle-aged or older adults (Chopik, Edelstein, & Fraley, 2013).
• Some studies report that young adults show more attachment-related avoidance (Schindler, Fagundes, & Murdock, 2010), while other studies find that middle-aged adults show higher avoidance than younger or older adults (Chopik et al., 2013).
• Young adults with more secure and positive relationships with their parents make the transition to adulthood more easily than do those with more insecure attachments (Fraley, 2013).
• Young adults with secure attachments and authoritative parents were less likely to be depressed than those with authoritarian or permissive parents or who experienced an avoidant or ambivalent attachment (Ebrahimi, Amiri, Mohamadlou, & Rezapur, 2017).
Do people with certain attachment styles attract those with similar styles? When people are asked what kinds of psychological or behavioral qualities they are seeking in a romantic partner, a large majority of people indicate that they are seeking someone who is kind, caring, trustworthy, and understanding, that is the kinds of attributes that characterize a “secure” caregiver (Chappell & Davis, 1998). However, we know that people do not always end up with others who meet their ideals. Are secure people more likely to end up with secure partners, and, vice versa, are insecure people more likely to end up with insecure partners? The majority of the research that has been conducted to date suggests that the answer is “yes.” Frazier, Byer, Fischer, Wright, and DeBord (1996) studied the attachment patterns of more than 83 heterosexual couples and found that, if the man was relatively secure, the woman was also likely to be secure.
Do early experiences as children shape adult attachment? The majority of research on this issue is retrospective; that is, it relies on adults’ reports of what they recall about their childhood experiences. This kind of work suggests that secure adults are more likely to describe their early childhood experiences with their parents as being supportive, loving, and kind (Hazan & Shaver, 1987). A number of longitudinal studies are emerging that demonstrate prospective associations between early attachment experiences and adult attachment styles and/or interpersonal functioning in adulthood. For example, Fraley, Roisman, Booth-LaForce, Owen, and Holland (2013) found in a sample of more than 700 individuals studied from infancy to adulthood that maternal sensitivity across development prospectively predicted security at age 18. Simpson, Collins, Tran, and Haydon (2007) found that attachment security, assessed in infancy in the strange situation, predicted peer competence in grades one to three, which, in turn, predicted the quality of friendship relationships at age 16, which, in turn, predicted the expression of positive and negative emotions in their adult romantic relationships at ages 20 to 23.
Factors influencing Attraction
attraction, or what makes people like, and even love, each other.
Similarity: One important factor in attraction is a perceived similarity in values and beliefs between the partners (Davis & Rusbult, 2001). The similarity is important for relationships because it is more convenient if both partners like the same activities and because similarity supports one’s values. We can feel better about ourselves and our choice of activities if we see that our partner also enjoys doing the same things that we do. Having others like and believe in the same things we do makes us feel validated in our beliefs. This is referred to as consensual validation and is an important aspect of why we are attracted to others.
Self-Disclosure: Liking is also enhanced by self-disclosure, the tendency to communicate frequently, without fear of reprisal, and in an accepting and empathetic manner. Friends are friends because we can talk to them openly about our needs and goals and because they listen and respond to our needs (Reis & Aron, 2008). However, self-disclosure must be balanced. If we open up about the concerns that are important to us, we expect our partner to do the same in return. If the self-disclosure is not reciprocal, the relationship may not last.
Proximity: Another important determinant of liking is proximity or the extent to which people are physically near us. Research has found that we are more likely to develop friendships with people who are nearby, for instance, those who live in the same dorm that we do, and even with people who just happen to sit nearer to us in our classes (Back, Schmukle, & Egloff, 2008).
mere exposure, which is the tendency to prefer stimuli (including, but not limited to people) that we have seen more frequently. The effect of mere exposure is powerful and occurs in a wide variety of situations. Infants tend to smile at a photograph of someone they have seen before more than they smile at a photograph of someone they are seeing for the first time (Brooks-Gunn & Lewis, 1981), and people prefer side-to-side reversed images of their own faces over their normal (nonreversed) face, whereas their friends prefer their normal face over the reversed one (Mita, Dermer, & Knight, 1977). This is expected on the basis of mere exposure since people see their own faces primarily in mirrors, and thus are exposed to the reversed face more often.
Love
Passion refers to the intense, physical attraction partners feel toward one another. Intimacy involves the ability the share feelings, psychological closeness and personal thoughts with the other. Commitment is the conscious decision to stay together. Passion can be found in the early stages of a relationship, but intimacy takes time to develop because it is based on the knowledge of the partner. Once intimacy has been established, partners may resolve to stay in the relationship. Although many would agree that all three components are important to a relationship, many love relationships do not consist of all three. Let’s look at other possibilities.
Liking: In this relationship, intimacy or knowledge of the other and a sense of closeness is present. Passion and commitment, however, are not. Partners feel free to be themselves and disclose personal information. They may feel that the other person knows them well and can be honest with them and let them know if they think the person is wrong. These partners are friends. However, being told that your partner “thinks of you as a friend” can be a devastating blow if you are attracted to them and seeking a romantic involvement.
Infatuation: Perhaps, this is Sternberg’s version of “love at first sight”. Infatuation consists of an immediate, intense physical attraction to someone. A person who is infatuated finds it hard to think of anything but the other person. Brief encounters are played over and over in one’s head; it may be difficult to eat and there may be a rather constant state of arousal. Infatuation is rather short-lived, however, lasting perhaps only a matter of months or as long as a year or so. It tends to be based on physical attraction and an image of what one “thinks” the other is all about.
Fatuous Love: However, some people who have a strong physical attraction push for commitment early in the relationship. Passion and commitment are aspects of fatuous love. There is no intimacy and the commitment is premature. Partners rarely talk seriously or share their ideas. They focus on their intense physical attraction and yet one, or both, is also talking of making a lasting commitment. Sometimes this is out of a sense of insecurity and a desire to make sure the partner is locked into the relationship.
Empty Love: This type of love may be found later in a relationship or in a relationship that was formed to meet needs other than intimacy or passion, including financial needs, childrearing assistance, or attaining/maintaining status. Here the partners are committed to staying in the relationship for the children, because of a religious conviction, or because there are no alternatives. However, they do not share ideas or feelings with each other and have no physical attraction for one another.
Romantic Love: Intimacy and passion are components of romantic love, but there is no commitment. The partners spend much time with one another and enjoy their closeness, but have not made plans to continue. This may be true because they are not in a position to make such commitments or because they are looking for passion and closeness and are afraid it will die out if they commit to one another and start to focus on other kinds of obligations.
Companionate Love: Intimacy and commitment are the hallmarks of companionate love. Partners love and respect one another and they are committed to staying together. However, their physical attraction may have never been strong or may have just died out over time. Nevertheless, partners are good friends and committed to one another.
Consummate Love: Intimacy, passion, and commitment are present in consummate love. This is often perceived by western cultures as “the ideal” type of love. The couple shares passion; the spark has not died, and the closeness is there. They feel like best friends, as well as lovers, and they are committed to staying together.
Adult Lifestyles
Singlehood: Being single is the most common lifestyle for people in their early 20s, and there has been an increase in the number of adults staying single. In 1960, only about 1 in 10 adults age 25 or older had never been married, in 2012 that had risen to 1 in 5 (Wang & Parker, 2014). While just over half (53%) of unmarried adults say they would eventually like to get married, 32 percent are not sure, and 13 percent do not want to get married. It is projected that by the time current young adults reach their mid-40s and 50s, almost 25% of them may not have married. The U.S. is not the only country to see a rise in the number of single adults.
• “Society is better off if people make marriage and having children a priority.”
• “Society is just as well off if people have priorities other than marriage and children”
Hooking Up: United States demographic changes have significantly affected the romantic relationships among emerging and early adults. As previously described, the age for puberty has declined, while the times for one’s first marriage and first child have been pushed to older ages. This results in a “historically unprecedented time gap where young adults are physiologically able to reproduce, but not psychologically or socially ready to settle down and begin a family and child-rearing,” (Garcia, Reiber, Massey, & Merriwether, 2012, p. 172). Consequently, according to Bogle (2007, 2008) traditional forms of dating have shifted to more casual hookups that involve uncommitted sexual encounters.
Friends with Benefits: Hookups are different than those relationships that involve continued mutual exchange. These relationships are often referred to as Friends with Benefits (FWB) or “Booty Calls.” These relationships involve friends having casual sex without commitment.
Hooking up Gender Differences: When asked about their motivation for hooking up, both males and females indicated physical gratification, emotional gratification, and a desire to initiate a romantic relationship as reasons (Garcia & Reiber, 2008). Although males and females are more similar than different in their sexual behaviors, a consistent finding among the research is that males demonstrate a greater permissiveness to casual sex (Oliver & Hyde, 1993). In another study involving 16,288 individuals across 52 nations, males reported a greater desire of sexual partner variety than females, regardless of relationship status or sexual orientation (Schmitt et al., 2003). This difference can be attributed to gender role expectations for both males and females regarding sexual promiscuity. Additionally, the risks of sexual behavior are higher for females and include unplanned pregnancy, increased sexually transmitted diseases, and susceptibility to sexual violence (Garcia et al., 2012).
Emotional Consequences of Hooking up: Concerns regarding hooking up behavior certainly are evident in the research literature. One significant finding is the high comorbidity of hooking up and substance use. Those engaging in non-monogamous sex are more likely to have used marijuana, cocaine, and alcohol, and the overall risks of sexual activity are drastically increased with the addition of alcohol and drugs (Garcia et al., 2012). Regret has also been expressed, and those who had the most regret after hooking up also had more symptoms of depression (Welsh, Grello, & Harper, 2006). Hookups were also found to lower self-esteem, increase guilt, and foster feelings of using someone or feeling used. Females displayed more negative reactions than males, and this may be due to females identifying more emotional involvement in sexual encounters than males.
gratification. However, they also want a more committed romantic relationship and may feel regret with uncommitted sex.
Online Dating: The ways people are finding love has changed with the advent of the Internet. Nearly 50 million Americans have tried an online dating website or mobile app (Bryant & Sheldon, 2017). Online dating has also increased dramatically among those aged 18 to 24. Today, one in five emerging adults report using a mobile dating app, while in 2013 only 5% did, and 27% report having used online dating, almost triple the rate in 2013 (Smith & Anderson, 2016).
As Finkel, Burnette, and Scissors (2007) found, social networking sites and the Internet perform three important tasks. Specifically, sites provide individuals with access to a database of other individuals who are interested in meeting someone. Dating sites generally reduce issues of proximity, as individuals do not have to be close in proximity to meet. Also, they provide a medium in which individuals can communicate with others. Finally, some Internet dating websites advertise special matching strategies, based on factors such as personality, hobbies, and interests, to identify the “perfect match” for people looking for love online. Social networking sites have provided opportunities for meeting others you would not have normally met. According to a recent survey of couples who met online versus offline (Brown, 2019), those who met online tended to have slightly different levels of education, and political views from their partners, but, the biggest difference was that they were much more likely to come from different racial and ethnic backgrounds (see Figure 7.27). This is not surprising as the average age of the couples who met online was 36, while the average age of couples who met offline was 51. Young adults are more likely to a relationship with people who are different from them, regardless of how they met.
Catfishing refers to “a deceptive activity involving the creation of a fake online profile for deceptive purposes” (Smith, Smith, & Blazka, 2017, p. 33). Notre Dame University linebacker Manti Ta’o fell victim to a catfishing scam. The young woman “Kekua” who he had struck up an online relationship with was a hoax, and he was not the first person to have been scammed by this fictitious woman. A number of US states have passed legislation to address online impersonation, from stealing the information and creating a fake account of a real person to the creation of a fictitious persona with the intent to defraud or harm others (National Conference of State Legislatures, 2017).
Cohabitation: In American society, as well as in a number of other cultures, cohabitation has become increasingly commonplace (Gurrentz, 2018). For many emerging adults, cohabitation has become more commonplace than marriage, as can be seen in Figures 7.28. While marriage is still a more common living arrangement for those 25-34, cohabitation has increased, while marriage has declined, as can be seen in Figure 7.29. Gurrentz also found that cohabitation varies by socioeconomic status. Those who are married tend to have higher levels of education, and thus higher earnings, or earning potential.
Three explanations have been given for the rise of cohabitation in Western cultures. The first notes that the increase in individualism and secularism, and the resulting decline in religious observance, has led to greater acceptance and adoption of cohabitation (Lesthaeghe & Surkyn, 1988). Moreover, the more people view cohabitating couples, the more normal this relationship becomes, and the more couples who will then cohabitate. Thus, cohabitation is both a cause and the effect of greater cohabitation.Three explanations have been given for the rise of cohabitation in Western cultures. The first notes that the increase in individualism and secularism, and the resulting decline in religious observance, has led to greater acceptance and adoption of cohabitation (Lesthaeghe & Surkyn, 1988).
equality and sexual freedom, with marriage, no longer being the only long-term relationship option (Bumpass, 1990). A final explanation suggests that the change in employment requirements, with many jobs now requiring more advanced education, has led to a competition between marriage and pursuing post-secondary education (Yu & Xie, 2015). This might account for the increase in the age of first marriage in many nations. Taken together, the greater acceptance of premarital sex, and the economic and educational changes would lead to a transition in relationships. Overall, cohabitation may become a step in the courtship processor may, for some, replace marriage altogether.
Cohabitation in Non-Western Cultures, The Philippines and China: Similar to other nations, young people in the Philippines are more likely to delay marriage, to cohabitate, and to engage in premarital sex as compared to previous generations (Williams, Kabamalan, & Ogena, 2007).
Marriage Worldwide: Cohen (2013) reviewed data assessing most of the world’s countries and found that marriage has declined universally during the last several decades. This decline has occurred in both poor and rich countries, however, the countries with the biggest drops in marriage were mostly rich: France, Italy, Germany, Japan, and the U.S. Cohen states that the decline is not only due to individuals delaying marriage but also because of high rates of non- marital cohabitation. Delayed or reduced marriage is associated with higher income and lower fertility rates that are reflected worldwide.
Marriage in the United States: In 1960, 72% of adults age 18 or older were married, in 2010 this had dropped to barely half (Wang & Taylor, 2011). At the same time, the age of first marriage has been increasing for both men and women. In 1960, the average age for first marriage was 20 for women and 23 for men. By 2010 this had increased to 26.5 for women and nearly 29 for men (see Figure 7.30). Many of the explanations for increases in singlehood and cohabitation previously given can also account for the drop and delay in marriage.
Same-Sex Marriage: On June 26, 2015, the United States Supreme Court ruled that the Constitution guarantees same-sex marriage. The decision indicated that limiting marriage to only heterosexual couples violated the 14th amendment’s guarantee of equal protection under the law. This ruling occurred 11 years after same-sex marriage was first made legal in Massachusetts, and at the time of the high court decision, 36 states and the District of Columbia had legalized same-sex marriage. Worldwide, 29 countries currently have national laws allowing gays and lesbians to marry (Pew Research Center, 2019). As can be seen in Table 7.8, these countries are located mostly in Europe and the Americas.
Cultural Influences on Marriage: Many cultures have both explicit and unstated rules that specify who is an appropriate mate. Consequently, mate selection is not completely left to the individual. Rules of endogamy indicate the groups we should marry within and those we should not marry in (Witt, 2009). For example, many cultures specify that people marry within their own race, social class, age group, or religion. Endogamy reinforces the cohesiveness of the group. Additionally, these rules encourage homogamy or marriage between people who share social characteristics. The majority of marriages in the U. S. are homogamous with respect to race, social class, age and to a lesser extent, religion. Homogamy is also seen in couples with similar personalities and interests.
Arranged Marriages and Elopement: Historically, marriage was not a personal choice, but one made by one’s family. Arranged marriages often ensured proper transference of a family’s wealth and the support of ethnic and religious customs. Such marriages were a marriage of families rather than of individuals. In Western Europe, starting in the 18th century the notion of personal choice in a marital partner slowly became the norm. Arranged marriages were seen as “traditional” and marriages based on love “modern”. Many of these early “love” marriages were obtained by eloping (Thornton, 2005).
Marital Arrangements in India: As the number of arranged marriages in India is declining, elopement is increasing. Allendorf’s (2013) study of a rural village in India, describes the elopement process. In many cases, the female leaves her family home and goes to the male’s home, where she stays with him and his parents. After a few days, a member of his family will inform her family of her whereabouts and gain consent for the marriage. In other cases, where the couple anticipates some degree of opposition to the union, the couple may run away without the knowledge of either family, often going to a relative of the male. After a few days, the couple comes back to the home of his parents, where at that point consent is sought from both families. Although, in some cases, families may sever all ties with their child or encourage him or her to abandon the relationship, typically, they agree to the union as the couple has spent time together overnight. Once consent has been given, the couple lives with his family and are considered married. A more formal ceremony takes place a few weeks or months later.
travel, and general Westernization of ideas. Besides India, China, Nepal, and several nations in Southeast Asia have seen a decline in the number of arranged marriages, and an increase in elopement or couples choosing their own partners with their families’ blessings (Allendorf, 2013).
Predictors of Marital Harmony: Advice on how to improve one’s marriage is centuries old. One of today’s experts on marital communication is John Gottman. Gottman (1999) differs from many marriage counselors in his belief that having a good marriage does not depend on compatibility. Rather, the way that partners communicate with one another is crucial. At the University of Washington in Seattle, Gottman has measured the physiological responses of thousands of couples as they discuss issues of disagreement. Fidgeting is one’s chair, leaning closer to or further away from the partner while speaking, and increases in respiration and heart rate are all recorded and analyzed along with videotaped recordings of the partners’ exchanges. Gottman believes he can accurately predict whether or not a couple will stay together by analyzing their communication. In marriages destined to fail, partners engage in the “marriage killers”: Contempt, criticism, defensiveness, and stonewalling. Each of these undermines the politeness and respect that healthy marriages require. Stonewalling, or shutting someone out, is the strongest sign that a relationship is destined to fail.
Accumulated Positive Deposits: When there is a positive balance of relationship deposits this can help the overall relationship in times of conflict. For instance, some research indicates that a husband’s level of enthusiasm in everyday marital interactions was related to a wife’s affection in the midst of conflict (Driver & Gottman, 2004), showing that being pleasant and making deposits can change the nature of the conflict. Also, Gottman and Levenson (1992) found that couples rated as having more pleasant interactions, compared with couples with less pleasant interactions, reported marital problems as less severe, higher marital satisfaction, better physical health, and less risk for divorce. Finally, Janicki, Kamarck, Shiffman, and Gwaltney (2006) showed that the intensity of conflict with a spouse predicted marital satisfaction unless there was a record of positive partner interactions, in which case the conflict did not matter as much.
Intimate Partner Abuse
situational couple violence, which is the violence that results when heated conflict escalates, and intimate terrorism, in which one partner consistently uses fear and violence to dominate the other (Bosson, et al., 2019). Men and women equally use and experience situational couple violence, while men are more likely to use intimate terrorism than are women. Consistent with this, a national survey described below, found that female victims of intimate partner violence experience different patterns of violence, such as rape, severe physical violence, and stalking than male victims, who most often experienced more slapping, shoving, and pushing.
• Nearly 1 in 3 women and 1 in 6 men experienced some form of contact sexual violence during their lifetime.
• Nearly 1 in 5 women and 1 in 39 men have been raped in their lifetime.
• Approximately 1 in 6 women and 1 in 10 men experienced sexual coercion (e.g., sexual pressure from someone in authority, or being worn down by requests for sex).
• Almost 1 in 5 women have been the victim of severe physical violence by an intimate partner, while 1 in 7 men have experienced the same.
• 1 in 6 women has been stalked during their lifetime, compared to 1 in 19 men.
• More than 1 in 4 women and more than 1 in 10 men have experienced contact sexual violence, physical violence, or stalking by an intimate partner and reported significant short- or long-term impacts, such as post-traumatic stress disorder symptoms and injury.
• An estimated 1 in 3 women experienced at least one act of psychological aggression by an intimate partner during their lifetime.
• Men and women who experienced these forms of violence were more likely to report frequent headaches, chronic pain, difficulty with sleeping, activity limitations, poor physical health, and poor mental health than men and women who did not experience these forms of violence.
Parenthood
Influences on Parenting: Parenting is a complex process in which parents and children influence on another. There are many reasons that parents behave the way they do. The multiple influences on parenting are still being explored. Proposed influences on parenting include Parent characteristics, child characteristics, and contextual can sociocultural characteristics. (Belsky, 1984; Demick, 1999).
Parent Characteristics: Parents bring unique traits and qualities to the parenting relationship that affect their decisions as parents. These characteristics include the age of the parent, gender, beliefs, personality, developmental history, knowledge about parenting and child development, and mental and physical health. Parents’ personalities affect parenting behaviors. Mothers and fathers who are more agreeable, conscientious, and outgoing are warmer and provide more structure to their children. Parents who are more agreeable, less anxious, and less negative also support their children’s autonomy more than parents who are anxious and less agreeable (Prinzie, Stams, Dekovic, Reijntes, & Belsky, 2009). Parents who have these personality traits appear to be better able to respond to their children positively and provide a more consistent, structured environment for their children.
Child Characteristics: Parenting is bidirectional. Not only do parents affect their children, but children also influence their parents. Child characteristics, such as gender, birth order, temperament, and health status, affect parenting behaviors and roles. For example, an infant with an easy temperament may enable parents to feel more effective, as they are easily able to soothe the child and elicit smiling and cooing. On the other hand, a cranky or fussy infant elicits fewer positive reactions from his or her parents and may result in parents feeling less effective in the parenting role (Eisenberg et al., 2008). Over time, parents of more difficult children may become more punitive and less patient with their children (Clark, Kochanska, & Ready, 2000; Eisenberg et al., 1999; Kiff, Lengua, & Zalewski, 2011). Parents who have a fussy, difficult child are less satisfied with their marriages and have greater challenges in balancing work and family roles (Hyde, Else-Quest, & Goldsmith, 2004). Thus, child temperament, as previously discussed in chapter 3, is one of the child characteristics that influence how parents behave with their children.
Contextual Factors and Sociocultural Characteristics: The parent-child relationship does not occur in isolation. Sociocultural characteristics, including economic hardship, religion, politics, neighborhoods, schools, and social support, also influence parenting. Parents who experience economic hardship are more easily frustrated, depressed, and sad, and these emotional characteristics affect their parenting skills (Conger & Conger, 2002). Culture also influences parenting behaviors in fundamental ways. Although promoting the development of skills necessary to function effectively in one’s community is a universal goal of parenting, the specific skills necessary vary widely from culture to culture. Thus, parents have different goals for their children that partially depend on their culture (Tamis-LeMonda et al., 2008). Parents vary in how much they emphasize goals for independence and individual achievements, maintaining harmonious relationships, and being embedded in a strong network of social relationships. Other important contextual characteristics, such as the neighborhood, school, and social networks, also affect parenting, even though these settings do not always include both the child and the parent (Brofenbrenner, 1989). Culture is also a contributing contextual factor, as discussed previously in chapter four. For example, Latina mothers who perceived their neighborhood as more dangerous showed less warmth with their children, perhaps because of the greater stress associated with living a threatening environment (Gonzales et al., 2011). The different influences are shown in Figure 7.35.
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/10%3A_Development_in_Early_Adulthood/10.03%3A_Chapter_24-_Psychosocial_Development_in_Early_Adulthood.txt |
Chapter 25 Learning Objectives
• Explain the difference between primary and secondary aging
• Describe sensory changes that occur during middle adulthood
• Identify health concerns in middle adulthood
• Explain what occurs during the climacteric for females and males
• Describe sexuality during middle adulthood
• Explain the importance of sleep and consequences of sleep deprivation
• Describe the importance of exercise and nutrition for optimal health
• Describe brain functioning in middle adulthood
biological factors, such as molecular and cellular changes, and oxidative damage are called primary aging, while aging that occurs due to controllable factors, such as an unhealthy lifestyle including lack of physical exercise and poor diet, is called secondary aging (Busse, 1969). These factors are shown in Figure 8.1
Physical Changes
Hair: When asked to imagine someone in middle adulthood, we often picture someone with the beginnings of wrinkles and gray or thinning hair. What accounts for these physical changes?
Skin: Skin continues to dry out and is prone to more wrinkling, particularly on the sensitive face area. Wrinkles, or creases in the skin, are a normal part of aging. As we get older, our skin dries and loses the underlying layer of fat, so our face no longer appears smooth. Loss of muscle tone and thinning skin can make the face appear flabby or drooping. Although wrinkles are a natural part of aging and genetics plays a role, frequent sun exposure and smoking will cause wrinkles to appear sooner. Dark spots and blotchy skin also occur as one ages and are due to exposure to sunlight (Moskowitz, 2014). Blood vessels become more apparent as the skin continues to dry and get thinner.
Sarcopenia: The loss of muscle mass and strength that occurs with aging is referred to as sarcopenia (Morley, Baumgartner, Roubenoff, Mayer, & Nair, 2001). Sarcopenia is thought to be a significant factor in the frailty and functional impairment that occurs when older. The decline of growth and anabolic hormones, especially testosterone, and decreased physical activity have been implicated as causes of sarcopenia (Proctor, Balagopal, & Nair, 1998). This decline in muscle mass can occur as early as 40 years of age and contributes significantly to a decrease in life quality, increase in health care costs, and early death in older adults (Karakelides & Nair, 2005). Exercise is certainly important to increase strength, aerobic capacity, and muscle protein synthesis, but unfortunately it does not reverse all the age-related changes that occur. The muscle-to-fat ratio for both men and women also changes throughout middle adulthood, with an accumulation of fat in the stomach area.
Lungs: The lungs serve two functions: Supply oxygen and remove carbon dioxide. Thinning of the bones with age can change the shape of the rib cage and result in a loss of lung expansion. Age-related changes in muscles, such as the weakening of the diaphragm, can also reduce lung capacity. Both of these changes will lower oxygen levels in the blood and increase the levels of carbon dioxide. Experiencing shortness of breath and feeling tired can result (NIH, 2014b). In middle adulthood, these changes and their effects are often minimal, especially in people who are non-smokers and physically active. However, in those with chronic bronchitis, or who have experienced frequent pneumonia, asthma other lung-related disorders, or who are smokers, the effects of these normal age changes can be more pronounced.
Sensory Changes
Vision: A normal change of the eye due to age is presbyopia, which is Latin for “old vision.” It refers to a loss of elasticity in the lens of the eye that makes it harder for the eye to focus on objects that are closer to the person. When we look at something far away, the lens flattens out; when looking at nearby objects tiny muscle fibers around the lens enable the eye to bend the lens. With age these muscles weaken and can no longer accommodate the lens to focus the light. Anyone over the age of 35 is at risk for developing presbyopia. According to the National Eye Institute (NEI) (2016), signs that someone may have presbyopia include:
• Hard time reading small print
• Having to hold reading material farther than arm’s distance
• Problems seeing objects that are close
• Headaches
• Eyestrain
floaters, little spots or “cobwebs” that float around the field of vision. They are most noticeable if you are looking at the sky on a sunny day, or at a lighted blank screen. Floaters occur when the vitreous, a gel-like substance in the interior of the eye, slowly shrinks. As it shrinks, it becomes somewhat stringy, and these strands can cast tiny shadows on the retina. In most cases, floaters are harmless, more of an annoyance than a sign of eye problems. However, floaters that appear suddenly, or that darken and obscure vision can be a sign of more serious eye problems, such a retinal tearing, infection, or inflammation. People who are very nearsighted (myopic), have diabetes, or who have had cataract surgery are also more likely to have floaters (NEI, 2009).
scotopic sensitivity, the ability to see in dimmer light. By age 60, the retina receives only one third as much light as it did at age 20, making working in dimmer light more difficult (Jackson & Owsley, 2000). Night vision is also affected as the pupil loses some of its ability to open and close to accommodate drastic changes in light. Eyes become more sensitive to glare from headlights and street lights making it difficult to see people and cars, and movements outside of our direct line of sight (NIH, 2016c).
dry eye syndrome, which occurs when the eye does not produce tears properly, or when the tears evaporate too quickly because they are not the correct consistency (NEI, 2013). While dry eye can affect people at any age, nearly 5 million Americans over the age of 50 experience dry eye. It affects women more than men, especially after menopause. Women who experienced an early menopause may be more likely to experience dry eye, which can cause surface damage to the eye.
Hearing: Hearing problems increase during middle adulthood. According to a recent UK study (Dawes et al., 2014), the rate of hearing problems in their sample doubled between the ages of 40 and 55 and tripled by age 64. Similar statistics are found in U.S. samples of middle-aged adults. Prior to age 40, about 5.5% of adults report hearing problems. This jumps to 19% among 40 to 69 year-olds (American Psychological Association, 2016). Middle-aged adults may experience more problems understanding speech when in noisy environments, in comparison to younger adults (Füllgrabe, Moore, & Stone, 2015; Neidleman, Wambacq, Besing, Spitzer, & Koehnke, 2015). As we age we also lose the ability to hear higher frequencies (Humes, Kewley-Port, Fogerty, & Kinney, 2010). Hearing changes are more common among men than women, but males may underestimate their hearing problems (Uchida, Nakashima, Ando, Niino, & Shimokata, 2003). For many adults, hearing loss accumulates after years of being exposed to intense noise levels. Men are more likely to work in noisy occupations. Hearing loss is also exacerbated by cigarette smoking, high blood pressure, diabetes, and stroke. Most hearing loss could be prevented by guarding against being exposed to extremely noisy environments.
Health Concerns
Heart Disease: According to the most recent National Vital Statistics Reports (Kochanek, Murphy, Xu, & Arias, 2019) heart disease continues to be the number one cause of death for Americans as it claimed 23% of those who died in 2017. It is also the number one cause of death worldwide (World Health Organization, 2018). Heart disease develops slowly over time and typically appears in midlife (Hooker & Pressman, 2016).
Atherosclerosis, or a buildup of fatty plaque in the arteries, is the most common cause of cardiovascular disease. The plaque buildup thickens the artery walls and restricts the blood flow to organs and tissues. Cardiovascular disease can lead to a heart attack, chest pain (angina), or stroke (Mayo Clinic, 2014a). Figure 8.5 illustrates atherosclerosis.
• Advanced Age-increased risk for narrowed arteries and weakened or thickened heart muscle.
• Sex-males are at greater risk, but a female’s risk increases after menopause.
• Family History-increased risk, especially if male parent or brother developed heart. disease before age 55 or female parent or sister developed heart disease before age 65.
• Smoking-nicotine constricts blood vessels and carbon monoxide damages the inner lining.
• Poor Diet-a diet high in fat, salt, sugar, and cholesterol.
• Excessive Alcohol Consumption-alcohol can raise the level of bad fats in the blood and increase blood pressure
• Stress-unrelieved stress can damage arteries and worsen other risk factors.
• Poor Hygiene-establishing good hygiene habits can prevent viral or bacterial infections that can affect the heart. Poor dental care can also contribute to heart disease.
Hypertension, or high blood pressure, is a serious health problem that occurs when the blood flows with a greater force than normal. One in three American adults (70 million people) have hypertension and only half have it under control (Nwankwo, Yoon, Burt, & Gu, 2013). It can strain the heart, increase the risk of heart attack and stroke, or damage the kidneys (CDC, 2014a). Uncontrolled high blood pressure in early and middle adulthood can also damage the brain’s white matter (axons) and may be linked to cognitive problems later in life (Maillard et al., 2012). Normal blood pressure is under 120/80 (see Table 8.1). The first number is the systolic pressure, which is the pressure in the blood vessels when the heartbeats. The second number is the diastolic pressure, which is the pressure in the blood vessels when the heart is at rest. High blood pressure is sometimes referred to as the silent killer, as most people with hypertension experience no symptoms. Making positive lifestyle changes can often reduce blood pressure.
• Family history of hypertension
• A diet that is too high in sodium often found in processed foods, and too low in potassium
• Sedentary lifestyle and Obesity
• Too much alcohol consumption
• Tobacco use, as nicotine raises blood pressure (CDC, 2014b)
Cancer: After heart disease, cancer was the second leading cause of death for Americans in 2017 as it accounted for 21.3% of all deaths (Kochanek et al., 2016). According to the National Institutes of Health (2015), cancer is the name given to a collection of related diseases in which the body’s cells begin to divide without stopping and spread into surrounding tissues. These extra cells can divide, and form growths called tumors, which are typically masses of tissue. Cancerous tumors are malignant, which means they can invade nearby tissues. When removed malignant tumors may grow back. Unlike malignant tumors, benign tumors do not invade nearby tissues. Benign tumors can sometimes be quite large, and when removed usually do not grow back. Although benign tumors in the body are not cancerous, benign brain tumors can be life-threatening.
Cholesterol is a waxy fatty substance carried by lipoprotein molecules in the blood. It is created by the body to create hormones and digest fatty foods and is also found in many foods. Your body needs cholesterol, but too much can cause heart disease and stroke. Two important kinds of cholesterol are low-density lipoprotein (LDL) and high-density lipoprotein (HDL). The third type of fat is called triglycerides. Your total cholesterol score is based on all three types of lipids (see Table 8.3). Total cholesterol is calculated by adding HDL plus LDL plus 20% of the Triglycerides.
Diabetes (Diabetes Mellitus) is a disease in which the body does not control the amount of glucose in the blood. This disease occurs when the body does not make enough insulin or does not use it the way it should (NIH, 2016a). Insulin is a type of hormone that helps glucose in the blood enter cells to give them energy. In adults, 90% to 95% of all diagnosed cases of diabetes are type 2 (American Diabetes Association (ADA), 2016). Type 2 diabetes usually begins with insulin resistance, a disorder in which the cells in the muscles, liver, and fat tissue do not use insulin properly (CDC, 2014d). As the need for insulin increases, cells in the pancreas gradually lose the ability to produce enough insulin. In some Type 2 diabetics, pancreatic beta cells will cease functioning, and the need for insulin injections will become necessary. Some people with diabetes experience insulin resistance with only minor dysfunction of the beta-cell secretion of insulin. Other diabetics experience only slight insulin resistance, with the primary cause being a lack of insulin secretion (CDC, 2014d).
• Those over age 45
• Obesity
• Family history of diabetes
• History of gestational diabetes (see Chapter 2)
• Race and ethnicity
• Physical inactivity
• Diet.
diabetic retinopathy, which is damage to the small blood vessels in the retina that may lead to loss of vision (NEI, 2015). More than 4% showed advanced diabetic retinopathy. Diabetes is linked as the primary cause of almost half (44%) of new cases of kidney failure each year. About 60% of non-traumatic limb amputations occur in people with diabetes. Diabetes has been linked to hearing loss, tinnitus (ringing in the ears), gum disease, and neuropathy (nerve disease) (CDC, 2014d).
Metabolic Syndrome is a cluster of several cardiometabolic risk factors, including large waist circumference, high blood pressure, and elevated triglycerides, LDL, and blood glucose levels, which can lead to diabetes and heart disease (Crist et al., 2012). The prevalence of metabolic syndrome in the U.S. is approximately 34% and is especially high among Hispanics and African Americans (Ford, Li, & Zhao, 2010). Prevalence increases with age, peaking in one’s 60s (Ford et al., 2010). Metabolic syndrome increases morbidity from cardiovascular disease and diabetes (Hu et al., 2004; Malik, 2004). Hu and colleagues found that even having one or two of the risk factors for metabolic syndrome increased the risk of mortality. Crist et al. (2012) found that increasing aerobic activity and reducing weight led to a drop in many of the risk factors of metabolic syndrome, including a reduction in waist circumference and blood pressure, and an increase in HDL cholesterol.
Rheumatoid arthritis (RA) is an inflammatory disease that causes pain, swelling, stiffness, and loss of function in the joints (NIH, 2016b). RA occurs when the immune system attacks the membrane lining the joints (see Figure 8.8). RA is the second most common form of arthritis after osteoarthritis, which is the normal wear and tear on the joints discussed in chapter 9. Unlike osteoarthritis, RA is symmetric in its attack of the body, thus, if one shoulder is affected so is the other. In addition, those with RA may experience fatigue and fever. Below are the common features of RA (NIH, 2016b).
Features of Rheumatoid Arthritis
• Tender, warm, swollen joints
• Symmetrical pattern of affected joints
• Joint inflammation often affecting the wrist and finger joints closest to the hand
• Joint inflammation sometimes affecting other joints, including the neck, shoulders, elbows, hips, knees, ankles, and feet
• Fatigue, occasional fevers, a loss of energy
• Pain and stiffness lasting for more than 30 minutes in the morning or after a long rest
• Symptoms that last for many years
• Variability of symptoms among people with the disease.
Fatty liver disease (hepatic steatosis) refers to the accumulation of fat in the liver. The liver normally contains little fat, and anything below 5% of liver weight is considered normal. This disease is present in 33% of American adults. In the past, the main cause of fat accumulation in the liver was due to excessive alcohol consumption, often eventually leading to cirrhosis and liver failure. Today, increased caloric intake, especially resulting in obesity, and little physical activity are the main causes. Mild to moderate levels of hepatic steatosis can be reversed through healthy lifestyle changes (Nassir, Rector, Hammoud, & Ibdah, 2015).
Digestive Issues
Heartburn, also called acid indigestion or pyrosis, is a common digestive problem in adults and is the result of stomach acid backing up into the esophagus. Prolonged contact with the digestive juices injures the lining of the esophagus and causes discomfort. Heartburn that occurs more frequently may be due to gastroesophageal reflux disease or GERD. Normally the lower sphincter muscle in the esophagus keeps the acid in the stomach from entering the esophagus. In GERD this muscle relaxes too frequently and the stomach acid flows into the esophagus. In the U.S., 60 million people experience heartburn at least once a month, and 15 million experience it every day. Prolonged problems with heartburn can lead to more serious complications, including esophageal cancer, one of the most lethal forms of cancer in the U.S. Problems with heartburn can be linked to eating fatty or spicy foods, caffeine, smoking, and eating before bedtime (American College of Gastroenterology, 2016a).
Gallstones are hard particles, including fatty materials, bile pigments, and calcium deposits, that can develop in the gallbladder. Ranging in size from a grain of sand to a golf ball, they typically take years to develop, but in some people have developed over the course of a few months. About 75% of gallstones do not create any symptoms, but those that do may cause sporadic upper abdominal pain when stones block bile or pancreatic ducts. If stones become lodged in the ducts, it may necessitate surgery or other medical intervention as it could become life-threatening if left untreated (American College of Gastroenterology, 2016b).
Sleep
Sleep problems: According to the Sleep in America poll (National Sleep Foundation, 2015), 9% of Americans report being diagnosed with a sleep disorder, and of those 71% have sleep apnea and 24% suffer from insomnia. Pain is also a contributing factor in the difference between the amount of sleep Americans say they need and the amount they are getting. An average of 42 minutes of sleep debt occur for those with chronic pain, and 14 minutes for those who have suffered from acute pain in the past week. Stress and overall poor health are also key components of shorter sleep durations and worse sleep quality. Those in midlife with lower life satisfaction experienced greater delay in the onset of sleep than those with higher life satisfaction. Delayed onset of sleep could be the result of worry and anxiety during midlife, and improvements in those areas should improve sleep. Lastly, menopause can affect a woman’s sleep duration and quality (National Sleep Foundation, 2016).
Children in the home and sleep: As expected, having children at home affects the amount of sleep one receives. According to a 2016 National Center for Health Statistics analysis (CDC, 2016) having children decreases the amount of sleep an individual receives, however, having a partner can improve the amount of sleep for both males and females. Table 8.6 illustrates the percentage of individuals not receiving seven hours of sleep per night based on parental role.
Negative consequences of insufficient sleep: There are many consequences of too little sleep, and they include physical, cognitive, and emotional changes. Sleep deprivation suppresses immune responses that fight off infection, and can lead to obesity, memory impairment, and hypertension (Ferrie et al., 2007; Kushida, 2005). Insufficient sleep is linked to an increased risk for colon cancer, breast cancer, heart disease and type 2 diabetes (Pattison, 2015). A lack of sleep can increase stress as cortisol (a stress hormone) remains elevated which keeps the body in a state of alertness and hyperarousal which increases blood pressure. Sleep is also associated with longevity. Dew et al. (2003) found that older adults who had better sleep patterns also lived longer. During deep sleep a growth hormone is released which stimulates protein synthesis, breaks down fat that supplies energy, and stimulates cell division. Consequently, a decrease in deep sleep contributes to less growth hormone being released and subsequent physical decline seen in aging (Pattison, 2015).
Exercise, Nutrition, and Weight
The impact of exercise: Exercise is a powerful way to combat the changes we associate with aging. Exercise builds muscle, increases metabolism, helps control blood sugar, increases bone density, and relieves stress. Unfortunately, fewer than half of midlife adults exercise and only about 20 percent exercise frequently and strenuously enough to achieve health benefits. Many stop exercising soon after they begin an exercise program, particularly those who are very overweight. The best exercise programs are those that are engaged in regularly, regardless of the activity. A well-rounded program that is easy to follow includes walking and weight training. Having a safe, enjoyable place to walk can make the difference in whether or not someone walks regularly. Weight lifting and stretching exercises at home can also be part of an effective program. Exercise is particularly helpful in reducing stress in midlife. Walking, jogging, cycling, or swimming can release the tension caused by stressors. Learning relaxation techniques can also have healthful benefits. Exercise can be thought of as preventative health care. Promoting exercise for the 78 million “baby boomers” may be one of the best ways to reduce health care costs and improve quality of life (Shure & Cahan, 1998).
• Adults should avoid being inactive. Any activity will result in some health benefits.
• For substantial health benefits, adults should engage in at least 150 minutes per week of moderate-intensity exercise OR at least 75 minutes of vigorous-intensity aerobic activity. Aerobic activity should occur for at least 10 minutes and preferably spread throughout the week.
• For more extensive health benefits, adults can increase their aerobic activity to 300 minutes per week of moderate-intensity OR 150 minutes per week of vigorous-intensity aerobic activity.
• Adults should also participate in muscle-strengthening activities that are moderate or high intensity and involve all major muscle groups on two or more days per week.
Nutritional concerns: Aging brings about a reduction in the number of calories a person requires (see Table 8.7 for estimated caloric needs in middle-aged adults). Many Americans respond to weight gain by dieting. However, eating less does not typically mean eating right and people often suffer vitamin and mineral deficiencies as a result. All adults need to be especially cognizant of the amount of sodium, sugar, and fat they are ingesting.
Excess Sodium: According to dietary guidelines, adults should consume less than 2,300mg (1 teaspoon) per day of sodium. The American Heart Association (2016) reports that the average sodium intake among Americans is 3440mg per day. Processed foods are the main culprits of excess sodium. High sodium levels in the diet is correlated with increased blood pressure, and its reduction does show corresponding drops in blood pressure. Adults with high blood pressure are strongly encouraged to reduce their sodium intake to 1500mg (U.S. Department of Health and Human Services & U.S. Department of Agriculture (USHHS & USDA), 2015).
Excess Fat: Dietary guidelines also suggests that adults should consume less than 10 percent of calories per day from saturated fats. The American Heart Association (2016) says optimally we should aim for a dietary pattern that achieves 5% to 6% of calories from saturated fat. In a 2000 calorie diet that is about 120 calories from saturated fat. In the average American diet about 34.3% of the diet comes from fat, with 15.0% from saturated fat (Berglund et al., 1999). Diets high in fat not only contribute to weight gain, but have been linked to heart disease, stroke, and high cholesterol.
Added Sugar: According to the recent Dietary Guidelines for Americans (USHHS & USDA, 2015) eating healthy means adults should consume less than 10 percent of calories per day from added sugars. Yet, currently, about 15% of the calories in the American adult diet come from added sugars, or about 22 teaspoons of sugar per day (NIH, 2014c). Excess sugar not only contributes to weight gain but diabetes and other health problems.
Metabolism and Weight Gain: One of the common complaints of midlife adults is weight gain, especially the accumulation of fat in the abdomen, which is often referred to as the middle-aged spread (Lachman, 2004). Men tend to gain fat on their upper abdomen and back, while women tend to gain more fat on their waist and upper arms. Many adults are surprised at this weight gain because their diets have not changed, however, their metabolism has slowed during midlife. Metabolism is the process by which the body converts food and drink into energy. The calories consumed are combined with oxygen to release the energy needed to function (Mayo Clinic, 2014b). People who have more muscle burn more calories, even at rest, and thus have a higher metabolism.
Obesity: As discussed in the early adulthood chapter, obesity is a significant health concern for adults throughout the world, and especially America. Obesity rates continue to increase and the current rate for those 40-59 is 42.8%, which is the highest percentage per age group (CDC, 2017). Being overweight is associated with a myriad of health conditions including diabetes, high blood pressure, and heart disease. New research is now linking obesity to Alzheimer’s disease. Chang et al. (2016) found that being overweight in midlife was associated with earlier onset of Alzheimer’s disease. The study looked at 1,394 men and women who were part of the Baltimore Longitudinal Study of Aging. Their average age was around 60, and they were followed for 14 years. Results indicated that people with the highest body mass index, or BMI, at age 50 were more likely to develop Alzheimer’s disease. In fact, each one-point increase in BMI was associated with getting Alzheimer’s six to seven months earlier. Those with the highest BMIs also had more brain changes typical of Alzheimer’s, even if they did not have symptoms of the disease. Scientists speculate that fat cells may produce harmful chemicals that promote inflammation in blood vessels throughout the body, including in the brain. The conclusion of the study was that a healthy BMI at midlife may delay the onset of Alzheimer’s disease.
Concluding Thoughts: Many of the changes that occur in midlife can be easily compensated for, such as buying glasses, exercising, and watching what one eats. However, the percentage of middle adults who have a significant health concern has increased in the past 15 years. According to the 2016 United Health Foundation’s America’s Health Rankings Senior Report, the next generation of seniors will be less healthy than the current seniors (United Health Foundation, 2016). The study compared the health of middle-aged Americans (50-64 years of age) in 2014 to middle-aged Americans in 1999. Results indicated that in the past 15 years the prevalence of diabetes has increased by 55% and the prevalence of obesity has increased by 25%. At the state level, Massachusetts ranked first for healthy seniors, while Louisiana ranked last. Illinois ranked 36th, while Wisconsin scored higher at 13th.
Climacteric
climacteric, or the midlife transition when fertility declines, is biologically based but impacted by the environment. During midlife, men may experience a reduction in their ability to reproduce. Women, however, lose their ability to reproduce once they reach menopause.
Female Sexual and Reproductive Health: Perimenopause refers to a period of transition in which a woman’s ovaries stop releasing eggs and the level of estrogen and progesterone production decreases. Menopause is defined as 12 months without menstruation. The average age of menopause is approximately 51, however, many women begin experiencing symptoms in their 40s. These symptoms occur during perimenopause, which can occur 2 to 8 years before menopause (Huang, 2007). A woman may first begin to notice that her periods are more or less frequent than before. After a year without menstruation, a woman is considered menopausal and no longer capable of reproduction.
Symptoms: The symptoms that occur during perimenopause and menopause are typically caused by the decreased production of estrogen and progesterone (North American Menopause Society, 2016). The shifting hormones can contribute to the inability to fall asleep. Additionally, the declining levels of estrogen may make a woman more susceptible to environmental factors and stressors which disrupt sleep. A hot flash is a surge of adrenaline that can awaken the brain from sleep. It often produces sweat and a change of temperature that can be disruptive to sleep and comfort levels. Unfortunately, it may take time for the adrenaline to recede and allow sleep to occur again (National Sleep Foundation, 2016).
to change their lifestyle to counter any weight gain. Depression and mood swings are more common during menopause in women who have prior histories of these conditions rather than those who have not.
Hormone Replacement Therapy: Concerns about the effects of hormone replacement has changed the frequency with which estrogen replacement and hormone replacement therapies have been prescribed for menopausal women. Estrogen replacement therapy was once commonly used to treat menopausal symptoms. However, more recently, hormone replacement therapy has been associated with breast cancer, stroke, and the development of blood clots (NIH,
Menopause and Ethnicity: In a review of studies that mentioned menopause, symptoms varied greatly across countries, geographic regions, and even across ethnic groups within the same region (Palacios, Henderson, & Siseles, 2010). For example, the Study of Women’s Health across the Nation (SWAN) examined 14,906 white, African American, Hispanic, Japanese American, and Chinese American women’s menopausal experiences (Avis et al., 2001). After controlling for age, educational level, general health status, and economic stressors, white women were more likely to disclose symptoms of depression, irritability, forgetfulness, and headaches compared to women in the other racial/ethnic groups. African American women experienced more night sweats, but this varied across research sites. Finally, Chinese American and Japanese American reported fewer menopausal symptoms when compared to the women in the other groups. Overall, the Chinese and Japanese groups reported the fewest symptoms, while white women reported more mental health symptoms and African American women reported more physical symptoms.
Cultural Differences: Cultural influences seem to also play a role in the way menopause is experienced. Further, the prevalence of language specific to menopause is an important indicator of the occurrence of menopausal symptoms in a culture. Hmong tribal women living in Australia and Mayan women report that there is no word for “hot flashes” and both groups did not experience these symptoms (Yick-Flanagan, 2013). When asked about physical changes during menopause, the Hmong women reported lighter or no periods. They also reported no emotional symptoms and found the concept of emotional difficulties caused by menopause amusing (Thurston & Vissandjee, 2005). Similarly, a study with First Nation women in Canada found there was no single word for “menopause” in the Oji-Cree or Ojibway languages, with women referring to menopause only as “that time when periods stop” (Madden, St Pierre-Hansen & Kelly, 2010).
Male Sexual and Reproductive Health: Although males can continue to father children throughout middle adulthood, erectile dysfunction (ED) becomes more common. Erectile dysfunction refers to the inability to achieve an erection or an inconsistent ability to achieve an erection (Swierzewski, 2015). Intermittent ED affects as many as 50% of men between the ages of 40 and 70. About 30 million men in the United States experience chronic ED and the percentages increase with age. Approximately 4% of men in their 40s, 17% of men in their 60s, and 47% of men older than 75 experience chronic ED.
If testosterone levels decline significantly, it is referred to as andropause or late-onset hypogonadism. Identifying whether testosterone levels are low is difficult because individual blood levels vary greatly. Low testosterone is not a concern unless it accompanied by negative symptoms such as low sex drive, ED, fatigue, loss of muscle, loss of body hair, or breast enlargement. Low testosterone is also associated with medical conditions, such as diabetes, obesity, high blood pressure, and testicular cancer. The effectiveness of supplemental testosterone is mixed, and long term testosterone replacement therapy for men can increase the risk of prostate cancer, blood clots, heart attack, and stroke (WebMD, 2016). Most men with low testosterone do not have related problems (Berkeley Wellness, 2011).
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/11%3A_Development_in_Middle_Adulthood/11.01%3A_Chapter_25-_Physical_Development_in_Middle_Adulthood.txt |
Chapter 26 Learning Objectives
• Describe crystallized versus fluid intelligence
• Describe research from the Seattle Longitudinal Study
• Explain the importance of flow to creativity and life satisfaction
• Describe how middle adults are turning to college for advanced training
• Describe the difference between an expert and a novice
• Describe the changes in the U.S. workforce, especially among middle adults
• Explain the importance of leisure to mental health and a successful retirement
Crystalized versus Fluid Intelligence
, which refers to the capacity to learn new ways of solving problems and performing activities quickly and abstractly and crystallized intelligence, which refers to the accumulated knowledge of the world we have acquired throughout our lives (Salthouse, 2004). This intelligence is distinct, and crystallized intelligence increases with age, while fluid intelligence tends to decrease with age (Horn, Donaldson, & Engstrom, 1981; Salthouse, 2004).
of the world around them, that gives older adults the advantage of “wisdom” over the advantages of fluid intelligence which favors the young (Baltes, Staudinger, & Lindenberger, 1999; Scheibe, Kunzmann, & Baltes, 2009). The differential changes in crystallized versus fluid intelligence help explain why older adults do not necessarily show poorer performance on tasks that also require experience (i.e., crystallized intelligence), although they show poorer memory overall. A young chess player may think more quickly, for instance, but a more experienced chess player has more knowledge to draw on. Seattle Longitudinal Study: The Seattle Longitudinal Study has tracked the cognitive abilities of adults since 1956. Every seven years the current participants are evaluated, and new individuals are also added. Approximately 6000 people have participated thus far, and 26 people from the original group are still in the study today. Current results demonstrate that middle-aged adults perform better on four out of six cognitive tasks than those same individuals did when they were young adults. Verbal memory, spatial skills, inductive reasoning (generalizing from particular examples), and vocabulary increase with age until one’s 70s (Schaie, 2005; Willis & Shaie, 1999). However, numerical computation and perceptual speed decline in middle and late adulthood (see Figure 8.18). Cognitive skills in the aging brain have been studied extensively in pilots, and similar to the Seattle Longitudinal Study results, older pilots show declines in processing speed and memory capacity, but their overall performance seems to remain intact. According to Phillips (2011), researchers tested pilots age 40 to 69 as they performed on flight simulators. Older pilots took longer to learn to use the simulators but performed better than younger pilots at avoiding collisions.
Flow is the mental state of being completely present and fully absorbed in a task (Csikszentmihalyi, 1990). When in a state of flow, the individual is able to block outside distractions and the mind is fully open to producing. Additionally, the person is achieving great joy or intellectual satisfaction from the activity and accomplishing a goal. Further, when in a state of flow, the individual is not concerned with extrinsic rewards. Csikszentmihalyi (1996) used his theory of flow to research how some people exhibit high levels of creativity as he believed that a state of flow is an important factor in creativity (Kaufman & Gregoire, 2016). Other characteristics of creative people identified by Csikszentmihalyi (1996) include curiosity and drive, value for intellectual endeavors, and an ability to lose our sense of self and feel a part of something greater. In addition, he believed that the tortured creative person was a myth and that creative people were very happy with their lives. According to Nakamura and Csikszentmihalyi (2002), people describe flow as the height of enjoyment. The more they experience it, the more they judge their lives to be gratifying. The qualities that allow for flow are well-developed in middle adulthood.
Tacit knowledge is the knowledge that is pragmatic or practical and learned through experience rather than explicitly taught, and it also increases with age (Hedlund, Antonakis, & Sternberg, 2002). Tacit knowledge might be thought of as “know-how” or “professional instinct.” It is referred to as tacit because it cannot be codified or written down. It does not involve academic knowledge, rather it involves being able to use skills and to problem-solve in practical ways. Tacit knowledge can be understood in the workplace and used by blue-collar workers, such as carpenters, chefs, and hairdressers.
Middle Adults Returning to Education
been neglected, older students tend to approach the learning process differently than younger college students (Knowles, Holton, & Swanson, 1998).
Plus 50 Initiative that assists community college in creating or expanding programs that focus on workforce training and new careers for the plus-50 population. Since 2008 the program has provided grants for programs to 138 community colleges affecting over 37, 000 students. The participating colleges offer workforce training programs that prepare 50 plus adults for careers in such fields as early childhood educators, certified nursing assistants, substance abuse counselors, adult basic education instructors, and human resources specialists. These training programs are especially beneficial as 80% of people over the age of 50 say they will retire later in life than their parents or continue to work in retirement, including in a new field.
Gaining Expertise: The Novice and the Expert
Expertise refers to specialized skills and knowledge that pertain to a particular topic or activity. In contrast, a novice is someone who has limited experiences with a particular task. Everyone develops some level of “selective” expertise in things that are personally meaningful to them, such as making bread, quilting, computer programming, or diagnosing illness. Expert thought is often characterized as intuitive, automatic, strategic, and flexible.
• Intuitive: Novices follow particular steps and rules when problem-solving, whereas experts can call upon a vast amount of knowledge and past experience. As a result, their actions appear more intuitive than formulaic. Novice cooks may slavishly follow the recipe step by step, while chefs may glance at recipes for ideas and then follow their own procedure.
• Automatic: Complex thoughts and actions become more routine for experts. Their reactions appear instinctive over time, and this is because expertise allows us to process information faster and more effectively (Crawford & Channon, 2002).
• Strategic: Experts have more effective strategies than non-experts. For instance, while both skilled and novice doctors generate several hypotheses within minutes of an encounter with a patient, the more skilled clinicians’ conclusions are likely to be more accurate. In other words, they generate better hypotheses than the novice. This is because they are able to discount misleading symptoms and other distractors and hone in on the most likely problem the patient is experiencing (Norman, 2005). Consider how your note-taking skills may have changed after being in school over a number of years. Chances are you do not write down everything the instructor says, but the more central ideas. You may have even come up with your own short forms for commonly mentioned words in a course, allowing you to take down notes faster and more efficiently than someone who may be a novice academic note taker.
• Flexible: Experts in all fields are more curious and creative; they enjoy a challenge and experiment with new ideas or procedures. The only way for experts to grow in their knowledge is to take on more challenging, rather than routine tasks.
Work at Midlife
Who is the U.S. workforce? The civilian, non-institutionalized workforce; the population of those aged 16 and older, who are employed has steadily declined since it reached its peak in the late 1990s when 67% of the civilian workforce population was employed. In 2012 the rate had dropped to 64% and by 2019 it declined to 62.9% (Bureau of Labor Statistics, 2019). The U.S. population is expected to grow more slowly based on census projections for the next few years. Those new entrants to the labor force, adults age 16 to 24, are the only population of adults that will shrink in size over the next few years by nearly half a percent, while those age 55 and up will grow by 2.3% over current rates, and those age 65 to 74 will grow by nearly 4% (Monthly Labor Review (MLR), 2013). In 1992, 26% of the population was 55+, by 2022 it is projected to be 38%. Table 8.8 shows the rates of employment by age. In 2002, baby boomers were between the ages of 38 to 56, the prime employment group. In 2012, the youngest baby boomers were 48 and the oldest had just retired (age 66). These changes might explain some of the steady declines in work participation as this large population cohort ages out of the workforce.
Hispanic males have the highest rate of participation in the labor force. In 2012, 76% of Hispanic males, compared with 71% of White, 72% of Asians, and 64% of Black men ages 16 or older were employed. Among women, Black women were more likely to be participating in the workforce (58%) compared with almost 57% of Hispanic and Asian, and 55% of White females. The rates for all racial and ethnic groups are expected to decline by 2022 (MLR, 2013).
Climate in the Workplace for Middle-aged Adults: A number of studies have found that job satisfaction tends to peak in middle adulthood (Besen, Matz-Costa, Brown, Smyer, & Pitt- Catsouphers, 2013; Easterlin, 2006). This satisfaction stems from not only higher wages, but often greater involvement in decisions that affect the workplace as they move from worker to supervisor or manager. Job satisfaction is also influenced by being able to do the job well, and after years of experience at a job, many people are more effective and productive. Another reason for this peak in job satisfaction is that at midlife many adults lower their expectations and goals (Tangri, Thomas, & Mednick, 2003). Middle-aged employees may realize they have reached the highest they are likely to in their careers. This satisfaction at work translates into lower absenteeism, greater productivity, and less job-hopping in comparison to younger adults (Easterlin, 2006).
burnout, defined as unsuccessfully managed workplace stress (World Health Organization, 2019). Burnout consists of:
• Feelings of energy depletion or exhaustion
• Increased mental distance from one’s job, or feelings of job negativism or cynicism
• Reduced professional efficacy
Challenges in the Workplace for Middle-aged Adults: In recent years middle-aged adults have been challenged by economic downturns, starting in 2001, and again in 2008. Fifty-five percent of adults reported some problems in the workplace, such as fewer hours, pay-cuts, having to switch to part-time, etc., during the most recent economic recession (see Figure 8.21, Pew Research Center, 2010a). While young adults took the biggest hit in terms of levels of unemployment, middle-aged adults also saw their overall financial resources suffer as their retirement nest eggs disappeared and house values shrank, while foreclosures increased (Pew Research Center, 2010b). Not surprisingly this age group reported that the recession hit them worse than did other age groups, especially those aged 50-64. Middle-aged adults who find themselves unemployed are likely to remain unemployed longer than those in early adulthood (U.S. Government Accountability Office, 2012). In the eyes of employers, it may be more cost-effective to hire a young adult, despite their limited experience, as they would be starting out at lower levels of the pay scale. In addition, hiring someone who is 25 and has many years of work ahead of them versus someone who is 55 and will likely retire in 10 years may also be part of the decision to hire a younger worker (Lachman, 2004). American workers are also competing with global markets and changes in technology. Those who are able to keep up with all these changes or are willing to uproot and move around the country or even the world have a better chance of finding work. The decision to move may be easier for people who are younger and have fewer obligations to others.
Leisure
time off from work and duties, referred to as leisure? Around the world, the most common leisure activity in both early and middle adulthood is watching television (Marketing Charts Staff, 2014). On average, middle-aged adults spend 2-3 hours per day watching TV (Gripsrud, 2007) and watching TV accounts for more than half of all the leisure time (see Figure 8.22).
In the United States, men spend about 5 hours more per week in leisure activities, especially on weekends, than do women (Drake, 2013; U.S. Bureau of Labor Statistics, 2016). The leisure gap between mothers and fathers is slightly smaller, about 3 hours a week, than among those without children under age 18 (Drake, 2013). Those age 35-44 spend less time on leisure activities than any other age group, 15 or older (U.S. Bureau of Labor Statistics, 2016). This is not surprising as this age group is more likely to be parents and still working up the ladder of their career, so they may feel they have less time for leisure.
But do U.S. workers take their time off? According to Project Time-Off (2016), 55% of U.S. workers in 2015 did not take all of their paid vacation and holiday leave. A large percentage of this leave is lost. It cannot be rolled over into the next year or paid out. A total of 658 million vacation days or an average of 2 vacation days per worker was lost in 2015. The reasons most often given for not taking time off was worry that there would be a mountain of work to return to (40%), a concern that no one else could do the job (35%), not being able to afford a vacation (33%), feeling it was harder to take time away when you have or are moving up in the company (33%), and not wanting to seem replaceable (22%). Since 2000, more American workers are willing to work for free rather than take the time that is allowed to them. A lack of support from their boss and even their colleagues to take a vacation is often a driving force in deciding to forgo time off. In fact, 80% of the respondents to the survey above said they would take time away if they felt they had support from their boss. Two-thirds reported that they hear nothing, mixed messages, or discouraging remarks about taking their time off. Almost a third (31%) feel they should contact their workplace, even while on vacation.
The benefits of taking time away from work: Several studies have noted the benefits of taking time away from work. It reduces job stress burnout (Nimrod, Kleiber, & Berdychevesky, 2012), improves both mental health (Qian, Yarnal, & Almeida, 2013) and physical health (Stern & Konno, 2009), especially if that leisure time also includes moderate physical activity (Lee et al., 2015). Leisure activities can also improve productivity and job satisfaction (Kühnel & Sonnentag, 2011) and help adults deal with balancing family and work obligations (Lee, et al., 2015).
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/11%3A_Development_in_Middle_Adulthood/11.02%3A_Chapter_26-_Cognitive_Development_in_Middle_Adulthood.txt |
Chapter 27 Learning Objectives
• Explain the controversy surrounding the concept of a midlife crisis
• Explain the sources of stress confronting adults in midlife and the strategies to cope
• Summarize Erikson’s seventh psychosocial task of generativity vs. stagnation
• Describe the relationships middle-aged adults have with their children, parents, and other family members
• Describe singlehood, marriage, divorce, and remarriage at midlife
• Describe the contemporary roles of grandparents
• Describe friendships at midlife
• Explain how women are uniquely affected at midlife
• Describe friendships at midlife
• Explain how women are uniquely affected at midlife
• Explain the role of religion at midlife
Midlife Crisis?
The Seasons of a Man’s Life in which he presented a theory of development in adulthood. Levinson’s work was based on in-depth interviews with 40 men between the ages of 35-45. Levinson (1978) indicated that adults go through stages and have an image of the future that motivates them. This image is called “the dream” and for the men interviewed, it was a dream of how their career paths would progress and where they would be at midlife. According to Levinson the midlife transition (40-45) was a time of reevaluating previous commitments; making dramatic changes if necessary; giving expression to previously ignored talents or aspirations, and feeling more of a sense of urgency about life and its meaning. By the time the men entered middle adulthood (45-50), they believed they committed to the new choices made and placed one’s energies into these commitments.
Stress
stress is defined as a pattern of physical and psychological responses in an organism after it perceives a threatening event that disturbs its homeostasis and taxes its abilities to cope with the event (Hooker & Pressman, 2016). Stress was originally derived from the field of mechanics where it is used to describe materials under pressure. The word was first used in a psychological manner by researcher Hans Selye, who was examining the effect of an ovarian hormone that he thought caused sickness in a sample of rats. Surprisingly, he noticed that almost any injected hormone produced this same sickness. He smartly realized that it was not the hormone under investigation that was causing these problems, but instead, the aversive experience of being handled and injected by researchers led to high physiological arousal, and eventually to health problems like ulcers. Selye (1946) coined the term stressor to label a stimulus that had this effect on the body (that is, causing stress). He developed a model of the stress response called the General Adaptation Syndrome, which is a three-phase model of stress, which includes a mobilization of physiological resources phase, a coping phase, and an exhaustion phase (i.e., when an organism fails to cope with the stress adequately and depletes its resources). Figure 8.25 illustrates the General Adaptation Syndrome.
Dispositions and Stress: Negative dispositions and personality traits have been strongly tied to an array of health risks. One of the earliest negative trait-to-health connections was discovered in the 1950s by two cardiologists. They made the interesting discovery that there were common behavioral and psychological patterns among their heart patients that were not present in other patient samples. This pattern included being competitive, impatient, hostile, and time urgent. They labeled it Type A Behavior. Importantly, it was found to be associated with double the risk of heart disease as compared with Type B Behavior (absence of Type A behaviors) (Friedman & Rosenman, 1959). Since the 1950s, researchers have discovered that it is the hostility and competitiveness components of Type A that are especially harmful to heart health (Iribarren et al., 2000; Matthews, Glass, Rosenman, & Bortner, 1977; Miller, Smith, Turner, Guijarro, & Hallet, 1996). Hostile individuals are quick to get upset, and this angry arousal can damage the arteries of the heart. In addition, given their negative personality style, hostile people often lack a heath-protective supportive social network.
Social Relationships and Stress: Research has shown that the impact of social isolation on our risk for disease and death is similar in magnitude to the risk associated with smoking regularly (Holt-Lunstad, Smith, & Layton, 2010; House, Landis, & Umberson, 1988). In fact, the importance of social relationships for our health is so significant that some scientists believe our body has developed a physiological system that encourages us to seek out our relationships, especially in times of stress (Taylor et al., 2000). Social integration is the concept used to describe the number of social roles that you have (Cohen & Willis, 1985). For example, you might be a daughter, a basketball team member, a Humane Society volunteer, a coworker, and a student. Maintaining these different roles can improve your health via encouragement from those around you to maintain a healthy lifestyle. Those in your social network might also provide you with social support (e.g., when you are under stress). This support might include emotional help (e.g., a hug when you need it), tangible help (e.g., lending you money), or advice. By helping to improve health behaviors and reduce stress, social relationships can have a powerful, protective impact on health, and in some cases, might even help people with serious illnesses stay alive longer (Spiegel, Kraemer, Bloom, & Gottheil, 1989).
Caregiving and Stress: A disabled child, spouse, parent, or other family member is part of the lives of some midlife adults. According to the National Alliance for Caregiving (2015), 40 million Americans provide unpaid caregiving. The typical caregiver is a 49-year-old female currently caring for a 69-year-old female who needs care because of a long-term physical condition. Looking more closely at the age of the recipient of caregiving, the typical caregiver for those 18-49 years of age is a female (61%) caring mostly for her own child (32%) followed by a spouse or partner (17%). When looking at older recipients (50+) who receive care, the typical caregiver is female (60%) caring for a parent (47%) or spouse (10%).
difference in how one is affected by the stress of caring for a child with special needs. Using data from the Study of Midlife in the United States, Ha, Hong, Seltzer, and Greenberg (2008) found that older parents were significantly less likely to experience the negative effects of having a disabled child than younger parents. They concluded that an age-related weakening of the stress occurred over time. This follows with the greater emotional stability noted at midlife.
Spousal Care: Certainly, caring for a disabled spouse would be a difficult experience that could negatively affect one’s health. However, research indicates that there can be a positive health effect on caring for a disabled spouse. Beach, Schulz, Yee, and Jackson (2000) evaluated health-related outcomes in four groups: Spouses with no caregiving needed (Group 1), living with a disabled spouse but not providing care (Group 2), living with a disabled spouse and providing care (Group 3), and helping a disabled spouse while reporting caregiver strain, including elevated levels of emotional and physical stress (Group 4). Not surprisingly, the participants in Group 4 were the least healthy and identified poorer perceived health, an increase in health-risk behaviors, and an increase in anxiety and depression symptoms. However, those in Group 3 who provided care for a spouse, but did not identify caregiver strain, actually identified decreased levels of anxiety and depression compared to Group 2 and were actually similar to those in Group 1. It appears that greater caregiving involvement was related to better mental health as long as the caregiving spouse did not feel the strain. The beneficial effects of helping identified by the participants were consistent with previous research (Krause, Herzog, & Baker, 1992; Schulz et al., 1997).
concerns with the opinions of others (Arai, Sugiura, Miura, Washio, & Kudo, 2000). Also contributing to women’s poorer caregiving outcomes is that disabled males are more aggressive than females, especially males with dementia who display more physical and sexual aggression toward their caregivers (Eastley & Wilcock, 1997; Zuidema, de Jonghe, Verhey, & Koopmans, 2009). Female caregivers are certainly at risk for negative consequences of caregiving, and greater support needs to be available to them.
Stress Management: On a scale from 1 to 10, those Americans aged 39-52 rated their stress at 5.3, and those aged 53-71 rated their stress at 3.9 (American Psychological Association, 2017). The most common sources of stress included the future of our nation, money, work, current political climate, and violence and crime. Given that these sources of our stress are often difficult to change, a number of interventions have been designed to help reduce the aversive responses to duress, especially related to health. For example, relaxation activities and forms of meditation are techniques that allow individuals to reduce their stress via breathing exercises, muscle relaxation, and mental imagery. Physiological arousal from stress can also be reduced via biofeedback, a technique where the individual is shown bodily information that is not normally available to them (e.g., heart rate), and then taught strategies to alter this signal. This type of intervention has even shown promise in reducing heart and hypertension risk, as well as other serious conditions (Moravec, 2008; Patel, Marmot, & Terry, 1981). Reducing stress does not have to be complicated. For example, exercise is a great stress reduction activity (Salmon, 2001) that has a myriad of health benefits.
Coping Strategies: Coping is often classified into two categories: Problem-focused coping or emotion-focused coping (Carver, Scheier, & Weintraub, 1989). Problem-focused coping is thought of as actively addressing the event that is causing stress in an effort to solve the issue at hand. For example, say you have an important exam coming up next week. A problem-focused strategy might be to spend additional time over the weekend studying to make sure you understand all of the material. Emotion-focused coping, on the other hand, regulates the emotions that come with stress. In the above examination example, this might mean watching a funny movie to take your mind off the anxiety you are feeling. In the short term, emotion-focused coping might reduce feelings of stress, but problem-focused coping seems to have the greatest impact on mental wellness (Billings & Moos, 1981; Herman-Stabl, Stemmler, & Petersen, 1995). That being said, when events are uncontrollable (e.g., the death of a loved one), emotion-focused coping directed at managing your feelings, at first, might be the better strategy. Therefore, it is always important to consider the match of the stressor to the coping strategy when evaluating its plausible benefits.
Erikson: Generativity vs Stagnation
generativity encompasses procreativity, productivity, and creativity. This stage includes the generation of new beings, new products, and new ideas, as well as self-generation concerned with further identity development. Erikson believed that the stage of generativity, during which one established a family and career, was the longest of all the stages. Individuals at midlife are primarily concerned with leaving a positive legacy of themselves, and parenthood is the primary generative type. Erikson understood that work and family relationships may be in conflict due to the obligations and responsibilities of each, but he believed it was overall a positive developmental time. In addition to being parents and working, Erikson also described individuals being involved in the community during this stage. A sense of stagnation occurs when one is not active in generative matters, however, stagnation can motive a person to redirect energies into more meaningful activities.
Middle Adult Lifestyles
Singlehood: According to a Pew Research study, 16 per 1,000 adults age 45 to 54 and 7 per 1000 age 55 and over have never married in the U. S. (Wang & Parker, 2014). However, some of them may be living with a partner. In addition, some singles at midlife may be single through divorce or widowhood. DePaulo (2014) has challenged the idea that singles, especially the always single, fair worse emotionally and in health when compared to those married. DePaulo suggests there is a bias in how studies examine the benefits of marriage. Most studies focus on comparisons between married versus not married, which do not include a separate comparison between those always single, and those who are single because of divorce or widowhood. Her research has found that those who are married may be more satisfied with life than the divorced or widowed, but there is little difference between married and always single, especially when comparing those who are recently married with those who have been married for four or more years. It appears that once the initial blush of the honeymoon wears off, those who are wedded are no happier or healthier than those who remained single. This might also suggest that there may be problems with how the “married” category is also seen as one homogeneous group.
Online Dating: Montenegro (2003) surveyed over 3,000 singles aged 40–69, and almost half of the participants reported their most important reason for dating was to have someone to talk to or do things with. Additionally, sexual fulfillment was also identified as an important goal for many. Alterovitz & Mendelsohn (2013) reviewed online personal ads for men and women over age 40 and found that romantic activities and sexual interests were mentioned at similar rates among the middle-age and young-old age groups, but less for the old-old age group.
Marriage: As you read in Chapter 7, there has been a number of changes in the marriage rate as more people are cohabitating, more are deciding to stay single, and more are getting married at a later age. As you can see in Figure 8.34, 48% of adults age 45-54 are married; either in their first marriage (22%) or have remarried (26%). This makes marriage the most common relationship status for middle-aged adults in the United States. Marital satisfaction tends to increase for many couples in midlife as children are leaving home (Landsford, Antonucci, Akiyama, & Takahashi, 2005). Not all researchers agree. They suggest that those who are unhappy with their marriage are likely to have gotten divorced by now, making the quality of marriages later in life only look more satisfactory (Umberson, Williams, Powers, Chen, & Campbell, 2005).
Divorce: Livingston (2014) found that 27% of adults age 45 to 54 were divorced (see Figure 8.32). Additionally, 57% of divorced adults were women. This reflects the fact that men are more likely to remarry than are women. Two-thirds of divorces are initiated by women (AARP, 2009). Most divorces take place within the first 5 to 10 years of marriage. This timeline reflects people’s initial attempts to salvage the relationship. After a few years of limited success, the couple may decide to end the marriage. It used to be that divorce after having been married for 20 or more years was rare, but in recent years the divorce rate among more long-term marriages has been increasing. Brown and Lin (2013) note that while the divorce rate in the U.S. has declined since the 1990s, the rate among those 50 and older has doubled. They suggest several reasons for the “graying of divorce”. There is less stigma attached to divorce today than in the past. Some older women are out-earning their spouses, and thus may be more financially capable of supporting themselves, especially as most of their children have grown. Finally, given increases in human longevity, the prospect of living several more years or decades with an incompatible spouse may prompt middle-aged and older adults to leave the marriage.
enhancers, those who had used the experience to better themselves and seek more productive intimate relationships, and the competent loners, those who used their divorce experience to grow emotionally, but who choose to stay single, the overwhelming majority were women.
Dating Post-Divorce: Most divorced adults have dated by one year after filing for divorce (Anderson et al., 2004; Anderson & Greene, 2011). One in four recent filers report having been in or were currently in a serious relationship, and over half were in a serious relationship by one year after filing for divorce. Not surprisingly, younger adults were more likely to be dating than were middle-aged or older adults, no doubt due to the larger pool of potential partners from which they could to draw. Of course, these relationships will not all end in marriage. Teachman (2008) found that more than two-thirds of women under the age of 45 had cohabited with a partnership between their first and second marriages.
gatekeep, that is, they regulate the flow of information about their new romantic partner to their children, in an attempt to balance their own needs for romance with consideration regarding the needs and reactions of their children. Anderson et al. (2004) found that almost half (47%) of dating parents gradually introduce their children to their dating partner, giving both their romantic partner and children time to adjust and get to know each other. Many parents who use this approach do so to avoid their children having to keep meeting someone new until it becomes clearer that this relationship might be more than casual. It might also help if the adult relationship is on the firmer ground so it can weather any initial push back from children when it is revealed. Forty percent are open and transparent about the new relationship at the outset with their children. Thirteen percent do not reveal the relationship until it is clear that cohabitation and or remarriage is likely. Anderson and colleagues suggest that practical matters influence which gatekeeping method parents may use. Parents may be able to successfully shield their children from a parade of suitors if there is reliable childcare available. The age and temperament of the child, along with concerns about the reaction of the ex-spouse, may also influence when parents reveal their romantic relationships to their children.
Rates of remarriage: The rate for remarriage, like the rate for marriage, has been declining overall. In 2013 the remarriage rate was approximately 28 per 1,000 adults 18 and older. This represents a 44% decline since 1990 and a 16% decline since 2008 (Payne, 2015). Brown and Lin (2013) found that the rate of remarriage dropped more for younger adults than middle-aged and older adults, and Livingston (2014) found that as we age we are more likely to have remarried (see Figure 8.35). This is not surprising as it takes some time to marry, divorce, and then find someone else to marry. However, Livingston found that unlike those younger than 55, those 55 and up are remarrying at a higher rate than in the past. In 2013, 67% of adults 55-64 and 50% of adults 65 and older had remarried, up from 55% and 34% in 1960, respectively.
Success of Remarriage: Reviews are mixed as to the happiness and success of remarriages. While some remarriages are more successful, especially if the divorce motivated the adult to engage in self-improvement and personal growth (Hetherington & Kelly, 2002), a number of divorced adults end up in very similar marriages the second or third time around (Hetherington & Kelly, 2002). Remarriages have challenges that are not found in first marriages that may create additional stress in the marital relationship. There can often be a general lack of clarity in family roles and expectations when trying to incorporate new kin into the family structure, even determining the appropriate terms for this kin, along with their roles can be a challenge.
Children’s Influence on Repartnering: Does having children affect whether a parent remarries? Goldscheider and Sassler (2006) found children residing with their mothers reduces the mothers’ likelihood of marriage, only with respect to marrying a man without children. Further, having children in the home appears to increase single men’s likelihood of marrying a woman with children (Stewart, Manning, & Smock, 2003). There is also some evidence that individuals who participated in a stepfamily while growing up may feel better prepared for stepfamily living as adults. Goldscheider and Kaufman (2006) found that having experienced family divorce as a child is associated with a greater willingness to marry a partner with children.
Grandparents
remote as they rarely saw their grandchildren. Usually, they lived far away from their grandchildren but may also have had a distant relationship. Contact was typically made on special occasions, such as holidays or birthdays. Fifty-five percent of grandparents were described as companionate as they did things with their grandchildren but had little authority or control over them. They preferred to spend time with them without interfering in parenting. They were more like friends to their grandchildren. Fifteen percent of grandparents were described as involved as they took a very active role in their grandchild’s life. The involved grandparent had frequent contact with and authority over the grandchild, and their grandchildren might even have lived with them. Grandmothers, more so than grandfathers, played this role. In contrast, more grandfathers than grandmothers saw their role as a family historian and family advisor (Neugarten and Weinstein, 1964).
Friendships
Internet Friendships: What influence does the Internet have on friendships? It is not surprising that people use the Internet with the goal of meeting and making new friends (Fehr, 2008; McKenna, 2008). Researchers have wondered if the issue of not being face-to-face reduces the authenticity of relationships, or if the Internet really allows people to develop deep, meaningful connections. Interestingly, research has demonstrated that virtual relationships are often as intimate as in-person relationships; in fact, Bargh and colleagues found that online relationships are sometimes more intimate (Bargh, McKenna, & Fitsimons, 2002). This can be especially true for those individuals who are more socially anxious and lonely as such individuals are more likely to turn to the Internet to find new and meaningful relationships (McKenna, Green, & Gleason, 2002). McKenna and colleagues suggest that for people who have a hard time meeting and maintaining relationships, due to shyness, anxiety, or lack of face-to-face social skills, the Internet provides a safe, nonthreatening place to develop and maintain relationships. Similarly, Benford (2008) found that for high-functioning autistic individuals, the Internet facilitated communication and relationship development with others, which would have been more difficult in face-to-face contexts, leading to the conclusion that Internet communication could be empowering for those who feel frustrated when communicating face to face.
Workplace Friendships: Friendships often take root in the workplace, due to the fact that people are spending as much, or more, time at work than they are with their family and friends (Kaufman & Hotchkiss, 2003). Often, it is through these relationships that people receive mentoring and obtain social support and resources, but they can also experience conflicts and the potential for misinterpretation when sexual attraction is an issue. Indeed, Elsesser and Peplau (2006) found that many workers reported that friendships grew out of collaborative work projects, and these friendships made their days more pleasant.
In addition to those benefits, Riordan and Griffeth (1995) found that people who worked in an environment where friendships could develop and be maintained were more likely to report higher levels of job satisfaction, job involvement, and organizational commitment, and they were less likely to leave that job. Similarly, a Gallup poll revealed that employees who had close friends at work were almost 50% more satisfied with their jobs than those who did not (Armour, 2007).
Religion and Spirituality
benefit, but so too do those identified as being spiritual. According to Greenfield, Vaillant, and Marks (2009) religiosity refers to engaging with a formal religious group’s doctrines, values, traditions, and co-members. In contrast, spirituality refers to an individual’s intrapsychic sense of connection with something transcendent (that which exists apart from and not limited by the material universe) and the subsequent feelings of awe, gratitude, compassion, and forgiveness. Research has demonstrated a strong relationship between spirituality and psychological well-being, irrespective of an individual’s religious participation (Vaillant, 2008). Additionally, Sawatzky, Ratner, & Chiu (2005) found that spirituality was related to a higher quality of life for both individuals and societies.
personal growth, purpose in life, positive relationships with others, self-acceptance, environmental mastery, and autonomy. In contrast, formal religious participation was only associated with higher levels of purpose in life and personal growth among just older adults and lower levels of autonomy. In summary, it appears that formal religious participation and spirituality relate differently to an individual’s overall psychological well-being.
Age: Older individuals identify religion/spirituality as being more important in their lives than those younger (Beit-Hallahmi & Argyle, 1998). This age difference has been explained by several factors including that religion and spirituality assist older individuals in coping with age-related losses, provide opportunities for socialization and social support in later life, and demonstrate a cohort effect in that older individuals were socialized more to be religious and spiritual than those younger (Greenfield et al., 2009).
Gender: In the United States, women report identifying as being more religious and spiritual than men do (de Vaus & McAllister, 1987). According to the Pew Research Center (2016), women in the United States are more likely to say religion is very important in their lives than men (60% vs. 47%). American women also are more likely than American men to say they pray daily (64% vs. 47%) and attend religious services at least once a week (40% vs. 32%). Theories to explain this gender difference include that women may benefit more from the social-relational aspects of religion/spirituality because social relationships more strongly influence women’s mental health. Additionally, women have been socialized to internalize the behaviors linked with religious values, such as cooperation and nurturance, more than males (Greenfield et al., 2009).
Worldwide: To measure the religious beliefs and practices of men and women around the world, the Pew Research Center (2016) conducted surveys of the general population in 84 countries between 2008 and 2015. Overall, an estimated 83% of women worldwide identified with religion compared with 80% of men. This equaled 97 million more women than men identifying with a religion. There were no countries in which men were more religious than women by 2 percentage points or more. Among Christians, women reported higher rates of weekly church attendance and higher rates of daily prayer. In contrast, Muslim women and Muslim men showed similar levels of religiousness, except the frequency of attendance at worship services. Because of religious norms, Muslim men worshiped at a mosque more often than Muslim women. Similarly, Jewish men attended a synagogue more often than Jewish women. In Orthodox Judaism, communal worship services cannot take place unless a minyan, or quorum of at least 10 Jewish men, is present, thus ensuring that men will have high rates of attendance. Only in Israel, where roughly 22% of all Jewish adults self-identify as Orthodox, did a higher percentage of men than women report engaging in daily prayer.
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/11%3A_Development_in_Middle_Adulthood/11.03%3A_Chapter_27-_Psychosocial_Development_in_Middle_Adulthood.txt |
Chapter 28 Learning Objectives
• Describe different theories of aging
• Describe the changes in physical appearance in late adulthood
• Describe the sensory changes in late adulthood
• Describe chronic health conditions during late adulthood
• Describe the importance of nutrition and exercise in late adulthood
• Describe the physical and functional changes in the brain during late adulthood
• Explain what happens in Parkison’s disease
• Explain how sleep patterns change in late adulthood
• Explain how sexuality changes in late adulthood
Theories of Aging
Why do we age? There are many theories that attempt to explain how we age, however, researchers still do not fully understand what factors contribute to the human lifespan (Jin, 2010). Research on aging is constantly evolving and includes a variety of studies involving genetics, biochemistry, animal models, and human longitudinal studies (NIA, 2011a). According to Jin (2010), modern biological theories of human aging involve two categories. The first is Programmed Theories that follow a biological timetable, possibly a continuation of childhood development. This timetable would depend on “changes in gene expression that affect the systems responsible for maintenance, repair, and defense responses,” (p. 72). The second category includes Damage or Error Theories which emphasize environmental factors that cause cumulative damage in organisms. Examples from each of these categories will be discussed.
Genetics: One’s genetic make-up certainly plays a role in longevity, but scientists are still attempting to identify which genes are responsible. Based on animal models, some genes promote longer life, while other genes limit longevity. Specifically, longevity may be due to genes that better equip someone to survive a disease. For others, some genes may accelerate the rate of aging, while others decrease the rate. To help determine which genes promote longevity and how they operate, researchers scan the entire genome and compare genetic variants in those who live longer with those who have an average or shorter lifespan. For example, a National Institutes of Health study identified genes possibly associated with blood fat levels and cholesterol, both risk factors for coronary disease and early death (NIA, 2011a).
Evolutionary Theory: Evolutionary psychology emphasizes the importance of natural selection; that is, those genes that allow one to survive and reproduce will be more likely to be transmitted to offspring. Genes associated with aging, such as Alzheimer’s Disease, do not appear until after the individual has passed their main reproductive years. Consequently, natural selection has not eliminated these damaging disorders from the gene pool. If these detrimental disorders occurred earlier in the development cycle, they may have been eliminated already (Gems, 2014).
Cellular Clock Theory: This theory suggests that biological aging is due to the fact that normal cells cannot divide indefinitely. This is known as the Hayflick limit and is evidenced in cells studied in test tubes, which divide about 40-60 times before they stop (Bartlett, 2014). But what is the mechanism behind this cellular senescence? At the end of each chromosomal strand is a sequence of DNA that does not code for any particular protein, but protects the rest of the chromosome, which is called a telomere. With each replication, the telomere gets shorter. Once it becomes too short the cell does one of three things. It can stop replicating by turning itself off, called cellular senescence. It can stop replicating by dying, called apoptosis. Or, as in the development of cancer, it can continue to divide and become abnormal. Senescent cells can also create problems. While they may be turned off, they are not dead, thus they still interact with other cells in the body and can lead to an increased risk of disease. When we are young, senescent cells may reduce our risk of serious diseases such as cancer, but as we age they increase our risk of such problems (NIA, 2011a). Understanding why cellular senescence changes from being beneficial to being detrimental are still under investigation. The answer may lead to some important clues about the aging process.
DNA Damage: Over time DNA, which contains the genetic code for all organisms, accumulates damage. This is usually not a concern as our cells are capable of repairing damage throughout our life. Further, some damage is harmless. However, some damage cannot be repaired and remains in our DNA. Scientists believe that this damage, and the body’s inability to fix itself, is an important part of aging (NIA, 2011a). As DNA damage accumulates with increasing age, it can cause cells to deteriorate and malfunction (Jin, 2010). Factors that can damage DNA include ultraviolet radiation, cigarette smoking, and exposure to hydrocarbons, such as auto exhaust and coal (Dollemore, 2006).
Mitochondrial Damage: Damage to mitochondrial DNA can lead to a decaying of the mitochondria, which is a cell organelle that uses oxygen to produce energy from food. The mitochondria convert oxygen to adenosine triphosphate (ATP) which provides the energy for the cell. When damaged, mitochondria become less efficient and generate less energy for the cell and can lead to cellular death (NIA, 2011a).
Free Radicals: When the mitochondria use oxygen to produce energy, they also produce potentially harmful byproducts called oxygen free radicals (NIA, 2011a). The free radicals are missing an electron and create instability in surrounding molecules by taking electrons from them.
Immune and Hormonal Stress Theories: Ever notice how quickly U.S. presidents seem to age? Before and after photos reveal how stress can play a role in the aging process.
To understand how this stress affects aging, researchers note that both problems with the innate and adaptive immune system play a key role. The innate immune system is made up of the skin, mucous membranes, cough reflex, stomach acid, and specialized cells that alert the body of an impending threat . With age these cells lose their ability to communicate as effectively, making it harder for the body to mobilize its defenses. The adaptive immune system includes the tonsils, spleen, bone marrow, thymus, circulatory system and the lymphatic system that work to produce and transport T cells . T-cells , or lymphocytes , fight bacteria, viruses, and other foreign threats to the body. T-cells are in a “naïve” state before they are programmed to fight an invader and become “memory cells”. These cells now remember how to fight a certain infection should the body ever come across this invader again. Memory cells can remain in your body for many decades, and why the measles vaccine you received as a child is still protecting you from this virus today. As older adults produce fewer new T-cells to be programmed, they are less able to fight off new threats and new vaccines work less effectively. The reason why the shingles vaccine works well with older adults is that they already have some existing memory cells against the varicella virus. The shingles vaccine is acting as a booster (NIA, 2011a).
Hormonal Stress Theory, also known as Neuroendocrine Theory of Aging, suggests that as we age the ability of the hypothalamus to regulate hormones in the body begins to decline to lead to metabolic problems (American Federation of Aging Research (AFAR) 2011). This decline is linked to an excess of the stress hormone cortisol. While many of the body’s hormones decrease with age, cortisol does not (NIH, 2014a). The more stress we experience, the more cortisol released, and the more hypothalamic damage that occurs. Changes in hormones have been linked to several metabolic and hormone-related problems that increase with age, such as diabetes (AFAR, 2011), thyroid problems (NIH, 2013), osteoporosis, and orthostatic hypotension (NIH, 2014a).
Physical Changes of Aging
• Heart muscles thicken with age
• Arteries become less flexible
• Lung capacity diminishes
• Kidneys become less efficient in removing waste from the blood
• Bladder loses its ability to store urine
• Brain cells also lose some functioning, but new neurons can also be produced.
Body Changes: Everyone’s body shape changes naturally as they age. According to the National Library of Medicine (2014) after age 30 people tend to lose lean tissue, and some of the cells of the muscles, liver, kidney, and other organs are lost. Tissue loss reduces the amount of water in your body and bones may lose some of their minerals and become less dense (a condition called osteopenia in the early stages and osteoporosis in the later stages). The amount of body fat goes up steadily after age 30, and older individuals may have almost one third more fat compared to when they were younger. Fat tissue builds up toward the center of the body, including around the internal organs.
Skin, Hair and Nails: With age skin becomes thinner, less elastic, lose fat, and no longer looks plump and smooth. Veins and bones can be seen easier, and scratches, cuts, and bumps can take longer to heal. Years exposed to the sun may lead to wrinkles, dryness, age spots, and cancer. Older people may bruise more easily, and it can take longer for these bruises to heal. Some medicines or illnesses may also cause bruising. Gravity can cause the skin to sag and wrinkle, and smoking can wrinkle the skin. Also, seen in older adults are age spots, previously called “liver spots”. They look like flat, brown spots and are often caused by years in the sun. Skin tags are small, usually flesh-colored growths of skin that have a raised surface. They become common as people age, especially for women, but both age spots and skin tags are harmless (NIA, 2015f).
Height and Weight: The tendency to become shorter as one age occurs among all races and both sexes. Height loss is related to aging changes in the bones, muscles, and joints. People typically lose almost one-half inch every 10 years after age 40, and height loss is even more rapid after age 70. A total of 1 to 3 inches in height is lost with aging. Changes in body weight vary for men and women. Men often gain weight until about age 55, and then begin to lose weight later in life, possibly related to a drop in the male sex hormone testosterone. Women usually gain weight until age 65, and then begin to lose weight. Weight loss later in life occurs partly because fat replaces lean muscle tissue, and fat weighs less than muscle. Diet and exercise are important factors in weight changes in late adulthood (National Library of Medicine, 2014).
Sarcopenia is the loss of muscle tissue as a natural part of aging. Sarcopenia is most noticeable in men, and physically inactive people can lose as much as 3% to 5% of their muscle mass each decade after age 30, but even when active muscle loss still occurs (Webmd, 2016). Symptoms include a loss of stamina and weakness, which can decrease physical activity and subsequently further shrink muscles. Sarcopenia typically happens faster around age 75, but it may also speed up as early as 65 or as late as 80. Factors involved in sarcopenia include a reduction in nerve cells responsible for sending signals to the muscles from the brain to begin moving, a decrease in the ability to turn protein into energy, and not receiving enough calories or protein to sustain adequate muscle mass. Any loss of muscle is important because it lessens strength and mobility, and sarcopenia is a factor in frailty and the likelihood of falls and fractures in older adults. Maintaining strong leg and heart muscles are important for independence. Weight-lifting, walking, swimming, or engaging in other cardiovascular exercises can help strengthen the muscles and prevent atrophy.
Sensory Changes in Late Adulthood
Vision: In late adulthood, all the senses show signs of decline, especially among the oldest-old. In the last chapter, you read about the visual changes that were beginning in middle adulthood, such as presbyopia, dry eyes, and problems seeing in dimmer light. By later adulthood, these changes are much more common. Three serious eye diseases are more common in older adults: Cataracts, macular degeneration, and glaucoma. Only the first can be effectively cured in most people.
Cataracts are a clouding of the lens of the eye. The lens of the eye is made up of mostly water and protein. The protein is precisely arranged to keep the lens clear, but with age, some of the protein starts to clump. As more of the protein clumps together the clarity of the lens is reduced. While some adults in middle adulthood may show signs of cloudiness in the lens, the area affected is usually small enough to not interfere with vision. More people have problems with cataracts after age 60 (NIH, 2014b) and by age 75, 70% of adults will have problems with cataracts (Boyd, 2014). Cataracts also cause a discoloration of the lens, tinting it more yellow and then brown, which can interfere with the ability to distinguish colors such as black, brown, dark blue, or dark purple.
darkest red color on the map, more than 990 out of 100,00 people have a shortened lifespan due to the disability caused by cataracts.
age-related macular degeneration, which is the loss of clarity in the center field of vision, due to the deterioration of the macula, the center of the retina. Macular degeneration does not usually cause total vision loss, but the loss of the central field of vision can greatly impair day-to-day functioning. There are two types of macular degeneration: dry and wet. The dry type is the most common form and occurs when tiny pieces of a fatty protein called drusen form beneath the retina. Eventually the macular becomes thinner and stops working properly (Boyd, 2016). About 10% of people with macular degeneration have the wet type, which causes more damage to their central field of vision than the dry form. This form is caused by abnormal development of blood vessels beneath the retina. These vessels may leak fluid or blood causing more rapid loss of vision than the dry form.
glaucoma, which is the loss of peripheral vision, frequently due to a buildup of fluid in the eye that damages the optic nerve. As you age the pressure in the eye may increase causing damage to the optic nerve. The exterior of the optic nerve receives input from retinal cells on the periphery, and as glaucoma progresses more and more of the peripheral visual field deteriorates toward the central field of vision. In the advanced stages of glaucoma, a person can lose their sight. Fortunately, glaucoma tends to progress slowly (NEI, 2016b). Glaucoma is the most common cause of blindness in the U.S. (NEI, 2016b). African Americans over age 40 and everyone else over age 60 has a higher risk for glaucoma.
Hearing: As you read in Chapter 8, our hearing declines both in terms of the frequencies of sound we can detect, and the intensity of sound needed to hear as we age. These changes continue in late adulthood. Almost 1 in 4 adults aged 65 to 74 and 1 in 2 aged 75 and older have disabling hearing loss (NIH, 2016). Table 9.4 lists some common signs of hearing loss.
Presbycusis is a common form of hearing loss in late adulthood that results in a gradual loss of hearing. It runs in families and affects hearing in both ears (NIA, 2015c). Older adults may also notice tinnitus, a ringing, hissing, or roaring sound in the ears. The exact cause of tinnitus is unknown, although it can be related to hypertension and allergies. It may come and go or persist and get worse over time (NIA, 2015c). The incidence of both presbycusis and tinnitus increase with age and males have higher rates of both around the world (McCormak, Edmondson-Jones, Somerset, & Hall, 2016).
Taste and Smell: Our sense of taste and smell are part of our chemical sensing system. Our sense of taste, or gustation, appears to age well. Normal taste occurs when molecules that are released by chewing food stimulate taste buds along with the tongue, the roof of the mouth, and in the lining of the throat. These cells send messages to the brain, where specific tastes are identified. After age 50 we start to lose some of these sensory cells. Most people do not notice any changes in taste until one’s 60s (NIH: Senior Health, 2016b). Given that the loss of taste buds is very gradual, even in late adulthood, many people are often surprised that their loss of taste is most likely the result of a loss of smell.
loss of smell due to aging is called presbyopia. Olfactory cells are located in a small area high in the nasal cavity. These cells are stimulated by two pathways; when we inhale through the nose, or via the connection between the nose and the throat when we chew and digest food. It is a problem with this second pathway that explains why some foods such as chocolate or coffee seem tasteless when we have a head cold. There are several types of loss of smell. Total loss of smell, or anosmia, is extremely rare.
Touch: Research has found that with age, people may experience reduced or changed sensations of vibration, cold, heat, pressure, or pain (Martin, 2014). Many of these changes are also aligned with a number of medical conditions that are more common among the elderly, such as diabetes. However, there are changes in the touch sensations among healthy older adults. The ability to detect changes in pressure have been shown to decline with age, with it being more pronounced by the 6th decade and diminishing further with advanced age (Bowden & McNelty, 2013). Yet, there is considerable variability, with almost 40% showing sensitivity that is comparable to younger adults (Thornbury & Mistretta, 1981). However, the ability to detect the roughness/smoothness or hardness/softness of an object shows no appreciable change with age (Bowden & McNulty, 2013). Those who show increasing insensitivity to pressure, temperature, or pain are at risk for injury (Martin, 2014).
Pain: According to Molton and Terrill (2014), approximately 60%-75% of people over the age of 65 reports at least some chronic pain, and this rate is even higher for those individuals living in nursing homes. Although the presence of pain increases with age, older adults are less sensitive to pain than younger adults (Harkins, Price, & Martinelli, 1986). Farrell (2012) looked at research studies that included neuroimaging techniques involving older people who were healthy and those who experienced a painful disorder. Results indicated that there were age-related decreases in brain volume in those structures involved in pain. Especially noteworthy were changed in the prefrontal cortex, brainstem, and hippocampus. Women are more likely to identify feeling pain than men (Tsang et al., 2008). Women have fewer opioid receptors in the brain, and women also receive less relief from opiate drugs (Garrett, 2015).
Nutrition
dairy products such as milk, cheeses, and yogurts. Unfortunately, changes in sensory functions, such as smell and taste, along with loss of teeth, can derail an older adult’s ability to eat right.
Chronic Conditions
Chronic illnesses are illnesses that are ongoing, generally incurable conditions that require continuous medical attention and affect daily life. As individuals live longer, diseases that affect older individuals will become more prevalent, and the burden of chronic illness grows with age. Less than 50% of adults 50-64 have a chronic condition, 90% aged 75 and up do (Cohen, 2011). Almost 80% have at least one chronic disease, and 77% have at least two (National Council on Aging, 2019). Older women are more likely to have a chronic condition than are older men (83% vs. 88%) (CDC, 2009). Table 9.6 lists the percentage of older adults who have certain chronic illnesses based on the National Health Survey conducted in 2014. Other studies place the figure of diabetes in older adults at 26% (CDC, 2014).
Cancer and Major Cardiovascular Disease: As discussed in chapter 8, cancer and cardiovascular disease are the overall leading causes of death, and they are especially high reasons for death in middle and late adults. Table 9.7 identifies the percentages of deaths due to cancer and cardiovascular disease for selected age groups in 2016; the most recent year for data (Heron, 2018).
Cancer: Advancing age is a significant risk factor for cancer, with persons over 65 accounting for 60% of newly diagnosed cancer and 70% of all cancer deaths (Berger et al., 2006). Additionally, more than 70% of the mortality associated including prostate, bladder, colon, uterus, pancreas, stomach, rectum and lung occurs in patients 65 and older. Other conditions that affect the elderly can occur with cancer, including anemia, coronary artery diseases, congestive heart failure, chronic obstructive pulmonary diseases, renal insufficiency, cerebrovascular diseases, neurovascular complications of diabetes mellitus, and arthritis that restricts mobility (Balducci & Extermann, 2000). Comorbidity will complicate treatment.
Heart Disease: There are changes to the heart that happen with age, and some may increase a person’s risk of heart disease. These include stiffening blood vessels and valves, which may result in leaks or problems pumping blood out of the heart (NIA, 2012). As previously stated, heart disease is the leading cause of death for those in late adulthood (CDC, 2016b). There are different types of heart disease, and as already discussed in chapter 8, the most common is atherosclerosis, the buildup of fatty deposits or plaques in the walls of arteries. As plaque builds up, blood is unable to flow normally and bring oxygen throughout the body, including to the heart. Depending on where the buildup is, atherosclerosis can cause a heart attack, leg pain, or a stroke. However, Atherosclerosis is not part of normal aging. Many of the problems older people have with their heart and blood vessels are caused by disease and not by aging. For example, an older heart can normally pump blood as strong as a younger heart, while less ability to pump blood is caused by disease. Therefore, leading a heart-healthy lifestyle is most important to keeping one’s heart strong in late adulthood.
Arthritis: Arthritis and other rheumatic conditions are the most common cause of disability among US adults and have been the most common cause of disability among US adults for the past 15 years (NIH: National Institute of Arthritis and Musculoskeletal and Skin Diseases, 2014). According to the NIH, approximately 62% of adults with arthritis are 65 years old and up. Almost 1 in 2 older adults with arthritis have some degree of mobility limitations, such as climbing stairs, walking, and grasping objects. The pain and other limitations of arthritis can also increase the risk of depression and other forms of mental distress. Osteoarthritis is the most common type of arthritis. “When the cartilage, the slick, cushioning surface on the ends of bones wears away, bone rubs against bone, causing pain, swelling, and stiffness. Over time, joints can lose strength and pain may become chronic” (Arthritis Foundation, 2017, para 3). Common risk factors for osteoarthritis include genetics, obesity, age, previous injury, and other medical conditions.
Osteoporosis and Kyphosis: Osteoporosis is a disease that thins and weakens bones to the point that they become fragile and break easily. After age 50, 1 in 2 women and 1 in 4 men will experience an osteoporosis-related fracture in their lifetime, often leading to hip, spine, and wrist fractures (Dailey & Cravedi, 2006). Broken hips are a very serious problem as we age. They greatly increase the risk of death, especially during the year after they break (NIH Senior Health, 2015). In the U.S., more than 53 million adults either already have osteoporosis or at high risk due to low bone mass (NIH Senior Health, 2015). As bones weaken in the spine, adults gradually lose height and their posture becomes hunched over, which is called Kyphosis. Over time a bent spine can make it hard to walk or even sit up. Adults can prevent the loss of bone mass by eating a healthy diet with enough calcium and vitamin D, regularly exercising, limiting alcohol, and not smoking (National Osteoporosis Foundation, 2016).
Chronic obstructive pulmonary disease (COPD) is a progressive lung disease in which the airways become damaged making it difficult to breathe. COPD includes problems such as emphysema and chronic bronchitis (NIH Senior Health, 2013). COPD kills more than 120,000 people every year, making it one of the leading causes of death. COPD was once considered a “man’s disease”. However, since 2000, 58% of those with COPD are women and they comprise 8% of all women (American Lung Association, 2019). Research has indicated that women may be more susceptible to the effects of cigarette smoke due to having smaller lungs and estrogen worsening the effects.
cirrhosis, which is a disease in which the liver becomes scarred and does not function properly. While some people with ATT deficiency are not affected and live a normal life, COPD is more likely to occur in such individuals if their lungs are exposed to environmental irritants.
Shingles: According to the National Institute on Aging (2015e), the shingle is a disease that affects your nerves. Shingles are caused by the same virus as chickenpox, the varicella-zoster virus (VZV). After you recover from chickenpox, the virus continues to live in some of your nerve cells. It is usually inactive, and most adults live with VZV in their bodies and never get shingles. However, the virus will become active in one in three adults. Instead of causing chickenpox again, it produces shingles. A risk factor for shingles includes advanced age as people have a harder time fighting off infections as they get older. About half of all shingles cases are in adults age 60 or older, and the chance of getting shingles becomes much greater by age 70. Other factors that weaken an individual’s ability to fight infections, such as cancer, HIV infections, or other medical conditions, can put one at a greater risk for developing shingles.
some people may be left with ongoing pain, called post-herpetic neuralgia (PHN) in the area where the rash had been (NIA, 2015e). The older one is when getting shingles, the greater the chance of developing PHN. Some people with PHN find it hard to go about their daily activities, like dressing, cooking and eating. They can also suffer from depression, anxiety, and sleeplessness. Medicines can help with pain and usually, PHN will disappear. Unfortunately, the blisters from shingles may become infected or leave a scar. Blisters near or in the eye can cause lasting eye damage or blindness. A brief paralysis of the face, hearing loss, and very rarely, swelling of the brain (encephalitis) can also occur. There is a shingles vaccine that is recommended for those aged 50 and older. Shingles are not contagious, but one can catch chickenpox from someone with shingles.
Beliefs about Health: Despite the fact that the majority of older adults have at least one chronic illness, most rate their overall health positively (Graham, 2019). Based on the results of the CDC’s 2017 National Health Interview Survey, 82% of those aged 65-74 and 73% of those 75 and older rated their health as excellent, very good or good. Because older adults focus more on emotional well-being, positive social relationships, remaining active, and overall life satisfaction, poor physical functioning is not considered as important. Older adults often look to those who are worse off than themselves, including those having died or are in a nursing home, and consequently feel more positive about themselves. This perspective is in contrast to those younger who believe that there should not be anything wrong with them, and consequently experience negative feelings when they have an illness. Older adults expect there will be some deterioration in their health and are able to adapt to it. Similarly, most older adults identify positive mental health in conjunction with their physical health.
Brain Functioning
Continued Neurogenesis: Researchers at the University of Chicago found that new neurons continued to form into old age. Tobin et al. (2019) examined the post-mortem brain tissue of individuals between the ages of 79 and 99 (average age 90.6) and found evidence of neurogenesis in the hippocampus. Approximately 2000 neural progenitor cells and 150, 000 developing neurons were found per brain, although the number of developing neurons was lower in people with cognitive impairments or Alzheimer’s disease. Tobin et al. hypothesized that the lower levels of neurogenesis in the hippocampus were associated with symptoms of cognitive decline and reduced synaptic plasticity.
Scaffolding Theory of Aging and Cognition which states that the brain adapts to neural atrophy (dying of brain cells) by building alternative connections, referred to as scaffolding. This scaffolding allows older brains to retain high levels of performance. Brain compensation is especially noted in the additional neural effort demonstrated by those individuals who are aging well. For example, older adults who performed just as well as younger adults on a memory task used both prefrontal areas, while only the right prefrontal cortex was used in younger participants (Cabeza, Anderson, Locantore, & McIntosh, 2002). Consequently, this decrease in brain lateralization appears to assist older adults with their cognitive skills.
Healthy Brain Functioning: Cheng (2016) found that physical activity and stimulating cognitive activity resulted in significant reductions in the risk of neurocognitive disorders in longitudinal studies. Physical activity, especially aerobic exercise, is associated with less age-related gray and white matter loss, as well and diminished neurotoxins in the brain. Overall, physical activity preserves the integrity of neurons and brain volume. Cognitive training improves the efficiency of the prefrontal cortex and executive functions, such as working memory, and strengthens the plasticity of neural circuits. Both activities support cognitive reserve, or “the structural and dynamic capacities of the brain that buffer against atrophies and lesions” (p. 85). Although it is optimal to begin physical and cognitive activities earlier in life, it is not too late to start these programs in late adulthood to improve one’s cognitive health.
Can we improve brain functioning? Many training programs have been created to improve brain functioning. ACTIVE (Advanced Cognitive Training for Independent and Vital Elderly), a study conducted between 1999 and 2001 in which 2,802 individuals age 65 to 94, suggests that the answer is “yes”. These racially diverse participants received 10 group training sessions and 4 follow up sessions to work on tasks of memory, reasoning, and speed of processing. These mental workouts improved cognitive functioning even 5 years later. Many of the participants believed that this improvement could be seen in everyday tasks as well (Tennstedt et al., 2006). However, programs for the elderly on memory, reading, and processing speed training demonstrate that there is an improvement in the specific tasks trained, but there is no generalization to other abilities (Jarrett, 2015). Further, these programs have not been shown to delay or slow the progression of Alzheimer’s disease. Although these programs are not harmful, “physical exercise, learning new skills, and socializing remain the most effective ways to train your brain” (p. 207). These activities appear to build a reserve to minimize the effects of primary aging of the brain.
Parkinson’s disease is characterized by motor tremors, loss of balance, poor coordination, rigidity, and difficulty moving (Garrett, 2015). Parkinson’s affects approximately 1% of those over the age of 60, and it appears more frequently in family members in a little less than 10% of cases. Twenty-eight chromosomal areas have been implicated in Parkinson’s disease, but environmental factors have also been identified and include brain injury. Being knocked unconscious once increases the risk by 32% and being knocked out several times increases the risk by 174% (Garrett, 2015). Other environmental influences include toxins, industrial chemicals, carbon monoxide, herbicides and pesticides (Olanow & Tatton, 1999). The symptoms are due to the deterioration of the substantia nigra, an area in the midbrain whose neurons send dopamine-releasing axons to the basal ganglia which affect motor activity. Treatment typically includes the medication levodopa (L-dopa), which crosses the blood-brain barrier and is converted into dopamine in the brain. Deep brain stimulation, which involves inserting an electrode into the brain that provides electrical stimulation, has resulted in improved motor functioning (Garrett, 2015).
Sleep
but they tend to go to sleep earlier and get up earlier than those younger. This pattern is called advanced sleep phase syndrome and is based on changes in circadian rhythms (National Sleep Foundation, 2009). There are sleep problems in older adults, and insomnia is the most common problem in those 60 and older (NIA, 2016). People with insomnia have trouble falling asleep and staying asleep. There are many reasons why older people may have insomnia, including certain medications, being in pain, having a medical or psychiatric condition, and even worrying before bedtime about not being able to sleep. Using over the counter sleep aids or medication may only work when used for a short time. Consequently, sleep problems should be discussed with a health care professional.
Sleep apnea refers to repeated short pauses in breathing, while an individual sleeps, which can lead to reduced oxygen in the blood. Snoring is a common symptom of sleep apnea and it often worsens with age. Untreated sleep apnea can lead to impaired daytime functioning, high blood pressure, headaches, stroke, and memory loss. Restless legs syndrome feels like there is tingling, crawling, or pins and needles in one or both legs, and this feeling is worse at night.
Periodic limb movement disorder causes people to jerk and kick their legs every 20 to 40 seconds during sleep. Rapid eye movement sleep behavior disorder occurs when one’s muscles can move during REM sleep and sleep is disrupted.
Sexuality
Causes of Sexual Problems: According to the National Institute on Aging (2013), chronic illnesses including arthritis (joint pain), diabetes (erectile dysfunction), heart disease (difficulty achieving orgasm for both sexes), stroke (paralysis), and dementia (inappropriate sexual behavior) can all adversely affect sexual functioning. Hormonal changes, physical disabilities, surgeries, and medicines can also affect a senior’s ability to participate in and enjoy sex. How one feels about sex can also affect performance. For example, a woman who is unhappy about her appearance as she ages may think her partner will no longer find her attractive. A focus on youthful physical beauty for women may get in the way of her enjoyment of sex. Likewise, most men have a problem with erectile dysfunction (ED) once in a while, and some may fear that ED will become a more common problem as they age. If there is a decline in sexual activity for a heterosexual couple, it is typically due to a decline in the male’s physical health (Erber & Szuchman, 2015).
oncluding Thoughts: Key players in improving the quality of life among older adults will be those adults themselves. By exercising, reducing stress, stopping smoking, limiting the use of alcohol, and consuming more fruits and vegetables, older adults can expect to live longer and more active lives (He et al., 2005). Stress reduction, both in late adulthood and earlier in life, is also crucial. The reduction of societal stressors can promote active life expectancy. In the last 40 years, smoking rates have decreased, but obesity has increased, and physical activity has only modestly increased.
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/12%3A_Development_in_Late_Adulthood/12.01%3A_Chapter_28-_Physical_Development_in_Late_Adulthood.txt |
Chapter 29 Learning Objectives
• Describe how memory changes for those in late adulthood
• Describe the theories for why memory changes occur
• Describe how cognitive losses in late adulthood are exaggerated
• Explain the pragmatics and mechanics of intelligence
• Define what is a neurocognitive disorder
• Explain Alzheimer’s disease and other neurocognitive disorders
• Describe work and retirement in late adulthood
• Describe how those in late adulthood spend their leisure time
Memory
Changes in Working Memory: As discussed in chapter 4, working memory is the more active, effortful part of our memory system. Working memory is composed of three major systems: The phonological loop that maintains information about auditory stimuli, the visuospatial sketchpad, that maintains information about visual stimuli, and the central executive, that oversees working memory, allocating resources where needed and monitoring whether cognitive strategies are being effective (Schwartz, 2011). Schwartz reports that it is the central executive that is most negatively impacted by age. In tasks that require allocation of attention between different stimuli, older adults fair worse than do younger adults. In a study by Göthe, Oberauer, and Kliegl (2007) older and younger adults were asked to learn two tasks simultaneously. Young adults eventually managed to learn and perform each task without any loss in speed and efficiency, although it did take considerable practice. None of the older adults were able to achieve this. Yet, older adults could perform at young adult levels if they had been asked to learn each task individually. Having older adults learn and perform both tasks together was too taxing for the central executive. In contrast, working memory tasks that do not require much input from the central executive, such as the digit span test, which uses predominantly the phonological loop, we find that older adults perform on par with young adults (Dixon & Cohen, 2003).
Changes in Long-term Memory: As you should recall, long-term memory is divided into semantic (knowledge of facts), episodic (events), and implicit (procedural skills, classical conditioning, and priming) memories. Semantic and episodic memory is part of the explicit memory system, which requires conscious effort to create and retrieve. Several studies consistently reveal that episodic memory shows greater age-related declines than semantic memory (Schwartz, 2011; Spaniol, Madden, & Voss, 2006). It has been suggested that episodic memories may be harder to encode and retrieve because they contain at least two different types of memory, the event and when and where the event took place. In contrast, semantic memories are not tied to any particular timeline. Thus, only the knowledge needs to be encoded or retrieved (Schwartz, 2011). Spaniol et al. (2006) found that retrieval of semantic information was considerably faster for both younger and older adults than the retrieval of episodic information, with there being little difference between the two age groups for semantic memory retrieval. They note that older adults’ poorer performance on episodic memory appeared to be related to slower processing of the information and the difficulty of the task. They found that as the task became increasingly difficult, the gap between each age groups’ performance increased for episodic memory more so than for semantic memory.
“blocks” at retrieving information that they know. In other words, they experience more tip-of-the-tongue (TOT) events than do younger adults (Schwartz, 2011).
Priming refers to changes in behavior as a result of frequent or recent experiences. If you were shown pictures of food and asked to rate their appearance and then later were asked to complete words such as s_ _ p, you may be more likely to write soup than soap, or ship. The images of food “primed” your memory for words connected to food. Does this type of memory and learning change with age? The answer is typically “no” for most older adults (Schacter, Church, & Osowiecki, 1994).
Prospective memory refers to remembering things we need to do in the future, such as remembering a doctor’s appointment next week or to take medication before bedtime. It has been described as “the flip-side of episodic memory” (Schwartz, 2011, p. 119). Episodic memories are the recall of events in our past, while the focus of prospective memories is of events in our future. In general, humans are fairly good at prospective memory if they have little else to do in the meantime. However, when there are competing tasks that are also demanding our attention, this type of memory rapidly declines. The explanation given for this is that this form of memory draws on the central executive of working memory, and when this component of working memory is absorbed in other tasks, our ability to remember to do something else in the future is more likely to slip out of memory (Schwartz, 2011). However, prospective memories are often divided into time-based prospective memories, such as having to remember to do something at a future time, or event-based prospective memories, such as having to remember to do something when a certain event occurs. When age-related declines are found, they are more likely to be time-based, than event-based, and in laboratory settings rather than in the real-world, where older adults can show comparable or slightly better prospective memory performance (Henry, MacLeod, Phillips & Crawford, 2004; Luo & Craik, 2008). This should not be surprising given the tendency of older adults to be more selective in where they place their physical, mental, and social energy. Having to remember a doctor’s appointment is of greater concern than remembering to hit the space-bar on a computer every time the word “tiger” is displayed.
Recall versus Recognition: Memory performance often depends on whether older adults are asked to simply recognize previously learned material or recall material on their own. Generally, for all humans, recognition tasks are easier because they require less cognitive energy. Older adults show roughly equivalent memory to young adults when assessed with a recognition task (Rhodes, Castel, & Jacoby, 2008). With recall measures, older adults show memory deficits in comparison to younger adults. While the effect is initially not that large, starting at age 40 adults begin to show declines in recall memory compared to younger adults (Schwartz, 2011).
The Age Advantage: Fewer age differences are observed when memory cues are available, such as for recognition memory tasks, or when individuals can draw upon acquired knowledge or experience. For example, older adults often perform as well if not better than young adults on tests of word knowledge or vocabulary. With age often comes expertise, and research has pointed to areas where aging experts perform quite well. For example, older typists were found to compensate for age-related declines in speed by looking farther ahead at the printed text (Salthouse, 1984). Compared to younger players, older chess experts focus on a smaller set of possible moves, leading to greater cognitive efficiency (Charness, 1981). Accrued knowledge of everyday tasks, such as grocery prices, can help older adults to make better decisions than young adults (Tentori, Osheron, Hasher, & May 2001).
Attention and Problem Solving
Changes in Attention in Late Adulthood: Changes in sensory functioning and speed of processing information in late adulthood often translate into changes in attention (Jefferies et al., 2015). Research has shown that older adults are less able to selectively focus on information while ignoring distractors (Jefferies et al., 2015; Wascher, Schneider, Hoffman, Beste, & Sänger, 2012), although Jefferies and her colleagues found that when given double-time, older adults could perform at young adult levels. Other studies have also found that older adults have greater difficulty shifting their attention between objects or locations (Tales, Muir, Bayer, & Snowden, 2002). Consider the implication of these attentional changes for older adults.
suggested that older adults use more effective strategies than younger adults to navigate through social and emotional problems (Blanchard-Fields, 2007). In the context of work, researchers rarely find that older individuals perform poorer on the job (Park & Gutchess, 2000). Similar to everyday problem solving, older workers may develop more efficient strategies and rely on expertise to compensate for cognitive decline.
Problem Solving: Problem-solving tasks that require processing non-meaningful information quickly (a kind of task that might be part of a laboratory experiment on mental processes) declines with age. However, many real-life challenges facing older adults do not rely on the speed of processing or making choices on one’s own. Older adults resolve everyday problems by relying on input from others, such as family and friends. They are also less likely than younger adults to delay making decisions on important matters, such as medical care (Strough, Hicks, Swenson, Cheng & Barnes, 2003; Meegan & Berg, 2002).
What might explain these deficits as we age? The processing speed theory, proposed by Salthouse (1996, 2004), suggests that as the nervous system slows with advanced age our ability to process information declines. This slowing of processing speed may explain age differences in many different cognitive tasks. For instance, as we age, working memory becomes less efficient (Craik & Bialystok, 2006). Older adults also need a longer time to complete mental tasks or make decisions. Yet, when given sufficient time older adults perform as competently as do young adults (Salthouse, 1996). Thus, when speed is not imperative to the task healthy older adults do not show cognitive declines.
inhibition theory argues that older adults have difficulty with inhibitory functioning, or the ability to focus on certain information while suppressing attention to less pertinent information tasks (Hasher & Zacks, 1988). Evidence comes from directed forgetting research. In directed forgetting people are asked to forget or ignore some information, but not other information. For example, you might be asked to memorize a list of words but are then told that the researcher made a mistake and gave you the wrong list and asks you to “forget” this list. You are then given a second list to memorize. While most people do well at forgetting the first list, older adults are more likely to recall more words from the “forget-to-recall” list than are younger adults (Andrés, Van der Linden, & Parmentier, 2004).
Cognitive losses exaggerated: While there are information processing losses in late adulthood, the overall loss has been exaggerated (Garrett, 2015). One explanation is that the type of tasks that people are tested on tend to be meaningless. For example, older individuals are not motivated to remember a random list of words in a study, but they are motivated for more meaningful material related to their life, and consequently perform better on those tests. Another reason is that the research is often cross-sectional. When age comparisons occur longitudinally, however, the amount of loss diminishes (Schaie, 1994). A third reason is that the loss may be due to a lack of opportunity in using various skills. When older adults practiced skills, they performed as well as they had previously. Although diminished performance speed is especially noteworthy in the elderly, Schaie (1994) found that statistically removing the effects of speed diminished the individual’s performance declines significantly. In fact, Salthouse and Babcock (1991) demonstrated that processing speed accounted for all but 1% of age-related differences in working memory when testing individuals from 18 to 82. Finally, it is well established that our hearing and vision decline as we age. Longitudinal research has proposed that deficits in sensory functioning explain age differences in a variety of cognitive abilities (Baltes & Lindenberger, 1997). Not surprisingly, more years of education, and subsequently higher income, are associated with the higher cognitive level and slower cognitive decline (Zahodne, Stern, & Manly, 2015).
Intelligence and Wisdom
crystallized intelligence encompasses abilities that draw upon experience and knowledge. Measures of crystallized intelligence include vocabulary tests, solving number problems, and understanding texts. Fluid intelligence refers to information processing abilities, such as logical reasoning, remembering lists, spatial ability, and reaction time. Baltes (1993) introduced two additional types of intelligence to reflect cognitive changes in aging. Pragmatics of intelligence are cultural exposure to facts and procedures that are maintained as one age and are similar to crystallized intelligence. Mechanics of intelligence are dependent on brain functioning and decline with age, similar to fluid intelligence. Baltes indicated that pragmatics of intelligence show a little decline and typically increase with age.
Wisdom is the ability to use accumulated knowledge about practical matters that allow for sound judgment and decision making. A wise person is insightful and has knowledge that can be used to overcome obstacles in living. Does aging bring wisdom? While living longer brings experience, it does not always bring wisdom. Paul Baltes and his colleagues (Baltes & Kunzmann, 2004; Baltes & Staudinger, 2000) suggest that wisdom is rare. In addition, the emergence of wisdom can be seen in late adolescence and young adulthood, with there being few gains in wisdom over the course of adulthood (Staudinger & Gluck, 2011). This would suggest that factors other than age are stronger determinants of wisdom. Occupations and experiences that emphasize others rather than self, along with personality characteristics, such as openness to experience and generativity, are more likely to provide the building blocks of wisdom (Baltes & Kunzmann, 2004). Age combined with certain types of experience and/or personality brings wisdom.
Neurocognitive Disorders
major neurocognitive disorder is diagnosed as a significant cognitive decline from a previous level of performance in one or more cognitive domains and interferes with independent functioning, while a minor neurocognitive disorder is diagnosed as a modest cognitive decline from a previous level of performance in one or more cognitive domains and does not interfere with independent functioning. There are several different neurocognitive disorders that are typically demonstrated in late adulthood and determining the exact type can be difficult because the symptoms may overlap with each other. Diagnosis often includes a medical history, physical exam, laboratory tests, and changes noted in behavior. Alzheimer’s disease, vascular neurocognitive disorder and neurocognitive disorder with Lewy bodies will be discussed below.
Alzheimer’s Disease: Probably the most well-known and most common neurocognitive disorder for older individuals is Alzheimer’s disease. In 2016 an estimated 5.4 million Americans were diagnosed with Alzheimer’s disease (Alzheimer’s Association, 2016), which was approximately one in nine aged 65 and over. By 2050 the number of people age 65 and older with Alzheimer’s disease is projected to be 13.8 million if there are no medical breakthroughs to prevent or cure the disease. Alzheimer’s disease is the 6th leading cause of death in the United States, but the 5th leading cause for those 65 and older. Among the top 10 causes of death in America, Alzheimer’s disease is the only one that cannot be prevented, cured, or even slowed. Current estimates indicate that Alzheimer’s disease affects approximately 50% of those identified with a neurocognitive disorder (Cohen & Eisdorfer, 2011).
next. In the later stages, the individual loses physical coordination and is unable to complete everyday tasks, including self-care and personal hygiene (Erber & Szuchman, 2015). Lastly, individuals lose the ability to respond to their environment, to carry on a conversation, and eventually to control movement (Alzheimer’s Association, 2016). On average people with Alzheimer’s survive eight years, but some may live up to 20 years. The disease course often depends on the individual’s age and whether they have other health conditions.
Βeta Amyloid and Tau: According to Erber and Szuchman (2015) the problems that occur with Alzheimer’s disease are due to the “death of neurons, the breakdown of connections between them, and the extensive formation of plaques and tau, which interfere with neuron functioning and neuron survival” (p. 50). Plaques are abnormal formations of protein pieces called beta-amyloid. Beta-amyloid comes from a larger protein found in the fatty membrane surrounding nerve cells. Because beta-amyloid is sticky, it builds up into plaques (Alzheimer’s Association, 2016). These plaques appear to block cell communication and may also trigger an inflammatory response in the immune system, which leads to further neuronal death.
functioning. For example, the hippocampus is involved in learning and memory, and the brain cells in this region are often the first to be damaged. This is why memory loss is often one of the earliest symptoms of Alzheimer’s disease. Figures 9.32 and 9.33 illustrate the difference between an Alzheimer’s brain and a healthy brain.
Sleep Deprivation and Alzheimer’s: Studies suggest that sleep plays a role in clearing both beta-amyloid and tau out of the brain. Shokri-Kojori et al. (2018) scanned participants’ brains after getting a full night’s rest and after 31 hours without sleep. Beta-amyloid increased by about 5% in the participants’ brains after losing a night of sleep. These changes occurred in brain regions that included the thalamus and hippocampus, which are associated with the early stages of Alzheimer’s disease. Shokri-Kojori et al. also found that participants with the largest increases in beta-amyloid reported the worst mood after sleep deprivation. These findings support other studies that have found that the hippocampus and thalamus are involved in mood disorders.
Healthy Lifestyle Combats Alzheimer’s: Dhana and colleagues with the Rush University Medical Center in Chicago examined how healthy lifestyle mitigates the risk of Alzheimer’s disease (Natanson, 2019). The researchers followed a diverse group of 2765 participants for 9 years and focused on five low-risk lifestyle factors: healthy diet, at least 150 minutes/week of moderate to vigorous physical activity, not smoking, light to moderate alcohol intake, and engaging in cognitively stimulating activities.
factors. The authors concluded that incorporating these lifestyle changes can have a positive effect on one’s brain functioning and lower the risk for Alzheimer’s disease.
Vascular Neurocognitive Disorder is the second most common neurocognitive disorder affecting 0.2% in the 65-70 years age group and 16% of individuals 80 years and older (American Psychiatric Association, 2013). The vascular neurocognitive disorder is associated with a blockage of cerebral blood vessels that affects one part of the brain rather than a general loss of brain cells seen with Alzheimer’s disease. Personality is not as affected in vascular neurocognitive disorder, and more males are diagnosed than females (Erber and Szuchman, 2015). It also comes on more abruptly than Alzheimer’s disease and has a shorter course before death. Risk factors include smoking, diabetes, heart disease, hypertension, or a history of strokes.
Neurocognitive Disorder with Lewy bodies: According to the National Institute on Aging (2015a), Lewy bodies are microscopic protein deposits found in neurons seen postmortem. They affect chemicals in the brain that can lead to difficulties in thinking, movement, behavior, and mood. Neurocognitive Disorder with Lewy bodies is the third most common form and affects more than 1 million Americans. It typically begins at age 50 or older and appears to affect slightly more men than women. The disease lasts approximately 5 to 7 years from the time of diagnosis to death but can range from 2 to 20 years depending on the individual’s age, health, and severity of symptoms. Lewy bodies can occur in both the cortex and brain stem which results in cognitive as well as motor symptoms (Erber & Szuchman, 2015). The movement symptoms are similar to those with Parkinson’s disease and include tremors and muscle rigidity. However, the motor disturbances occur at the same time as the cognitive symptoms, unlike Parkinson’s disease when the cognitive symptoms occur well after the motor symptoms.
Work, Retirement, and Leisure
Work: According to the United States Census Bureau, in 1994, approximately 12% of those employed were 65 and over, and by 2016, the percentage had increased to 18% of those employed (McEntarfer, 2019). Looking more closely at the age ranges, more than 40% of Americans in their 60s are still working, while 14% of people in their 70s and just 4% of those 80 and older are currently employed (Livingston, 2019). Even though they make up a smaller number of workers overall, those 65- to 74-year-old and 75-and- older age groups are projected to have the fastest rates of growth in the next decade. See Figure 9.35 for the projected annual growth rate in the labor force by age in percentages, 2014-2024.
Transitioning into Retirement: For most Americans, retirement is a process and not a one-time event (Quinn & Cahill, 2016). Sixty percent of workers transition straight to bridge jobs, which are often part-time and occur between a career and full retirement. About 15% of workers get another job after being fully retired. This may be due to not having adequate finances after retirement or not enjoying their retirement. Some of these jobs may be in encore careers or work in a different field from the one in which they retired. Approximately 10% of workers begin phasing into retirement by reducing their hours. However, not all employers will allow this due to pension regulations.
Retirement age changes: Looking at retirement data, the average age of retirement declined from more than 70 in 1910 to age 63 in the early 1980s. However, this trend has reversed and the current average age is now 65. Additionally, 18.5% of those over the age of 65 continue to work (US Department of Health and Human Services, 2012) compared with only 12% in 1990 (U. S. Government Accountability Office, 2011). With individuals living longer, once retired the average amount of time a retired worker collects social security is approximately 17-18 years (James, Matz-Costa, & Smyer, 2016).
When to retire: Laws often influence when someone decides to retire. In 1986 the Age Discrimination in Employment Act (ADEA) was amended, and mandatory retirement was eliminated for most workers (Erber & Szuchman, 2015). Pilots, air traffic controllers, federal law enforcement, national park rangers, and firefighters continue to have enforced retirement ages. Consequently, for most workers, they can continue to work if they choose and are able. Social security benefits also play a role. For those born before 1938, they can receive full social security benefits at age 65. For those born between 1943 and 1954, they must wait until age 66 for full benefits, and for those born after 1959, they must wait until age 67 (Social Security Administration, 2016). Extra months are added to those born in years between. For example, if born in 1957, the person must wait until 66 years and 6 months. The longer one waits to receive social security, the more money will be paid out. Those retiring at age 62, will only receive 75% of their monthly benefits. Medicare health insurance is another entitlement that is not available until one is aged 65.
Delayed Retirement: Older adults primarily choose to delay retirement due to economic reasons (Erber & Szchman, 2015). Financially, continuing to work provides not only added income but also does not dip into retirement savings which may not be sufficient. Historically, there have been three parts to retirement income; that is, social security, a pension plan, and individual savings (Quinn & Cahill, 2016). With the 2008 recession, pension plans lost value for most workers. Consequently, many older workers have had to work later in life to compensate for absent or minimal pension plans and personal savings. Social security was never intended to replace full income, and the benefits provided may not cover all the expenses, so elders continue to work. Unfortunately, many older individuals are unable to secure later employment, and those especially vulnerable include persons with disabilities, single women, the oldest- old, and individuals with intermittent work histories.
Retirement Stages: Atchley (1994) identified several phases that individuals go through when they retire:
• Remote pre-retirement phase includes fantasizing about what one wants to do in retirement
• Immediate pre-retirement phase when concrete plans are established
• Actual retirement
• Honeymoon phase when retirees travel and participate in activities they could not do while working
• Disenchantment phase when retirees experience an emotional let-down
• Reorientation phase when the retirees attempt to adjust to retirement by making less hectic plans and getting into a regular routine
Post-retirement: Those who look most forward to retirement and have plans are those who anticipate adequate income (Erber & Szuchman, 2015). This is especially true for males who have worked consistently and have a pension and/or adequate savings. Once retired, staying active and socially engaged is important. Volunteering, caregiving, and informal helping can keep seniors engaged. Kaskie, Imhof, Cavanaugh, and Culp (2008) found that 70% of retirees who are not involved in productive activities spent most of their time watching TV, which is correlated with negative affect. In contrast, being productive improves well-being.
Elder Education: Attending college is not just for the young as discussed in the previous chapter. There are many reasons why someone in late adulthood chooses to attend college.
Leisure: During the past 10 years, leisure time for Americans 60 and older has remained at about 7 hours a day. However, the amount of time spent on TVs, computers, tablets or other electronic devices has risen almost 30 minutes per day over the past decade (Livingston, 2019). Those 60 and older now spend more than half of their daily leisure time (4 hours and 16 minutes) in front of screens. Screen time has increased for those in their 60s, 70s, 80s and beyond, and across genders and education levels. This rise in screen time coincides with significant growth in the use of digital technology by older Americans. In 2000, 14% of those aged 65 and older used the Internet, and now 73% are users and 53% own smartphones. Alternatively, the time spent on other recreational activities, such as reading or socializing, has gone down slightly. People with less education spend more of their leisure time on screens and less time reading compared with those with more education. Less-educated adults also spend less time exercising: 12 minutes a day for those with a high school diploma or less, compared with 26 minutes for college graduates.
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/12%3A_Development_in_Late_Adulthood/12.02%3A_Chapter_29-_Cognitive_Development_in_Late_Adulthood.txt |
Chapter 30 Learning Objectives
• Explain the stereotypes of those in late adulthood and how it impacts their lives
• Summarize Erikson’s eight psychosocial tasks of integrity vs. despair
• Explain how self-concept and self-esteem affect those in late adulthood
• Identify sources of despair and regret
• Describe paths to integrity, including the activity, socioemotional selectivity, and convoy theories
• Describe the continuation of generativity in late adulthood
• Describe the relationships those in late adulthood have with their children and other family members
• Describe singlehood, marriage, widowhood, divorce, and remarriage in late adulthood
• Describe the different types of residential living in late adulthood
• Describe friendships in late life
• Explain concerns experienced by those in late adulthood, such as abuse and mental health issues
• Explain how those in late adulthood use strategies to compensate for losses
Ageism
ageism or prejudice based on age. The term ageism was first used in 1969, and according to Nelson (2016), ageism remains one of the most institutionalized forms of prejudice today.
self-fulfilling prophecy or the belief in one’s ability results in actions that make it come true. Being the target of stereotypes can adversely affect individuals’ performance on tasks because they worry they will confirm the cultural stereotypes. This is known as stereotype threat, and it was originally used to explain race and gender differences in academic achievement (Gatz et al., 2016). Stereotype threat research has demonstrated that older adults who internalize the aging stereotypes will exhibit worse memory performance, worse physical performance, and reduced self-efficacy (Levy, 2009).
Minority status: Older minority adults accounted for approximately 21% of the U. S. population in 2012 but are expected to reach 39% of the population in 2050 (U. S. Census Bureau, 2012). Unfortunately, racism is a further concern for minority elderly already suffering from ageism. Older adults who are African American, Mexican American, and Asian American experience psychological problems that are often associated with discrimination by the White majority (Youdin, 2016). Ethnic minorities are also more likely to become sick, but less likely to receive medical intervention. Older, minority women can face ageism, racism, and sexism often referred to as triple jeopardy (Hinze, Lin, & Andersson, 2012), which can adversely affect their life in late adulthood.
Poverty rates: According to Quinn and Cahill (2016), the poverty rate for older adults varies based on gender, marital status, race, and age. Women aged 65 or older were 70% more likely to be poor than men, and older women aged 80 and above have higher levels of poverty than those younger. Married couples are less likely to be poor than nonmarried men and women, and poverty is more prevalent among older racial minorities. In 2012 the poverty rates for White older men (5.6%) and White older women (9.6%) were lower than for Black older men (14%), Black older women (21%), Hispanic older men (19%), and Hispanic older women (22%).
Do those in late adulthood primarily live alone? No. In 2017, of those 65 years of age and older, approximately 72% of men and 48% of women lived with their spouse or partner (Administration on Aging, 2017). Between 1900 and 1990 the number of older adults living alone increased, most likely due to improvements in health and longevity during this time (see Figure 9.40). Since 1990 the number of older adults living alone has declined, because of older women more likely to be living with their spouse or children (Stepler, 2016c). Women continue to make up the majority of older adults living alone in the U.S., although that number has dropped from those living alone in 1990 (Stepler, 2016a). Older women are more likely to be unmarried, living with children, with other relatives or non-relatives. Older men are more likely to be living alone than they were in 1990, although older men are more likely to reside with their spouses. The rise in divorce among those in late adulthood, along with the drop-in remarriage rate, has resulted in slightly more older men living alone today than in the past (Stepler, 2016c).
Do those in late adulthood primarily live with family members? No, but according to the Pew Research Center, there has been an increase in the number of families living in multigenerational housing; that is three generations living together than in previous generations (Cohn & Passel, 2018). In 2016, a record 64 million Americans, or 20% of the population, lived in a house with at least two adult generations. However, ethnic differences are noted in the percentage of multigenerational households with Hispanic (27%), Black (26%), and Asian (29%) families living together in greater numbers than White families (16%). Consequently, the majority of older adults wish to live independently for as long as they are able.
Do those in late adulthood move after retirement? No. According to Erber and Szuchman (2015), the majority of those in late adulthood remains in the same location, and often in the same house, where they lived before retiring. Although some younger late adults (65-74 years) may relocate to warmer climates, once they are older (75-84 years) they often return to their home states to be closer to adult children (Stoller & Longino, 2001). Despite the previous trends, however, the recent housing crisis has kept those in late adulthood in their current suburban locations because they are unable to sell their homes (Erber & Szuchman, 2015).
Do those in late adulthood primarily live in institutions? No. Only a small portion (3.2%) of adults older than 65 lived in an institution in 2015 (United States Department of Health and Human Services, 2015). However, as individuals increase in age the percentage of those living in institutions, such as a nursing home, also increases. Specifically: 1% of those 65-74, 3% of those 75-84, and 10% of those 85 years and older lived in an institution in 2015. Due to the increasing number of baby boomers reaching late adulthood, the number of people who will depend on long-term care is expected to rise from 12 million in 2010 to 27 million in 2050 (United States Senate Commission on Long-Term Care, 2013). To meet this higher demand for services, a focus on the least restrictive care alternatives has resulted in a shift toward home and community-based care instead of placement in a nursing home (Gatz et al., 2016).
Erikson: Integrity vs. Despair
Integrity vs. Despair. This stage includes, “a retrospective accounting of one’s life to date; how much one embraces life as having been well lived, as opposed to regretting missed opportunities,” (Erikson, 1982, p. 112). Those in late adulthood need to achieve both the acceptance of their life and the inevitability of their death (Barker, 2016). This stage includes finding meaning in one’s life and accepting one’s accomplishments, but also acknowledging what in life has not gone as hoped. It is also feeling a sense of contentment and accepting others’ deficiencies, including those of their parents. This acceptance will lead to integrity, but if elders are unable to achieve this acceptance, they may experience despair. Bitterness and resentment in relationships and life events can lead one to despair at the end of life. According to Erikson (1982), successful completion of this stage leads to wisdom in late life.
Staying Active: Many older adults want to remain active and work toward replacing opportunities lost with new ones. Those who prefer to keep themselves busy demonstrate the Activity Theory, which states that greater satisfaction with one’s life occurs with those who remain active (Lemon, Bengston, & Peterson, 1972). Not surprisingly, more positive views on aging and greater health are noted with those who keep active than those who isolate themselves and disengage from others. Community, faith-based, and volunteer organizations can all provide those in late adulthood with opportunities to remain active and maintain social networks. Erikson’s concept of generativity applies to many older adults, just as it did in midlife.
Generativity in Late Adulthood
Volunteering: Many older adults spend time volunteering. Hooyman and Kiyak (2011) found that religious organizations are the primary settings for encouraging and providing opportunities to volunteer. Hospitals and environmental groups also provide volunteer opportunities for older adults. While volunteering peaks in middle adulthood, it continues to remain high among adults in their 60s, with about 40% engaging in volunteerism (Hooyman & Kiyak, 2011). While the number of older adults volunteering their time does decline with age, the number of hours older adults volunteer does not show much decline until they are in their late 70s (Hendricks & Cutler, 2004). African-American older adults volunteer at higher levels than other ethnic groups (Taylor, Chatters, & Leving, 2004). Taylor and colleagues attribute this to the higher involvement in religious organizations by older African-Americans. Volunteering aids older adults as much as it does the community at large. Older adults who volunteer experience more social contact, which has been linked to higher rates of life satisfaction, and lower rates of depression and anxiety (Pilkington, Windsor, & Crisp, 2012).
Grandparents Raising Grandchildren: According to the 2014 American Community Survey (U.S. Census, 2014a), over 5.5 million children under the age of 18 were living in families headed by a grandparent. This was more than half a million increase from 2010. While most grandparents raising grandchildren are between the ages of 55 and 64, approximately 25% of grandparents raising their grandchildren are 65 and older (Office on Women’s Health, 2010a). For many grandparents, parenting a second time can be harder. Older adults have far less energy, and often the reason why they are now acting as parents to their grandchildren is that traumatic events. A survey by AARP (Goyer, 2010) found that grandparents were raising their grandchildren because the parents had problems with drugs and alcohol, had a mental illness, was incarcerated, had divorced, had a chronic illness, was homeless, had neglected or abused the child, were deployed in the military, or had died. While most grandparents state they gain great joy from raising their grandchildren, they also face greater financial, health, education, and housing challenges that often derail their retirement plans than do grandparents who do not have primary responsibility for raising their grandchildren.
Social Networks in Late Adulthood
However, the two theories differ in explaining why this occurs.
Convoy Model of Social Relations suggests that the social connections that people accumulate differ in levels of closeness and are held together by exchanges in social support (Antonucci, 2001; Kahn & Antonucci, 1980). According to the Convoy Model, relationships with a spouse and family members, people in the innermost circle of the convoy, should remain stable throughout the lifespan. In contrast, coworkers, neighbors, and acquaintances, people in the periphery of the convoy, should be less stable. These peripheral relationships may end due to changes in jobs, social roles, location, or other life events. These relationships are more vulnerable to changing situations than family relationships. Therefore, the frequency, type, and reciprocity of the social exchanges with peripheral relationships decrease with age.
Socioemotional Selectivity Theory focuses on changes in motivation for actively seeking social contact with others (Carstensen, 1993; Carstensen, Isaacowitz & Charles, 1999). This theory proposes that with increasing age, our motivational goals change based on how much time one has left to live. Rather than focusing on acquiring information from many diverse social relationships, as noted with adolescents and young adults, older adults focus on the emotional aspects of relationships. To optimize the experience of positive affect, older adults actively restrict their social life to prioritize time spent with emotionally close significant others. In line with this theory, older marriages are found to be characterized by enhanced positive and reduced negative interactions and older partners show more affectionate behavior during conflict discussions than do middle-aged partners (Carstensen, Gottman, & Levenson, 1995). Research showing that older adults have smaller networks compared to young adults, and tend to avoid negative interactions, also supports this theory.
Relationship with Adult Children: Many older adults provide financial assistance and/or housing to adult children. There is more support going from the older parent to the younger adult children than in the other direction (Fingerman & Birditt, 2011). In addition to providing for their own children, many elders are raising their grandchildren. Consistent with socioemotional selectivity theory, older adults seek and are helped by, their adult children providing emotional support (Lang & Schütze, 2002). Lang and Schütze, as part of the Berlin Aging Study (BASE), surveyed adult children (mean age 54) and their aging parents (mean age 84). They found that the older parents of adult children who provided emotional support, such as showing tenderness toward their parent, cheering the parent up when he or she was sad, tended to report greater life satisfaction. In contrast, older adults whose children provided informational support, such as providing advice to the parent, reported less life satisfaction. Lang and Schütze found that older adults wanted their relationship with their children to be more emotionally meaningful. Daughters and adult children who were younger tended to provide such support more than sons and adult children who were older. Lang and Schütze also found that adult children who were more autonomous rather than emotionally dependent on their parents, had more emotionally meaningful relationships with their parents, from both the parents’ and adult children’s point of view.
Friendships: Friendships are not formed in order to enhance status or careers, and may be based purely on a sense of connection or the enjoyment of being together. Most elderly people have at least one close friend. These friends may provide emotional as well as physical support. Being able to talk with friends and rely on others is very important during this stage of life. Bookwala, Marshall, and Manning (2014) found that the availability of a friend played a significant role in protecting health from the impact of widowhood. Specifically, those who became widowed and had a friend as a confidante reported significantly lower somatic depressive symptoms, better self-rated health, and fewer sick days in bed than those who reported not having a friend as a confidante. In contrast, having a family member as a confidante did not provide health protection for those recently widowed.
Loneliness or Solitude: Loneliness is the discrepancy between the social contact a person has and the contacts a person wants (Brehm, Miller, Perlman, & Campbell, 2002). It can result from social or emotional isolation. Women tend to experience loneliness due to social isolation; men from emotional isolation. Loneliness can be accompanied by a lack of self-worth, impatience, desperation, and depression. Being alone does not always result in loneliness. For some, it means solitude. Solitude involves gaining self-awareness, taking care of the self, being comfortable alone, and pursuing one’s interests (Brehm et al., 2002). In contrast, loneliness is perceived as social isolation.
increase in risk for dementia and a 30% increase in the risk of stroke or coronary heart disease. This was hypothesized to be due to a rise in stress hormones, depression, and anxiety, as well as the individual lacking encouragement from others to engage in healthy behaviors. In contrast, older adults who take part in social clubs and church groups have a lower risk of death. Opportunities to reside in mixed-age housing and continuing to feel like a productive member of society have also been found to decrease feelings of social isolation, and thus loneliness.
Late Adult Lifestyles
Marriage: As can be seen in Figure 9.45, the most common living arrangement for older adults in 2015 was marriage (AOA, 2017). Although this was more common for older men.
Widowhood: Losing one’s spouse is one of the most difficult transitions in life. The Social Readjustment Rating Scale, commonly known as the Holmes-Rahe Stress Inventory, rates the death of a spouse as the most significant stressor (Holmes & Rahe, 1967). The loss of a spouse after many years of marriage may make an older adult feel adrift in life. They must remake their identity after years of seeing themselves as a husband or wife. Approximately, 1 in 3 women aged 65 and older are widowed, compared with about 1 in 10 men.
widowhood mortality effect refers to the higher risk of death after the death of a spouse (Sullivan & Fenelon, 2014). Subramanian, Elwert, and Christakis (2008) found that widowhood increases the risk of dying from almost all causes.
Divorce: As noted in Chapter 8, older adults are divorcing at higher rates than in prior generations. However, adults age 65 and over are still less likely to divorce than middle-aged and young adults (Wu & Schimmele, 2007). Divorce poses a number of challenges for older adults, especially women, who are more likely to experience financial difficulties and are more likely to remain single than are older men (McDonald & Robb, 2004). However, in both America (Lin, 2008) and England (Glaser, Stuchbury, Tomassini, & Askham, 2008) studies have found that the adult children of divorced parents offer more support and care to their mothers than their fathers. While divorced, older men may be better off financially and are more likely to find another partner, they may receive less support from their adult children.
Dating: Due to changing social norms and shifting cohort demographics, it has become more common for single older adults to be involved in dating and romantic relationships (Alterovitz & Mendelsohn, 2011). An analysis of widows and widowers ages 65 and older found that 18 months after the death of a spouse, 37% of men and 15% of women were interested in dating (Carr, 2004a). Unfortunately, opportunities to develop close relationships often diminish in later life as social networks decrease because of retirement, relocation, and the death of friends and loved ones (de Vries, 1996). Consequently, older adults, much like those younger, are increasing their social networks using technologies, including e-mail, chat rooms, and online dating sites (Fox, 2004; Wright & Query, 2004; Papernow, 2018).
wanting to lose their autonomy, care for a potentially ill partner, or merge their finances with someone (Watson & Stelle, 2011).
Remarriage and Cohabitation: Older adults who remarry often find that their remarriages are more stable than those of younger adults. Kemp and Kemp (2002) suggest that greater emotional maturity may lead to more realistic expectations regarding marital relationships, leading to greater stability in remarriages in later life. Older adults are also more likely to be seeking companionship in their romantic relationships. Carr (2004a) found that older adults who have considerable emotional support from their friends were less likely to seek romantic relationships. In addition, older adults who have divorced often desire the companionship of intimate relationships without marriage. As a result, cohabitation is increasing among older adults, and like remarriage, cohabitation in later adulthood is often associated with more positive consequences than it is in younger age groups (King & Scott, 2005). No longer being interested in raising children, and perhaps wishing to protect family wealth, older adults may see cohabitation as a good alternative to marriage. In 2014, 2% of adults age 65 and up were cohabitating (Stepler, 2016b).
Living Apart Together: In addition to cohabiting there has been an increase in living apart together (LAT), which is “a monogamous intimate partnership between unmarried individuals who live in separate homes but identify themselves as a committed couple” (Benson & Coleman, 2016, p. 797). This trend has been found in several nations and is motivated by:
• A strong desire to be independent in day-to-day decisions
• Maintaining their own home
• Keeping boundaries around established relationships
• Maintaining financial stability
Gay and Lesbian Elders
LGBT Elder Care: Approximately 7 million LGBT people over age 50 will reside in the United States by 2030, and 4.7 million of them will need elder care. Decisions regarding elder care are often left for families, and because many LGBT people are estranged from their families, they are left in a vulnerable position when seeking living arrangements (Alleccia & Bailey, 2019). A history of discriminatory policies, such as housing restricted to married individuals involving one man and one woman, and stigma associated with LGBT people make them especially vulnerable to negative housing experiences when looking for eldercare.
no laws to protect them from victimization. The baby boomers, who grew up in the 1960s and 1970s, began to see states repeal laws that criminalized homosexual behavior. Future lesbian and gay elders will have different experiences due to the legal right for same-sex marriage and greater societal acceptance. Consequently, just like all those in late adulthood, understanding that gay and lesbian elders are a heterogeneous population is important when understanding their overall development.
Type Description
Physical Abuse Physical force resulting in injury, pain, or impairment
Sexual Abuse Nonconsensual sexual contact
Psychological and Emotional Abuse Infliction of distress through verbal or nonverbal acts such as yelling, threatening, or isolating
Financial Abuse and Exploitation Improper use of an elder’s finances, property, or assets
Neglect and Abandonment Intentional or unintentional refusal or failure to fulfill caregiving duties to an elder
did not consider verbal abuse as elder abuse, and higher socioeconomic status African American and White women did not consider financial abuse as a form of elder abuse (as cited in Roberto, 2016, p. 304).
Substance Abuse and the Elderly
• There are 2.5 million older adults with an alcohol or drug problem.
• Six to eleven percent of elderly hospital admissions, 14 percent of elderly emergency room admissions, and 20 percent of elderly psychiatric hospital admissions are a result of alcohol or drug problems.
• Widowers over the age of 75 have the highest rate of alcoholism in the U.S.
• Nearly 50 percent of nursing home residents have alcohol-related problems.
• Older adults are hospitalized as often for alcoholic related problems as for heart attacks.
• Nearly 17 million prescriptions for tranquilizers are prescribed for older adults each year. Benzodiazepines, a type of tranquilizing drug, are the most commonly misused and abused prescription medications.
Diagnosis Difficulties: Using criteria from the Diagnostic and Statistical Manual of Disorder-5th Edition (American Psychiatric Association, 2013), diagnosing older adults with a substance use disorder can be difficult (Youdin, 2016). For example, compared to adolescents and younger adults, older adults are not looking to get high, but rather become dependent by accident.
of a substance use disorder. Further, a diagnosis of a substance use disorder involves impairment in work, school, or home obligations, and because older adults are not typically working, in school or caring for children, these impairments would not be exhibited. Stigma and shame about use, as well as the belief that one’s use is a private matter, may keep older adults from seeking assistance. Lastly, physicians may be biased against asking those in late adulthood if they have a problem with drugs or alcohol (NCADD, 2015).
Abused Substances: Drugs of choice for older adults include alcohol, benzodiazepines, opioid prescription medications, and marijuana. The abuse of prescription medications is expected to increase significantly. Siriwardena, Qureshi, Gibson, Collier, and Lathamn (2006) found that family physicians prescribe benzodiazepines and opioids to older adults to deal with psychosocial and pain problems rather than prescribe alternatives to medication such as therapy. Those in late adulthood are also more sensitive to the effects of alcohol than those younger because of an age-related decrease in the ratio between lean body mass and fat (Erber & Szuchman, 2015).
Cannabis Use: Blazer and Wu (2009) found that adults aged 50-64 were more likely to use cannabis than older adults. These “baby boomers” with the highest cannabis use included men, those unmarried/unpartnered, and those with depression. In contrast to the negative effects of cannabis, which include panic reactions, anxiety, perceptual distortions and exacerbation of mood and psychotic disorders, cannabis can provide benefits to an older adults with medical conditions (Youdin, 2016). For example, cannabis can be used in the treatment of multiple sclerosis, Parkinson’s disease, chronic pain, and fatigue and nausea from the effects of chemotherapy (Williamson & Evans, 2000).
Future Substance Abuse Concerns: There will be an increase in the number of seniors abusing substances in the future because the baby boomer generation has a history of having been exposed to, and having experienced, psychoactive substance use over their adult life. This is a significant difference between the current and previous generations of older adults (National Institutes of Health, 2014c). Efforts will be needed to adequately address these future substance abuse issues for the elderly due to both the health risks for them and the expected burden on the health care system.
Successful Aging
• Relative avoidance of disease, disability, and risk factors, like high blood pressure, smoking, or obesity
• Maintenance of high physical and cognitive functioning
• Active engagement in social and productive activities
selective optimization with compensation is used when the elder makes adjustments, as needed, in order to continue living as independently and actively as possible (Baltes & Dickson, 2001). When older adults lose functioning, referred to as loss-based selection, they may first use new resources/technologies or continually practice tasks to maintain their skills. However, when tasks become too difficult, they may compensate by choosing other ways to achieve their goals. For example, a person who can no longer drive needs to find alternative transportation, or a person who is compensating for having less energy learns how to reorganize the daily routine to avoid over-exertion.
Attribution
Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license. | textbooks/socialsci/Social_Work_and_Human_Services/Remix%3A_Human_Behavior_and_the_Social_Environment_I_(Tyler)/12%3A_Development_in_Late_Adulthood/12.03%3A_Chapter_30-_Psychosocial_Development_in_Late_Adulthood.txt |
How do social workers know the right thing to do? It’s an important question. Incorrect social work actions may actively harm clients and communities. Timely and effective social work interventions further social justice and promote individual change. To do make the right choices, we must have a basis of knowledge, the skills to understand it, and the commitment to growing that knowledge. The source of social work knowledge is social science and this book is about how to understand and apply it to social work practice.
This chapter discusses or mentions the following topics: stereotypes of people on welfare, sexual harassment and sexist job discrimination, sexism, poverty, homelessness, mental illness, and substance abuse.
01: Introduction to Research
Learning Objectives
• Reflect on how we know what to do as social workers
• Differentiate between micro-, meso-, and macro-level analysis
• Describe intuition, its purpose in social work, and its limitations
• Identify specific types of cognitive biases and how the influence thought
• Define scientific inquiry
What would you do?
Imagine you are a clinical social worker at a children’s mental health agency. Today, you receive a referral from your town’s middle school about a client who often skips school, gets into fights, and is disruptive in class. The school has suspended him and met with the parents multiple times, who say they practice strict discipline at home. Yet, the client’s behavior only gotten worse. When you arrive at the school to meet with the boy, you notice he has difficulty maintaining eye contact with you, appears distracted, and has a few bruises on his legs. At the same time, he is also a gifted artist, and you two spend the hour in which you assess him painting and drawing.
• Given the strengths and challenges you notice, what interventions would you select for this client and how would you know your interventions worked?
Imagine you are a social worker in an urban food desert, a geographic area in which there is no grocery store that sells fresh food. Many of your low-income clients rely on food from the dollar store or convenience stores in order to live or simply order takeout. You are becoming concerned about your clients’ health, as many of them are obese and say they are unable to buy fresh food. Because convenience stores are more expensive and your clients mostly survive on minimum wage jobs or Supplemental Nutrition Assistance Program (SNAP) benefits, they often have to rely on food pantries towards the end of the month once their money runs out. You have spent the past month building a coalition composed of members from your community, including non-profit agencies, religious groups, and healthcare workers to lobby your city council.
• How should your group address the issue of food deserts in your community? What intervention do you suggest? How would you know if your intervention worked?
You are a social worker working at a public policy center focused on homelessness. Your city is seeking a large federal grant to address the growing problem of homelessness in your city and has hired you as a consultant to work on the grant proposal. After conducting a needs assessment in collaboration with local social service agencies and interviewing people who are homeless, you meet with city councilmembers to talk about your options to create a program. Local agencies want to spend the money to build additional capacity at existing shelters in the community. They also want to create a transitional housing program at an unused apartment complex where people can live after the shelter and learn independent living skills. On the other hand, the clients you interview want to receive housing vouchers so they can rent an apartment from a landlord in the community. They also fear the agencies running the shelter and transitional housing program would dictate how to live their lives and impose unnecessary rules, like restrictions on guests or quiet hours. When you ask the agencies about client feedback, they state that clients could not be trusted to manage in their own apartments and need the structure and supervision provided by agency support workers.
• What kind of program should your city choose to implement? Which program is most likely to be effective?
Assuming you’ve taken a social work course before, you will notice that the case studies cover different levels of analysis in the social ecosystem—micro, meso, and macro. At the micro-level, social workers examine the smallest levels of interaction; even in some cases, just “the self” alone. That is our misbehaving child in case 1. When social workers investigate groups and communities, such as our food desert in case 2, their inquiry is at the meso-level. At the macro-level, social workers examine social structures and institutions. Research at the macro-level examines large-scale patterns, including culture and government policy, as in case 3. These domains interact with each other, and it is common for a social work research project to address more than one level of analysis. Moreover, research that occurs on one level is likely to have implications at the other levels of analysis.
How do social workers know what to do?
Welcome to social work research. This chapter begins with three problems that social workers might face in practice and three questions about what a social worker should do next. If you haven’t already, spend a minute or two thinking about how you would respond to each case and jot down some notes. How would you respond to each of these cases?
I assume it is unlikely you are an expert in the areas of children’s mental health, community responses to food deserts, and homelessness policy. Don’t worry, I’m not either. In fact, for many of you this textbook will likely come at an early point in your social work education, so it may seem unfair for me to ask you what the right answers are. And to disappoint you further, this course will not teach you the right answer to these questions. It will, however, teach you how to answer these questions for yourself. Social workers must learn how to examine the literature on a topic, come to a reasoned conclusion, and use that knowledge in their practice. Similarly, social workers engage in research to make sure their interventions are helping, not harming, clients and to contribute to social science as well as social justice.
Again, assuming you did not have advanced knowledge of the topics in the case studies, when you thought about what you might do in those practice situations, you were likely using intuition (Cheung, 2016). [1] Intuition is a way of knowing that is mostly unconscious. You simply have a gut feeling about what you should do. As you think about a problem such as those in the case studies, you notice certain details and ignore others. Using your past experiences, you apply knowledge that seems to be relevant and make predictions about what might be true.
In this way, intuition is based on direct experience. Many of us know things simply because we’ve experienced them directly. For example, you would know that electric fences can be pretty dangerous and painful if you touched one while standing in a puddle of water. We all probably have times we can recall when we learned something because we experienced it. If you grew up in Minnesota, you would observe plenty of kids learning each winter that it really is true that your tongue will stick to metal if it’s very cold outside. Similarly, if you passed a police officer on a two-lane highway while driving 20 miles over the speed limit, you would probably learn that that’s a good way to earn a traffic ticket.
Intuition and direct experience are powerful forces. Uniquely, social work is a discipline that values intuition, though it will take quite a while for you to develop what social workers refer to as practice wisdom. Practice wisdom is the “learning by doing” that develops as one practices social work over a period of time. Social workers also reflect on their practice, independently and with colleagues, which sharpens their intuitions and opens their mind to other viewpoints. While your direct experience in social work may be limited at this point, feel confident that through reflective practice you will attain practice wisdom.
However, it’s important to note that intuitions are not always correct. Think back to the first case study. What might be your novice diagnosis for this child’s behavior? Does he have attention deficit hyperactivity disorder (ADHD) because he is distractible and getting into trouble at school? Or are those symptoms of autism spectrum disorder or an attachment disorder? Are the bruises on his legs an indicator of ADHD, or do they indicate possible physical abuse at home? Even if you arrived at an accurate assessment of the situation, you would still need to figure out what kind of intervention to use with the client. If he has a mental health issue, you might say, “give him therapy.” Well…what kind of therapy? Should we use cognitive-behavioral therapy, play therapy, art therapy, family therapy, or animal assisted therapy? Should we try a combination of therapy and medication prescribed by a psychiatrist?
We could guess which intervention would be best…but in practice, that would be highly unethical. If we guessed wrong, we could be wasting time, or worse, actively harming a client. We need to ground our social work interventions with clients and systems with something more secure than our intuition and experience.
Cognitive biases
Although the human mind is a marvel of observation and data analysis, there are universal flaws in thinking that must be overcome. We all rely on mental shortcuts to help us make sense of a continuous stream of new information. All people, including me and you, must train our minds to be aware of predictable flaws in thinking, termed cognitive biases. Here is a link to the Wikipedia entry on cognitive biases. As you can see, it is quite long. We will review some of the most important ones here, but take a minute and browse around to get a sense of how baked-in cognitive biases are to how humans think.
The most important cognitive bias for social scientists to be aware of is confirmation bias. Confirmation bias involves observing and analyzing information in a way that confirms what you already think is true. No person is a blank slate. We all arrive at each moment with a set of beliefs, experiences, and models of how the world works that we develop over time. Often, these are grounded in our own personal experiences. Confirmation bias assumes these intuitions are correct and ignores or manipulates new information order to avoid challenging what we already believe to be true.
Confirmation bias can be seen in many ways. Sometimes, people will only pay attention to the information that fits their preconceived ideas and ignore information that does not fit. This is called selective observation. Other times, people will make hasty conclusions about a broad pattern based on only a few observations. This is called overgeneralization. Let’s walk through an example and see how they each would function.
In our second case study, we are trying to figure out how to help people who receive SNAP (formerly Food Stamps) who live in a food desert. Let’s say that we have arrived at a solution and are now lobbying the city council to implement it. There are many people who have negative beliefs about people who are “on welfare.” These people believe individuals who receive social welfare benefits spend their money irresponsibly, are too lazy to get a job, and manipulate the system to maintain or increase their government payout. People expressing this belief may provide an example like Louis Cuff, who bought steak and lobster with his SNAP benefits and resold them for a profit.
City council members who hold these beliefs may ignore the truth about your client population—that people experiencing poverty usually spend their money responsibly and genuinely need help accessing fresh and healthy food. This would be an example of selective observation, only looking at the cases that confirm their biased beliefs about people in poverty and ignoring evidence that challenges that perspective. Likely, these are grounded in overgeneralization, in which one example, like Mr. Cuff, is applied broadly to the population of people using social welfare programs. Social workers in this situation would have to hope that city council members are open to another perspective and can be swayed by evidence that challenges their beliefs. Otherwise, they will continue to rely on a biased view of people in poverty when they create policies.
But where do these beliefs and biases come from? Perhaps, someone who the person considers an authority told them that people in poverty are lazy and manipulative. Naively relying on authority can take many forms. We might rely on our parents, friends, or religious leaders as authorities on a topic. We might consult someone who identifies as an expert in the field and simply follow what they say. We might hop aboard a “bandwagon” and adopt the fashionable ideas and theories of our peers and friends.
Now, it is important to note that experts in the field should generally be trusted to provide well-informed answers on a topic, though that knowledge should be receptive to skeptical critique and will develop over time as more scholars study the topic. There are limits to skepticisim, however. Disagreeing with experts about global warming, the shape of the earth, or the efficacy and safety of vaccines does not make one free of cognitive biases. On the contrary, it is likely that the person is falling victim to the Dunning-Kruger effect, in which unskilled people overestimate their ability to find the truth. As this comic illustrates, they are at the top of Mount Stupid. Only through rigorous, scientific inquiry can they progress down the back slope and hope to increase their depth of knowledge about a topic.
Scientific Inquiry
Cognitive biases are most often expressed when people are using informal observation. Until I asked at the beginning of this chapter, you may have had little reason to formally observe and make sense of information about children’s mental health, food deserts, or homelessness policy. Because you engaged in informal observation, it is more likely that you will express cognitive biases in your responses. The problem with informal observation is that sometimes it is right, and sometimes it is wrong. And without any systematic process for observing or assessing the accuracy of our observations, we can never really be sure that our informal observations are accurate. In order to minimize the effect of cognitive biases and come up with the truest understanding of a topic, we must apply a systematic framework for understanding what we observe.
The opposite of informal observation is scientific inquiry, used interchangeably with the term research methods in this text. These terms refer to an organized, logical way of knowing that involves both theory and observation. Science accounts for the limitations of cognitive biases—not perfectly, though—by ensuring observations are done rigorously, following a prescribed set of steps. Scientists clearly describe the methods they use to conduct observations and create theories about the social world. Theories are tested by observing the social world, and they can be shown to be false or incomplete. In short, scientists try to learn the truth. Social workers use scientific truths in their practice and conduct research to revise and extend our understanding of what is true in the social world. Social workers who ignore science and act based on biased or informal observation may actively harm clients.
Key Takeaways
• Social work research occurs on the micro-, meso-, and macro-level.
• Intuition is a powerful, though woefully incomplete, guide to action in social work.
• All human thought is subject to cognitive biases.
• Scientific inquiry accounts for cognitive biases by applying an organized, logical way of observing and theorizing about the world.
Glossary
• Authority- learning by listening to what people in authority say is true
• Cognitive biases- predictable flaws in thinking
• Confirmation bias- observing and analyzing information in a way that confirms what you already think is true
• Direct experience- learning through informal observation
• Dunning-Kruger effect- when unskilled people overestimate their ability and knowledge (and experts underestimate their ability and knowledge)
• Intuition- your “gut feeling” about what to do
• Macro-level- examining social structures and institutions
• Meso-level- examining interaction between groups
• Micro-level- examining the smallest levels of interaction, usually individuals
• Overgeneralization- using limited observations to make assumptions about broad patterns
• Practice wisdom- “learning by doing” that guides social work intervention and increases over time
• Research methods- an organized, logical way of knowing based on theory and observation
Image Attributions
Thinking woman by Free-Photos via Pixabay CC-0
Light bulb by MasterTux via Pixabay CC-0
1. Cheung, J. C. S. (2016). Researching practice wisdom in social work. Journal of Social Intervention: Theory and Practice, 25(3), 24-38. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/01%3A_Introduction_to_Research/1.01%3A_How_do_social_workers_know_what_to_do.txt |
Learning Objectives
• Define science
• Describe the the difference between objective and subjective truth(s)
• Describe the role of ontology and epistemology in scientific inquiry
Science and social work
Science is a particular way of knowing that attempts to systematically collect and categorize facts or truths. A key word here is systematically–conducting science is a deliberate process. Scientists gather information about facts in a way that is organized and intentional, usually following a set of predetermined steps. More specifically, social work is informed by social science, the science of humanity, social interactions, and social structures. In other words, social work research uses organized and intentional procedures to uncover facts or truths about the social world. And social workers rely on social scientific research to promote individual and social change.
Philosophy of social science
This approach to finding truth probably sounds similar to something you heard in your middle school science classes. When you learned about the gravitational force or the mitochondria of a cell, you were learning about the theories and observations that make up our understanding of the physical world. These theories rely on an ontology, or a set of assumptions about what is real. We assume that gravity is real and that the mitochondria of a cell are real. Mitochondria are easy to spot with a powerful enough microscope and we can observe and theorize about their function in a cell. The gravitational force is invisible, but clearly apparent from observable facts, like watching an apple fall. The theories about gravity have changed over the years, but improvements in theory were made when observations could not be correctly interpreted using existing theories.
If we weren’t able to perceive mitochondria or gravity, they would still be there, doing their thing because they exist independent of our observation of them. This is a philosophical idea called realism, and it simply means that the concepts we talk about in science really and truly exist. Ontology in physics and biology is focused on objectivetruth. Chances are you’ve heard of “being objective” before. It involves observing and thinking with an open mind, pushing aside anything that might bias your perspective. Objectivity also means we want to find what is true for everyone, not just what is true for one person. Certainly, gravity is true for everyone and everywhere. Let’s consider a social work example, though. It is objectively true that children who are subjected to severely traumatic experiences will experience negative mental health effects afterwards. A diagnosis of post-traumatic stress disorder (PTSD) is considered to be objective, referring to a real mental health issue that exists independent of the social worker observing it and that is highly similar in its presentation with our client as it would be with other clients.
So, an objective ontological perspective means that what we observe is true for everyone and true even when we aren’t there to observe it. How do we come to know objective truths like these? This is the study of epistemology, or our assumptions about how we come to know what is real and true. The most relevant epistemological question in the social sciences is whether truth is better accessed using numbers or words. Generally, scientists approaching research with an objective ontology and epistemology will use quantitative methods to arrive at scientific truth. Quantitative methods examine numerical data to precisely describe and predict elements of the social world. This is due to the epistemological assumption that mathematics can represent the phenomena and relationships we observe in the social world.
Mathematical relationships are uniquely useful, in that they allow comparisons across individuals as well as across time and space. For example, while people can have different definitions for poverty, an objective measurement such as an annual income of less than \$25,100 for a family of four provides (1) a precise measurement, (2) that can be compared to incomes from all other people in any society from any time period, (3) and refer to real quantities of money that exist in the world. In this book, we will review survey and experimental methods, which are the most common designs that use quantitative methods to answer research questions.
It may surprise you to learn that objective facts, such as income or mental health diagnosis, are not the only facts in the social sciences. Indeed, social science is not only concerned with objective truth. Social science also describes subjective truth, or the truths that are unique to individuals, groups, and contexts. Unlike objective truth, which is true for all people, subjective truths will vary based on who you are observing and the context in which you are observing them. The beliefs, opinions, and preferences of people are actually truths that social scientists measure and describe. Additionally, subjective truths do not exist independent of human observation because they are the product of the human mind. We negotiate what is true in the social world through language, arriving at a consensus and engaging in debate.
Epistemologically, a scientist seeking subjective truth assumes that truth lies in what people say, their words. A scientist uses qualitative methods to analyze words or other media to understand their meaning. Humans are social creatures, and we give meaning to our thoughts and feelings through language. Linguistic communication is unique. We share ideas with each other at a remarkable rate. In so doing, ideas come into and out of existence in a spontaneous and emergent fashion. Words are given a meaning by their creator. But anyone who receives that communication can absorb, amplify, and even change its original intent. Because social science studies human interaction, subjectivists argue that language is the best way to understand the world.
This epistemology is based on some interesting ontological assumptions. What happens when someone incorrectly interprets a situation? While their interpretation may be wrong, it is certainly true to them that they are right. Furthermore, they act on the assumption that they are right. In this sense, even incorrect interpretations are truths, even though they are only true to one person. This leads us to question whether the social concepts we think about really exist. They might only exist in our heads, unlike concepts from the natural sciences which exist independent of our thoughts. For example, if everyone ceased to believe in gravity, we wouldn’t all float away. It has an existence independent of human thought.
Let’s think through an example. In the Diagnositic and Statistical Manual (DSM) classification of mental health disorders, there is a list of culture-bound syndromes which only appear in certain cultures. For example, susto describes a unique cluster of symptoms experienced by people in Latin American cultures after a traumatic event that focus on the body. Indeed, many of these syndromes do not fit within a Western conceptualization of mental health because they differentiate less between the mind and body. To a Western scientist, susto may seem less real than PTSD. To someone from Latin America, their symptoms may not fit neatly into the PTSD framework developed within Western society. This conflict raises the question–do either susto or PTSD really exist at all? If your answer is “no,” you are adopting the ontology of anti-realism, that social concepts do not have an existence apart from human thought. Unlike the realists who seek a single, universal truth, the anti-realists see a sea of truths, created and shared within a social and cultural environment.
Let’s consider another example: manels or all-male panel discussions at conferences and conventions. Check out this National Public Radio article for some hilarious examples, ironically including panels about diversity and gender representation. Manels are a problem in academic gatherings, Comic-Cons, and other large group events. A holdover of sexist stereotypes and gender-based privilege, manels perpetuate the sexist idea that men are the experts who deserve to be listened to by other, less important and knowledgeable people. At least, that’s what we’ve come to recognize over the past few decades thanks to feminist critique. However, let’s take the perspective of a few different participants at a hypothetical conference and examine their individual, subjective truths.
When the conference schedule is announced, we see that of the ten panel discussions announced, there are only two that contain women. Pamela, an expert on the neurobiology of child abuse, thinks that this is unfair and as she was excluded from a panel on her specialty. Marco, an event organizer, feels that since the organizers simply went with who was most qualified to speak and did not consider gender, the results could not be sexist. Dionne, a professor who specializes in queer theory and indigenous social work, agrees with Pamela that manels are sexist but also feels that the focus on gender excludes and overlooks the problems with race, disability, sexual and gender identity, and social class among the conference panel members. Given these differing interpretations, how can we come to know what is true about this situation?
Honestly, there are a lot of truths here, not just one truth. Clearly, Pamela’s truth is that manels are sexist. Marco’s truth is that they are not necessarily sexist, as long as they were chosen in a sex-blind manner. While none of these statements is objectively true—a single truth for everyone, in all possible circumstances—they are subjectively true to the people who thought them up. Subjective truth consists of the the different meanings, understandings, and interpretations created by people and communicated throughout society. The communication of ideas is important, as it is how people come to a consensus on how to interpret a situation, negotiating the meaning of events, and informing how people act. Thus, as feminist critiques of society become more accepted, people will behave in less sexist ways. From a subjective perspective, there is no magical number of female panelists conferences much reach to be sufficiently non-sexist. Instead, we should investigate using language how people interpret the gender issues at the event, analyzing them within a historical and cultural context. But how do we find truth when everyone had their own unique interpretation? By finding patterns.
Science means finding patterns in data
Regardless of whether you are seeking objective truth or subjective truths, research and scientific inquiry aim to find and explain patterns. Most of the time, a pattern will not explain every single person’s experience, a fact about social science that is both fascinating and frustrating. Even individuals who do not know each other and do not coordinate in any deliberate way can create patterns that persist over time. Those new to social science may find these patterns frustrating because they may believe that the patterns that describe their gender, age, or some other facet of their lives don’t really represent their experience. It’s true. A pattern can exist among your cohort without your individual participation in it. There is diversity within diversity.
Let’s consider some specific examples. One area that social workers commonly investigate is the impact of a person’s social class background on their experiences and lot in life. You probably wouldn’t be surprised to learn that a person’s social class background has an impact on their educational attainment and achievement. In fact, one group of researchers [1] in the early 1990s found that the percentage of children who did not receive any postsecondary schooling was four times greater among those in the lowest quartile (25%) income bracket than those in the upper quartile of income earners (i.e., children from high- income families were far more likely than low-income children to go on to college). Another recent study found that having more liquid wealth that can be easily converted into cash actually seems to predict children’s math and reading achievement (Elliott, Jung, Kim, & Chowa, 2010). [2]
These findings—that wealth and income shape a child’s educational experiences—are probably not that shocking to any of us. Yet, some of us may know someone who may be an exception to the rule. Sometimes the patterns that social scientists observe fit our commonly held beliefs about the way the world works. When this happens, we don’t tend to take issue with the fact that patterns don’t necessarily represent all people’s experiences. But what happens when the patterns disrupt our assumptions?
For example, did you know that teachers are far more likely to encourage boys to think critically in school by asking them to expand on answers they give in class and by commenting on boys’ remarks and observations? When girls speak up in class, teachers are more likely to simply nod and move on. The pattern of teachers engaging in more complex interactions with boys means that boys and girls do not receive the same educational experience in school (Sadker & Sadker, 1994). [3] You and your classmates, of all genders, may find this news upsetting.
People who object to these findings tend to cite evidence from their own personal experience, refuting that the pattern actually exists. However, the problem with this response is that objecting to a social pattern on the grounds that it doesn’t match one’s individual experience misses the point about patterns. Patterns don’t perfectly predict what will happen to an individual person. Yet, they are a reasonable guide that, when systematically observed, can help guide social work thought and action.
A final note on qualitative and quantitative methods
There is no one superior way to find patterns that help us understand the world. As we will learn about in Chapter 6, there are multiple philosophical, theoretical, and methodological ways to approach uncovering scientific truths. Qualitative methods aim to provide an in-depth understanding of a relatively small number of cases. Quantitative methods offer less depth on each case but can say more about broad patterns in society because they typically focus on a much larger number of cases. A researcher should approach the process of scientific inquiry by formulating a clear research question and conducting research using the methodological tools best suited to that question.
Believe it or not, there are still significant methodological battles being waged in the academic literature on objective vs. subjective social science. Usually, quantitative methods are viewed as “more scientific” and qualitative methods are viewed as “less scientific.” Part of this battle is historical. As the social sciences developed, they were compared with the natural sciences, especially physics, which rely on mathematics and statistics to find truth. It is a hotly debated topic whether social science should adopt the philosophical assumptions of the natural sciences—with its emphasis on prediction, mathematics, and objectivity—or use a different set of tools—understanding, language, and subjectivity—to find scientific truth.
You are fortunate to be in a profession that values multiple scientific ways of knowing. The qualitative/quantitative debate is fueled by researchers who may prefer one approach over another, either because their own research questions are better suited to one particular approach or because they happened to have been trained in one specific method. In this textbook, we’ll operate from the perspective that qualitative and quantitative methods are complementary rather than competing. While these two methodological approaches certainly differ, the main point is that they simply have different goals, strengths, and weaknesses. A social work researcher should choose the methods that best match with the question they are asking.
Key Takeaways
• Social work is informed by science.
• Social science is concerns with both objective and subjective knowledge.
• Social science research aims to understand patterns in the social world.
• Social scientists use both qualitative and quantitative methods. While different, these methods are often complementary.
Glossary
• Epistemology- a set of assumptions about how we come to know what is real and true
• Objective truth- a single truth, observed without bias, that is universally applicable
• Ontology- a set of assumptions about what is real
• Qualitative methods- examine words or other media to understand their meaning
• Quantitative methods- examine numerical data to precisely describe and predict elements of the social world
• Science- a particular way of knowing that attempts to systematically collect and categorize facts or truth
• Subjective truth- one truth among many, bound within a social and cultural context
Image Attributions
Science and Technology by Petr Kratochvil CC-0
Abstract art blur bright by Pixabay CC-0
1. (Ellwood & Kane, 2000) Ellwood, D., & Kane, T. (2000). Who gets a college education? Family background and growing gaps in enrollment. In S. Danziger & J. Waldfogel (Eds.), Securing thefuture (p. 283–324). New York, NY: Russell Sage Foundation. ↵
2. Elliott, W., Jung, H., Kim, K., & Chowa, G. (2010). A multi-group structural equation model (SEM) examining asset holding effects on educational attainment by race and gender. Journal of Children & Poverty, 16, 91–121. ↵
3. Sadker, M., & Sadker, D. (1994). Failing at fairness: How America’s schools cheat girls. New York, NY: Maxwell Macmillan International. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/01%3A_Introduction_to_Research/1.02%3A_Science_and_social_work.txt |
Learning Objectives
• Describe and discuss four important reasons why students should care about social scientific research methods
• Identify how social workers use research as part of evidence-based practice
At this point, you may be wondering about the relevance of research methods to your life. Whether or not you choose to become a social worker, you should care about research methods for two basic reasons: (1) research methods are regularly applied to solve social problems and issues that shape how our society is organized, thus you have to live with the results of research methods every day of your life, and (2) understanding research methods will help you evaluate the effectiveness of social work interventions, an important skill for future employment.
Consuming research and living with its results
Another New Yorker cartoon depicts two men chatting with each other at a bar. One is saying to the other, “Are you just pissing and moaning, or can you verify what you’re saying with data?” (https://condenaststore.com/featured/are-you-just-pissing-and-moaning-edward-koren.html). Which would you rather be, just a complainer or someone who can actually verify what you’re saying? Understanding research methods and how they work can help position you to actually do more than just complain. Further, whether you know it or not, research probably has some impact on your life each and every day. Many of our laws, social policies, and court proceedings are grounded in some degree of empirical research and evidence (Jenkins & Kroll-Smith, 1996). [1] That’s not to say that all laws and social policies are good or make sense. However, you can’t have an informed opinion about any of them without understanding where they come from, how they were formed, and what their evidence base is. All social workers, from micro to macro, need to understand the root causes and policy solutions to social problems that their clients are experiencing.
A recent lawsuit against Walmart provides an example of social science research in action. A sociologist named Professor William Bielby was enlisted by plaintiffs in the suit to conduct an analysis of Walmart’s personnel policies in order to support their claim that Walmart engages in gender discriminatory practices. Bielby’s analysis shows that Walmart’s compensation and promotion decisions may indeed have been vulnerable to gender bias. In June 2011, the United States Supreme Court decided against allowing the case to proceed as a class-action lawsuit (Wal-Mart Stores, Inc. v. Dukes, 2011). [2] While a class-action suit was not pursued in this case, consider the impact that such a suit against one of our nation’s largest employers could have on companies and their employees around the country and perhaps even on your individual experience as a consumer. [3]
In addition to having to live with laws and policies that have been crafted based on social science research, you are also a consumer of all kinds of research, and understanding methods can help you be a smarter consumer. Ever notice the magazine headlines that peer out at you while you are waiting in line to pay for your groceries? They are geared toward piquing your interest and making you believe that you will learn a great deal if you follow the advice in a particular article. However, since you would have no way of knowing whether the magazine’s editors had gathered their data from a representative sample of people like you and your friends, you would have no reason to believe that the advice would be worthwhile. By having some understanding of research methods, you can avoid wasting your money by buying the magazine and wasting your time by following inappropriate advice.
Pick up or log on to the website for just about any magazine or newspaper, or turn on just about any news broadcast, and chances are you’ll hear something about some new and exciting research results. Understanding research methods will help you read past any hype and ask good questions about what you see and hear. In other words, research methods can help you become a more responsible consumer of public and popular information. And who wouldn’t want to be more responsible?
Evidence-based practice
Probably the most asked questions, though seldom asked directly, are “Why am I in this class?” or “When will I ever use this information?“ While it may seem strange, the answer is “pretty often.” Social work supervisors and administrators at agency-based settings will likely have to demonstrate that their agency’s programs are effective at achieving their goals. Most private and public grants will require evidence of effectiveness in order to continue receiving money and keep the programs running. Social workers at community-based organization commonly use research methods to target their interventions to the needs of their service area. Clinical social workers must also make sure that the interventions they use in practice are effective and not harmful to clients. Social workers may also want to track client progress on goals, help clients gather data about their clinical issues, or use data to advocate for change. All social workers in all practice situations must also remain current on the scientific literature to ensure competent and ethical practice.
In all of these cases, a social worker needs to be able to understand and evaluate scientific information. Evidence-based practice (EBP) for social workers involves making decisions on how to help clients based on the best available evidence. A social worker must examine the literature, understanding both the theory and evidence relevant to the practice situation. According to Rubin and Babbie (2017), [4] EBP also involves understanding client characteristics, using practice wisdom and existing resources, and adapting to environmental context. It is not simply “doing what the literature says,” but rather a process by which practitioners examine the literature, client, self, and context to inform interventions with clients and systems. As we discussed in Section 1.2, the patterns discovered by scientific research are not perfectly applicable to all situations. Instead, we rely on the critical thinking of social workers to apply scientific knowledge to real-world situations.
Let’s consider an example of a social work administrator at a children’s mental health agency. The agency uses private grant funds to fund a program that provides low-income children with bicycles, teaches the children how to repair and care for their bicycles, and leads group bicycle outings after school. Physical activity has been shown to improve mental health outcomes in scientific studies, but is this social worker’s program improving mental health in their clients? Ethically, the social worker should make sure that the program is achieving its goals. If the program is not beneficial, the resources should be spent on more effective programs. Practically, the social worker will also need to demonstrate to the agency’s funders that bicycling truly helps children deal with their mental health concerns.
The example above demonstrates the need for social workers to engage in evaluation research or research that evaluates the outcomes of a policy or program. She will choose from many acceptable ways to investigate program effectiveness, and those choices are based on the principles of scientific inquiry you will learn in this textbook. As the example above mentions, evaluation research is baked into how nonprofit human service agencies are funded. Government and private grants need to make sure their money is being spent wisely. If your program does not work, then the money should go to a program that has been shown to be effective or a new program that may be effective. Just because a program has the right goal doesn’t mean it will actually accomplish that goal. Grant reporting is an important part of agency-based social work practice. Agencies, in a very important sense, help us discover what approaches actually help clients.
In addition to engaging in evaluation research to satisfy the requirements of a grant, your agency may engage in evaluation research for the purposes of validating a new approach to treatment. Innovation in social work is incredibly important. Sam Tsemberis relates an “aha” moment from his practice in this Ted talk on homelessness (https://youtu.be/HsFHV-McdPo). A faculty member at the New York University School of Medicine, he noticed a problem with people cycling in and out of the local psychiatric hospital wards. Clients would arrive in psychiatric crisis, stabilize under medical supervision in the hospital, and end up back at the hospital back in psychiatric crisis shortly after discharge. When he asked the clients what their issues were, they said they were unable to participate in homelessness programs because they were not always compliant with medication for their mental health diagnosis and they continued to use drugs and alcohol. Collaboratively, the problem facing these clients was defined as a homelessness service system that was unable to meet clients where they were. Clients who were unwilling to remain completely abstinent from drugs and alcohol or who did not want to take psychiatric medications were simply cycling in and out of psychiatric crisis, moving from the hospital to the street and back to the hospital.
The solution that Sam Tsemberis implemented and popularized was called Housing First, and it is an approach to homelessness prevention that starts by, you guessed it, providing people with housing first. Similar to an approach to child and family homelessness created by Tanya Tull, Tsemberis created a model of addressing chronic homelessness with people with co-occurring disorders (substance abuse and mental illness). The Housing First model holds that housing is a human right, one that should not be denied based on substance use or mental health diagnosis. Clients are given housing as soon as possible. The Housing First agency provides wraparound treatment from an interdisciplinary team, including social workers, nurses, psychiatrists, and former clients who are in recovery. Over the past few decades, this program has gone from one program in New York City to the program of choice for federal, state, and local governments seeking to address homelessness in their communities.
The main idea behind Housing First is that once clients have an apartment of their own, they are better able to engage in mental health and substance abuse treatment. While this approach may seem logical to you, it is backwards from the traditional homelessness treatment model. The traditional approach began with the client stopping drug and alcohol use and taking prescribed medication. Only after clients achieved these goals were they offered group housing. If the client remained sober and medication compliant, they could then graduate towards less restrictive individual housing.
Evaluation research helps practitioners establish that their innovation is better than the alternatives and should be implemented more broadly. By comparing clients who were served through Housing First and traditional treatment, Tsemberis could establish that Housing First was more effective at keeping people housed and progressing on mental health and substance abuse goals. Starting first with smaller studies and graduating to much larger ones, Housing First built a reputation as an effective approach to addressing homelessness. When President Bush created the Collaborative Initiative to Help End Chronic Homelessness in 2003, Housing First was used in a majority of the interventions and demonstrated its effectiveness on a national scale. In 2007, it was acknowledged as an evidence-based practice in the Substance Abuse and Mental Health Services Administration’s (SAMHSA) National Registry of Evidence-Based Programs and Policies (NREPP). [5]
I suggest browsing around the NREPP website (nrepp.samhsa.gov/landing.aspx) and looking for interventions on topics that interest you. Other sources of evidence-based practices include the Cochrane Reviews digital library (www.cochranelibrary.com/) and Campbell Collaboration (https://campbellcollaboration.org/). In the next few chapters, we will talk more about how to find literature about interventions in social work. The use of systematic reviews, meta-analyses, and randomized controlled trials are particularly important in this regard.
So why share the story of Housing First? Well, I want you think about what you hope to contribute to our knowledge on social work practice. What is your bright idea and how can it change the world? Practitioners innovate all the time, often incorporating those innovations into their agency’s approach and mission. Through the use of research methods, agency-based social workers can demonstrate to policymakers and other social workers that their innovations should be more widely used. Without this wellspring of new ideas, social services would not be able to adapt to the changing needs of clients. Social workers in agency-based practice may also participate in research projects happening at their agency. Partnerships between schools of social work and agencies are a common way of testing and implementing innovations in social work. Clinicians receive specialized training, clients receive additional services, agencies gain prestige, and researchers can study how an intervention works in the real world.
While you may not become a scientist in the sense of wearing a lab coat and using a microscope, social workers must understand science in order to engage in ethical practice. In this section, we reviewed many ways in which research is a part of social work practice, including:
• Determining the best intervention for a client or system
• Ensuring existing services are accomplishing their goals
• Satisfying requirements to receive funding from private agencies and government grants
• Testing a new idea and demonstrating that it should be more widely implemented
Key Takeaways
• Whether we know it or not, our everyday lives are shaped by social scientific research.
• Understanding research methods is important for competent and ethical social work practice.
• Understanding social science and research methods can help us become more astute and more responsible consumers of information.
• Knowledge about social scientific research methods is important for ethical practice, as it ensures interventions are based on evidence.
Glossary
• Evaluation research- research that evaluates the outcomes of a policy or program
• Evidence-based practice- making decisions on how to help clients based on the best available evidence
Image Attributions
A peer counselor with mother by US Department of Agriculture CC-BY-2.0
Homeless man in New York 2008 by JMSuarez CC-BY-2.0
1. Jenkins, P. J., & Kroll-Smith, S. (Eds.). (1996). Witnessing for sociology: Sociologists in court. Westport, CT: Praeger. ↵
2. Wal-MartStores, Inc. v. Dukes, 564 U.S. (2011); The American Sociological Association filed an amicus brief in support of what would be the class of individuals claiming gender discrimination. You can read the brief at http://asanet.org/images/press/docs/pdf/Amicus_Brief_Wal-Mart_vDukes_et_al.pdf. For other recent amicus briefs filed by the ASA, see [1]http://asanet.org/about/amicus_briefs.cfm. ↵
3. Want to know more about the suit against Walmart or about Bielby’s analysis for the case? Check out the following source: Hart, M., & Secunda, P. M. (2009). A matter of context: Social framework evidence in employment discrimination class actions. Fordham Law Review, 78, 37-70. (2009). A matter of context: Social framework evidence in employment discrimination class action. Fordham Law Review, 78, 37–70. Retrieved from: http://www.fordhamlawreview.org/assets/pdfs/Vol_78/Hart_Secunda_October_2009.pdf
4. Rubin, A., and Babbie, E. R. (2017). Research methods for social work (9th ed.). Belmont: Wadsworth. ↵
5. Substance Abuse and Mental Health Services Administration (2007). Pathways' housing first program. Retrieved from: nrepp.samhsa.gov/Legacy/ViewIntervention.aspx? id=365 ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/01%3A_Introduction_to_Research/1.03%3A_Why_should_we_care.txt |
Learning Objectives
• Describe common barriers to engaging with social work research
• Identify alternative ways to thinking about research methods
I’ve been teaching research methods for six years and have found many students struggle to see the connection between research and social work practice. Most students enjoy a social work theory class because they can better understand the world around them. Students also like practice because it shows them how to conduct clinical work with clients—i.e., what most social work students want to do. However, while I typically have a few students each year who are interested in becoming researchers, it’s not very common. For this reason, I want to end this chapter on a more personal note. Most student barriers to research come from the following beliefs:
Research is useless!
Students who tell me that research methods is not a useful class to them are saying something important. As a scholar (or student), your most valuable asset is your time. You give your time to the subjects you consider important to you and your future practice. Because most social workers don’t become researchers or practitioner-researchers, students feel like a research methods class is a waste of time.
Our discussion of evidence-based practice and the ways in which social workers use research methods in practice brought home the idea that social workers play an important role in creating new knowledge about social services. On a more immediate level, research methods will also help you become a stronger social work student. The next few chapters of this textbook will review how to search for literature on a topic and write a literature review. These skills are relevant in every classroom during your academic career. The rest of the textbook will help you understand the mechanics of research methods so you can better understand the content of those pesky journal articles your professors force you to cite in your papers.
Research is too hard!
Research methods involves a lot of terminology that is entirely new to social workers. Other domains of social work, such as practice, are easier to apply your intuition towards. You understand how to be an empathetic person, and your experiences in life can help guide you through a practice situation or even theoretical or conceptual question. Research may seem like a totally new area in which you have no previous experience. It can seem like a lot to learn. In addition to the normal memorization and application of terms, research methods also has wrong answers. There are certain combinations of methods that just don’t work together.
The fear is entirely understandable. Research is not straightforward. As Figure 1.1 shows, it is a process that is non-linear, involving multiple revisions, wrong turns, and dead ends before you figure out the best question and research approach. You may have to go back to chapters after having read them or even peek ahead at chapters your class hasn’t covered yet.
Figure 1.1 Research as a non-linear process
Moreover, research is something you learn by doing…and stumbling a few times. It’s an iterative process, or one that requires lots of tries to get right. There isn’t a shortcut for learning research, but hopefully your research methods class is one in which your research project is broken down into smaller parts and you get consistent feedback throughout the process. No one just knows research. It’s something you pick up by doing it, reflecting on the experiences and results, redoing your work, and revising it in consultation with your professor.
Research is boring!
We’ve talked already about the arcane research terminology, so I won’t go into it again here. But research methods is sometimes seen as a boring topic by many students. Practice knowledge and even theory are fun to learn because they are easy to apply and give you insight into the world around you. Research just seems like its own weird, remote thing.
I completely understand where this perspective comes from and hope there are a few things you will take away from this course that aren’t boring to you. In the first section of this textbook, you will learn how to take any topic and learn what is known about it. It may seem trivial, but it is actually a superpower. Your social work education will present some generalist material, which is applicable to nearly all social work practice situations, and some applied material, which is applicable to specific social work practice situations. However, no education will provide you with everything you need to know. And certainly, no education will tell you what will be discovered over the next few decades of your practice. Our work on literature reviews in the next few chapters will help you in becoming a strong social work student and practitioner. Following that, our exploration of research methods will help you further understand how the theories, practice models, and techniques you learn in your other classes are created and tested scientifically.
Get out of your own way
Together, the beliefs of “research is useless, boring, and hard” can create a self-fulfilling prophecy for students. If you believe research is boring, you won’t find it interesting. If you believe research is hard, you will struggle more with assignments. If you believe research is useless, you won’t see its utility. While I certainly acknowledge that students aren’t going to love research as much as I do (it’s a career for me, so I like it a lot!), I suggest reframing how you think about research using these touchstones:
• All social workers rely on social science research to engage in competent practice.
• No one already knows research. It’s something I’ll learn through practice. And it’s challenging for everyone.
• Research is relevant to me because it allows me to figure out what is known about any topic I want to study.
• If the topic I choose to study is important to me, I will be more interested in research.
Structure of this textbook
While you may not have chosen this course, by reframing your approach to it, you increase the likelihood of getting a lot out of it. To that end, here is the structure of this book:
In Chapters 2-4, we’ll review how to begin a research project. This involves searching for relevant literature, academic journal articles specifically, and synthesizing what they say about your topic into a literature review.
In Chapters 5-9, you’ll learn about how research informs and tests theory. We’ll discuss how to conduct research in an ethical manner, create research questions, and measure concepts in the social world.
Chapters 10-14 will describe how to conduct research, whether it’s a quantitative survey or experiment, or alternately, a qualitative interview or focus group. We’ll also review how to analyze data that someone else has already collected.
Finally, Chapters 15 and 16 will review the types of research most commonly used in social work practice, including evaluation research and action research, and how to report the results of your research to various audiences.
Key Takeaways
• Anxiety about research methods is a common experience for students.
• Research methods will help you become a better scholar and practitioner.
1. Untitled image created by Ohio State University Libraries (n.d.) Retrieved from: https://ohiostate.pressbooks.pub/choosingsources/front-matter/introduction/. Shared under a CC-BY 4.0 license. https://creativecommons.org/licenses/by/4.0/ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/01%3A_Introduction_to_Research/1.04%3A_Understanding_research.txt |
Research methods is my favorite course to teach. It is somewhat less popular with students, but I’m working on that issue. Part of the excitement of teaching this class comes from the uniquely open framework—students get to design a research study about a topic that interests them. By reading my students’ papers every semester, I learn about a wide range of topics relevant to social work that I otherwise would not have known about. But what topic should you choose?
This chapter discusses or mentions the following topics: racism and hate groups, police violence, substance abuse, and mental health.
02: Beginning a Research Project
Learning Objectives
• Find a topic to investigate
• Create a working question
Choosing a social work research topic
According to the Action Network for Social Work Education and Research (Answer), social work research is conducted to benefit “consumers, practitioners, policymakers, educators, and the general public through the examination of societal issues” (Answer, n.d., para. 2). [1] Common social issues that are studied include “health care, substance abuse, community violence, family issues, child welfare, aging, well-being and resiliency, and the strengths and needs of underserved populations” (Answer, n.d., para. 2). This list is certainly not exhaustive. Social workers may study any area that impacts their practice. However, the unifying feature of social work research is its focus on promoting the wellbeing of target populations.
But as undergraduate social work students, you are likely not yet practicing social work. How do you identify researchable topics then? Part of the joy in being a social work student is figuring out what areas of social work are appealing to you. Perhaps there are certain theories that speak to you, based on your values or experiences. Perhaps there are social issues you wish to change. Perhaps there are certain groups of people you want to help. Perhaps there are clinical interventions that interest you. Any one of these is a good place to start. At the beginning of a research project, your main focus should be finding a social work topic that is interesting enough to spend a semester reading and writing about it.
A good topic selection plan begins with a general orientation into the subject you are interested in pursuing in more depth. Here are some suggestions when choosing a topic area:
• Pick an area of interest, pick an area of experience, or pick an area where you know there is a need for more research.
• It may be easier to start with “what” and “why” questions and expand on those. For example, what are the best methods of treating severe depression? Or why are people receiving SNAP more likely to be obese?
• If you already have practice experience in social work through employment, an internship, or volunteer work, think about practice issues you noticed in the placement.
• Ask a professor, preferably one active in research, about possible topics.
• Read departmental information on research interests of the faculty. Faculty research interests vary widely, and it might surprise you what they’ve published on in the past. Most departmental websites post the curriculum vitae, or CV, of faculty which lists their publications, credentials, and interests.
• Read a research paper that interests you. The paper’s literature review or background section will provide insight into the research question the author was seeking to address with their study. Is the research incomplete, imprecise, biased, or inconsistent? As you’re reading the paper, look for what’s missing. These may be “gaps in the literature” that you might explore in your own study. The conclusion or discussion section at the end may also offer some questions for future exploration. A recent blog posting in Science (Pain, 2016) [2] provides several tips from researchers and graduate students on how to effectively read these papers.
• Think about papers you enjoyed researching and writing in other classes. Research is a unique class and will use the tools of social science for you to think more in depth about a topic. It will bring a new perspective that will deepen your knowledge of the topic.
• Identify and browse journals related to your research interests. Faculty and librarians can help you identify relevant journals in your field and specific areas of interest.
How do you feel about your topic?
Perhaps you have started with a specific population in mind—for example, youth who identify as LGBTQ or visitors to a local health clinic. In other cases, you may start with a social problem, such as gang violence, or social policy or program, such as zero-tolerance policies in schools. Alternately, maybe there are interventions like dialectical behavioral therapy or applied behavior analysis about which you would like to learn more. Your motivation for choosing a topic does not have to be objective. Because social work is a values-based profession, social work researchers often find themselves motivated to conduct research that furthers social justice or fights oppression. Just because you think a policy is wrong or a group is being marginalized, for example, does not mean that your research will be biased. It means you must understand how you feel, why you feel that way, and what would cause you to feel differently about your topic.
Start by asking yourself how you feel about your topic. Be totally honest, and ask yourself whether you believe your perspective is the only valid one. Perhaps yours isn’t the only perspective, but do you believe it is the wisest one? The most practical one? How do you feel about other perspectives on this topic? If you feel so strongly that certain findings would upset you or that either you would design a project to get only the answer you believe to be the best one or you might feel compelled to cover up findings that you don’t like, then you need to choose a different topic. For example, a researcher may want to find out whether there is any relationship between intelligence and political party affiliation—certain that members of her party are without a doubt the most intelligent. Her strong opinion would not be a problem by itself. However, if she feels rage when considering the possibility that the opposing party’s members are more intelligent than those of her party, the topic is probably too near and dear for her to use it to conduct unbiased research.
Of course, just because you feel strongly about a topic does not mean that you should not study it. Sometimes the best topics to research are those about which you do feel strongly. What better way to stay motivated than to study something that you care about? You must be able to accept that people will have a different perspective than you do, and try to represent their viewpoints fairly in your research. If you feel prepared to accept all findings, even those that may be unflattering to or distinct from your personal perspective, then perhaps you should intentionally study a topic about which you have strong feelings.
Kathleen Blee (2002) [3] has taken this route in her research. Blee studies hate movement participants, people whose racist ideologies she studies but does not share. You can read her accounts of this research in two of her most well-known publications, Inside Organized Racism and Women of the Klan. Blee’s research is successful because she was willing to report her findings and observations honestly, even those about which she may have strong feelings. Unlike Blee, if you think about it and conclude that you cannot accept or share with others findings with which you disagree, then you should study a different topic. Knowing your own hot-button issues is an important part of self-knowledge and reflection in social work.
Social workers often use personal experience as a starting point for what topics are interesting to cover. As we’ve discussed here, personal experience can be a powerful motivator to study a topic in detail. However, social work researchers should be mindful of their own mental health during the research process. A social worker who has experienced a mental health crisis or traumatic event should approach researching related topics cautiously. There is no need to retraumatize yourself or jeopardize your mental health for a research paper. For example, a student who has just experienced domestic violence may want to know about Eye Movement Desensitization and Reprocessing (EMDR) therapy. While the student might gain some knowledge about potential treatments for domestic violence, they will likely have to read through many stories and reports about domestic violence. Unless the student’s trauma has been processed in therapy, conducting a research project on this topic may negatively impact the student’s mental health. Nevertheless, she will acquire skills in research methods that will help her understand the EMDR literature and whether to begin treatment in that modality.
Whether you feel strongly about your topic or not, you will also want to consider what you already known about it. There are many ways we know what we know. Perhaps your mother told you something is so. Perhaps it came to you in a dream. Perhaps you took a class last semester and learned something about your topic there. Or you may have read something about your topic in your local newspaper or in People magazine. We discussed the strengths and weaknesses associated with some of these different sources of knowledge in Chapter 1, and we’ll talk about other sources of knowledge, such as prior research in the next few sections. For now, take some time to think about what you know about your topic from all possible sources. Thinking about what you already know will help you identify any biases you may have, and it will help as you begin to frame a question about your topic.
What do you want to know?
Once you have a topic, begin to think about it in terms of a question. What do you really want to know about the topic? As a warm-up exercise, try dropping a possible topic idea into one of the blank spaces below. The questions may help bring your subject into sharper focus and provide you with the first important steps towards developing your topic.
1. What does ___ mean? (Definition)
2. What are the various features of ___? (Description)
3. What are the component parts of ___? (Simple analysis)
4. How is ___ made or done? (Process analysis)
5. How should ___ be made or done? (Directional analysis)
6. What is the essential function of ___? (Functional analysis)
7. What are the causes of ___? (Causal analysis)
8. What are the consequences of ___? (Causal analysis)
9. What are the types of ___? (Classification)
10. How is ___ like or unlike ___? (Comparison)
11. What is the present status of ___? (Comparison)
12. What is the significance of ___? (Interpretation)
13. What are the facts about ___? (Reportage)
14. How did ___ happen? (Narration)
15. What kind of person is ___? (Characterization/Profile)
16. What is the value of ___? (Evaluation)
17. What are the essential major points or features of ___? (Summary)
18. What case can be made for or against ___? (Persuasion)
19. What is the relationship between _____ and the outcome of ____? (Explorative)
Take a minute right now and write down a question you want to answer. Even if it doesn’t seem perfect, everyone needs a place to start. Make sure your research topic is relevant to social work. You’d be surprised how much of the world that encompasses. It’s not just research on mental health treatment or child welfare services. Social workers can study things like the pollution of irrigation systems and entrepreneurship in women, among infinite other topics. The only requirement is your research must inform action to fight social problems faced by target populations.
Your question is only a starting place, as research is an iterativeprocess, one that subject to constant revision. As we progress in this textbook, you’ll learn how to refine your question and include the necessary components for proper qualitative and quantitative research questions. Your question will also likely change as you engage with the literature on your topic. You will learn new and important concepts that may shift your focus or clarify your original ideas. Trust that a strong question will emerge from this process.
Key Takeaways
• Many researchers choose topics by considering their own personal experiences, knowledge, and interests.
• Researchers should be aware of and forthcoming about any strong feelings they might have about their research topics.
• There are benefits and drawbacks associated with studying a topic about which you already have some prior knowledge or experience. Researchers should be aware of and consider both.
• Writing a question down will help guide your inquiry.
Image Attributions
Transportation/Traffic by Max Pixel CC-0
Justice by Geralt CC-0
Question by Max Pixel CC-0
1. Action Network for Social Work Education and Research (n.d.). Advocacy. Retrieved from: www.socialworkers.org/Advocacy/answer↵
2. Pain, E. (2016, March 21). How to (seriously) read a scientific paper. Science. Retrieved from: http://www.sciencemag.org/careers/2016/03/how-seriously-read-scientific-paper
3. Blee, K. (2002). Inside organized racism: Women and men of the hate movement. Berkeley, CA: University of California Press; Blee, K. (1991). Women of the Klan: Racism and gender in the 1920s. Berkeley, CA: University of California Press. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/02%3A_Beginning_a_Research_Project/2.01%3A_Getting_started.txt |
Learning Objectives
• Explain how information is created and how it evolves over time
• Select appropriate sources for your inquiry
• Describe the strengths and limitations of each type of source
Because a literature review is a summary and analysis of the relevant publications on a topic, we first have to understand what is meant by “the literature.” In this case, “the literature” is a collection of all of the relevant written sources on a topic.
Disciplines of knowledge
When drawing boundaries around an idea, topic, or subject area, it helps to think about how and where the information for the field is produced. For this, you need to identify the disciplines of knowledge production in a subject area.
Information does not exist in the environment like some kind of raw material. It is produced by individuals working within a particular field of knowledge who use specific methods for generating new information. Disciplines consume, produce, and disseminate knowledge. Looking through a university’s course catalog gives clues to disciplinary structure. Fields such as political science, biology, history, and mathematics are unique disciplines, as is social work, with its own logic for how and where new knowledge is introduced and made accessible.
You will need to become comfortable with identifying the disciplines that might contribute information to any search. When you do this, you will also learn how to decode the way how people talk about a topic within a discipline. This will be useful to you when you begin a review of the literature in your area of study.
For example, think about the disciplines that might contribute information to a topic such as the role of sports in society. Try to anticipate the type of perspective each discipline might have on the topic. Consider the following types of questions as you examine what different disciplines might contribute:
• What is important about the topic to the people in that discipline?
• What is most likely to be the focus of their study about the topic?
• What perspective would they be likely to have on the topic?
In this example, we identify two disciplines that have something to say about the role of sports in society: the human service professions of nursing and social work. What would each of these disciplines raise as key questions or issues related to that topic? A nursing researcher might study how sports affect individuals’ health and well-being, how to assess and treat sports injuries, or the physical conditioning required for athletics. A social work researcher might study how schools privilege or punish student athletes, how athletics impact social relationships and hierarchies, or the differences between boys’ and girls’ participation in organized sports. In this example, we see that a single topic can be approached from many different perspectives depending on how the disciplinary boundaries are drawn and how the topic is framed. Nevertheless, it is useful for a social worker to be aware of the nursing literature, as they could better appreciate the physical toll that sports take on athletes’ bodies and how that may interact with other issues. An interdisciplinary perspective is usually a more comprehensive perspective.
Types of sources
“The literature” consists of the published works that document a scholarly conversation on a specific topic within and between disciplines. You will find in “the literature” documents that explain the background of your topic. You will also find controversies and unresolved questions that can inspire your own project. By now in your social work academic career, you’ve probably heard that you need to get “peer-reviewed journal articles.” But what are those exactly? How do they differ from news articles or encyclopedias? That is the focus of this section of the text—the different types of literature.
First, let’s discuss periodicals. Periodicals include journals, trade publications, magazines, and newspapers. While they may appear similar, particularly online, each of these periodicals has unique features designed for a specific purpose. Magazine and newspaper articles are usually written by journalists, are intended to be short and understandable for the average adult, contain color images and advertisements, and are designed as commodities sold to an audience. Magazines may contain primary or secondary literature depending on the article in question. The New Social Worker is an excellent magazine for social workers. An article that is a primarysource would gather information as an event happened, like an interview with a victim of a local fire, or relate original research done by the journalists, like the Guardian newspaper’s The Counted webpage which tracks how many people were killed by police officers in the United States. [1]
Is it okay to use a magazine or newspaper as a source in your research methods class? If you were in my class, the answer is “probably not.” There are some exceptions like the Guardian page mentioned above or breaking news about a policy or community, but most of what newspapers and magazines publish is secondary literature. Secondarysources interpret, discuss, and summarize primary sources. Often, news articles will summarize a study done in an academic journal. Your job in this course is to read the original source of the information, in this case, the academic journal article itself. Journalists are not scientists. If you have seen articles about how chocolate cures cancer or how drinking whiskey can extend your life, you should understand how journalists can exaggerate or misinterpret results. Careful scholars will critically examine the primary source, rather than relying on someone else’s summary. Many newspapers and magazines also contain opinion articles, which are even less reputable as the author will choose facts to support their viewpoint and exclude facts that contract their viewpoint. Nevertheless, newspaper and magazine articles are excellent places to start your journey into the literature, as they do not require specialized knowledge to understand and may inspire deeper inquiry.
Unlike magazines and newspapers, trade publications may take some specialized knowledge to understand. Trade publications or trade journals are periodicals directed to members of a specific profession. They often have information about industry trends and practical information for people working in the field. Because of this trade publications are somewhat more reputable than newspapers or magazines, as the authors are specialists on their field. NASW News is a good example a trade publication in social work, published by the National Association of Social Workers. Its intended audience is social work practitioners who want to know about important practice issues. They report news and trends in a field but not scholarly research. They may also provide product or service reviews, job listings, and advertisements.
So, can you use trade publications in a formal research proposal? Again, if you’re in my class, the answer would be “probably not.” A main shortcoming trade publication is the lack of peer review. Peer review refers to a formal process in which other esteemed researchers and experts ensure your work meets the standards and expectations of the professional field. While trade publications do contain a staff of editors, the level of review is not as stringent as academic journal articles. On the other hand, if you are doing a study about practitioners, then trade publications may be quite relevant sources for your proposal. Peer review is part of the cycle of publication illustrated below and acts as a gatekeeper, ensuring that only top-quality articles are published. While peer review is far from perfect, the process provides for stricter scrutiny of scientific publications.
In summary, newspapers and other popular press publications are useful for getting general topic ideas. Trade publications are useful for practical application in a profession and may also be a good source of keywords for future searching. Scholarly journals are the conversation of the scholars who are doing research in a specific discipline and publishing their research findings.
Types of journal articles
As you’ve probably heard by now, academic journal articles are considered to be the most reputable sources of information, particularly in research methods courses. Journal articles are written by scholars with the intended audience of other scholars (like you!) interested in the subject matter. The articles are often long and contain extensive references for the arguments made by the author. The journals themselves are often dedicated to a single topic, like violence or child welfare, and include articles that seek to advance the body of knowledge about their chosen topic.
Most journals are peer-reviewed or refereed, which means a panel of scholars reviews articles to decide if they should be accepted into a specific publication. Scholarly journals provide articles of interest to experts or researchers in a discipline. An editorial board of respected scholars (peers) reviews all articles submitted to a journal. Editors and volunteer reviewers decide if the article provides a noteworthy contribution to the field and should be published. For this reason, journal articles are the main source of information for researchers and for literature reviews. You can tell whether a journal is peer reviewed by going to its website. Usually, under the “About Us” section, the website will list the editorial board or otherwise note its procedures for peer review. If a journal does not provide such information, you may have found a “predatory journal.” These journals will publish any article—no matter how bad it is—as long as the author pays them. Not all journals are created equal!
A kind of peer review also occurs after publication. Scientists regularly read articles and use them to inform their research. A seminal article is “a classic work of research literature that is more than 5 years old and is marked by its uniqueness and contribution to professional knowledge” (Houser, 2018, p. 112). [2] Basically, it is a really important article. Seminal articles are cited a lot in the literature. You can see how many authors have cited an article using Google Scholar’s citation count feature when you search for the article. Generally speaking, articles that have been cited more often are considered more reputable. There is nothing wrong with citing an article with a low citation count, but it is an indication that not many other scholars have found the source to be useful or important.
Journal articles fall into a few different categories. Empiricalarticles apply theory to a behavior and reports the results of a quantitative or qualitative data analysis conducted by the author. Just because an article includes quantitative or qualitative results does not mean it is an empirical journal article. Since most articles contain a literature review with empirical findings, you need to make sure the finds reported in the study are from the author’s own analysis. Fortunately, empirical articles follow a similar structure—introduction, method, results, and discussion sections appear in that order. While the exact headings may differ slightly from publication to publication and other sections like conclusions, implications, or limitations may appear, this general structure applies to nearly all empirical journal articles.
Theoretical articles, by contrast, do not follow a set structure. They follow whatever format the author finds most useful to organize their information. Theoretical articles discuss a theory, conceptual model, or framework for understanding a problem. They may delve into philosophy or values, as well. Theoretical articles help you understand how to think about a topic and may help you make sense of the results of empirical studies. Practicalarticles describe “how things are done” (Wallace & Wray, 2016, p. 20). [3] They are usually shorter than other types of articles and are intended to inform practitioners of a discipline on current issues. They may also provide a reflection on a “hot topic” in the practice domain, a complex client situation, or an issue that may affect the profession as a whole.
No one type of article is better than the other, as each serves a different purpose. Seminal articles relevant to your topic area are important to read because of their influence on the field. Theoretical articles will help you understand the social theory behind your topic. Empirical articles should test those theories quantitatively or create those theories qualitatively, a process we will discuss in greater detail later in this book. Practical articles will help you understand a practitioner’s perspective, though these are less useful when writing a literature review as they only present a single person’s opinions on a topic.
Other sources of information
As I mentioned previously, newspaper and magazine articles are good places to start your search (though they should not be the end of your search!). Another source students go to almost immediately is Wikipedia. Wikipedia is a marvel of human knowledge. It is a digital encyclopedia to which anyone can contribute. The entries for each Wikipedia article are overseen by skilled and specialized editors who volunteer their time and knowledge to making sure their articles are correct and up to date. Wikipedia is an example of a tertiary source. We reviewed primary and secondary sources in the previous section. Tertiarysources synthesize or distill primary and secondary sources. Examples of tertiary sources include encyclopedias, directories, dictionaries, and textbooks like this one. Tertiary sources are an excellent place to start (but are not a good place to end your search). A student might consult Wikipedia or the Encyclopedia of Social Work (available at http://socialwork.oxfordre.com/) to get a general idea of the topic.
The difference between secondary and tertiary sources is not exact, and as we’ve discussed, using one or both at the beginning of a project is a good idea. As your study of the topic progresses, you will naturally have to transition away from secondary and tertiary sources and towards primary sources. We’ve already talked about one particular kind of primary source—the academic journal article. We will spend more time on this primary source than any other in this textbook. However, it is important to understand how other types of sources can be used as well.
Books contain important scholarly information. They are particularly helpful for theoretical, philosophical, and historical inquiry. For example, in my research on self-determination for individuals with intellectual and developmental disabilities, I needed to define and explore the concept of self-determination. I learned how to define it from the philosophical literature on self-determination and the advocacy literature contained in books. You can use books to learn definitions, key concepts, and keywords you can use to find additional sources. They will help you understand the scope and foundations of a topic and how it has changed over time. Some books contain chapters that look like academic journal articles. These are called edited volumes, and they contain articles that may not have made it into academic journals or seminal articles that are republished in the book. Edited volumes are considered less reputable than journal articles, as they do not have as strong of a peer review process. However, papers in social science journals will often include references to books and edited volumes.
Conferences are a great source of information. At conferences such as the Council on Social Work Education’s Annual Program Meeting or your state’s NASW conference, researchers present papers on their most recent research and obtain feedback from the audience. The papers presented at conferences are sometimes published in a volume called a conference proceeding. Conference proceedings highlight current discussion in a discipline and can lead you to scholars who are interested in specific research areas. A word about conference papers: several factors contribute to making these documents difficult to find. It is not unusual that papers delivered at professional conferences are not published in print or electronic form, although an abstract may be available. In these cases, the full paper may only be available from the author or authors. The most important thing to remember is that if you have any difficulty finding a conference proceeding or paper, ask a librarian for assistance.
Another source of information is the gray literature, which is research and information released by non-commercial publishers, such as government agencies, policy organizations, and think-tanks. If you have already taken a policy class, perhaps you’ve come across the Center on Budget and Policy Priorities (https://www.cbpp.org/). CBPP is a think tank or a group of scholars that conduct research and perform advocacy on social issues. Similarly, students often find the Centers for Disease Control website helpful for understanding the prevalence of social problems like mental illness and child abuse. Think tanks and policy organizations often have a specific viewpoint they support. There are conservative, liberal, and libertarian think tanks, for example. Policy organizations may be funded by private businesses to push a given message to the public. Government agencies are generally more objective, though they may be less critical of government programs than other sources might be. The main shortcoming of gray literature is the lack of peer review that is found in academic journal articles, though many gray literature sources are of good quality.
Dissertations and theses can be rich sources of information and have extensive reference lists to scan for resources. They are considered gray literature because they are not peer reviewed. The accuracy and validity of the paper itself may depend on the school that awarded the doctoral or master’s degree to the author. Having completed a dissertation, they take a long time to write and a long time to read. If you come across a dissertation that is relevant, it is a good idea to read the literature review and plumb the sources the author uses in your literature search. However, the data analysis from these sources is considered less reputable as it has not passed through peer review yet. Consider searching for journal articles by the author to see if any of the results passed peer review. You will also be thankful that journal articles are much shorter than dissertations and theses!
The final source of information we must talk about is webpages. My graduate research focused on substance abuse and drugs, and I was fond of reading Drug War Rant (http://www.drugwarrant.com/), a blog about drug policy. It provided me with breaking news about drug policy and editorial opinion about the drug war. I would never cite the blog in a research proposal, but it was an excellent source of information that warranted further investigation. Webpages will also help you locate professional organizations and human service agencies that address your problem. Looking at their social media feeds, reports, publications, or “news” sections on an organization’s webpage can clue you into important topics to study. Because anyone can begin their own webpage, they are usually not considered scholarly sources to use in formal writing, but they are still useful when you are first learning about a topic. Additionally, many advocacy webpages will provide references for the facts they site, providing you with the primary source of the information.
As you think about each source, remember:
All information sources are not created equal. Sources can vary greatly in terms of how carefully they are researched, written, edited, and reviewed for accuracy. Common sense will help you identify obviously questionable sources, such as tabloids that feature tales of alien abductions, or personal websites with glaring typos. Sometimes, however, a source’s reliability—or lack of it—is not so obvious…You will consider criteria such as the type of source, its intended purpose and audience, the author’s (or authors’) qualifications, the publication’s reputation, any indications of bias or hidden agendas, how current the source is, and the overall quality of the writing, thinking, and design. (Writing for Success, 2015, p. 448). [4]
While each of these sources is an important part of how we learn about a topic, your research should focus on finding academic journal articles about your topic. These are the primary sources of the research world. While it may be acceptable and necessary to use other primary sources—like books, government reports, or an investigative article by a newspaper or magazine—academic journal articles are preferred. Finding these journal articles is the topic of the next section.
Key Takeaways
• Social work involves reading research from a variety of disciplines.
• While secondary and tertiary sources are okay to start with, primary sources provide the most accurate and authoritative information about a topic.
• Peer-reviewed journal articles are considered the best source of information for literature reviews, though other sources are often used.
• Peer review is the process by which other scholars evaluate the merits of an article before publication.
• Social work research requires critical evaluation of each source in a literature review
Glossary
• Empirical articles- apply theory to a behavior and reports the results of a quantitative or qualitative data analysis conducted by the author
• Gray literature- research and information released by non-commercial publishers, such as government agencies, policy organizations, and think-tanks
• Peer review- a formal process in which other esteemed researchers and experts ensure your work meets the standards and expectations of the professional field
• Practical articles- describe “how things are done” in practice (Wallace & Wray, 2016, p. 20)
• Primary source- published results of original research studies
• Secondary source- interpret, discuss, summarize original sources
• Seminal articles– classic work noted for its contribution to the field and high citation count
• Tertiary source- synthesize or distill primary and secondary sources, such as Wikipedia
• Theoretical articles – articles that discuss a theory, conceptual model or framework for understanding a problem
Image Attributions
Knowledge by geralt CC-0
Yahoo news portal by Simon CC-0
Research journals by M. Imran CC-0
Books door entrance culture by ninocare CC-0
1. The Guardian (n.d.). The counted: People killed by police in the US. Retrieved from: https://www.theguardian.com/us-news/ng-interactive/2015/jun/01/the-counted-police-killings-us-database
2. Houser, J., (2018). Nursing research reading, using, and creating evidence (4th ed.). Burlington, MA: Jones & Bartlett. ↵
3. Wallace, M., & Wray, A. (2016). Critical reading and writing for postgraduates (3rd ed.). Thousand Oaks, CA: Sage Publications. ↵
4. Writing for Success (2015). Strategies for gathering reliable information. http://open.lib.umn.edu/writingforsuccess/chapter/11-4-strategies-for-gathering-reliable-information/ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/02%3A_Beginning_a_Research_Project/2.02%3A_Sources_of_information.txt |
Learning Objectives
• Describe useful strategies to employ when searching for literature
• Identify how to narrow down search results to the most relevant sources
One of the drawbacks (or joys, depending on your perspective) of being a researcher in the 21st century is that we can do much of our work without ever leaving the comfort of our recliners. This is certainly true of familiarizing yourself with the literature. Most libraries offer incredible online search options and access to important databases of academic journal articles.
A literature search usually follows these steps:
1. Building search queries
2. Finding the right database
3. Skimming the abstracts of articles
4. Looking at authors and journal names
5. Examining references
6. Searching for meta-analyses and systematic reviews
Step 1: Building a search query with keywords
What do you type when you are searching for something on Google? Are you a question-asker? Do you type in full sentences or just a few keywords? What you type into a database or search engine like Google is called a query. Well-constructed queries get you to the information you need faster, while unclear queries will force you to sift through dozens of irrelevant articles before you find the ones you want.
The words you use in your search query will determine the results you get. Unfortunately, different studies often use different words to mean the same thing. A study may describe its topic as substance abuse, rather than addiction. Think of different keywords that are relevant to your topic area and write them down. Often in social work research, there is a bit of jargon to learn in crafting your search queries. If you wanted to learn more about people of low-income who do not have access to a bank account, you may need to learn the jargon term “unbanked,” which refers to people without bank accounts, and include “unbanked” in your search query. If you wanted to learn about children who take on parental roles in families, you may need to include “parentification” as part of your search query. As undergraduate researchers, you are not expected to know these terms ahead of time. Instead, start with the keywords you already know. Once you read more about your topic, start including new keywords that will return the most relevant search results for you.
Google is a “natural language” search engine, which means it tries to use its knowledge of how people to talk to better understand your query. Google’s academic database, Google Scholar, incorporates that same approach. However, other databases that are important for social work research—such as Academic Search Complete, PSYCinfo, and PubMed—will not return useful results if you ask a question or type a sentence or phrase as your search query. Instead, these databases are best used by typing in keywords. Instead of typing “the effects of cocaine addiction on the quality of parenting,” you might type in “cocaine AND parenting” or “addiction AND child development.” Note: you would not actually use the quotation marks in your search query for these examples.
These operators (AND, OR, NOT) are part of what is called Boolean searching. Boolean searching works like a simple computer program. Your search query is made up of words connected by operators. Searching for “cocaine AND parenting” returns articles that mention both cocaine and parenting. There are lots of articles on cocaine and lots of articles on parenting, but fewer articles on both of those topics. In this way, the AND operator reduces the number of results you will get from your search query because both terms must be present. The NOT operator also reduces the number of results you get from your query. For example, perhaps you wanted to exclude issues related to pregnancy. Searching for “cocaine AND parenting NOT pregnancy” would exclude articles that mentioned pregnancy from your results. Conversely, the OR operator would increase the number of results you get from your query. For example, searching for “cocaine OR parenting” would return not only articles that mentioned both words but also those that mentioned only one of your two search terms. This relationship is visualized in Figure 2.1 below.
As my students have said in the past, probably the most frustrating part about literature searching is looking at the number of search results for your query. How could anyone be expected to look at hundreds of thousands of articles on a topic? Don’t worry. You don’t have to read all those articles to know enough about your topic area to produce a good research study. A good search query should bring you to at least a few relevant articles to your topic, which is more than enough to get you started. However, an excellent search query can narrow down your results to a much smaller number of articles, all of which are specifically focused on your topic area. Here are some tips for reducing the number of articles in your topic area:
1. Use quotation marks to indicate exact phrases, like “mental health” or “substance abuse.”
2. Search for your keywords in the ABSTRACT. A lot of your results may be from articles about irrelevant topics simply that mention your search term once. If your topic isn’t in the abstract, chances are the article isn’t relevant. You can be even more restrictive and search for your keywords in the TITLE. Academic databases provide these options in their advanced search tools.
3. Use multiple keywords in the same query. Simply adding “addiction” onto a search for “substance abuse” will narrow down your results considerably.
4. Use a SUBJECT heading like “substance abuse” to get results from authors who have tagged their articles as addressing the topic of substance abuse. Subject headings are likely to not have all the articles on a topic but are a good place to start.
5. Narrow down the years of your search. Unless you are gathering historical information about a topic, you are unlikely to find articles older than 10-15 years to be useful. They no longer tell you the current knowledge on a topic. All databases have options to narrow your results down by year.
6. Talk to a librarian. They are professional knowledge-gatherers, and there is often a librarian assigned to your department. Their job is to help you find what you need to know.
Step 2: Finding the right database
The big four databases you will probably use for finding academic journal articles relevant to social work are: Google Scholar, Academic Search Complete, PSYCinfo, and PubMed. Each has distinct advantages and disadvantages.
Because Google Scholar is a natural language search engine, you are more likely to get what you want without having to fuss with wording. It can be linked via Library Links to your university login, allowing you to access journal articles with one click on the Google Scholar page. Google Scholar also allows you to save articles in folders and provides a (somewhat correct) APA citation for each article. However, Google Scholar also will automatically display not only journal articles, but books, government and foundation reports, and gray literature. You need to make sure that the source you are using is reputable. Look for the advanced search feature to narrow down your results further.
Academic Search Complete is available through your school’s library, usually under page titled databases. It is similar to Google Scholar in its breadth, as it contains a number of smaller databases from a variety of social science disciplines (including Social Work Abstracts). You have to use Boolean searching techniques, and there are a number of advanced search features to further narrow down your results.
PSYCinfo and PubMed focus on specific disciplines. PSYCinfo indexes articles on psychology, and PubMed indexes articles related to medical science. Because these databases are more narrowly targeted, you are more likely to get the specific psychological or medical knowledge you desire. If you were to use a more general search engine like Google Scholar, you may get more irrelevant results. Finally, it is worth mentioning that many university libraries have a meta-search engine which searches all the databases to which they have access.
Step 3: Skimming abstracts and downloading articles
Once you’ve settled on your search query and database, you should start to see articles that might be relevant to your topic. Rather than read every article, skim through the abstract and see if that article is really one you need to read. If you like the article, make sure to download the full text PDF to your computer so you can read it later. Part of the tuition and fees your university charges you goes to paying major publishers of academic journals for the privilege of accessing their articles. Because access fees are incredibly costly, your school likely does not pay for access to all the journals in the world. While you are in school, you should never have to pay for access to an academic journal article. Instead, if your school does not subscribe to a journal you need to read, try using inter-library loan to get the article. On your university library’s homepage, there is likely a link to inter-library loan. Just enter the information for your article (e.g. author, publication year, title), and a librarian will work with librarians at other schools to get you the PDF of the article that you need. After you leave school, getting a PDF of an article becomes more challenging. However, you can always ask an author for a copy of their article. They will usually be happy to hear someone is interested in reading and using their work.
What do you do with all of those PDFs? I usually keep mine in folders on my cloud storage drive, arranged by topic. For those who are more ambitious, you may want to use a reference manager like Mendeley or RefWorks, which can help keep your sources and notes organized. At the very least, take notes on each article and think about how it might be of use in your study.
Step 4: Searching for author and journal names
As you scroll through the list of articles in your search results, you should begin to notice that certain authors keep appearing. If you find an author that has written multiple articles on your topic, consider searching the AUTHOR field for that particular author. You can also search the web for that author’s Curriculum Vitae or CV (an academic resume) that will list their publications. Many authors maintain personal websites or host their CV on their university department’s webpage. Just type in their name and “CV” into a search engine. For example, you may find Michael Sherraden’s name often if your search terms are about assets and poverty. You can find his CV on the Washington University of St. Louis website.
Another way to narrow down your results is by journal name. As you are scrolling, you should also notice that many of the articles you’ve skimmed come from the same journals. Searching with that journal name in the JOURNAL field will allow you to narrow down your results to just that journal. For example, if you are searching for articles related to values and ethics in social work, you might want to search within the Journal of Social Work Values and Ethics. You can also navigate to the journal’s webpage and browse the abstracts of the latest issues.
Step 5: Examining references
As you begin to read your articles, you’ll notice that the authors cite additional articles that are likely relevant to your topic area. This is called archival searching. Unfortunately, this process will only allow you to see relevant articles from before the publication date. That is, the reference section of an article from 2014 will only have references from pre-2014. You can use Google Scholar’s “cited by” feature to do a future-looking archival search. Look up an article on Google Scholar and click the “cited by” link. This is a list of all the articles that cite the article you just read. Google Scholar even allows you to search within the “cited by” articles to narrow down ones that are most relevant to your topic area. For a brief discussion about archival searching check out this article by Hammond & Brown (2008): http://www.infotoday.com/cilmag/may08/Hammond_Brown.shtml. [2]
Step 6: Searching for systematic reviews and other sources
Another way to save time in literature searching is to look for articles that synthesize the results of other articles. Systematic reviews provide a summary of the existing literature on a topic. If you find one on your topic, you will be able to read one person’s summary of the literature and go deeper by reading their references. Similarly, meta-analyses and meta-syntheses have long reference lists that are useful for finding additional sources on a topic. They use data from each article to run their own quantitative or qualitative data analysis. In this way, meta-analyses and meta-syntheses provide a more comprehensive overview of a topic. To find these kinds of articles, include the term “meta-analysis,” “meta-synthesis,” or “systematic review” to your search terms. Another way to find systematic reviews is through the Cochrane Collaboration or Campbell Collaboration. These institutions are dedicated to producing systematic reviews for the purposes of evidence-based practice.
Putting it all together
Familiarizing yourself with research that has already been conducted on your topic is one of the first stages of conducting a research project and is crucial for coming up with a good research design. But where to start? How to start? Earlier in this chapter you learned about some of the most common databases that house information about published social work research. As you search for literature, you may have to be fairly broad in your search for articles. Let’s walk through an example. Dr. Blackstone, one of the original authors of this textbook, relates an example from her research methods class: On a college campus nearby, much to the chagrin of a group of student smokers, smoking was recently banned. These students were so upset by the idea that they would no longer be allowed to smoke on university grounds that they staged several smoke-outs during which they gathered in populated areas around campus and enjoyed a puff or two together.
A student in her research methods class wanted to understand what motivated this group of students to engage in activism centered on what she perceived to be, in this age of smoke-free facilities, a relatively deviant act. Were the protesters otherwise politically active? How much effort and coordination had it taken to organize the smoke-outs? The student researcher began her research by attempting to familiarize herself with the literature on her topic. Yet her search in Academic Search Complete for “college student activist smoke-outs,” yielded no results. Concluding there was no prior research on her topic, she informed her professor that she would not be able to write the required literature review since there was no literature for her to review. How do you suppose her professor responded to this news? What went wrong with this student’s search for literature?
In her first attempt, the student had been too narrow in her search for articles. But did that mean she was off the hook for completing a literature review? Absolutely not. Instead, she went back to Academic Search Complete and searched again using different combinations of search terms. Rather than searching for “college student activist smoke-outs” she tried, among other sets of terms, “college student activism.” This time her search yielded a great many articles. Of course, they were not focused on pro-smoking activist efforts, but they were focused on her population of interest, college students, and on her broad topic of interest, activism. Her professor suggested that reading articles on college student activism might give her some idea about what other researchers have found in terms of what motivates college students to become involved in activist efforts. Her professor also suggested she could play around with her search terms and look for research on activism centered on other sorts of activities that are perceived by some as deviant, such as marijuana use or veganism. In other words, she needed to be broader in her search for articles.
While this student found success by broadening her search for articles, her reading of those articles needed to be narrower than her search. Once she identified a set of articles to review by searching broadly, it was time to remind herself of her specific research focus: college student activist smoke-outs. Keeping in mind her particular research interest while reviewing the literature gave her the chance to think about how the theories and findings covered in prior studies might or might not apply to her particular point of focus. For example, theories on what motivates activists to get involved might tell her something about the likely reasons the students she planned to study got involved. At the same time, those theories might not cover all the particulars of student participation in smoke-outs. Thinking about the different theories then gave the student the opportunity to focus her research plans and even to develop a few hypotheses about what she thought she was likely to find.
Key Takeaways
• When identifying and reading relevant literature, be broad in your search for articles, but be narrower in your reading of articles.
• Conducting a literature search involves the skillful use of keywords to find relevant articles.
• It is important to narrow down the number of articles in your search results to only those articles that are most relevant to your inquiry.
Glossary
• Query- search terms used in a database to find sources
Image Attributions
Magnifying glass google by Simon CC-0
No smoking by OpenIcons CC-0
1. Figure 2.1 copied from image “Search operators” by TU Delft Libraries (2017). Shared using a CC-BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). Retrieved from: https://tulib.tudelft.nl/searching-resources/search-operators/
2. Hammond, C. C. & Brown, S. W. (2008, May 14). Citation searching: Searching smarter & find more. Computers in libraries. Retrieved from: http://www.infotoday.com/cilmag/may08/Hammond_Brown.shtml | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/02%3A_Beginning_a_Research_Project/2.03%3A_Finding_literature.txt |
I can spend hours looking for articles online. I love browsing around and searching on Google Scholar for articles to download and read. Unfortunately, once I have acquired a dozen or so articles I start to feel overwhelmed that I actually have to read these articles. It certainly takes a lot of time to do it right, even for faculty. In this chapter, we will learn how to understand and evaluate the sources you find. We will also review how your research questions might change as you start reading in your area of interest and learn more.
This chapter discusses or mentions the following topics: sexual harassment and gender-based violence, mental health, pregnancy, and obesity.
03: Reading and Evaluating Literature
Learning Objectives
• Identify the key components of empirical journal articles
• Define the basic elements of the results section in a journal article
• Describe statistical significance and confidence intervals
Reading scholarly articles can be a more challenging than reading a book, magazine, news article—or even some textbooks. Theoretical and practical articles are, generally speaking, easier to understand. Empirical articles, because they add new knowledge, must go through great detail to demonstrate that the information they offer is based on solid science. Empirical articles can be challenging to read, and this section is designed to make that process easier for you.
Nearly all articles will have an abstract, the short paragraph at the beginning of an article that summarizes the author’s research question, methods used to answer the question, and key findings. The abstract may also give you some idea about the theoretical perspective of the author. So, reading the abstract gives you both a framework for understanding the rest of the article and its punch line–what the author(s) found and whether the article is relevant to your area of inquiry. For this reason, I suggest skimming abstracts as part of the literature search process.
As you will recall from Chapter 2, theoretical articles have no set structure and will look similar to reading a chapter of a book. Empirical articles contain the following sections (although exact section names vary): introduction, methods, results, and discussion. The introduction contains the literature review for the article and is an excellent source of information as you build your own literature review. The methods section reviews how the author gathered their sample, how they measured their variables, and how the data were analyzed. The results section provides an in-depth discussion of the findings of the study. The discussion section reviews the main findings and addresses how those findings fit in with the existing literature. Of course, there will also be a list of references (which you should read!) and there may be a few tables, figures, or appendices at the end of the article as well.
While you should get into the habit of familiarizing yourself with each part of the articles you wish to cite, there are strategic ways to read journal articles that can make them a little easier to digest. Once you have read the abstract for an article and determined it is one you’d like to read in full, read through the introduction and discussion sections next. Because your own review of literature is likely to emphasize findings from previous literature, you should mine the article you’re reading for what’s important to know about your topic. Reading the introduction helps you see the findings and articles the author considers to be significant in the topic area. Reading an article’s discussion section helps you understand what the author views as their study’s major findings and how the author perceives those findings to relate to other research.
As you progress through your research methods course, you will pick up additional research elements that are important to understand. You will learn how to identify qualitative and quantitative methods, the criteria for establishing causality, different types of causality, as well as exploratory, explanatory, and descriptive research. Subsequent chapters of this textbook will address other elements of journal articles, including choices about measurement, sampling, and design. As you learn about these additional items, you will find that the methods and results sections begin to make more sense and you will understand how the authors reached their conclusions.
As you read a research report, there are several questions you can ask yourself about each section, from abstract to conclusion. Those questions are summarized in Table 3.1. Keep in mind that the questions covered here are designed to help you, the reader, to think critically about the research you come across and to get a general understanding of the strengths, weaknesses, and key takeaways from a given study. I hope that by considering how you might respond to the following questions while reading research reports, you’ll gain confidence in describing the report to others and discussing its meaning and impact with them.
Table 3.1 Questions worth asking while reading research reports
Report section Questions worth asking
Abstract What are the key findings? How were those findings reached? What framework does the researcher employ?
Acknowledgments Who are this study’s major stakeholders? Who provided feedback? Who provided support in the form of funding or other resources?
Problem statement (introduction) How does the author frame their research focus? What other possible ways of framing the problem exist? Why might the author have chosen this particular way of framing the problem?
Literature review
(introduction)
How selective does the researcher appear to have been in identifying relevant literature to discuss? Does the review of literature appear appropriately extensive? Does the researcher provide a critical review?
Sample (methods) Where was the data collected? Did the researcher collect their own data or use someone else’s data? What population is the study trying to make claims about, and does the sample represent that population well? What are the sample’s major strengths and major weaknesses?
Data collection (methods) How were the data collected? What do you know about the relative strengths and weaknesses of the method employed? What other methods of data collection might have been employed, and why was this particular method employed? What do you know about the data collection strategy and instruments (e.g., questions asked, locations observed)? What don’t you know about the data collection strategy and instruments?
Data analysis (methods) How were the data analyzed? Is there enough information provided for you to feel confident that the proper analytic procedures were employed accurately?
Results What are the study’s major findings? Are findings linked back to previously described research questions, objectives, hypotheses, and literature? Are sufficient amounts of data (e.g., quotes and observations in qualitative work, statistics in quantitative work) provided in order to support conclusions drawn? Are tables readable?
Discussion/conclusion Does the author generalize to some population beyond her/his/their sample? How are these claims presented? Are claims made supported by data provided in the results section (e.g., supporting quotes, statistical significance)? Have limitations of the study been fully disclosed and adequately addressed? Are implications sufficiently explored?
Understanding the results section
As mentioned previously in this chapter, reading the abstract that appears in most reports of scholarly research will provide you with an excellent, easily digestible review of a study’s major findings and of the framework the author is using to position their findings. Abstracts typically contain just a few hundred words, so reading them is a nice way to quickly familiarize yourself with a study. If the study seems relevant to your paper, it’s probably worth reading more. If it’s not, then you have only spent a minute or so reading the abstract. Another way to get a snapshot of the article is to scan the headings, tables, and figures throughout the report (Green & Simon, 2012). [1]
At this point, I have read hundreds of literature reviews written by students. One of the challenges I have noted is that students will report the summarized results from the abstract, rather than the detailed findings in the results section of the article. This is a problem when you are writing a literature review because you need to provide specific and clear facts that support your reading of the literature. The abstract may say something like: “we found that poverty is associated with mental health status.” For your literature review, you want the details, not the summary. In the results section of the article, you may find a sentence that states: “for households in poverty, children are three times more likely to have a mental health diagnosis.” This more detailed information provides a stronger basis on which to build a literature review.
Using the summarized results in an abstract is an understandable mistake to make. The results section often contains diagrams and symbols that are challenging to understand. Often, without having completed more advanced coursework on statistical or qualitative analysis, some of the terminology, symbols, or diagrams may be difficult to comprehend. To that end, the purpose of this section is to improve reading comprehension by providing an introduction to the basic components of a results section.
Journal articles often contain tables, and scanning them is a good way to begin reading an article. A table provides a quick, condensed summary of the report’s key findings. The use of tables is not limited to one form or type of data, though they are used most commonly in quantitative research. Tables are a concise way to report large amounts of data. Some tables present descriptive information about a researcher’s sample, which is often the first table in a results section. These tables will likely contain frequencies (N) and percentages (%). For example, if gender happened to be an important variable for the researcher’s analysis, a descriptive table would show how many and what percent of all study participants are women, men, or other genders. Frequencies or “how many” will probably be listed as N, while the percent symbol (%) might be used to indicate percentages.
In a table presenting a causal relationship, two sets of variables are represented. The independent variable, or cause, and the dependent variable, the effect. We’ll go into more detail on variables in Chapter 6. The independent variable attributes are typically presented in the table’s columns, while dependent variable attributes are presented in rows. This allows the reader to scan across a table’s rows to see how values on the dependent variable attributes change as the independent variable attribute values change. Tables displaying results of quantitative analysis will also likely include some information about the strength and statistical significance of the relationships presented in the table. These details tell the reader how likely it is that the relationships presented will have occurred simply by chance.
Let’s look at a specific example. Table 3.2, which is based on data from a study of older workers conducted by Dr. Blackstone, an original author of this textbook. It presents the causal relationship between gender and experiencing harassing behaviors at work. In this example, gender is the independent variable (the cause) and the harassing behaviors listed are the dependent variables (the effects). [2] Therefore, we place gender in the table’s columns and harassing behaviors in the table’s rows.
Reading across the table’s top row, we see that 2.9% of women in the sample reported experiencing subtle or obvious threats to their safety at work, while 4.7% of men in the sample reported the same. We can read across each of the rows of the table in this way. Reading across the bottom row, we see that 9.4% of women in the sample reported experiencing staring or invasion of their personal space at work while just 2.3% of men in the sample reported having the same experience. We’ll discuss p value later in this section.
Table 3.2 Percentage reporting harassing behaviors at work
Behavior Experienced at work Women Men p value
Subtle or obvious threats to your safety 2.9% 4.7% 0.623
Being hit, pushed, or grabbed 2.2% 4.7% 0.480
Comments or behaviors that demean your gender 6.5% 2.3% 0.184
Comments or behaviors that demean your age 13.8% 9.3% 0.407
Staring or invasion of your personal space 9.4% 2.3% 0.039
Note: Sample size was 138 for women and 43 for men.
These statistics represent what the researchers found in their sample, and they are using their sample to make conclusions about the true population of all employees in the real world. Because the methods we use in social science are never perfect, there is some amount of error in that value. The researchers in this study estimated the true value we would get if we asked every employee in the world the same questions on our survey. Researchers will often provide a confidence interval, or a range of values in which the true value is likely to be, to provide a more accurate description of their data. For example, at the time I’m writing this, my wife and I are expecting our first child next month. The doctor told us our due date was August 15th. But the doctor also told us that August 15th was only their best estimate. They were actually 95% sure our baby might be born any time between August 1st and September 1st. Confidence intervals are often listed with a percentage, like 90% or 95%, and a range of values, such as between August 1st and Setptember 1st. You can read that as: we are 95% sure your baby will be born between August 1st and September 1st. So, while we get a due date of August 15th, the uncertainty about the exact date is reflected in the confidence interval provided by our doctor.
Of course, we cannot assume that these patterns didn’t simply occur by chance. How confident can we be that the findings presented in the table did not occur by chance? This is where tests of statistical significance come in handy. Statistical significance tells us the likelihood that the relationships we observe could be caused by something other than chance. While your statistics class will give you more specific details on tests of statistical significance and reading quantitative tables, the important thing to be aware of as a non-expert reader of tables is that some of the relationships presented will be statistically significant and others may not be. Tables should provide information about the statistical significance of the relationships presented. When reading a researcher’s conclusions, pay attention to which relationships are statistically significant and which are not.
In Table 3.2, you may have noticed that a p value is noted in the very last column of the table. A p value is a statistical measure of the probability that there is no relationship between the variables under study. Another way of putting this is that the p value provides guidance on whether or not we should reject the null hypothesis. The null hypothesis is simply the assumption that no relationship exists between the variables in question. In Table 3.2, we see that for the first behavior listed, the p value is 0.623. This means that there is a 62.3% chance that the null hypothesis is correct in this case. In other words, it seems likely that any relationship between observed gender and experiencing threats to safety at work in this sample is simply due to chance.
In the final row of the table, however, we see that the p value is 0.039. In other words, there is a 3.9% chance that the null hypothesis is correct. Thus, we can be somewhat more confident than in the preceding example that there may be some relationship between a person’s gender and their experiencing the behavior noted in this row. Statistical significance is reported in reference to a value, usually 0.05 in the social science. This means that the probability that the relationship between gender and experiencing staring or invasion of personal space at work is due to random chance is less than 5 in 100. Social science often uses 0.05, but other values are used. Studies using 0.1 are using a more forgiving standard of significance, and therefore, have a higher likelihood of error (10%). Studies using 0.01 are using a more stringent standard of significance, and therefore, have a lower likelihood of error (1%).
Notice that I’m hedging my bets here by using words like somewhat and may be. When testing hypotheses, social scientists generally phrase their findings in terms of rejecting the null hypothesis rather than making bold statements about the relationships observed in their tables. You can learn more about creating tables, reading tables, and tests of statistical significance in a class focused exclusively on statistical analysis. For now, I hope this brief introduction to reading tables will improve your confidence in reading and understanding the quantitative tables you encounter while reading reports of social science research.
A final caveat is worth noting here. The previous discussion of tables and reading the results section is applicable to quantitative articles. Quantitative articles will contain a lot of numbers and the results of statistical tests demonstrating association between those numbers. Qualitative articles, on the other hand, will consist mostly of quotations from participants. For most qualitative articles, the authors want to put their results in the words of their participants, as they are the experts. The results section may be organized by theme, with each paragraph or subsection illustrating through quotes how the authors interpret what people in their study said.
Key Takeaways
• Reading a research article requires reading beyond the abstract.
• In tables presenting causal relationships, the independent variable is typically presented in the table’s columns while the dependent variables are presented in the table’s rows.
• When reading a research report, there are several key questions you should ask yourself for each section of the report.
Glossary
• Abstract- the short paragraph at the beginning of an article that summarizes the its main point
• Confidence interval- a range of values in which the true value is likely to be
• Null hypothesis- the assumption that no relationship exists between the variables in question
• P-value- a statistical measure of the probability that there is no relationship between the variables under study
• Statistical significance- the likelihood that the relationships that are observed could be caused by something other than chance
• Table- a quick, condensed summary of the report’s key findings
Image Attributions
CSAF releases 2009 reading list by Master Sgt. Steven Goetsch public domain
1. Green, W. & Simon, B. L. (2012). The Columbia guide to social work writing. New York, NY: Columbia University Press. ↵
2. It wouldn’t make any sense to say that people’s workplace experiences cause their gender, so in this example, the question of which is the independent variable and which are the dependent variables has a pretty obvious answer. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/03%3A_Reading_and_Evaluating_Literature/3.01%3A_Reading_an_empirical_journal_article.txt |
Learning Objectives
• Critically evaluate the sources of the information you have found
• Apply the information from each source to your research proposal
• Identify how to be a responsible consumer of research
In Chapter 2, you developed a “working question” to guide your inquiry and learned how to use online databases to find sources. By now, you’ve hopefully collected a number of academic journal articles relevant to your topic area. It’s now time to evaluate the information you found. Not only do you want to be sure of the source and the quality of the information, but you also want to determine whether each item is an appropriate fit for your literature review.
This is also the point at which you make sure you have searched for and obtained publications for all areas of your research question and that you go back into the literature for another search, if necessary. You may also want to consult with your professor or the syllabus for your class to see what is expected for your literature review. In my class, I have specific questions I will ask students to address in their literature reviews.
It is likely that most of the resources you locate for your review will be from the scholarly literature of your discipline or in your topic area. As we have already seen, peer-reviewed articles are written by and for experts in a field. They generally describe formal research studies or experiments with the purpose of providing insight on a topic. You may have located these articles through the four databases in Chapter 2 or through archival searching. You now may want to know how to evaluate the usefulness for your research.
In general, when we discuss evaluation of sources, we are talking about quality, accuracy, relevance, bias, reputation, currency, and credibility factors in a specific work, whether it’s a book, ebook, article, website, or blog posting. Before you include a source in your literature review, you should clearly understand what it is and why you are including it. According to Bennard et al. (2014), “Using inaccurate, irrelevant, or poorly researched sources can affect the quality of your own work” (para. 4). When evaluating a work for inclusion in, or exclusion from, your literature review, ask yourself a series of questions about each source.
1. Is the information outdated? Is the source more than 5-10 years old? If so, it will not provide what we currently know about the topic–just what we used to know. Older sources are helpful for historical information, but unless historical analysis is the focus of your literature review, try to limit your sources to those that are current.
2. How old are the sources used by the author? If you are reading an article from 10 years ago, they are likely citing material from 15-20 years ago. Again, this does not reflect what we currently know about a topic.
3. Does the author have the credentials to write on the topic? Search the author’s name in a general web search engine like Google. What are the researcher’s academic credentials? What else has this author written? Search by author in the databases and see how much they have published on any given subject.
4. Who published the source? Books published under popular press imprints (such as Random House or Macmillan) will not present scholarly research in the same way as Sage, Oxford, Harvard, or the University of Washington Press. For grey literature and websites, check the About Us page to learn more about potential biases and funding of the organization who wrote the report.
5. Is the source relevant to your topic? How does the article fit into the scope of the literature on this topic? Does the information support your thesis or help you answer your question, or is it a challenge to make some kind of connection? Does the information present an opposite point of view, so you can show that you have addressed all sides of the argument in your paper? Many times, literature searches will include articles that ultimately are not that relevant to your final topic. You don’t need to read everything!
6. How important is this source in the literature? If you search for the article on Google Scholar (see Figure 3.1 for an example of a search result from Google Scholar), you can see how many other sources cited this information. Generally, the higher the number of citations, the more important the article. This is a way to find seminal articles – “A classic work of research literature that is more than 5 years old and is marked by its uniqueness and contribution to professional knowledge” (Houser, 2018, p. 112).
Figure 3.1 Google Scholar
[1]
7. Is the source accurate? Check the facts in the article. Can statistics be verified through other sources? Does this information seem to fit with what you have read in other sources?
8. Is the source reliable and objective? Is a particular point of view or bias immediately obvious, or does it seem objective at first glance? What point of view does the author represent? Are they clear about their point of view? Is the article an editorial that is trying to argue a position? Is the article in a publication with a particular editorial position?
9. What is the scope of the article? Is it a general work that provides an overview of the topic or is it specifically focused on only one aspect of your topic?
10. How strong is the evidence in the article? What are the research methods used in the article? Where does the method fall in the hierarchy of evidence?
• Meta-analysis and meta-synthesis: a systematic and scientific review that uses quantitative or qualitative methods (respectively) to summarize the results of many studies on a topic.
• Experiments and quasi-experiments: include a group of patients in an experimental group, as well as a control group. These groups are monitored for the variables/outcomes of interest. Randomized control trials are the gold standard.
• Longitudinal surveys: follow a group of people to identify how variables of interest change over time.
• Cross-sectional surveys: observe individuals at one point in time and discover relationships between variables.
• Qualitative studies: use in-depth interviews and analysis of texts to uncover the meaning of social phenomen
The last point above comes with some pretty strong caveats, as no study is really better than another. Foremost, your research question should guide which kinds of studies you collect for your literature review. If you are conducting a qualitative study, you should include some qualitative studies in your literature review so you can understand how others have studied the topic before you. Even if you are conducting a quantitative study, qualitative research is important for understanding processes and the lived experience of people. Any article that demonstrates rigor in thought and methods is appropriate to use in your inquiry.
At the beginning of a project, you may not know what kind of research project you will ultimately propose. It is at this point that consulting a meta-analysis, meta-synthesis, or systematic review might be especially helpful as these articles try to summarize an entire body of literature into one article. Every type of source listed here is reputable, but some have greater explanatory power than others.
Thinking about your project
Thinking about the overarching goals of your research project and finding and reviewing the existing literature on your topic are two of the initial steps you’ll take when designing a research project. Forming a working research question, as discussed in section 2.1, is another crucial step. Creating and refining your research question will help you identify the key concepts you will study. Once you have identified those concepts, you’ll need to decide how to define them, and how you’ll know that you’re observing them when it comes time to collect your data. Defining your concepts, and knowing them when you see them, relates to conceptualization and operationalization. Of course, you also need to know what approach you will take to collect your data. Thus, identifying your research method is another important part of research design.
You also need to think about who your research participants will be and what larger group(s) they may represent. Last, but certainly not least, you should consider any potential ethical concerns that could arise during the course of your research project. These concerns might come up during your data collection, but they might also arise when you get to the point of analyzing or sharing your research results.
Decisions about the various research components do not necessarily occur in sequential order. In fact, you may have to think about potential ethical concerns even before zeroing in on a specific research question. Similarly, the goal of being able to make generalizations about your population of interest could shape the decisions you make about your method of data collection. Putting it all together, the following list shows some of the major components you’ll need to consider as you design your research project. Make sure you have information that will help inform how you think about each component.
• Research question
• Literature review
• Research strategy (idiographic or nomothetic, inductive or deductive)
• Units of analysis and units of observation
• Key concepts (conceptualization and operationalization)
• Method of data collection
• Research participants (sample and population)
• Ethical concerns
Being a responsible consumer of research
Being a responsible consumer of research requires you to take seriously your identity as a social scientist. Now that you are familiar with how to conduct research and how to read the results of others’ research, you have some responsibility to put your knowledge and skills to use. Doing so is in part a matter of being able to distinguish what you do know based on the information provided by research findings from what you do not know. It is also a matter of having some awareness about what you can and cannot reasonably know as you encounter research findings.
When assessing social scientific findings, think about what information has been provided to you. In a scholarly journal article, you will presumably be given a great deal of information about the researcher’s method of data collection, her sample, and information about how the researcher identified and recruited research participants. All of these details provide important contextual information that can help you assess the researcher’s claims. If, on the other hand, you come across some discussion of social scientific research in a popular magazine or newspaper, chances are that you will not find the same level of detailed information that you would find in a scholarly journal article. In this case, what you do and do not know is more limited than in the case of a scholarly journal article. If the research appears in popular media, search for the author or study title in an academic database.
Also, take into account whatever information is provided about a study’s funding source. Most funders want, and in fact require, that recipients acknowledge them in publications. But more popular press may leave out a funding source. In this Internet age, it can be relatively easy to obtain information about how a study was funded. If this information is not provided in the source from which you learned about a study, it might behoove you to do a quick search on the web to see if you can learn more about a researcher’s funding. Findings that seem to support a particular political agenda, for example, might have more or less weight once you know whether and by whom a study was funded.
There is some information that even the most responsible consumer of research cannot know. Because researchers are ethically bound to protect the identities of their subjects, for example, we will never know exactly who participated in a given study. Researchers may also choose not to reveal any personal stakes they hold in the research they conduct. While researchers may “start where they are,” we cannot know for certain whether or how researchers are personally connected to their work unless they choose to share such details. Neither of these “unknowables” is necessarily problematic, but having some awareness of what you may never know about a study does provide important contextual information from which to assess what one can “take away” from a given report of findings.
Key Takeaways
• Not all published articles are the same. Evaluating sources requires a careful investigation of each source.
• Being a responsible consumer of research means giving serious thought to and understanding what you do know, what you don’t know, what you can know, and what you can’t know.
Image attributions
130329-A-XX000-001 by Master Sgt. Michael Chann public domain | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/03%3A_Reading_and_Evaluating_Literature/3.02%3A_Evaluating_sources.txt |
Learning Objectives
• Develop and revise questions that focus your inquiry
• Create a concept map that demonstrates the relationships between concepts
Once you have selected your topic area and reviewed literature related to it, you may need to narrow it to something that can be realistically researched and answered. In the last section, we learned about asking who, what, when, where, why, and how questions. As you read more about your topic area you the focus of your inquiry should become more specific and clear. As a result, you might begin to ask to begin to ask questions that describe a phenomenon, compare one phenomenon with another, or probe the relationship between two concepts.
You might begin by asking a series of PICO questions. Although the PICO method is used primarily in the health sciences, it can also be useful for narrowing/refining a research question in the social sciences as well. A way to formulate an answerable question using the PICO model could look something like this:
• Patient, population or problem: What are the characteristics of the patient or population? (e.g., gender, age, other demographics) What is the social problem or diagnosis you are interested in? (e.g., poverty or substance use disorder)
• Intervention or exposure: What do you want to do with the patient, person, or population (e.g., treat, diagnose, observe)? For example, you may want to observe a client’s behavior or a reaction to a specific type of treatment.
• Comparison: What is the alternative to the intervention? (e.g., other therapeutic interventions, programs, or policies) For example, how does a sample group that is assigned to mandatory rehabilitation compare to an intervention that builds motivation to enter treatment voluntarily?
• Outcome: What are the relevant outcomes? (e.g., academic achievement, healthy relationships, shame) For example, how does recognizing triggers for trauma flashbacks impact the target population?
Some examples of how the PICO method is used to refine a research question include:
• “Can music therapy help autistic students improve their communication skills?”
• Population (autistic students)
• Intervention (music therapy)
• “How effective are antidepressant medications on anxiety and depression?”
• Population (clients with anxiety and depression)
• Intervention (antidepressants)
• “How does race impact help-seeking for students with mental health diagnoses?
• Population (students with mental health diagnoses, students of minority races)
• Comparison (students of different races)
• Outcome (seeking help for mental health issues)
Another mnemonic technique used in the social sciences for narrowing a topic is SPICE. An example of how SPICE factors can be used to develop a research question is given below:
Setting – for example, a college campus
Perspective – for example, college students
Intervention – for example, text message reminders
Comparisons – for example, telephone message reminders
Evaluation – for example, number of cigarettes used after text message reminder compared to the number of cigarettes used after a telephone reminder
Developing a concept map
Likewise, developing a concept map or mind map around your topic may help you analyze your question and determine more precisely what you want to research. Using this technique, start with the broad topic, issue, or problem, and begin writing down all the words, phrases and ideas related to that topic that come to mind and then ‘map’ them to the original idea. This technique is illustrated in Figure 3.2.
Figure 3.2 Basic concept map
Concept mapping aims to improve the “description of the breadth and depth of literature in a domain of inquiry. It also facilitates identification of the number and nature of studies underpinning mapped relationships among concepts, thus laying the groundwork for systematic research reviews and meta-analyses” (Lesley, Floyd, & Oermann, 2002, p. 229). [2] Its purpose, like the other methods of question refining, is to help you organize, prioritize, and integrate material into a workable research area; one that is interesting, answerable, feasible, objective, scholarly, original, and clear.
In addition to helping you get started with your own literature review, the concept mapping will give you some keywords and concepts that will be useful when you begin searching the literature for relevant studies and publications on your topic. Concept mapping can also be helpful when creating a topical outline or drafting your literature review, as it demonstrates the important of each concept and sub-concepts as well as the relationships between each concept.
For example, perhaps your initial idea or interest is how to prevent obesity. After an initial search of the relevant literature, you realize the topic of obesity is too broad to adequately cover in the time you have to do your literature review. You decide to narrow your focus to causes of childhood obesity. Using PICO factors, you further narrow your search to the influence of family factors on overweight children. A potential research question might then be “What maternal factors are associated with toddler obesity in the United States?” You’re now ready to begin searching the literature for studies, reports, cases, and other information sources that relate to this question.
Similarly, for a broad topic like school performance or grades, and after an initial literature search that provides some variables, examples of a narrow research question might be:
• “To what extent does parental involvement in children’s education relate to school performance over the course of the early grades?”
• “Do parental involvement levels differ by family social, demographic, and contextual characteristics?”
• “What forms of parent involvement are most highly correlated with children’s outcomes? What factors might influence the extent of parental involvement?” (Early Childhood Longitudinal Program, 2011). [3]
In either case, your literature search, working question, and understanding of the topic are constantly changing as your knowledge of the topic deepens. A literature review is an iterative process, one that stops, starts, and loops back on itself multiple times before completion. As research is a practice behavior of social workers, you should apply the same type of critical reflection to your inquiry as you would to your clinical or macro practice.
Key Takeaways
• As you read more articles, you should revise your original question to make it more focused and clear.
• You can further develop the important concepts and relationships for your project by using concept maps and the PICO/SPICE frameworks.
1. Figure 3.2 image “gaming and narrative discussion” created by Bryan Alexander (2012). Shared under a CC-BY 2.0 license (https://creativecommons.org/licenses/by/2.0/) and retrieved from: https://www.flickr.com/photos/bryanalexander/6737919649
2. Leslie, M., Floyd, J., & Oermann, M. (2002). Use of MindMapper software for research domain mapping. Computers, informatics, nursing, 20(6), 229-235. ↵
3. Early Childhood Longitudinal Program. (2011). Example research questions. nces.ed.gov/ecls/researchquestions2011.asp↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/03%3A_Reading_and_Evaluating_Literature/3.03%3A_Refining_your_question.txt |
Whether you plan to engage in clinical, administrative, or policy practice, all social workers must be able to look at the available literature on a topic and synthesize the relevant facts into a coherent review. Literature reviews can have a powerful effect, for example by providing the factual basis for a new program or policy in an agency or government. In your own research proposal, conducting a thorough literature review will help you build strong arguments for why your topic is important and why your research question must be answered.
This chapter discusses or mentions the following topics: homelessness, suicide, depression, LGBTQ oppression, drug use, and psychotic disorders.
04: Conducting a Literature Review
Learning Objectives
• Describe the components of a literature review
• Recognize commons errors in literature reviews
Pick up nearly any book on research methods and you will find a description of a literature review. At a basic level, the term implies a survey of factual or nonfiction books, articles, and other documents published on a particular subject. Definitions may be similar across the disciplines, with new types and definitions continuing to emerge. Generally speaking, a literature review is a:
• “comprehensive background of the literature within the interested topic area” (O’Gorman & MacIntosh, 2015, p. 31). [1]
• “critical component of the research process that provides an in-depth analysis of recently published research findings in specifically identified areas of interest” (Houser, 2018, p. 109). [2]
• “written document that presents a logically argued case founded on a comprehensive understanding of the current state of knowledge about a topic of study” (Machi & McEvoy, 2012, p. 4). [3]
Literature reviews are indispensable for academic research. “A substantive, thorough, sophisticated literature review is a precondition for doing substantive, thorough, sophisticated research…A researcher cannot perform significant research without first understanding the literature in the field” (Boote & Beile, 2005, p. 3). [4] In the literature review, a researcher shows she is familiar with a body of knowledge and thereby establishes her credibility with a reader. The literature review shows how previous research is linked to the author’s project, summarizing and synthesizing what is known while identifying gaps in the knowledge base, facilitating theory development, closing areas where enough research already exists, and uncovering areas where more research is needed. (Webster & Watson, 2002, p. xiii). [5] They are often necessary for real world social work practice. Grant proposals, advocacy briefs, and evidence-based practice rely on a review of the literature to accomplish practice goals.
A literature review is a compilation of the most significant previously published research on your topic. Unlike an annotated bibliography or a research paper you may have written in other classes, your literature review will outline, evaluate, and synthesize relevant research and relate those sources to your own research question. It is much more than a summary of all the related literature. A good literature review lays the foundation for the importance of the problem your research project addresses defines the main ideas in your research question and their interrelationships.
Literature review basics
All literature reviews, whether they focus on qualitative or quantitative data, will at some point:
1. Introduce the topic and define its key terms.
2. Establish the importance of the topic.
3. Provide an overview of the important literature on the concepts in the research question and other related concepts.
4. Identify gaps in the literature or controversies.
5. Point out consistent finding across studies.
6. Arrive at a synthesis that organizes what is known about a topic, rather than just summarizing.
7. Discusses possible implications and directions for future research.
There are many different types of literature reviews, including those that focus solely on methodology, those that are more conceptual, and those that are more exploratory. Regardless of the type of literature review or how many sources it contains, strong literature reviews have similar characteristics. Your literature review is, at its most fundamental level, an original work based on an extensive critical examination and synthesis of the relevant literature on a topic. As a study of the research on a particular topic, it is arranged by key themes or findings, which should lead up to or link to the research question.
A literature review is a mandatory part of any research project. It demonstrates that you can systematically explore the research in your topic area, read and analyze the literature on the topic, use it to inform your own work, and gather enough knowledge about the topic to conduct a research project. Literature reviews should be reasonably complete, and not restricted to a few journals, a few years, or a specific methodology or research design. A well-conducted literature review should indicate to you whether your initial research questions have already been addressed in the literature, whether there are newer or more interesting research questions available, and whether the original research questions should be modified or changed in light of findings of the literature review. The review can also provide some intuitions or potential answers to the questions of interest and/or help identify theories that have previously been used to address similar questions and may provide evidence to inform policy or decision-making (Bhattacherjee, 2012). [6]
Literature reviews are also beneficial to you as a researcher and scholar in social work. By reading what others have argued and found in their work, you become familiar with how people talk about and understand your topic. You will also refine your writing skills and your understanding of the topic you have chosen. The literature review also impacts the question you want to answer. As you learn more about your topic, you will clarify and redefine the research question guiding your inquiry. Literature reviews make sure you are not “reinventing the wheel” by repeating a study done so many times before or making an obvious error that others have encountered. The contribution your research study will have depends on what others have found before you. Try to place the study you wish to do in the context of previous research and ask, “Is this contributing something new?” and “Am I addressing a gap in knowledge or controversy in the literature?”
In summary, you should conduct a literature review to:
• Locate gaps in the literature of your discipline
• Avoid “reinventing the wheel”
• Carry on the unfinished work of other scholars
• Identify other people working in the same field
• Increase breadth and depth of knowledge in your subject area
• Read the seminal works in your field
• Provide intellectual context for your own work
• Acknowledge opposing viewpoints
• Put your work in perspective
• Demonstrate you can find and understand previous work in the area
Common literature review errors
Literature reviews are more than a summary of the publications you find on a topic. As you have seen in this brief introduction, literature reviews are a very specific type of research, analysis, and writing. We will explore these topics more in the next chapters. As you begin your literature review, here are some common errors to avoid:
• Accepting another researcher’s finding as valid without evaluating methodology and data
• Ignoring contrary findings and alternative interpretations
• Using findings that are not clearly related to your own study or using findings that are too general
• Dedicating insufficient time to literature searching
• Simply reporting isolated statistical results, rather than synthesizing the results
• Relying too heavily on secondary sources
• Overusing quotations from sources
• Not justifying arguments using specific facts or theories from the literature
For a quick review of some of the pitfalls and challenges a new researcher faces when she begins work, see “Get Ready: Academic Writing, General Pitfalls and (oh yes) Getting Started!”.
Key Takeaways
• Literature reviews are the first step in any research project, as they help you learn about the topic you chose to study.
• You must do more than summarize sources for a literature review. You must have something to say about them and demonstrate you understand their content.
Glossary
• Literature review- a survey of factual or nonfiction books, articles, and other documents published on a particular subject
Image attributions
Book library by MVA CC-0
1. O’Gorman, K., & MacIntosh, R. (2015). Research methods for business & management: A guide to writing your dissertation (2nd ed.). Oxford: Goodfellow Publishers. ↵
2. Houser, J., (2018). Nursing research reading, using, and creating evidence (4th ed.). Burlington, MA: Jones & Bartlett. ↵
3. Machi, L., & McEvoy, B. (2012). The literature review: Six steps to success (2nd ed). Thousand Oaks, CA: Corwin. ↵
4. Boote, D., & Beile, P. (2005). Scholars before researchers: On the centrality of the dissertation literature review in research preparation. Educational Researcher 34(6), 3-15. ↵
5. Webster, J., & Watson, R. (2002). Analyzing the past to prepare for the future: Writing a literature review. MIS Quarterly, 26(2), xiii-xxiii. https://web.njit.edu/~egan/Writing_A_Literature_Review.pdf
6. Bhattacherjee, A., (2012). Social science research: Principles, methods, and practices. Textbooks Collection. 3. http://scholarcommons.usf.edu/oa_textbooks/3 | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/04%3A_Conducting_a_Literature_Review/4.01%3A_What_is_a_literature_review%3F.txt |
Learning Objectives
• Connect the sources you read with key concepts in your research question and proposal
• Systematize the information and facts from each source you read
Putting the pieces together
Combining separate elements into a whole is the dictionary definition of synthesis. It is a way to make connections among and between numerous and varied source materials. A literature review is not an annotated bibliography, organized by title, author, or date of publication. Rather, it is grouped by topic and argument to create a whole view of the literature relevant to your research question.
Your synthesis must demonstrate a critical analysis of the papers you collected, as well as your ability to integrate the results of your analysis into your own literature review. Each source you collect should be critically evaluated and weighed based on the criteria from Chapter 3 before you include it in your review.
Begin the synthesis process by creating a grid, table, or an outline where you will summarize your literature review findings, using common themes you have identified and the sources you have found. The summary, grid, or outline will help you compare and contrast the themes, so you can see the relationships among them as well as areas where you may need to do more searching. A basic summary table is provided in Figure 4.2. Whichever method you choose, this type of organization will help you to both understand the information you find and structure the writing of your review. Remember, although “the means of summarizing can vary, the key at this point is to make sure you understand what you’ve found and how it relates to your topic and research question” (Bennard et al., 2014, para. 10). [1]
Figure 4.2 Summary table
As you read through the material you gather, look for common themes as they may provide the structure for your literature review. And, remember, research is an iterative process. It is not unusual to go back and search academic databases for more sources of information as you read the articles you’ve collected.
Literature reviews can be organized sequentially or by topic, theme, method, results, theory, or argument. It’s important to develop categories that are meaningful and relevant to your research question. Take detailed notes on each article and use a consistent format for capturing all the information each article provides. These notes and the summary table can be done manually using note cards. However, given the amount of information you will be recording, an electronic file created in a word processing or spreadsheet is more manageable. Examples of fields you may want to capture in your notes include:
• Authors’ names
• Article title
• Publication year
• Main purpose of the article
• Methodology or research design
• Participants
• Variables
• Measurement
• Results
• Conclusions
Other fields that will be useful when you begin to synthesize the sum total of your research:
• Specific details of the article or research that are especially relevant to your study
• Key terms and definitions
• Statistics
• Strengths or weaknesses in research design
• Relationships to other studies
• Possible gaps in the research or literature (for example, many research articles conclude with the statement “more research is needed in this area”)
• Finally, note how closely each article relates to your topic. You may want to rank these as high, medium, or low relevance. For papers that you decide not to include, you may want to note your reasoning for exclusion, such as small sample size, local case study, or lacks evidence to support conclusions.
An example of how to organize summary tables by author or theme is shown in Table 4.1.
Table 4.1: Summary table
Author/Year Research Design Participants or Population Studied Comparison Outcome
Smith/2010 Mixed methods Undergraduates Graduates Improved access
King/2016 Survey Females Males Increased representation
Miller/2011 Content analysis Nurses Doctors New procedure
For a summary table template, see blogs.monm.edu/writingatmc/files/2013/04/Synthesis-Matrix-Template.pdf
Creating a topical outline
An alternative way to organize your articles for synthesis it to create an outline. After you have collected the articles you intend to use (and have put aside the ones you won’t be using), it’s time to extract as much as possible from the facts provided in those articles. You are starting your research project without a lot of hard facts on the topics you want to study, and by using the literature reviews provided in academic journal articles, you can gain a lot of knowledge about a topic in a short period of time.
As you read an article in detail, I suggest copying the information you find relevant to your research topic in a separate word processing document. Copying and pasting from PDF to Word can be a pain because PDFs are image files not documents. To make that easier, use the HTML version of the article, convert the PDF to Word in Adobe Acrobat or another PDF reader, or use “paste special” command to paste the content into Word without formatting. If it’s an old PDF, you may have to simply type out the information you need. It can be a messy job, but having all of your facts in one place is very helpful for drafting your literature review.
You should copy and paste any fact or argument you consider important. Some good examples include definitions of concepts, statistics about the size of the social problem, and empirical evidence about the key variables in the research question, among countless others. It’s a good idea to consult with your professor and the syllabus for the course about what they are looking for when they read your literature review. Facts for your literature review are principally found in the introduction, results, and discussion section of an empirical article or at any point in a non-empirical article. Copy and paste into your notes anything you may want to use in your literature review.
Importantly, you must make sure you note the original source of that information. Nothing is worse than searching your articles for hours only to realize you forgot to note where your facts came from. If you found a statistic that the author used in the introduction, it almost certainly came from another source that the author cited in a footnote or internal citation. You will want to check the original source to make sure the author represented the information correctly. Moreover, you may want to read the original study to learn more about your topic and discover other sources relevant to your inquiry.
Assuming you have pulled all of the facts out of multiple articles, it’s time to start thinking about how these pieces of information relate to each other. Start grouping each fact into categories and subcategories as shown in Figure 4.3. For example, a statistic stating that homeless single adults are more likely to be male may fit into a category of gender and homelessness. For each topic or subtopic you identified during your critical analysis of each paper, determine what those papers have in common. Likewise, determine which ones in the group differ. If there are contradictory findings, you may be able to identify methodological or theoretical differences that could account for the contradiction. For example, one study may sample only high-income earners or those in a rural area. Determine what general conclusions you can report about the topic or subtopic, based on all of the information you’ve found.
Create a separate document containing a topical outline that combines your facts from each source and organizes them by topic or category. As you include more facts and more sources into your topical outline, you will begin to see how each fact fits into a category and how categories are related to each other. Your category names may change over time, as may their definitions. This is a natural reflection of the learning you are doing.
Table 4.2 Topical outline[3]
Facts copied from an article Topical outline: Facts organized by category
• A complete topical outline is a long list of facts, arranged by category about your topic. As you step back from the outline, you should understand the topic areas where you have enough information to make strong conclusions about what the literature says. You should also assess in what areas you need to do more research before you can write a robust literature review. The topical outline should serve as a transitional document between the notes you write on each source and the literature review you submit to your professor. It is important to note that they contain plagiarized information that is copied and pasted directly from the primary sources. That’s okay because these are just notes and are not meant to be turned in as your own ideas. For your final literature review, you must paraphrase these sources to avoid plagiarism. More importantly, you should keep your voice and ideas front-and-center in what you write as this is your analysis of the literature. Make strong claims and support them thoroughly using facts you found in the literature. We will pick up the task of writing your literature review in section 4.3.
Additional resources for synthesizing literature
There are many ways to approach synthesizing literature. We’ve reviewed two examples here: summary tables and topical outlines. Other examples you may encounter include annotated bibliographies and synthesis matrixes. As you are learning research, find a method that works for you. Reviewing the literature is a core component of evidence-based practice in social work at any level. See the resources below if you need some additional help:
Literature Reviews: Using a Matrix to Organize Research / Saint Mary’s University of Minnesota
Literature Review: Synthesizing Multiple Sources / Indiana University
Writing a Literature Review and Using a Synthesis Matrix / Florida International University
Sample Literature Reviews Grid / Complied by Lindsay Roberts
Killam, Laura (2013). Literature review preparation: Creating a summary table. Includes transcript. https://www.youtube.com/watch?v=nX2R9FzYhT0
Key Takeaways
• It is necessary to take notes on research articles as you read. Try to develop a system that works for you to keep your notes organized, such as a summary table.
• Summary tables and topical outlines help researchers synthesize sources for the purpose of writing a literature review.
Image attributions
Pieces of the puzzle by congerdesign CC-0
Adult diary by Pexels CC-0
1. Bernnard, D., Bobish, G., Hecker, J., Holden, I., Hosier, A., Jacobson, T., Loney, T., & Bullis, D. (2014). Presenting: Sharing what you’ve learned. In Bobish, G., & Jacobson, T. (eds.) The information literacy users guide: An open online textbook. https://milnepublishing.geneseo.edu/the-information-literacy-users-guide-an-open-online-textbook/chapter/present-sharing-what-youve-learned/
2. Figure 4.2 copied from Frederiksen, L. & Phelps, S. F. (2018). Literature reviews for education and nursing graduate students. Shared under a CC-BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). ↵
3. This table was adapted from the work of Amanda Parsons. For more of Amanda's work see the exemplars for assignments linked in the front matter of this textbook. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/04%3A_Conducting_a_Literature_Review/4.02%3A_Synthesizing_literature.txt |
Learning Objectives
• Begin to write your literature review
• Identify the purpose of a problem statement
• Apply the components of a formal argument to your topic
• Use elements of formal writing style, including signposting and transitions
Congratulations! By now, you should have discovered, retrieved, evaluated, synthesized, and organized the information you need for your literature review. It’s now time to turn that stack of articles, papers, and notes into a literature review–it’s time to start writing!
If you’ve followed the steps in this chapter, you likely have an outline from which you can begin the writing process. But what do you need to include in your literature review? We’ve mentioned it before here, but just to summarize, a literature review should:
…clearly describe the questions that are being asked. They also locate the research within the ongoing scholarly dialogue. This is done by summarizing current understandings and by discussing why what we already knows leads to the need for the present research. Literature reviews also define the primary concepts. While this information can appear in any order, these are the elements in all literature reviews. (Loseke, 2017, p. 61) [1]
Do you have enough facts and sources to accomplish these tasks? It’s a good time to consult your outlines and notes on each article you plan to include in your literature review. You may also want to consult with your professor on what they expect from you. If there is something that you are missing, you may want to jump back to section 2.3 where we discussed how to search for literature on your topic. While you can always fill in material later, there is always the danger that you will start writing without really knowing what you are talking about or what you want to say. For example, if you don’t have a solid definition of your key concepts or a sense of how the literature has developed over time, it will be difficult to make coherent scholarly claims about your topic.
There is no magical point at which everyone is ready to write. As you consider whether you are ready or not, it may be useful to ask yourself these questions:
• How will my literature review be organized?
• What section headings will I be using?
• How do the various studies relate to each other?
• What contributions do they make to the field?
• What are the limitations of a study/where are the gaps in the research?
• And finally, but most importantly, how does my own research fit into what has already been done?\
The problem statement
Many scholarly works begin with a problem statement. The problem statement serves two functions. On one hand, it establishes why your topic is a social problem worth studying. At the same time, it also pulls your reader into the literature review. Who would want to read about something unimportant?
A problem statement generally answers the following questions, though these are far from exhaustive:
• Why is this an important problem to study?
• How many people are affected by the problem?
• How does this problem impact other social issues or target populations relevant to social work?
• Why is your target population an important one to study?
A strong problem statement, like the rest of your literature review, should be filled with facts, theory, and arguments based on the literature you’ve found. A research proposal differs significantly from other more reflective essays you’ve likely completed during your social work studies. If your topic were domestic violence in rural Appalachia in the USA, I’m sure you could come up with answers to the above questions without looking at a single source. However, the purpose of the literature review is not to test your intuition, personal experience, or empathy. Instead, research methods are about learning specific and articulable facts to inform social work action. With a problem statement, you can take a “boring” topic like the color of rooms used in an inpatient psychiatric facility, transportation patterns in major cities, or the materials used to manufacture baby bottles and help others see the topic as you see it—an important part of the social world that impacts social work practice.
The structure of a literature review
The problem statement generally belongs at the beginning of the literature review. Take care not to go on for too long. I usually advise my students to spend no more than a paragraph or two for a problem statement. For the rest of your literature review, there is no set formula for how it should be organized. However, a literature review generally follows the format of any other essay—Introduction, Body, and Conclusion.
The introduction to the literature review contains a statement or statements about the overall topic. At minimum, the introduction should define or identify the general topic, issue, or area of concern. You might consider presenting historical background, mention the results of a seminal study, and provide definitions of important terms. The introduction may also point to overall trends in what has been previously published on the topic or conflicts in theory, methodology, evidence, conclusions, or gaps in research and scholarship. I also suggest putting in a few sentences that walk the reader through the rest of the literature review. Highlight your main arguments from the body of the literature review and preview your conclusion. An introduction should let someone know what to expect from the rest of your review.
The body of your literature review is where you demonstrate your synthesis and analysis of the literature on your topic. Again, take care not to just summarize your literature. I would also caution against organizing your literature review by source—that is, one paragraph for source A, one paragraph for source B, etc. That structure will likely provide an okay summary of the literature you’ve found, but it would give you almost no synthesis of the literature. That approach doesn’t tell your reader how to put those facts together, points of agreement or contention in the literature, or how each study builds on the work of others. In short, it does not demonstrate critical thinking.
Instead, use your outlines and notes as a guide to the important topics you need to cover, and more importantly, what you have to say about those topics. Literature reviews are written from the perspective of an expert on the field. After an exhaustive literature review, you should feel like you are able to make strong claims about what is true—so make them! There is no need to hide behind “I believe” or “I think.” Put your voice out in front, loud and proud! But make sure you have facts and sources that back up your claims.
I’ve used the term “argument” here in a specific way. An argument in writing means more than simply disagreeing with what someone else said. Toulman, Rieke, and Janik (1984) identify six elements of an argument:
1. Claim: the thesis statement—what you are trying to prove
2. Grounds: theoretical or empirical evidence that supports your claim
3. Warrant: your reasoning (rule or principle) connecting the claim and its grounds
4. Backing: further facts used to support or legitimize the warrant
5. Qualifier: acknowledging that the argument may not be true for all cases
6. Rebuttal: considering both sides (as cited in Burnette, 2012) [2]
Let’s walk through an example of an argument. If I were writing a literature review on a negative income tax, a policy in which people in poverty receive an unconditional cash stipend from the government each month equal to the federal poverty level. I would want to lay out the following:
1. Claim: the negative income tax is superior to other forms of anti-poverty assistance.
2. Grounds: data comparing negative income tax recipients to those in existing programs, theory supporting a negative income tax, data from evaluations of existing anti-poverty programs, etc.
3. Warrant: cash-based programs like the negative income tax are superior to existing anti-poverty programs because they allow the recipient greater self-determination over how to spend their money.
4. Backing: data demonstrating the beneficial effects of self-determination on people in poverty.
5. Qualifier: the negative income tax does not provide taxpayers and voters with enough control to make sure people in poverty are not wasting financial assistance on frivolous items.
6. Rebuttal: policy should be about empowering the oppressed, not protecting the taxpayer, and there are ways of addressing taxpayer opposition through policy design.
Like any effective argument, your literature review must have some kind of structure. For example, it might begin by describing a phenomenon in a general way along with several studies that provide some detail, then describing two or more competing theories of the phenomenon, and finally presenting a hypothesis to test one or more of the theories. Or, it might describe one phenomenon, then describe another phenomenon that seems inconsistent with the first one, then propose a theory that resolves the inconsistency, and finally present a hypothesis to test that theory. In applied research, it might describe a phenomenon or theory, then describe how that phenomenon or theory applies to some important real-world situation, and finally suggest a way to test whether it does, in fact, apply to that situation.
Another important issue is signposting. It may not be a term you are familiar with, but you are likely familiar with the concept. Signposting refers to the words used to identify the organization and structure of your literature review to your reader. The most basic form of signposting is using a topic sentence at the beginning of each paragraph. A topic sentence introduces the argument you plan to make in that paragraph. For example, you might start a paragraph stating, “There is strong disagreement in the literature as to whether psychedelic drugs cause psychotic disorders, or whether people with psychotic disorders cause people to use psychedelic drugs.” Within that paragraph, your reader would likely assume you will present evidence for both arguments. The concluding sentence of your paragraph should address the topic sentence, addressing how the facts and arguments from other authors support a specific conclusion. To continue with our example, I might say, “There is likely a reciprocal effect in which both the use of psychedelic drugs worsens pre-psychotic symptoms and worsening psychosis causes use of psychedelic drugs to self-medicate or escape.”
Signposting also involves using headings and subheadings. Your literature review will use APA formatting, which means you need to follow their rules for bolding, capitalization, italicization, and indentation of headings. Headings help your reader understand the structure of your literature review. They can also help if the reader gets lost and needs to re-orient themselves within the document. I often tell my students to assume I know nothing (they don’t mind) and need to be shown exactly where they are addressing each part of the literature review. It’s like walking a small child around, telling them “First we’ll do this, then we’ll do that, and when we’re done, we’ll know this!”
Another way to use signposting is to open each paragraph with a sentence that links the topic of the paragraph with the one before it. Alternatively, one could end each paragraph with a sentence that links it with the next paragraph. For example, imagine we wanted to link a paragraph about barriers to accessing healthcare with one about the relationship between the patient and physician. We could use a transition sentence like this: “Even if patients overcome these barriers to accessing care, the physician-patient relationship can create new barriers to positive health outcomes.” A transition sentence like this builds a connection between two distinct topics. Transition sentences are also useful within paragraphs. They tell the reader how to consider one piece of information in light of previous information. Even simple transitions like however, similarly, and others demonstrate critical thinking and make your arguments clearer.
Many beginning researchers have difficulty with incorporating transitions into their writing. Let’s look at an example. Instead of beginning a sentence or paragraph by launching into a description of a study, such as “Williams (2004) found that…,” it is better to start by indicating something about why you are describing this particular study. Here are some simple examples:
• Another example of this phenomenon comes from the work of Williams (2004).
• Williams (2004) offers one explanation of this phenomenon.
• An alternative perspective has been provided by Williams (2004).
Now that we know to use signposts, the natural question is “What goes on the signposts?” First, it is extremely important to start with an outline of the main points that you want to make, organized in the order that you want to make them. The basic structure of your argument then should be apparent from the outline itself. Unfortunately, there is no formula I can give you that will work for everyone. I can provide some general pointers on structuring your literature review, though.
The literature review generally moves from general ideas to more specific ones. You can build a review by identifying areas of consensus and areas of disagreement. You may choose to present earlier, historical studies—preferably seminal studies that are of significant importance—and close with most recent work. Another approach is to start with the most distantly related facts and literature and then report on those most closely related to your specific research question. You could also compare and contrast valid approaches, features, characteristics, theories – that is, one approach, then a second approach, followed by a third approach.
Here are some additional tips for writing the body of your literature review:
• Start broad and then narrow down to more specific information.
• When appropriate, cite two or more sources for a single point, but avoid long strings of references for a single point.
• Use quotes sparingly. Quotations for definitions are okay, but reserve quotes for when someone says something so well you couldn’t possible phrase it differently. Never use quotes for statistics.
• Paraphrase when you need to relate the specific details within an article, and try to reword it in a way that is understandable to your audience.
• Include only the aspects of the study that are relevant to your literature review. Don’t insert extra facts about a study just to take up space.
• Avoid first-person like language like “I” and “we” to maintain objectivity.
• Avoid informal language like contractions, idioms, and rhetorical questions.
• Note any sections of your review that lack citations and facts from literature. Your arguments need to be based in specific empirical or theoretical facts. Do not approach this like a reflective journal entry.
• Point out consistent findings and emphasize stronger studies over weaker ones.
• Point out important strengths and weaknesses of research studies, as well as contradictions and inconsistent findings.
• Implications and suggestions for further research (where there are gaps in the current literature) should be specific.
The conclusion should summarize your literature review, discuss implications, and create a space for future or further research needed in this area. Your conclusion, like the rest of your literature review, should have a point that you are trying to make. What are the important implications of your literature review? How do they inform the question you are trying to answer?
While you should consult with your professor and their syllabus for the final structure your literature review should take, here is an example of the possible structure for a literature review:
• Problem statement
• o Establish the importance of the topic
• o Number and type of people affected
• o Seriousness of the impact
• o Physical, psychological, economic, social consequences of the problem
• Introduction
• o Definitions of key terms
• o Important arguments you will make
• o Overview of the organization of the rest of the review
• Body of the review
• o Topic 1
• Supporting evidence
• o Topic 2
• Supporting evidence
• o Topic 3
• Supporting evidence
• Conclusion
• o Implications
• o Specific suggestions for future research
• o How your research topic adds to the literature
Here are some additional resources, if you are having trouble putting together your literature review:
Doing a literature review / University of Leicester
Get Lit: The Literature Review / Texas A&M Writing Centre
Editing your literature review
For your literature review, remember that your goal is to construct an argument for why your research question is interesting and worth addressing—not necessarily why your favorite answer to it is correct. As you start editing your literature review, make sure that it is balanced. If you want to emphasize the generally accepted understanding of a phenomenon, then of course you should discuss various studies that have demonstrated it. However, if there are other studies that have found contradictory findings, you should discuss them, too. Or, if you are proposing a new theory, then you should discuss findings that are consistent with that theory. However, if there are other findings that are inconsistent with it, again, you should discuss them too. It is acceptable to argue that the balance of the research supports the existence of a phenomenon or is consistent with a theory (and that is usually the best that researchers in social work can hope for), but it is not acceptable to ignore contradictory evidence. Besides, a large part of what makes a research question interesting is uncertainty about its answer (University of Minnesota, 2016). [3]
In addition to subjectivity and bias, another obstruction to getting your literature review written is writer’s block. Often times, writer’s block can come from confusing the creating and editing parts of the writing process. Many writers often start by simply trying to type out what they want to say, regardless of how good it is. Author Anne Lamott (1995) [4] terms these “shitty first drafts” and we all write them. They are a natural and important part of the writing process. Even if you have a detailed outline to work from, the words are not going to fall into place perfectly the first time you start writing. You should consider turning off the editing and critiquing part of your brain for a little while and allow your thoughts to flow. Don’t worry about putting the correct internal citation when you first write. Just get the information out. Only after you’ve reached a natural stopping point might you go back and edit your draft for grammar, APA formatting, organization, flow, and more. Divorcing the writing and editing process can go a long way to addressing writer’s block—as can picking a topic about which you have something to say!
As you are editing, keep in mind these questions adapted from Green (2012): [5]
• Content: Have I clearly stated the main idea or purpose of the paper and address all the issues? Is the thesis or focus clearly presented and appropriate for the reader?
• Organization: How well is it structured? Is the organization spelled out for the reader and easy to follow?
• Flow: Is there a logical flow from section to section, paragraph to paragraph, sentence to sentence? Are there transitions between and within paragraphs that link ideas together?
• Development: Have I validated the main idea with supporting material? Are supporting data sufficient? Does the conclusion match the introduction?
• Form: Are there any APA style issues, redundancy, problematic wording and terminology (always know the definition of any word you use!), flawed sentence constructions and selection, spelling, and punctuation?
Key Takeaways
• The problem statement draws the reader into your topic by highlighting how important the topic is to social work and overall society.
• Signposting is an important component of academic writing that helps your reader follow the structure of your argument and literature review.
• Transitions demonstrate critical thinking and help guide your reader through your arguments.
• Editing and writing are separate processes.
Glossary
• Signposting- words that identify the organization and structure of a literature review
Image attributions
Startup notebooks by StartupStockPhotos CC-0
Board front problem by geralt CC-0
Person holding white paper and typewriter by Pexels CC-0
Signs direction Bergen by Mariamichelle CC-0
Mistakes by annekarakash CC-0
1. Loseke, D. (2017). Methodological thinking: Basic principles of social research design (2nd ed.). Los Angeles, CA: Sage. ↵
2. Burnett, D. (2012). Inscribing knowledge: Writing research in social work. In W. Green & B. L. Simon (Eds.), The Columbia guide to social work writing (pp. 65-82). New York, NY: Columbia University Press. ↵
3. University of Minnesota Libraries Publishing. (2016). This is a derivative of Research Methods in Psychology by a publisher who has requested that they and the original author not receive attribution, which was originally released and is used under CC BY-NC-SA. This work, unless otherwise expressly stated, is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. ↵
4. Lamott, A. (1995). Bird by bird: Some instructions on writing and life. New York, NY: Penguin. ↵
5. Green, W. Writing strategies for academic papers. In W. Green & B. L. Simon (Eds.), The Columbia guide to social work writing (pp. 25-47). New York, NY: Columbia University Press. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/04%3A_Conducting_a_Literature_Review/4.03%3A_Writing_the_literature_review.txt |
Would it surprise you learn that scientists who conduct research may withhold effective treatments from individuals with diseases? Perhaps it wouldn’t surprise you, since you may have heard of the Tuskegee Syphilis Experiment, in which treatments for syphilis were knowingly withheld from African-American participants for decades. Would it surprise you to learn that the practice of withholding treatment continues today? Multiple studies in the developing world continue to use placebo control groups in testing for cancer screenings, cancer treatments, and HIV treatments (Joffe & Miller, 2014). [1] What standards would you use to judge withholding treatment as ethical or unethical? Most importantly, how can you make sure that your study respects the human rights of your participants?
This chapter discusses or mentions the following topics: unethical research that has occurred in the past against marginalized groups in America and during the Holocaust.
1. Joffe, S., & Miller, F. G. (2014). Ethics of cancer clinical trials in low-resource settings. Journal of Clinical Oncology, 32(28), 3192-3196.
05: Ethics in Social Work Research
Learning Objectives
• Define human subjects research
• Describe and provide examples of nonhuman subjects that researchers might examine
• Define institutional review boards and describe their purpose
• Distinguish between the different levels of review conducted by institutional review boards
In 1998, actor Jim Carey starred in the movie The Truman Show. [1] At first glance, the film appears to depict a perfect research experiment. Just imagine the possibilities if we could control every aspect of a person’s life, from how and where that person lives to where they work to whom they marry. Of course, keeping someone in a bubble, controlling every aspect of their life, and sitting back and watching would be highly unethical (not to mention illegal). However, the movie clearly inspires thoughts about the differences between scientific research and research on nonhumans. One of the most exciting—and most challenging—aspects of conducting social work research is the fact that (at least much of the time) our subjects are living human beings whose free will and human rights will always have an impact on what we are able to research and how we are able to conduct that research.
Human research versus nonhuman research
While all research comes with its own set of ethical concerns, those associated with research conducted on human subjects vary dramatically from those of research conducted on nonliving entities. The US Department of Health and Human Services (USDHHS) defines a human subject as “a living individual about whom an investigator (whether professional or student) conducting research obtains (1) data through intervention or interaction with the individual, or (2) identifiable private information” (USDHHS, 1993, para. 1). [2] Some researchers prefer the term participants to subjects, as it acknowledges the agency of people who participate in the study. For our purposes, we will use the two terms interchangeably.
In some states, human subjects also include deceased individuals and human fetal materials. Nonhuman research subjects, on the other hand, are objects or entities that investigators manipulate or analyze in the process of conducting research. Nonhuman research subjects typically include sources such as newspapers, historical documents, clinical notes, television shows, buildings, and even garbage (to name just a few) that are analyzed for unobtrusive research projects. Unsurprisingly, research on human subjects is regulated much more heavily than research on nonhuman subjects. However, there are ethical considerations that all researchers must consider regardless of their research subject. We’ll discuss those considerations in addition to concerns that are unique to research on human subjects.
A historical look at research on humans
Research on humans hasn’t always been regulated in the way that it is today. The earliest documented cases of research using human subjects are of medical vaccination trials (Rothman, 1987). [3] One such case took place in the late 1700s, when scientist Edward Jenner exposed an 8-year-old boy to smallpox in order to identify a vaccine for the devastating disease. Medical research on human subjects continued without much law or policy intervention until the mid-1900s when, at the end of World War II, a number of Nazi doctors and scientists were put on trial for conducting human experimentation during the course of which they tortured and murdered many concentration camp inmates (Faden & Beauchamp, 1986). [4] The trials, conducted in Nuremberg, Germany, resulted in the creation of the Nuremberg Code, a 10-point set of research principles designed to guide doctors and scientists who conduct research on human subjects. Today, the Nuremberg Code guides medical and other research conducted on human subjects, including social scientific research.
Medical scientists are not the only researchers who have conducted questionable research on humans. In the 1960s, psychologist Stanley Milgram (1974) [5] conducted a series of experiments designed to understand obedience to authority in which he tricked subjects into believing they were administering an electric shock to other subjects. In fact, the shocks weren’t real at all, but some, though not many, of Milgram’s research participants experienced extreme emotional distress after the experiment (Ogden, 2008). [6] A reaction of emotional distress is understandable. The realization that one is willing to administer painful shocks to another human being just because someone who looks authoritative has told you to do so might indeed be traumatizing—even if you later learn that the shocks weren’t real.
Around the same time that Milgram conducted his experiments, sociology graduate student Laud Humphreys (1970) [7] was collecting data for his dissertation research on the tearoom trade, which was the practice of men engaging in anonymous sexual encounters in public restrooms. Humphreys wished to understand who these men were and why they participated in the trade. To conduct his research, Humphreys offered to serve as a “watch queen,” who is the person who keeps an eye out for police and gets the benefit of being able to watch the sexual encounters, in a local park restroom where the tearoom trade was known to occur. What Humphreys did not do was identify himself as a researcher to his research subjects. Instead, he watched his subjects for several months, getting to know several of them, learning more about the tearoom trade practice and, without the knowledge of his research subjects, jotting down their license plate numbers as they pulled into or out of the parking lot near the restroom.
Sometime after participating as a watch queen, with the help of several insiders who had access to motor vehicle registration information, Humphreys used those license plate numbers to obtain the names and home addresses of his research subjects. Then, disguised as a public health researcher, Humphreys visited his subjects in their homes and interviewed them about their lives and their health. Humphreys’ research dispelled a good number of myths and stereotypes about the tearoom trade and its participants. He learned, for example, that over half of his subjects were married to women and many of them did not identify as gay or bisexual. [8]
Once Humphreys’ work became public, the result was some major controversy at his home university (e.g., the chancellor tried to have his degree revoked), among scientists in general, and among members of the public, as it raised public concerns about the purpose and conduct of social science research. In addition, the WashingtonPost journalist Nicholas von Hoffman wrote the following warning about “sociological snoopers”:
We’re so preoccupied with defending our privacy against insurance investigators, dope sleuths, counterespionage men, divorce detectives and credit checkers, that we overlook the social scientists behind the hunting blinds who’re also peeping into what we thought were our most private and secret lives. But they are there, studying us, taking notes, getting to know us, as indifferent as everybody else to the feeling that to be a complete human involves having an aspect of ourselves that’s unknown (von Hoffman, 1970). [9]
In the original version of his report, Humphreys defended the ethics of his actions. In 2008, years after Humphreys’ death, his book was reprinted with the addition of a retrospect on the ethical implications of his work. [10] In his written reflections on his research and the fallout from it, Humphreys maintained that his tearoom observations constituted ethical research on the grounds that those interactions occurred in public places. But Humphreys added that he would conduct the second part of his research differently. Rather than trace license numbers and interview unwitting tearoom participants in their homes under the guise of public health research, Humphreys instead would spend more time in the field and work to cultivate a pool of informants. Those informants would know that he was a researcher and would be able to fully consent to being interviewed. In the end, Humphreys concluded “there is no reason to believe that any research subjects have suffered because of my efforts, or that the resultant demystification of impersonal sex has harmed society” (Humphreys, 2008, p. 231). [10]
Today, given increasing regulation of social scientific research, chances are slim that a researcher would be allowed to conduct a project similar to Humphreys’. Some argue that Humphreys’ research was deceptive, put his subjects at risk of losing their families and their positions in society, and was therefore unethical (Warwick, 1973; Warwick, 1982). [11] Others suggest that Humphreys’ research “did not violate any premise of either beneficence or the sociological interest in social justice” and that the benefits of Humphreys’ research, namely the dissolution of myths about the tearoom trade specifically and human sexual practice more generally, outweigh the potential risks associated with the work (Lenza, 2004, p. 23). [12] What do you think, and why?
These and other studies (Reverby, 2009) [13] led to increasing public awareness of and concern about research on human subjects. In 1974, the US Congress enacted the National Research Act, which created the National Commission for the Protection of Human Subjects in Biomedical and Behavioral Research. The commission produced The Belmont Report, a document outlining basic ethical principles for research on human subjects (National Commission for the Protection of Human Subjects in Biomedical and Behavioral Research, 1979). [14] The National Research Act (1974) [15] also required that all institutions receiving federal support establish institutional review boards (IRBs) to protect the rights of human research subjects. Since that time, many organizations that do not receive federal support but where research is conducted have also established review boards to evaluate the ethics of the research that they conduct.
Institutional Review Boards (IRBs)
Institutional Review Boards, or IRBs, are tasked with ensuring that the rights and welfare of human research subjects will be protected at all institutions, including universities, hospitals, nonprofit research institutions, and other organizations, that receive federal support for research. IRBs typically consist of members from a variety of disciplines, such as sociology, economics, education, social work, and communications (to name a few). Most IRBs also include representatives from the community in which they reside. For example, representatives from nearby prisons, hospitals, or treatment centers might sit on the IRBs of university campuses near them. The diversity of membership helps to ensure that the many and complex ethical issues that may arise from human subjects research will be considered fully and by a knowledgeable and experienced panel. Investigators conducting research on human subjects are required to submit proposals outlining their research plans to IRBs for review and approval prior to beginning their research. Even students who conduct research on human subjects must have their proposed work reviewed and approved by the IRB before beginning any research (though, on some campuses, some exceptions are made for classroom projects that will not be shared outside of the classroom).
The IRB has three levels of review, defined in statute by the USDHHS. Exempt review is the lowest level of review. Studies that are considered exempt expose participants to the least potential for harm and often involves little participation by human subjects. In social work, exempt studies often examine data that is publicly available or secondary data from another researcher that has been de-identified by the person who collected it. Expedited review is the middle level of review. Studies considered under expedited review do not have to go before the full IRB board because they expose participants to minimal risk. However, the studies must be thoroughly reviewed by a member of the IRB committee. While there are many types of studies that qualify for expedited review, the most relevant to social workers include the use of existing medical records, recordings (such as interviews) gathered for research purposes, and research on individual group characteristics or behavior. Finally, the highest level of review is called a full board review. A full board review will involve multiple members of the IRB evaluating your proposal. When researchers submit a proposal under full board review, the full IRB board will meet, discuss any questions or concerns with the study, invite the researcher to answer questions and defend their proposal, and vote to approve the study or send it back for revision. Full board proposals pose greater than minimal risk to participants. They may also involve the participation of vulnerable populations, or people who need additional protection from the IRB. Vulnerable populations include pregnant women, prisoners, children, people with cognitive impairments, people with physical disabilities, employees, and students. While some of these populations can fall under expedited review in some cases, they will often require the full IRB to approve their study.
It may surprise you to hear that IRBs are not always popular or appreciated by researchers. Who wouldn’t want to conduct ethical research, you ask? In some cases, the concern is that IRBs are most well-versed in reviewing biomedical and experimental research, neither of which is particularly common within social work. Much social work research, especially qualitative research, is open ended in nature, a fact that can be problematic for IRBs. The members of IRBs often want to know in advance exactly who will be observed, where, when, and for how long, whether and how they will be approached, exactly what questions they will be asked, and what predictions the researcher has for her findings. Providing this level of detail for a year-long participant observation within an activist group of 200-plus members, for example, would be extraordinarily frustrating for the researcher in the best case and most likely would prove to be impossible. Of course, IRBs do not intend to have researchers avoid studying controversial topics or avoid using certain methodologically sound data collection techniques, but unfortunately, that is sometimes the result. The solution is not to do away with review boards, which serve a necessary and important function, but instead to help educate IRB members about the variety of social scientific research methods and topics covered by social workers and other social scientists.
Key Takeaways
• Research on human subjects presents a unique set of challenges and opportunities when it comes to conducting ethical research.
• Research on human subjects has not always been regulated to the extent that it is today.
• All institutions receiving federal support for research must have an IRB. Organizations that do not receive federal support but where research is conducted also often include IRBs as part of their organizational structure.
• Researchers submit studies for IRB review at one of three different levels, depending on the level of harm the study may cause.
Glossary
• Exempt review- lowest level of IRB review, for studies for studies with minimal risk or human subject involvement
• Expedited review- middle level of IRB review, for studies with minimal risk but greater human subject involvement
• Full board review- highest level of IRB, for studies with greater than minimal risk to participants
• Vulnerable populations- groups of people who receive additional protection during IRB review
Image attributions
ethics by Tumisu CC-0
roundtable meeting by Debora Cartagena CC-0
1. You can read a brief synopsis of the film at [1]http://www.imdb.com/title/tt0120382. ↵
2. US Department of Health and Human Services. (1993). Institutional review board guidebook glossary. Retrieved from https://ori.hhs.gov/education/products/ucla/chapter2/page00b.htm
3. Rothman, D. J. (1987). Ethics and human experimentation. The New England Journal of Medicine, 317, 1195–1199. ↵
4. One little-known fact, as described by Faden and Beauchamp in their 1986 book, is that at the very time that the Nazis conducted their horrendous experiments, Germany did actually have written regulations specifying that human subjects must clearly and willingly consent to their participation in medical research. Obviously these regulations were completely disregarded by the Nazi experimenters, but the fact that they existed suggests that efforts to regulate the ethical conduct of research, while necessary, are certainly not sufficient for ensuring that human subjects’ rights will be honored. Faden, R. R., & Beauchamp, T. L. (1986). A history and theory of informed consent. Oxford, UK: Oxford University Press. ↵
5. Milgram, S. (1974). Obedience to authority: An experimental view. New York, NY: Harper & Row. ↵
6. Ogden, R. (2008). Harm. In L. M. Given (Ed.), The sage encyclopedia of qualitative research methods (p. 379–380). Los Angeles, CA: Sage. ↵
7. Humphreys, L. (1970). Tearoom trade: Impersonal sex in public places. London, UK: Duckworth. ↵
8. Humphreys’s research is still relevant today. In fact, as the 2007 arrest of Idaho Senator Larry Craig in a public restroom at the Minneapolis–St. Paul airport attests, undercover police operations targeting tearoom activities still occur, more than 40 years after Humphreys conducted his research. Humphreys’s research is also frequently cited by attorneys who represent clients arrested for lewd behavior in public restrooms. ↵
9. von Hoffman, N. (1970, January 30). Sociological snoopers. The Washington Post, p. B1. ↵
10. Humphreys, L. (2008). Tearoom trade: Impersonal sex in public places, enlarged edition with a retrospect on ethical issues. New Brunswick, NJ: Aldine Transaction. ↵
11. Warwick, D. P. (1973). Tearoom trade: Means and ends in social research. Hastings Center Studies, 1, 39–49. See also Warwick, D. P. (1982). Types of harm in social research. In T. L. Beauchamp, R. R. Faden, R. J. Wallace Jr., & L. Walters (Eds.), Ethical issues in social science research. Baltimore, MD: Johns Hopkins University Press. ↵
12. Lenza, M. (2004). Controversies surrounding Laud Humphreys’ tearoom trade: An unsettling example of politics and power in methodological critiques. International Journal of Sociology and Social Policy, 24, 20–31. See also Nardi, P. M. (1995). “The breastplate of righteousness”: Twenty- five years after Laud Humphreys’ Tearoomtrade: Impersonal sex in public places. Journalof Homosexuality, 30, 1–10. ↵
13. One such study is the Tuskegee Syphilis Experiment, conducted in Alabama from the 1930s to the 1970s. The goal of the study was to understand the natural progression of syphilis in human beings. Investigators working for the Public Health Service enrolled hundreds of poor African American men in the study, some of whom had been diagnosed with syphilis and others who had not. Even after effective syphilis treatment was identified in the 1940s, research participants were denied treatment so that researchers could continue to observe the progression of the disease. The study came to an end in 1972 after knowledge of the experiment became public. In 1997, President Clinton publicly apologized on behalf of the American people for the study (clinton4.nara.gov/textonly/New/Remarks/Fri/19970516-898.html). For more on the Tuskegee Syphilis Experiment, see Reverby, S. M. (2009). Examining Tuskegee: The infamous syphilis study and its legacy. Chapel Hill, NC: University of North Carolina Press. ↵
14. National Commission for the Protection of Human Subjects in Biomedical and Behavioral Research. (1979). The Belmont report: Ethical principles and guidelines for the protection of human subjects of research. Retrieved from https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/index.html
15. National Research Act of 1974, Pub. L. no. 93-348 Stat 88. (1974). The act can be read at history.nih.gov/research/downloads/PL93-348.pdf↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/05%3A_Ethics_in_Social_Work_Research/5.01%3A_Research_on_humans.txt |
Learning Objectives
• Define informed consent, and describe how it works
• Identify the unique concerns related to the study of vulnerable populations
• Differentiate between anonymity and confidentiality
• Explain the ethical responsibilities of social workers conducting research
As should be clear by now, conducting research on humans presents a number of unique ethical considerations. Human research subjects must be given the opportunity to consent to their participation in research, fully informed of the study’s risks, benefits, and purpose. Further, subjects’ identities and the information they share should be protected by researchers. Of course, how consent and identity protection are defined may vary by individual researcher, institution, or academic discipline. In section 5.1, we examined the role that institutions play in shaping research ethics. In this section, we’ll take a look at a few specific topics that individual researchers and social workers in general must consider before embarking on research with human subjects.
Informed consent
A norm of voluntary participation is presumed in all social work research projects. In other words, we cannot force anyone to participate in our research without that person’s knowledge or consent (so much for that Truman Show experiment). Researchers must therefore design procedures to obtain subjects’ informed consent to participate in their research. Informed consent is defined as a subject’s voluntary agreement to participate in research based on a full understanding of the research and of the possible risks and benefits involved. Although it sounds simple, ensuring that one has actually obtained informed consent is a much more complex process than you might initially presume.
The first requirement is that, in giving their informed consent, subjects may neither waive nor even appear to waive any of their legal rights. Subjects also cannot release a researcher, her sponsor, or institution from any legal liability should something go wrong during the course of their participation in the research (USDHHS,2009). [1] Because social work research does not typically involve asking subjects to place themselves at risk of physical harm by, for example, taking untested drugs or consenting to new medical procedures, social work researchers do not often worry about potential liability associated with their research projects. However, their research may involve other types of risks.
For example, what if a social work researcher fails to sufficiently conceal the identity of a subject who admits to participating in a local swinger’s club? In this case, a violation of confidentiality may negatively affect the participant’s social standing, marriage, custody rights, or employment. Social work research may also involve asking about intimately personal topics, such as trauma or suicide that may be difficult for participants to discuss. Participants may re-experience traumatic events and symptoms when they participate in your study. Even if you are careful to fully inform your participants of all risks before they consent to the research process, I’m sure you can empathize with thinking you could bear talking about a difficult topic and then finding it too overwhelming once you start. In cases like these, it is important for a social work researcher to have a plan to provide supports. This may mean providing referrals to counseling supports in the community or even calling the police if the participants is an imminent danger to themselves or others.
It is vital that social work researchers explain their mandatory reporting duties in the consent form and ensure participants understand them before they participate. Researchers should also emphasize to participants that they can stop the research process at any time or decide to withdraw from the research study for any reason. Importantly, it is not the job of the social work researcher to act as a clinician to the participant. While a supportive role is certainly appropriate for someone experiencing a mental health crisis, social workers must ethically avoid dual roles. Referring a participant in crisis to other mental health professionals who may be better able to help them is preferred.
Beyond the legal issues, most IRBs require researchers to share some details about the purpose of the research, possible benefits of participation, and, most importantly, possible risks associated with participating in that research with their subjects. In addition, researchers must describe how they will protect subjects’ identities, how, where, and for how long any data collected will be stored, and whom to contact for additional information about the study or about subjects’ rights. All this information is typically shared in an informed consent form that researchers provide to subjects. In some cases, subjects are asked to sign the consent form indicating that they have read it and fully understand its contents. In other cases, subjects are simply provided a copy of the consent form and researchers are responsible for making sure that subjects have read and understand the form before proceeding with any kind of data collection. Figure 5.1 showcases a sample informed consent form taken from a research project on child-free adults. Note that this consent form describes a risk that may be unique to the particular method of data collection being employed: focus groups.
Figure 5.1 Sample informed consent form
One last point to consider when preparing to obtain informed consent is that not all potential research subjects are considered equally competent or legally allowed to consent to participate in research. Subjects from vulnerable populations may be at risk of experiencing undue influence or coercion. [3] The rules for consent are more stringent for vulnerable populations. For example, minors must have the consent of a legal guardian in order to participate in research. In some cases, the minors themselves are also asked to participate in the consent process by signing special, age-appropriate consent forms designed specifically for them. Prisoners and parolees also qualify as vulnerable populations. Concern about the vulnerability of these subjects comes from the very real possibility that prisoners and parolees could perceive that they will receive some highly desired reward, such as early release, if they participate in research. Another potential concern regarding vulnerable populations is that they may be underrepresented in research, and even denied potential benefits of participation in research, specifically because of concerns about their ability to consent. So, on the one hand, researchers must take extra care to ensure that their procedures for obtaining consent from vulnerable populations are not coercive. The procedures for receiving approval to conduct research on these groups may be more rigorous than that for non-vulnerable populations. On the other hand, researchers must work to avoid excluding members of vulnerable populations from participation simply on the grounds that they are vulnerable or that obtaining their consent may be more complex. While there is no easy solution to this double-edged sword, an awareness of the potential concerns associated with research on vulnerable populations is important for identifying whatever solution is most appropriate for a specific case.
Protection of identities
As mentioned earlier, the informed consent process includes the requirement that researchers outline how they will protect the identities of subjects. This aspect of the process, however, is one of the most commonly misunderstood aspects of research.
In protecting subjects’ identities, researchers typically promise to maintain either the anonymity or confidentiality of their research subjects. Anonymity is the more stringent of the two. When a researcher promises anonymity to participants, not even the researcher is able to link participants’ data with their identities. Anonymity may be impossible for some social work researchers to promise because several of the modes of data collection that social workers employ. Face-to-face interviewing means that subjects will be visible to researchers and will hold a conversation, making anonymity impossible. In other cases, the researcher may have a signed consent form or obtain personal information on a survey and will therefore know the identities of their research participants. In these cases, a researcher should be able to at least promise confidentiality to participants.
Offering confidentiality means that some identifying information on one’s subjects is known and may be kept, but only the researcher can link participants with their data and she promises not to do so publicly. Confidentiality in research is quite similar to confidentiality in clinical practice. You know who your clients are, but others do not. You agree to keep their information and identity private. As you can see under the “Risks” section of the consent form in Figure 5.1, sometimes it is not even possible to promise that a subject’s confidentiality will be maintained. This is the case if data are collected in public or in the presence of other research participants in the course of a focus group, for example. Participants who social work researchers deem to be of imminent danger to self or others or those that disclose abuse of children and other vulnerable populations fall under a social worker’s duty to report. Researchers must then violate confidentiality to fulfill their legal obligations.
Protecting research participants’ identities is not always a simple prospect, especially for those conducting research on stigmatized groups or illegal behaviors. Sociologist Scott DeMuth learned that all too well when conducting his dissertation research on a group of animal rights activists. As a participant observer, DeMuth knew the identities of his research subjects. So when some of his research subjects vandalized facilities and removed animals from several research labs at the University of Iowa, a grand jury called on Mr. DeMuth to reveal the identities of the participants in the raid. When DeMuth refused to do so, he was jailed briefly and then charged with conspiracy to commit animal enterprise terrorism and cause damage to the animal enterprise (Jaschik, 2009). [4]
Publicly, DeMuth’s case raised many of the same questions as Laud Humphreys’ work 40 years earlier. What do social scientists owe the public? Is DeMuth, by protecting his research subjects, harming those whose labs were vandalized? Is he harming the taxpayers who funded those labs? Or is it more important that DeMuth emphasize what he owes his research subjects, who were told their identities would be protected? DeMuth’s case also sparked controversy among academics, some of whom thought that as an academic himself, DeMuth should have been more sympathetic to the plight of the faculty and students who lost years of research as a result of the attack on their labs. Many others stood by DeMuth, arguing that the personal and academic freedom of scholars must be protected whether we support their research topics and subjects or not. DeMuth’s academic adviser even created a new group, Scholars for Academic Justice (http://sajumn.wordpress.com), to support DeMuth and other academics who face persecution or prosecution as a result of the research they conduct. What do you think? Should DeMuth have revealed the identities of his research subjects? Why or why not?
Disciplinary considerations
Often times, specific disciplines will provide their own set of guidelines for protecting research subjects and, more generally, for conducting ethical research. For social workers, the National Association of Social Workers (NASW) Code of Ethics section 5.02 describes the responsibilities of social workers in conducting research. Summarized below, these responsibilities are framed as part of a social worker’s responsibility to the profession. As representative of the social work profession, it is your responsibility to conduct and use research in an ethical manner.
A social worker should:
• Monitor and evaluate policies, programs, and practice interventions
• Contribute to the development of knowledge through research
• Keep current with the best available research evidence to inform practice
• Ensure voluntary and fully informed consent of all participants
• Not engage in any deception in the research process
• Allow participants to withdraw from the study at any time
• Provide access for participants to appropriate supportive services
• Protect research participants from harm
• Maintain confidentiality
• Report findings accurately
• Disclose any conflicts of interest
Key Takeaways
• Researchers must obtain the informed consent of the people who participate in their research.
• Social workers must take steps to minimize the harms that could arise during the research process.
• If a researcher promises anonymity, she cannot link individual participants with their data.
• If a researcher promises confidentiality, she promises not to reveal the identities of research participants, even though she can link individual participants with their data.
• The NASW Code of Ethics includes specific responsibilities for social work researchers.
Glossary
• Anonymity- the identity of research participants is not known to researchers
• Confidentiality- identifying information about research participants is known to the researchers but is not divulged to anyone else
• Informed consent- a research subject’s voluntary agreement to participate in a study based on a full understanding of the study and of the possible risks and benefits involved
Image attributions
consent by Catkin CC-0
Anonymous by kalhh CC-0
1. US Department of Health and Human Services. (2009). Code of federal regulations (45 CFR 46). The full set of requirements for informed consent can be read at https://www.hhs.gov/ohrp/regulations-and-policy/regulations/45-cfr-46/index.html
2. Figure 5.1 is copied from Blackstone, A. (2012) Principles of sociological inquiry: Qualitative and quantitative methods. Saylor Foundation. Retrieved from: https://saylordotorg.github.io/text_...ative-methods/ Shared under CC-BY-NC-SA 3.0 License (https://creativecommons.org/licenses/by-nc-sa/3.0/) ↵
3. The US Department of Health and Human Services’ guidelines on vulnerable populations can be read at www.hhs.gov/ohrp/regulations-and-policy/guidance/vulnerable-populations/index.html.↵
4. Jaschik, S. (2009, December 4). Protecting his sources. InsideHigher Ed. Retrieved from: http://www.insidehighered.com/news/2009/12/04/demuth | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/05%3A_Ethics_in_Social_Work_Research/5.02%3A_Specific_ethical_issues_to_consider.txt |
Learning Objectives
• Identify and distinguish between micro-, meso-, and macro-level considerations with respect to the ethical conduct of social scientific research
One useful way to think about the breadth of ethical questions that might arise out of any research project is to think about potential issues from the perspective of different analytical levels. In Chapter 1, you learned about the micro-, meso-, and macro-levels of inquiry and how a researcher’s specific point of focus might vary depending on her level of inquiry. Here we’ll apply this ecological framework to a discussion of research ethics. Within most research projects, there are specific questions that arise for researchers at each of these three levels.
At the micro-level, researchers must consider their own conduct and the rights of individual research participants. For example, did Stanley Milgram behave ethically when he allowed research participants to think that they were administering electronic shocks to fellow participants? Did Laud Humphreys behave ethically when he deceived his research subjects about his own identity? Were the rights of individuals in these studies protected? The questions posed here are the sort that you will want to ask yourself as a researcher when considering ethics at the micro-level.
At the meso-level, researchers should think about their duty to the community. How will the results of your study impact your target population? Ideally, your results will benefit your target population by identifying important areas for social workers to intervene. However, it is possible that your study may perpetuate negative stereotypes about your target population or damage its reputation. Indigenous people in particular have highlighted how historically social science has furthered marginalization of indigenous peoples (Smith, 2013). [1] In addition to your target population, you must also consider your responsibilities to the profession of social work. When you engage in social work research, you stand on the reputation the profession has built for over a century. Attending to research ethics helps to fulfill your responsibilities to the profession, in addition to your target population.
Finally, at the macro-level, a researcher should consider her duty to, and the expectations of, society. Perhaps the most high-profile case involving macro-level questions of research ethics comes from debates over whether to use data gathered by, or cite published studies based on data gathered from, the Nazis in the course of their unethical and horrendous experiments on humans during World War II (Moe, 1984). [2] Some argue that because the data were gathered in such an unquestionably unethical manner, they should never be used. Further, some who argue against using the Nazi data point out that not only were the experiments immoral but the methods used to collect data were also scientifically questionable. The data, say these people, are neither valid nor reliable and should therefore not be used in any current scientific investigation (Berger, 1990). [3]
On the other hand, some people argue that data themselves are neutral; that “information gathered is independent of the ethics of the methods and that the two are not linked together” (Pozos, 1992, p. 104). [4] Others point out that not using the data could inadvertently strengthen the claims of those who deny that the Holocaust ever happened. In his striking statement in support of publishing the data, medical ethics professor Velvl Greene (1992) says,
Instead of banning the Nazi data or assigning it to some archivist or custodial committee, I maintain that it be exhumed, printed, and disseminated to every medical school in the world along with the details of methodology and the names of the doctors who did it, whether or not they were indicted, acquitted, or hanged.…Let the students and the residents and the young doctors know that this was not ancient history or an episode from a horror movie where the actors get up after filming and prepare for another role. It was real. It happened yesterday (p. 169–170). [5]
While debates about the use of data collected by the Nazis are typically centered on medical scientists’ use of them, there are conceivable circumstances under which these data might be used by social scientists. Perhaps, for example, a social scientist might wish to examine contemporary reactions to the experiments. Or perhaps the data could be used in a study of the sociology of science. What do you think? Should data gathered by the Nazis be used or cited today? What arguments can you make in support of your position, and how would you respond to those who disagree? Table 5.1 summarizes the key questions that researchers might ask themselves about the ethics of their research at each level of inquiry.
Table 5.1 Key ethics questions at three different levels of inquiry
Level of inquiry Focus Key ethics questions for researchers to ask themselves
Micro-level Individual Does my research impinge on the individual’s right to privacy?
Could my research offend subjects in any way?
Could my research cause emotional distress to any of my subjects?
Has my own conduct been ethical throughout the research process?
Meso-level Group Does my research follow the ethical guidelines of my profession and discipline?
Could my research negatively impact a community?
Have I met my duty to those who funded my research?
Macro-level Society Does my research meet the societal expectations of social research?
Have I met my social responsibilities as a researcher?
Key Takeaways
• At the micro-level, researchers should consider their own conduct and the rights of individual research participants.
• At the meso-level, researchers should consider the expectations of their profession, any organizations that may have funded their research, and the communities affected by their research.
• At the macro-level, researchers should consider their duty to and the expectations of society with respect to social scientific research.
1. Smith, L. T. (2013). Decolonizing methodologies: Research and indigenous peoples (2nd edition). London: Zed Books, Ltd. ↵
2. Moe, K. (1984). Should the Nazi research data be cited? TheHastings Center Report, 14, 5–7. ↵
3. Berger, P. L. (1990). Nazi science: The Dachau hypothermia experiments. New England Journal of Medicine, 322, 1435–1440. ↵
4. Pozos, R. S. (1992). Scientific inquiry and ethics: The Dachau data. In A. L. Caplan (Ed.), When medicine went mad: Bioethics and the Holocaust (p. 104). Totowa, NJ: Humana Press. ↵
5. Greene, V. W. (1992). Can scientists use information derived from the concentration camps? Ancient answers to new questions. In A. L. Caplan (Ed.), When medicine went mad: Bioethics and the Holocaust (p. 169–170). Totowa, NJ: Humana Press. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/05%3A_Ethics_in_Social_Work_Research/5.03%3A_Ethics_at_micro%2C_meso%2C_and_macro_levels.txt |
Learning Objectives
• Identify why researchers must provide a detailed description of methodology
• Describe what it means to use science in an ethical way
Research ethics has to do with both how research is conducted and how findings from that research are used. In this section, we’ll consider research ethics from both angles.
Doing science the ethical way
As you should now be aware, researchers must consider their own personal ethical principles in addition to following those of their institution, their discipline, and their community. We’ve already considered many of the ways that social workers strive to ensure the ethical practice of research, such as informing and protecting subjects. But the practice of ethical research doesn’t end once subjects have been identified and data have been collected. Social workers must also fully disclose their research procedures and findings. This means being honest about how research subjects were identified and recruited, how exactly data were collected and analyzed, and ultimately, what findings were reached.
If researchers fully disclose how they conducted their research, then those who use their work to build research projects, create social policies, or make decisions can have confidence in the work. By sharing how research was conducted, a researcher helps assure readers she has conducted legitimate research and didn’t simply come to whatever conclusions she wanted to find. A description or presentation of research findings that is not accompanied by information about research methodology is missing some relevant information. Sometimes methodological details are left out because there isn’t time or space to share them. This is often the case with news reports of research findings. Other times, there may be a more insidious reason that that important information isn’t there. This may be the case if sharing methodological details would call the legitimacy of a study into question. As researchers, it is our ethical responsibility to fully disclose our research procedures. As consumers of research, it is our ethical responsibility to pay attention to such details. We’ll discuss this more in the next section.
There’s a New Yorker cartoon (www.art.com/products/p15063407512-sa-i6847806/dana-fradon-filing-cabinets-labeled-our-facts-their-facts-neutral-facts-disput-new-yorker-cartoon.htm?upi=PGQTTQ0) that depicts a set of filing cabinets that aptly demonstrates what we don’t want to see happen with research. Each filing cabinet drawer in the cartoon is labeled differently. The labels include such headings as, “Our Facts,” “Their Facts,” “Neutral Facts,” “Disputable Facts,” “Absolute Facts,” “Bare Facts,” “Unsubstantiated Facts,” and “Indisputable Facts.” The implication of this cartoon is that one might just choose to open the file drawer of her choice and pick whichever facts one likes best. While this may occur if we use some of the unscientific ways of knowing described in Chapter 1, it is fortunately not how the discovery of facts works in social work or in any other science for that matter. There actually is a method to this madness we call research.
Honesty in research is facilitated by the scientific principle of replication. Ideally, this means that one scientist could repeat another’s study with relative ease. By replicating a study, we may become more (or less) confident in the original study’s findings. Replication is far more difficult (perhaps impossible) to achieve in the case of ethnographic studies that last months or years, but it nevertheless sets an important standard for all social scientific researchers—that we provide as much detail as possible about the processes by which we reach our conclusions.
Full disclosure also includes the need to be honest about a study’s strengths and weaknesses, both with oneself and with others. Being aware of the strengths and weaknesses of your own work can help a researcher make reasonable recommendations about the next steps other researchers might consider taking in their inquiries. Awareness and disclosure of a study’s strengths and weaknesses can also help highlight the theoretical or policy implications of one’s work. In addition, openness about strengths and weaknesses helps those reading the research better evaluate the work and decide for themselves how or whether to rely on its findings. Finally, openness about a study’s sponsors is crucial. How can we effectively evaluate research without knowing who paid the bills?
The standard of replicability along with openness about a study’s strengths, weaknesses, and funders enable those who read the research to evaluate it fairly and completely. Knowledge of funding sources is often raised as an issue in medical research. Understandably, independent studies of new drugs may be more compelling to the Food and Drug Administration (FDA) than studies touting the virtues of a new drug that happen to have been funded by the company who created that drug. But medical researchers aren’t the only ones who need to be honest about their funding. If we know, for example, that a political think tank with ties to a particular party has funded some research, we can take that knowledge into consideration when reviewing the study’s findings and stated policy implications. Lastly, and related to this point, we must consider how, by whom, and for what purpose research may be used.
Using science the ethical way
Science has many uses. By “use” I mean the ways that science is understood and applied (as opposed to the way it is conducted). Some use science to create laws and social policies; others use it to understand themselves and those around them. Some people rely on science to improve their life conditions or those of other people, while still others use it to improve their businesses or other undertakings. In each case, the most ethical way for us to use science is to educate ourselves about the design and purpose of any studies we may wish to use or apply, to recognize our limitations in terms of scientific and methodological knowledge and how those limitations may impact our understanding of research, and to apply the findings of scientific investigation only in cases or to populations for which they are actually relevant.
Social scientists who conduct research on behalf of organizations and agencies may face additional ethical questions about the use of their research, particularly when the organization for which a study is conducted controls the final report and the publicity it receives. There is a potential conflict of interest for evaluation researchers who are employees of the agency being evaluated. A similar conflict of interest might exist between independent researchers whose work is being funded by some government agency or private foundation.
So who decides what constitutes ethical conduct or use of research? Perhaps we all do. What qualifies as ethical research may shift over time and across cultures as individual researchers; disciplinary organizations; members of society; and regulatory entities, such as institutional review boards, courts, and lawmakers all work to define the boundaries between ethical and unethical research.
Key Takeaways
• Conducting research ethically requires that researchers be ethical not only in their data collection procedures but also in reporting their methods and findings.
• The ethical use of research requires an effort to understand research, an awareness of your own limitations in terms of knowledge and understanding, and the honest application of research findings.
Image attributions
honesty by GDJ CC-0 | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/05%3A_Ethics_in_Social_Work_Research/5.04%3A_The_practice_of_science_versus_the_uses_of_science.txt |
In this chapter, we’ll explore the connections between paradigms, social theories, and social scientific research methods. We’ll also consider how our analytic, paradigmatic, and theoretical perspective might shape or be shaped by our methodological choices. In short, we’ll answer the question of what theory has to do with research methods.
This chapter discusses or mentions the following topics: laws regulating rape, sodomy, and child sexual abuse; gang communication styles; racism, policing, and lynching; domestic violence and sexual harassment; and substance abuse.
06: Linking Methods with Theory
Learning Objectives
• Describe a micro-level approach to research, and provide an example of a micro-level study
• Describe a meso-level approach to research, and provide an example of a meso-level study
• Describe a macro-level approach to research, and provide an example of a macro-level study
In Chapter 1, we reviewed the micro, meso, and macro framework that social workers use to understand the world. As you’ll recall, micro-level research studies individuals and one-on-one interactions, meso-level research studies groups, and macro-level research studies institutions and policies. Let’s take a closer look at some specific examples of social work research to better understand each of the three levels of inquiry described previously. Some topics are best suited to be examined at one specific level, while other topics can be studied at each of the three different levels. The particular level of inquiry might shape a social worker’s questions about the topic, or a social scientist might view the topic from different angles depending on the level of inquiry being employed.
First, let’s consider some examples of different topics that are best suited to a particular level of inquiry. Work by Stephen Marks offers an excellent example of research at the micro-level. In one study, Marks and Shelley MacDermid (1996) [1] draw from prior micro-level theories to empirically study how people balance their roles and identities. In this study, the researchers found that people who experience balance across their multiple roles and activities report lower levels of depression and higher levels of self-esteem and well-being than their less-balanced counterparts. In another study, Marks and colleagues examined the conditions under which husbands and wives feel the most balance across their many roles. They found that different factors are important for different genders. For women, having more paid work hours and more couple time were among the most important factors. For men, having leisure time with their nuclear families was important, and role balance decreased as work hours increased (Marks, Huston, Johnson, & MacDermid, 2001). [2] Both of these studies fall within the category of micro-level analysis.
At the meso-level, social scientists tend to study the experiences of groups and the interactions between groups. In a recent book based on their research with Somali immigrants, Kim Huisman and colleagues (Huisman, Hough, Langellier, & Toner, 2011) [3] examine the interactions between Somalis and Americans in Maine. These researchers found that stereotypes about refugees being unable or unwilling to assimilate and being overly dependent on local social systems are unsubstantiated. In a much different study of group-level interactions, Michael Messner (2009) [4] conducted research on children’s sports leagues. Messner studied interactions among parent volunteers, among youth participants, and between league organizers and parents and found that gender boundaries and hierarchies are perpetuated by the adults who run such leagues. These two studies, while very different in their specific points of focus, have in common their meso-level focus.
Social workers who conduct macro-level research study interactions at the broadest level, such as interactions between and across nations, states, or cultural systems. One example of macro-level research can be seen in a recent article by David Frank and colleagues (Frank, Camp, & Boutcher, 2010). [5] These researchers examined worldwide changes over time in laws regulating sex. By comparing laws across a number of countries over a period of many years (1945–2005), Frank learned that laws regulating rape, adultery, sodomy, and child sexual abuse shifted in focus from protecting larger entities, such as families, to protecting individuals. In another macro-level study, Leah Ruppanner (2010) [6] studied how national levels of gender equality in 25 different countries affect couples’ divisions of housework. Ruppanner found that as women’s parliamentary representation increases, so does men’s participation in housework.
While it is true that some topics lend themselves to a particular level of inquiry, there are many topics that could be studied from any of the three levels. The choice depends on the specific interest of the researcher, the approach she would like to take and the sorts of questions she wants to be able to answer about the topic.
Let’s look at an example. Gang activity has been a topic of interest to social workers for many years and has been studied from each of the levels of inquiry described here. At the micro-level, social workers might study the inner workings of a specific gang, communication styles, and what everyday life is like for gang members. Though not written by a social worker, one example of a micro-level analysis of gang activity can be found in Sanyika Shakur’s 1993 autobiography, Monster. [7] In his book, Shakur describes his former day-to-day life as a member of the Crips in South-Central Los Angeles. Shakur’s recounting of his experiences highlights micro-level interactions between himself, fellow Crips members, and other gangs.
At the meso-level, social workers are likely to examine interactions between gangs or perhaps how different branches of the same gang vary from one area to the next. At the macro-level, we could compare the impact of gang activity across communities or examine the economic impact of gangs on nations. Excellent examples of gang research at all three levels of analysis can be found in the Journal of Gang Research published by the National Gang Crime Research Center (NGCRC). [8] Sudhir Venkatesh’s (2008) study, Gang Leader for aDay, [9] is an example of research on gangs that utilizes all three levels of analysis. Venkatesh conducted participant observation with a gang in Chicago. He learned about the everyday lives of gang members (micro) and how the gang he studied interacted with and fit within the landscape of other gang “franchises” (meso). In addition, Venkatesh described the impact of the gang on the broader community and economy (macro).
Key Takeaways
• Social work research can occur at any of the following three analytical levels: micro, meso, or macro.
• Some topics lend themselves to one particular analytical level, while others could be studied from any, or all, of the three levels of analysis.
1. Marks, S. R., & MacDermid, S. M. (1996). Multiple roles and the self: A theory of role balance. Journalof Marriage and the Family, 58, 417–432. ↵
2. Marks, S. R., Huston, T. L., Johnson, E. M., & MacDermid, S. M. (2001). Role balance among white married couples. Journal of Marriage and the Family, 63, 1083–1098. ↵
3. Huisman, K. A., Hough, M., Langellier, K. M., & Toner, C. N. (2011). Somalis in Maine: Crossing cultural currents. New York, NY: Random House. ↵
4. Messner, M. A. (2009). It’s all for the kids: Gender, families, and youth sports. Berkeley, CA: University of California Press. ↵
5. Frank, D., Camp, B., & Boutcher, S. (2010). Worldwide trends in the criminal regulation of sex, 1945–2005. American Sociological Review, 75, 867–893. ↵
6. Ruppanner, L. E. (2010). Cross-national reports of housework: An investigation of the gender empowerment measure. Social Science Research, 39, 963–975. ↵
7. Shakur, S. (1993). Monster:The autobiography of an L.A. gang member. New York, NY: Atlantic Monthly Press. ↵
8. The Journal of Gang Research is the official publication of the National Gang Crime Research Center (NGCRC). You can learn more about the NGCRC and the journal at [1]http://www.ngcrc.com. ↵
9. Venkatesh, S. (2008). Gang leader for a day: A rogue sociologist takes to the streets. New York, NY: Penguin Group. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/06%3A_Linking_Methods_with_Theory/6.01%3A_Micro%2C_meso%2C_and_macro_approaches.txt |
Learning Objectives
• Define paradigm, and describe the significance of paradigms
• Identify and describe the four predominant paradigms found in the social sciences
• Define theory
• Describe the role that theory plays in social work research
The terms paradigm and theory are often used interchangeably in social science, although social scientists do not always agree whether these are identical or distinct concepts. In this text, I will make a clear distinction between the two ideas because thinking about each concept as analytically distinct provides a useful framework for understanding the connections between research methods and social scientific ways of thinking.
Paradigms in social science
For our purposes, we’ll define paradigm as a way of viewing the world (or “analytic lens” akin to a set of glasses) and a framework from which to understand the human experience (Kuhn, 1962). [1] It can be difficult to fully grasp the idea of paradigmatic assumptions because we are very ingrained in our own, personal everyday way of thinking. For example, let’s look at people’s views on abortion. To some, abortion is a medical procedure that should be undertaken at the discretion of each individual woman. To others, abortion is murder and members of society should collectively have the right to decide when, if at all, abortion should be undertaken. Chances are, if you have an opinion about this topic, you are pretty certain about the veracity of your perspective. Then again, the person who sits next to you in class may have a very different opinion and yet be equally confident about the truth of their perspective. Who is correct?
You are each operating under a set of assumptions about the way the world does—or at least should—work. Perhaps your assumptions come from your political perspective, which helps shape your view on a variety of social issues, or perhaps your assumptions are based on what you learned from your parents or in church. In any case, there is a paradigm that shapes your stance on the issue. Those paradigms are a set of assumptions. Your classmate might assume that life begins at conception and the fetus’ life should be at the center of moral analysis. Conversely, you may assume that life begins when the fetus is viable outside the womb and that a mother’s choice is more important than a fetus’s life. There is no way to scientifically test when life begins, whose interests are more important, or the value of choice. They are merely philosophical assumptions or beliefs. Thus, a pro-life paradigm may rest in part on a belief in divine morality and fetal rights. A pro-choice paradigm may rest on a mother’s self-determination and a belief that the positive consequences of abortion outweigh the negative ones. These beliefs and assumptions influence how we think about any aspect of the issue.
In Chapter 1, we discussed the various ways that we know what we know. Paradigms are a way of framing what we know, what we can know, and how we can know it. In social science, there are several predominant paradigms, each with its own unique ontological and epistemological perspective. Recall that ontology is the study of what is real, and epistemology is the study of how we come to know what is real. Let’s look at four of the most common social scientific paradigms that might guide you as you begin to think about conducting research.
The first paradigm we’ll consider, called positivism, is the framework that likely comes to mind for many of you when you think of science. Positivism is guided by the principles of objectivity, knowability, and deductive logic. Deductive logic is discussed in more detail in next section of this chapter. The positivist framework operates from the assumption that society can and should be studied empirically and scientifically. Positivism also calls for a value-free science, one in which researchers aim to abandon their biases and values in a quest for objective, empirical, and knowable truth.
Another predominant paradigm in social work is social constructionism. Peter Berger and Thomas Luckman (1966) [2] are credited by many for having developed this perspective in sociology. While positivists seek “the truth,” the social constructionist framework posits that “truth” varies. Truth is different based on who you ask, and people change their definitions of truth all the time based on their interactions with other people. This is because we, according to this paradigm, create reality ourselves (as opposed to it simply existing and us working to discover it) through our interactions and our interpretations of those interactions. Key to the social constructionist perspective is the idea that social context and interaction frame our realities.
Researchers operating within this framework take keen interest in how people come to socially agree, or disagree, about what is real and true. Consideration of how meanings of different hand gestures vary across different regions of the world aptly demonstrates that meanings are constructed socially and collectively. Think about what it means to you when you see a person raise their middle finger. We probably all know that person isn’t very happy (nor is the person to whom the finger is being directed). In some societies, it is another gesture, such as the thumbs up gesture, that raises eyebrows. While the thumbs up gesture may have a particular meaning in North American culture, that meaning is not shared across cultures (Wong, 2007). [3] So, what is the “truth” of the middle finger or thumbs up? It depends on what the person giving it intended, how the person receiving it interpreted it, and the social context in which the action occurred.
It would be a mistake to think of the social constructionist perspective as only individualistic. While individuals may construct their own realities, groups—from a small one such as a married couple to large ones such as nations—often agree on notions of what is true and what “is.” In other words, the meanings that we construct have power beyond the individual people who create them. Therefore, the ways that people and communities work to create and change such meanings is of as much interest to social constructionists as how they were created in the first place.
A third paradigm is the critical paradigm. At its core, the critical paradigm is focused on power, inequality, and social change. Although some rather diverse perspectives are included here, the critical paradigm, in general, includes ideas developed by early social theorists, such as Max Horkheimer (Calhoun, Gerteis, Moody, Pfaff, & Virk, 2007), [4] and later works developed by feminist scholars, such as Nancy Fraser (1989). [5] Unlike the positivist paradigm, the critical paradigm posits that social science can never be truly objective or value-free. Further, this paradigm operates from the perspective that scientific investigation should be conducted with the express goal of social change in mind. Researchers in the critical paradigm might start with the knowledge that systems are biased against, for example, women or ethnic minorities. Moreover, their research projects are designed not only to collect data, but also change the participants in the research as well as the systems being studied. The critical paradigm not only studies power imbalances but seeks to change those power imbalances.
Finally, postmodernism is a paradigm that challenges almost every way of knowing that many social scientists take for granted (Best & Kellner, 1991). [6] While positivists claim that there is an objective, knowable truth, postmodernists would say that there is not. While social constructionists may argue that truth is in the eye of the beholder (or in the eye of the group that agrees on it), postmodernists may claim that we can never really know such truth because, in the studying and reporting of others’ truths, the researcher stamps their own truth on the investigation. Finally, while the critical paradigm may argue that power, inequality, and change shape reality and truth, a postmodernist may in turn ask whose power, whose inequality, whose change, whose reality, and whose truth. As you might imagine, the postmodernist paradigm poses quite a challenge for researchers. How do you study something that may or may not be real or that is only real in your current and unique experience of it? This fascinating question is worth pondering as you begin to think about conducting your own research. Part of the value of the postmodern paradigm is its emphasis on the limitations of human knowledge. Table 6.1 summarizes each of the paradigms discussed here.
Table 6.1 Social scientific paradigms
Paradigm Emphasis Assumption
Positivism Objectivity, knowability, and deductive logic Society can and should be studied empirically and scientifically.
Social Constructionism Truth as varying, socially constructed, and ever-changing Reality is created collectively. Social context and interaction frame our realities.
Critical Power, inequality, and social change Social science can never be truly value-free and should be conducted with the express goal of social change in mind.
Postmodernism Inherent problems with previous paradigms. Truth is always bound within historical and cultural context. There are no universally true explanations.
Let’s work through an example. If we are examining a problem like substance abuse, what would a social scientific investigation look like in each paradigm? A positivist study may focus on precisely measuring substance abuse and finding out the key causes of substance abuse during adolescence. Forgoing the objectivity of precisely measuring substance abuse, social constructionist study might focus on how people who abuse substances understand their lives and relationships with various drugs of abuse. In so doing, it seeks out the subjective truth of each participant in the study. A study from the critical paradigm would investigate how people who have substance abuse problems are an oppressed group in society and seek to liberate them from external sources of oppression, like punitive drug laws, and internal sources of oppression, like internalized fear and shame. A postmodern study may involve one person’s self-reported journey into substance abuse and changes that occurred in their self-perception that accompanied their transition from recreational to problematic drug use. These examples should illustrate how one topic can be investigated across each paradigm.
Social science theories
Much like paradigms, theories provide a way of looking at the world and of understanding human interaction. Paradigms are grounded in big assumptions about the world—what is real, how do we create knowledge—whereas theories describe more specific phenomena. A common definition for theory in social work is “a systematic set of interrelated statements intended to explain some aspect of social life” (Rubin & Babbie, 2017, p. 615). [7] At their core, theories can be used to provide explanations of any number or variety of phenomena. They help us answer the “why” questions we often have about the patterns we observe in social life. Theories also often help us answer our “how” questions. While paradigms may point us in a particular direction with respect to our “why” questions, theories more specifically map out the explanation, or the “how,” behind the “why.”
Introductory social work textbooks introduce students to the major theories in social work—conflict theory, symbolic interactionism, social exchange theory, and systems theory. As social workers study longer, they are introduced to more specific theories in their area of focus, as well as perspectives and models (e.g., the strengths perspective), which provide more practice-focused approaches to understanding social work.
As you will probably recall from a class on social work theory, systems theorists view all parts of society as interconnected and focus on the relationships, boundaries, and flows of energy between these systems and subsystems (Schriver, 2011). [8] Conflict theorists are interested in questions of power and who wins and who loses based on the way that society is organized. Symbolic interactionists focus on how meaning is created and negotiated through meaningful (i.e., symbolic) interactions. Finally, social exchange theorists examine how human beings base their behavior on a rational calculation of rewards and costs.
Just as researchers might examine the same topic from different levels of inquiry or paradigms, they could also investigate the same topic from different theoretical perspectives. In this case, even their research questions could be the same, but the way they make sense of whatever phenomenon it is they are investigating will be shaped in large part by theory. Table 6.2 summarizes the major points of focus for each of major four theories and outlines how a researcher might approach the study of the same topic, in this case the study of substance abuse, from each of the three perspectives.
Table 6.2 Social work theories and the study of substance abuse
Theory Focuses on A study of substance abuse might examine
Systems Interrelations between parts of society; how parts work together How a lack of employment opportunities might impact rates of substance abuse in an area
Conflict Who wins and who loses based on the way that society is organized How the War on Drugs has impacted minority communities
Symbolic Interactionism How meaning is created and negotiated though interactions How people’s self-definitions as “addicts” helps or hurts their ability to remain sober
Social Exchange How behavior is influenced by costs and rewards Whether increased distribution of anti-overdose medications makes overdose more or less likely
Within each area of specialization in social work, there are many other theories that aim to explain more specific types of interactions. For example, within the study of sexual harassment, different theories posit different explanations for why harassment occurs. One theory, first developed by criminologists, is called routine activities theory. It posits that sexual harassment is most likely to occur when a workplace lacks unified groups and when potentially vulnerable targets and motivated offenders are both present (DeCoster, Estes, & Mueller, 1999). [9] Other theories of sexual harassment, called relational theories, suggest that a person’s relationships, such as their marriages or friendships, are the key to understanding why and how workplace sexual harassment occurs and how people will respond to it when it does occur (Morgan, 1999). [10] Relational theories focus on the power that different social relationships provide (e.g., married people who have supportive partners at home might be more likely than those who lack support at home to report sexual harassment when it occurs). Finally, feminist theories of sexual harassment take a different stance. These theories posit that the way our current gender system is organized, where those who are the most masculine have the most power, best explains why and how workplace sexual harassment occurs (MacKinnon, 1979). [11] As you might imagine, which theory a researcher applies to examine the topic of sexual harassment will shape the questions the researcher asks about harassment. It will also shape the explanations the researcher provides for why harassment occurs.
For an undergraduate student beginning their study of a new topic, it may be intimidating to learn that there are so many theories beyond what you’ve learned in your theory classes. What’s worse is that there is no central database of different theories on your topic. However, as you review the literature in your topic area, you will learn more about the theories that scientists have created to explain how your topic works in the real world. In addition to peer-reviewed journal articles, another good source of theories is a book about your topic. Books often contain works of theoretical and philosophical importance that are beyond the scope of an academic journal.
Paradigm and theory in social work
Theories, paradigms, levels of analysis, and the order in which one proceeds in the research process all play an important role in shaping what we ask about the social world, how we ask it, and in some cases, even what we are likely to find. A micro-level study of gangs will look much different than a macro-level study of gangs. In some cases, you could apply multiple levels of analysis to your investigation, but doing so isn’t always practical or feasible. Therefore, understanding the different levels of analysis and being aware of which level you happen to be employing is crucial. One’s theoretical perspective will also shape a study. In particular, the theory invoked will likely shape not only the way a question about a topic is asked but also which topic gets investigated in the first place. Further, if you find yourself especially committed to one theory over another, it may limit the kinds of questions you pose. As a result, you may miss other possible explanations.
The limitations of paradigms and theories do not mean that social science is fundamentally biased. At the same time, we can never claim to be entirely value free. Social constructionists and postmodernists might point out that bias is always a part of research to at least some degree. Our job as researchers is to recognize and address our biases as part of the research process, if an imperfect part. We all use our own approaches, be they theories, levels of analysis, or temporal processes, to frame and conduct our work. Understanding those frames and approaches is crucial not only for successfully embarking upon and completing any research-based investigation, but also for responsibly reading and understanding others’ work.
Key Takeaways
• Paradigms shape our everyday view of the world.
• Researchers use theory to help frame their research questions and to help them make sense of the answers to those questions.
• Applying the four key theories of social work is a good start, but you will likely have to look for more specific theories about your topic.
Glossary
• Critical paradigm- a paradigm in social science research focused on power, inequality, and social change
• Paradigm- a way of viewing the world and a framework from which to understand the human experience
• Positivism- a paradigm guided by the principles of objectivity, knowability, and deductive logic
• Postmodernism- a paradigm focused on the historical and contextual embeddedness of scientific knowledge and a skepticism towards certainty and grand explanations in social science
• Social constructionism- a paradigm based on the idea that social context and interaction frame our realities
• Theory- “a systematic set of interrelated statements intended to explain some aspect of social life” (Rubin & Babbie, 2017, p. 615)
Image attributions
point mold and cloud mold by tasaikensuke CC-0
why by GDJ CC-0
1. See Kuhn’s seminal work for more on paradigms: Kuhn, T. (1962). The structure of scientific revolutions. Chicago, IL: University of Chicago Press. ↵
2. Berger, P. L., & Luckman, T. (1966). The social construction of reality: A treatise in the sociology of knowledge. New York, NY: Doubleday. ↵
3. For more about how the meanings of hand gestures vary by region, you might read the following blog entry: Wong, W. (2007). The top 10 hand gestures you’d better get right. Retrieved from http://www.languagetrainers.co.uk/blog/2007/09/24/top-10-hand-gestures
4. Calhoun, C., Gerteis, J., Moody, J., Pfaff, S., & Virk, I. (Eds.). (2007). Classical sociological theory (2nd ed.). Malden, MA: Blackwell. ↵
5. Fraser, N. (1989). Unruly practices: Power, discourse, and gender in contemporary social theory. Minneapolis, MN: University of Minnesota Press. ↵
6. Best, S., & Kellner, D. (1991). Postmodern theory: Critical interrogations. New York, NY: Guilford. ↵
7. Rubin, A., and Babbie, E. R. (2017). Research methods for social work (9th ed.). Belmont: Wadsworth ↵
8. Schriver, J. M. (2011). Human behavior and the social environment: Shifting paradigms in essential knowledge for social work practice (5th ed.) Boston, MA: Pearson. ↵
9. DeCoster, S., Estes, S. B., & Mueller, C. W. (1999). Routine activities and sexual harassment in the workplace. Work andOccupations, 26, 21–49. ↵
10. Morgan, P. A. (1999). Risking relationships: Understanding the litigation choices of sexually harassed women. The Law and Society Review, 33, 201–226. ↵
11. MacKinnon, C. 1979. Sexual harassment of working women: A case of sex discrimination. New Haven, CT: Yale University Press. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/06%3A_Linking_Methods_with_Theory/6.02%3A_Paradigms%2C_theories%2C_and_how_they_shape_a_researcher%E2%80%99s_approach.txt |
Learning Objectives
• Describe the inductive approach to research, and provide examples of inductive research
• Describe the deductive approach to research, and provide examples of deductive research
• Describe the ways that inductive and deductive approaches may be complementary
Theories structure and inform social work research. So, too, does research structure and inform theory. The reciprocal relationship between theory and research often becomes evident to students new to these topics when they consider the relationships between theory and research in inductive and deductive approaches to research. In both cases, theory is crucial. But the relationship between theory and research differs for each approach.
Inductive and deductive approaches to research are quite different, but they can also be complementary. Let’s start by looking at each one and how they differ from one another. Then we’ll move on to thinking about how they complement one another.
Inductive approaches and some examples
In an inductive approach to research, a researcher begins by collecting data that is relevant to her topic of interest. Once a substantial amount of data have been collected, the researcher will then take a breather from data collection, stepping back to get a bird’s eye view of their data. At this stage, the researcher looks for patterns in the data, working to develop a theory that could explain those patterns. Thus, when researchers take an inductive approach, they start with a set of observations and then they move from those particular experiences to a more general set of propositions about those experiences. In other words, they move from data to theory, or from the specific to the general. Figure 6.1 outlines the steps involved with an inductive approach to research.
Figure 6.1 Inductive research
There are many good examples of inductive research, but we’ll look at just a few here. One fascinating study in which the researchers took an inductive approach is Katherine Allen, Christine Kaestle, and Abbie Goldberg’s (2011) study [1] of how boys and young men learn about menstruation. To understand this process, Allen and her colleagues analyzed the written narratives of 23 young men in which the men described how they learned about menstruation, what they thought of it when they first learned about it, and what they think of it now. By looking for patterns across all 23 men’s narratives, the researchers were able to develop a general theory of how boys and young men learn about this aspect of girls’ and women’s biology. They conclude that sisters play an important role in boys’ early understanding of menstruation, that menstruation makes boys feel somewhat separated from girls, and that as they enter young adulthood and form romantic relationships, young men develop more mature attitudes about menstruation. Note how this study began with the data—men’s narratives of learning about menstruation—and tried to develop a theory.
In another inductive study, Kristin Ferguson and colleagues (Ferguson, Kim, & McCoy, 2011) [2] analyzed empirical data to better understand how best to meet the needs of young people who are homeless. The authors analyzed data from focus groups with 20 young people at a homeless shelter. From these data they developed a set of recommendations for those interested in applied interventions that serve homeless youth. The researchers also developed hypotheses for people who might wish to conduct further investigation of the topic. Though Ferguson and her colleagues did not test the hypotheses that they developed from their analysis, their study ends where most deductive investigations begin: with a theory and a hypothesis derived from that theory.
Deductive approaches and some examples
Researchers taking a deductive approach take the steps described earlier for inductive research and reverse their order. They start with a social theory that they find compelling and then test its implications with data. That is, they move from a more general level to a more specific one. A deductive approach to research is the one that people typically associate with scientific investigation. The researcher studies what others have done, reads existing theories of whatever phenomenon she is studying, and then tests hypotheses that emerge from those theories. Figure 6.2 outlines the steps involved with a deductive approach to research.
Figure 6.2 Deductive research
While not all researchers follow a deductive approach, as you have seen in the preceding discussion, many do, and there are a number of excellent recent examples of deductive research. We’ll take a look at a couple of those next.
In a study of US law enforcement responses to hate crimes, Ryan King and colleagues (King, Messner, & Baller, 2009) [3] hypothesized that law enforcement’s response would be less vigorous in areas of the country that had a stronger history of racial violence. The authors developed their hypothesis from their reading of prior research and theories on the topic. They tested the hypothesis by analyzing data on states’ lynching histories and hate crime responses. Overall, the authors found support for their hypothesis. One might associate this research with critical theory.
In another recent deductive study, Melissa Milkie and Catharine Warner (2011) [4] studied the effects of different classroom environments on first graders’ mental health. Based on prior research and theory, Milkie and Warner hypothesized that negative classroom features, such as a lack of basic supplies and even heat, would be associated with emotional and behavioral problems in children. One might associate this research with systems theory. The researchers found support for their hypothesis, demonstrating that policymakers should probably be paying more attention to the mental health outcomes of children’s school experiences, just as they track academic outcomes (American Sociological Association, 2011). [5]
Complementary approaches
While inductive and deductive approaches to research seem quite different, they can actually be rather complementary. In some cases, researchers will plan for their study to include multiple components, one inductive and the other deductive. In other cases, a researcher might begin a study with the plan to only conduct either inductive or deductive research, but then discovers along the way that the other approach is needed to help illuminate findings. Here is an example of each such case.
The original author of the textbook from which this textbook is adapted, Dr. Amy Blackstone, relates a story about her collaborative research on sexual harassment.
We began the study knowing that we would like to take both a deductive and an inductive approach in our work. We therefore administered a quantitative survey, the responses to which we could analyze in order to test hypotheses, and also conducted qualitative interviews with a number of the survey participants. The survey data were well suited to a deductive approach; we could analyze those data to test hypotheses that were generated based on theories of harassment. The interview data were well suited to an inductive approach; we looked for patterns across the interviews and then tried to make sense of those patterns by theorizing about them.
For one paper (Uggen & Blackstone, 2004), [6] we began with a prominent feminist theory of the sexual harassment of adult women and developed a set of hypotheses outlining how we expected the theory to apply in the case of younger women’s and men’s harassment experiences. We then tested our hypotheses by analyzing the survey data. In general, we found support for the theory that posited that the current gender system, in which heteronormative men wield the most power in the workplace, explained workplace sexual harassment—not just of adult women but of younger women and men as well. In a more recent paper (Blackstone, Houle, & Uggen, 2006), [7] we did not hypothesize about what we might find but instead inductively analyzed interview data, looking for patterns that might tell us something about how or whether workers’ perceptions of harassment change as they age and gain workplace experience. From this analysis, we determined that workers’ perceptions of harassment did indeed shift as they gained experience and that their later definitions of harassment were more stringent than those they held during adolescence. Overall, our desire to understand young workers’ harassment experiences fully—in terms of their objective workplace experiences, their perceptions of those experiences, and their stories of their experiences—led us to adopt both deductive and inductive approaches in the work. (Blackstone, n.d., p. 21)
Researchers may not always set out to employ both approaches in their work but sometimes find that their use of one approach leads them to the other. One such example is described eloquently in Russell Schutt’s Investigating the Social World (2006). [8] As Schutt describes, researchers Lawrence Sherman and Richard Berk (1984) [9] conducted an experiment to test two competing theories of the effects of punishment on deterring deviance (in this case, domestic violence). Specifically, Sherman and Berk hypothesized that deterrencetheory would provide a better explanation of the effects of arresting accused batterers than labeling theory. Deterrence theory predicts that arresting an accused spouse batterer will reduce future incidents of violence. Conversely, labeling theory predicts that arresting accused spouse batterers will increase future incidents. Figure 6.3 summarizes the two competing theories and the predictions that Sherman and Berk set out to test.
Figure 6.3 Predicting the effects of arrest on future spouse battery
Sherman and Berk found, after conducting an experiment with the help of local police in one city, that arrest did in fact deter future incidents of violence, thus supporting their hypothesis that deterrence theory would better predict the effect of arrest. After conducting this research, they and other researchers went on to conduct similar experiments [10] in six additional cities (Berk, Campbell, Klap, & Western, 1992; Pate & Hamilton, 1992; Sherman & Smith, 1992). [11] Results from these follow-up studies were mixed. In some cases, arrest deterred future incidents of violence. In other cases, it did not. This left the researchers with new data that they needed to explain. The researchers therefore took an inductive approach in an effort to make sense of their latest empirical observations. The new studies revealed that arrest seemed to have a deterrent effect for those who were married and employed, but that it led to increased offenses for those who were unmarried and unemployed. Researchers thus turned to control theory, which predicts that having some stake in conformity through the social ties provided by marriage and employment, as the better explanation.
Figure 6.4 Predicting the effects of arrest on future spouse battery: A new theory
What the Sherman and Berk research, along with the follow-up studies, shows us is that we might start with a deductive approach to research, but then, if confronted by new data that we must make sense of, we may move to an inductive approach.
Key Takeaways
• The inductive approach begins with a set of empirical observations, seeking patterns in those observations, and then theorizing about those patterns.
• The deductive approach begins with a theory, developing hypotheses from that theory, and then collecting and analyzing data to test those hypotheses.
• Inductive and deductive approaches to research can be employed together for a more complete understanding of the topic that a researcher is studying.
• Though researchers don’t always set out to use both inductive and deductive strategies in their work, they sometimes find that new questions arise in the course of an investigation that can best be answered by employing both approaches.
Glossary
• Deductive approach- study what others have done, reads existing theories of whatever phenomenon she is studying, and then tests hypotheses that emerge from those theories
• Inductive approach- start with a set of observations and then move from particular experiences to a more general set of propositions about those experiences
1. Allen, K. R., Kaestle, C. E., & Goldberg, A. E. (2011). More than just a punctuation mark: How boys and young men learn about menstruation. Journal of Family Issues, 32, 129–156. ↵
2. Ferguson, K. M., Kim, M. A., & McCoy, S. (2011). Enhancing empowerment and leadership among homeless youth in agency and community settings: A grounded theory approach. Child and Adolescent Social Work Journal, 28, 1–22. ↵
3. King, R. D., Messner, S. F., & Baller, R. D. (2009). Contemporary hate crimes, law enforcement, and the legacy of racial violence. AmericanSociological Review, 74, 291–315. ↵
4. Milkie, M. A., & Warner, C. H. (2011). Classroom learning environments and the mental health of first grade children. Journal of Health andSocial Behavior, 52, 4–22. ↵
5. The American Sociological Association wrote a press release on Milkie and Warner’s findings: American Sociological Association. (2011). Study: Negative classroom environment adversely affects children’s mental health. Retrieved from: www.sciencedaily.com/releases/2011/03/110309073717.htm↵
6. Uggen, C., & Blackstone, A. (2004). Sexual harassment as a gendered expression of power. AmericanSociological Review, 69, 64–92. ↵
7. Blackstone, A., Houle, J., & Uggen, C. “At the time I thought it was great”: Age, experience, and workers’ perceptions of sexual harassment. Presented at the 2006 meetings of the American Sociological Association. ↵
8. Schutt, R. K. (2006). Investigating the social world: The process and practice of research. Thousand Oaks, CA: Pine Forge Press. ↵
9. Sherman, L. W., & Berk, R. A. (1984). The specific deterrent effects of arrest for domestic assault. American Sociological Review, 49, 261–272. ↵
10. The researchers did what’s called replication. ↵
11. Berk, R., Campbell, A., Klap, R., & Western, B. (1992). The deterrent effect of arrest in incidents of domestic violence: A Bayesian analysis of four field experiments. American Sociological Review, 57, 698–708; Pate, A., & Hamilton, E. (1992). Formal and informal deterrents to domestic violence: The Dade county spouse assault experiment. American Sociological Review, 57, 691–697; Sherman, L., & Smith, D. (1992). Crime, punishment, and stake in conformity: Legal and informal control of domestic violence. American Sociological Review, 57, 680–690. ↵
12. All figures in this section are copied from Blackstone, A. (2012) Principles of sociological inquiry: Qualitative and quantitative methods. Saylor Foundation. Retrieved from: https://saylordotorg.github.io/text_...ative-methods/ Shared under CC-BY-NC-SA 3.0 License (https://creativecommons.org/licenses/by-nc-sa/3.0/) ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/06%3A_Linking_Methods_with_Theory/6.03%3A_Inductive_and_deductive_reasoning.txt |
The last chapter oriented you to the theories relevant to your topic area; the macro, meso, or micro levels of analysis; and the assumptions or paradigms of research. This chapter will use these elements to help you conceptualize and design your research project. You will make specific choices about the purpose of your research, quantitative or qualitative methods, and establishing causality. You’ll also learn how and why researchers use both qualitative and quantitative methods in the same study.
This chapter discusses or mentions the following topics: child neglect and abuse, sexual harassment, the criminal justice system, homelessness, sexual and domestic violence, depression, and substance abuse.
07: Design and causality
Learning Objectives
• Differentiate among exploratory, descriptive, and explanatory research studies
A recent news story about college students’ addictions to electronic gadgets (Lisk, 2011) [1] describes findings from some current research by Professor Susan Moeller and colleagues from the University of Maryland (http://withoutmedia.wordpress.com). The story raises a number of interesting questions. Just what sorts of gadgets are students addicted to? How do these addictions work? Why do they exist, and who is most likely to experience them?
Social science research is great for answering just these sorts of questions. But in order to answer our questions well, we must take care in designing our research projects. In this chapter, we’ll consider what aspects of a research project should be considered at the beginning, including specifying the goals of the research, the components that are common across most research projects, and a few other considerations.
One of the first things to think about when designing a research project is what you hope to accomplish, in very general terms, by conducting the research. What do you hope to be able to say about your topic? Do you hope to gain a deep understanding of whatever phenomenon it is that you’re studying, or would you rather have a broad, but perhaps less deep, understanding? Do you want your research to be used by policymakers or others to shape social life, or is this project more about exploring your curiosities? Your answers to each of these questions will shape your research design.
Exploration, description, and explanation
You’ll need to decide in the beginning phases whether your research will be exploratory, descriptive, or explanatory. Each has a different purpose, so how you design your research project will be determined in part by this decision.
Researchers conducting exploratory research are typically at the early stages of examining their topics. These sorts of projects are usually conducted when a researcher wants to test the feasibility of conducting a more extensive study and to figure out the “lay of the land” with respect to the particular topic. Perhaps very little prior research has been conducted on this subject. If this is the case, a researcher may wish to do some exploratory work to learn what method to use in collecting data, how best to approach research subjects, or even what sorts of questions are reasonable to ask. A researcher wanting to simply satisfy her own curiosity about a topic could also conduct exploratory research. In the case of the study of college students’ addictions to their electronic gadgets, a researcher conducting exploratory research on this topic may simply wish to learn more about students’ use of these gadgets. Because these addictions seem to be a relatively new phenomenon, an exploratory study of the topic might make sense as an initial first step toward understanding it.
It is important to note that exploratory designs do not make sense for topic areas with a lot of existing research. For example, the question “What are common interventions for parents who neglect their children?” would not make much sense as a research question. One could simply look at journal articles and textbooks to see what interventions are commonly used with this population. Exploratory questions are best suited to topics that have not been studied. Students may sometimes say there is not much literature on their chosen topic, when there is in fact a large body of literature on that topic. However, that said, there are a few students each semester who pick a topic for which there is little existing research. Perhaps, if you were looking at child neglect interventions for parents who identify as transgender or parents who are refugees from the Syrian civil war, less would be known about child neglect for those specific populations. In that case, an exploratory design would make sense as there is less literature to guide your study.
Another purpose of research is to describe or define a particular phenomenon, termed descriptive research. For example, a social work researcher may want to understand what it means to be a first-generation college student or a resident in a psychiatric group home. In this case, descriptive research would be an appropriate strategy. A descriptive study of college students’ addictions to their electronic gadgets, for example, might aim to describe patterns in how many hours students use gadgets or which sorts of gadgets students tend to use most regularly.
Researchers at the Princeton Review conduct descriptive research each year when they set out to provide students and their parents with information about colleges and universities around the United States. They describe the social life at a school, the cost of admission, and student-to-faculty ratios (to name just a few of the categories reported). Although students and parents may be able to obtain much of this information on their own, having access to the data gathered by a team of researchers is much more convenient and less time consuming.
Social workers often rely on descriptive research to tell them about their service area. Keeping track of the number of children receiving foster care services, their demographic makeup (e.g., race, gender), and length of time in care are excellent examples of descriptive research. On a more macro-level, the Centers for Disease Control provides a remarkable amount of descriptive research on mental and physical health conditions. In fact, descriptive research has many useful applications, and you probably rely on findings from descriptive research without even being aware that that is what you are doing.
Finally, social work researchers often aim to explain why particular phenomena work in the way that they do. Research that answers “why” questions is referred to as explanatory research. In this case, the researcher is trying to identify the causes and effects of whatever phenomenon she is studying. An explanatory study of college students’ addictions to their electronic gadgets might aim to understand why students become addicted. Does it have anything to do with their family histories? With their other extracurricular hobbies and activities? With whom they spend their time? An explanatory study could answer these kinds of questions.
There are numerous examples of explanatory social scientific investigations. For example, in a recent study, Dominique Simons and Sandy Wurtele (2010) [2] sought to discover whether receiving corporal punishment from parents led children to turn to violence in solving their interpersonal conflicts with other children. In their study of 102 families with children between the ages of 3 and 7, the researchers found that experiencing frequent spanking did, in fact, result in children being more likely to accept aggressive problem-solving techniques. Another example of explanatory research can be seen in Robert Faris and Diane Felmlee’s (2011) [3] research study on the connections between popularity and bullying. From their study of 8th, 9th, and 10th graders in 19 North Carolina schools, they found that aggression increased as adolescents’ popularity increased. [4]
The choice between descriptive, exploratory, and explanatory research should be made with your research question in mind. What does your question ask? Are you trying to learn the basics about a new area, establish a clear “why” relationship, or define or describe an activity or concept? In the next section, we will explore how each type of research is associated with different methods, paradigms, and forms of logic.
Key Takeaways
• Exploratory research is usually conducted when a researcher has just begun an investigation and wishes to understand the topic generally.
• Descriptive research is research that aims to describe or define the topic at hand.
• Explanatory research is research that aims to explain why particular phenomena work in the way that they do.
Glossary
• Descriptive research- research that describes or define a particular phenomenon
• Explanatory research- explains why particular phenomena work in the way that they do, answers “why” questions
• Exploratory research- conducted during the early stages of a project, usually when a researcher wants to test the feasibility of conducting a more extensive study
Image attributions
Pencil by kaboompics CC-0
Two men and one woman in a photo by Rawpixel.com CC-0
1. Lisk, J. (2011). Addiction to our electronic gadgets. Retrieved from: https://www.youtube.com/watch?v=9lVHZZG5qvw
2. Simons, D. A., & Wurtele, S. K. (2010). Relationships between parents’ use of corporal punishment and their children’s endorsement of spanking and hitting other children. Child Abuse & Neglect, 34, 639–646. ↵
3. Faris, R., & Felmlee, D. (2011). Status struggles: Network centrality and gender segregation in same- and cross-gender aggression. American Sociological Review, 76, 48–73. The study has also been covered by several media outlets: Pappas, S. (2011). Popularity increases aggression in kids, study finds. Retrieved from: http://www.livescience.com/11737-popularity-increases-aggression-kids-study-finds.html
4. This pattern was found until adolescents reached the top 2% in the popularity ranks. After that, aggression declines. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/07%3A_Design_and_causality/7.01%3A_Types_of_research.txt |
Learning Objectives
• Define and provide an example of idiographic and nomothetic causal relationships
• Describe the role of causality in quantitative research as compared to qualitative research
• Identify, define, and describe each of the main criteria for nomothetic causal relationships
• Describe the difference between and provide examples of independent, dependent, and control variables
• Define hypothesis, be able to state a clear hypothesis, and discuss the respective roles of quantitative and qualitative research when it comes to hypotheses
Most social scientific studies attempt to provide some kind of causal explanation. A study on an intervention to prevent child abuse is trying to draw a connection between the intervention and changes in child abuse. Causality refers to the idea that one event, behavior, or belief will result in the occurrence of another, subsequent event, behavior, or belief. In other words, it is about cause and effect. It seems simple, but you may be surprised to learn there is more than one way to explain how one thing causes another. How can that be? How could there be many ways to understand causality?
Think back to our chapter on paradigms, which were analytic lenses comprised of assumptions about the world. You’ll remember the positivist paradigm as the one that believes in objectivity and social constructionist paradigm as the one that believes in subjectivity. Both paradigms are correct, though incomplete, viewpoints on the social world and social science.
A researcher operating in the social constructionist paradigm would view truth as subjective. In causality, that means that in order to try to understand what caused what, we would need to report what people tell us. Well, that seems pretty straightforward, right? Well, what if two different people saw the same event from the exact same viewpoint and came up with two totally different explanations about what caused what? A social constructionist would say that both people are correct. There is not one singular truth that is true for everyone, but many truths created and shared by people.
When social constructionists engage in science, they are trying to establish one type of causality—idiographic causality. An idiographiccausal explanation means that you will attempt to explain or describe your phenomenon exhaustively, based on the subjective understandings of your participants. These explanations are bound with the narratives people create about their lives and experience, and are embedded in a cultural, historical, and environmental context. Idiographic causal explanations are so powerful because they convey a deep understanding of a phenomenon and its context. From a social constructionist perspective, the truth is messy. Idiographic research involves finding patterns and themes in the causal relationships established by your research participants.
If that doesn’t sound like what you normally think of as “science,” you’re not alone. Although the ideas behind idiographic research are quite old in philosophy, they were only applied to the sciences at the start of the last century. If we think of famous scientists like Newton or Darwin, they never saw truth as subjective. There were objectively true laws of science that were applicable in all situations. Another paradigm was dominant and continues its dominance today, the positivist paradigm. When positivists try to establish causality, they are like Newton and Darwin, trying to come up with a broad, sweeping explanation that is universally true for all people. This is the hallmark of a nomothetic causal explanation.
Nomothetic causal explanations are also incredibly powerful. They allow scientists to make predictions about what will happen in the future, with a certain margin of error. Moreover, they allow scientists to generalize—that is, make claims about a large population based on a smaller sample of people or items. Generalizing is important. We clearly do not have time to ask everyone their opinion on a topic, nor do we have the ability to look at every interaction in the social world. We need a type of causal explanation that helps us predict and estimate truth in all situations.
If these still seem like obscure philosophy terms, let’s consider an example. Imagine you are working for a community-based non-profit agency serving people with disabilities. You are putting together a report to help lobby the state government for additional funding for community support programs, and you need to support your argument for additional funding at your agency. If you looked at nomothetic research, you might learn how previous studies have shown that, in general, community-based programs like yours are linked with better health and employment outcomes for people with disabilities. Nomothetic research seeks to explain that community-based programs are better for everyone with disabilities. If you looked at idiographic research, you would get stories and experiences of people in community-based programs. These individual stories are full of detail about the lived experience of being in a community-based program. Using idiographic research, you can understand what it’s like to be a person with a disability and then communicate that to the state government. For example, a person might say “I feel at home when I’m at this agency because they treat me like a family member” or “this is the agency that helped me get my first paycheck.”
Neither kind of causal explanation is better than the other. A decision to conduct idiographic research means that you will attempt to explain or describe your phenomenon exhaustively, attending to cultural context and subjective interpretations. A decision to conduct nomothetic research, on the other hand, means that you will try to explain what is true for everyone and predict what will be true in the future. In short, idiographic explanations have greater depth, and nomothetic explanations have greater breadth. More importantly, social workers understand the value of both approaches to understanding the social world. A social worker helping a client with substance abuse issues seeks idiographic knowledge when they ask about that client’s life story, investigate their unique physical environment, or probe how they understand their addiction. At the same time, a social worker also uses nomothetic knowledge to guide their interventions. Nomothetic research may help guide them to minimize risk factors and maximize protective factors or use an evidence-based therapy, relying on knowledge about what in general helps people with substance abuse issues.
Nomothetic causal relationships
One of my favorite classroom moments occurred in the early moments of my teaching career. Students were providing peer feedback on research questions. I overheard one group who was helping someone rephrase their research question. A student asked, “Are you trying to generalize or nah?” Teaching is full of fun moments like that one.
Answering that one question can help you understand how to conceptualize and design your research project. If you are trying to generalize, or create a nomothetic causal relationship, then the rest of these statements are likely to be true: you will use quantitative methods, reason deductively, and engage in explanatory research. How can I know all of that? Let’s take it part by part.
Because nomothetic causal relationships try to generalize, they must be able to reduce phenomena to a universal language, mathematics. Mathematics allows us to precisely measure, in universal terms, phenomena in the social world. Not all quantitative studies are explanatory. For example, a descriptive study could reveal the number of people without homes in your county, though it won’t tell you why they are homeless. But nearly all explanatory studies are quantitative. Because explanatory researchers want a clean “x causes y” explanation, they need to use the universal language of mathematics to achieve their goal. That’s why nomothetic causal relationships use quantitative methods.
What we’ve been talking about here is relationships between variables. When one variable causes another, we have what researchers call independent and dependent variables. For our example on spanking and aggressive behavior, spanking would be the independent variable and aggressive behavior addiction would be the dependent variable. An independent variable is the cause, and a dependent variable is the effect. Why are they called that? Dependent variables depend on independent variables. If all of that gets confusing, just remember this graphical relationship:
Figure 7.1 Visual representation of a nomothetic causal relationship
Relationship strength is another important factor to take into consideration when attempting to make causal claims when your research approach is nomothetic. I’m not talking strength of your friendships or marriage. In this context, relationship strength refers to statistical significance. The more statistically significant a relationship between two variables is shown to be, the greater confidence we can have in the strength of that relationship. You’ll remember from our discussion of statistical significance in Chapter 3, that it is usually represented in statistics as the p value.
A hypothesis is a statement describing a researcher’s expectation regarding what she anticipates finding. Hypotheses in quantitative research are a nomothetic causal relationship that the researcher expects to demonstrate. It is written to describe the expected relationship between the independent and dependent variables. Your prediction should be taken from a theory or model of the social world. For example, you may hypothesize that treating clinical clients with warmth and positive regard is likely to help them achieve their therapeutic goals. That hypothesis would be using the humanistic theories of Carl Rogers. Using previous theories to generate hypotheses is an example of deductive research. If Rogers’ theory of unconditional positive regard is accurate, your hypothesis should be true. This is how we know that all nomothetic causal relationships must use deductive reasoning.
Let’s consider a couple of examples. In research on sexual harassment (Uggen & Blackstone, 2004), [1] one might hypothesize, based on feminist theories of sexual harassment, that more females than males will experience specific sexually harassing behaviors. What is the causal relationship being predicted here? Which is the independent and which is the dependent variable? In this case, we hypothesized that a person’s gender (independent variable) would predict their likelihood to experience sexual harassment (dependent variable).
Sometimes researchers will hypothesize that a relationship will take a specific direction. As a result, an increase or decrease in one area might be said to cause an increase or decrease in another. For example, you might choose to study the relationship between age and support for legalization of marijuana. Perhaps you’ve taken a sociology class and, based on the theories you’ve read, you hypothesize that age is negatively related to support for marijuana legalization. [2] What have you just hypothesized? You have hypothesized that as people get older, the likelihood of their supporting marijuana legalization decreases. Thus, as age (your independent variable) moves in one direction (up), support for marijuana legalization (your dependent variable) moves in another direction (down). So, positive relationships involve two variables going in the same direction and negative relationships involve two variables going in opposite directions. If writing hypotheses feels tricky, it is sometimes helpful to draw them out and depict each of the two hypotheses we have just discussed.
Figure 7.2 Hypothesis describing the expected relationship between sex and sexual harassment
Figure 7.3 Hypothesis describing the expected direction of relationship between age and support for marijuana legalization
It’s important to note that once a study starts, it is unethical to change your hypothesis to match the data that you found. For example, what happens if you conduct a study to test the hypothesis from Figure 7.3 on support for marijuana legalization, but you find no relationship between age and support for legalization? It means that your hypothesis was wrong, but that’s still valuable information. It would challenge what the existing literature says on your topic, demonstrating that more research needs to be done to figure out the factors that impact support for marijuana legalization. Don’t be embarrassed by negative results, and definitely don’t change your hypothesis to make it appear correct all along!
Let’s say you conduct your study and you find evidence that supports your hypothesis, as age increases, support for marijuana legalization decreases. Success! Causal explanation complete, right? Not quite. You’ve only established one of the criteria for causality. The main criteria for causality have to do with covariation, plausibility, temporality, and spuriousness. In our example from Figure 7.3, we have established only one criteria—covariation. When variables covary, they vary together. Both age and support for marijuana legalization vary in our study. Our sample contains people of varying ages and varying levels of support for marijuana legalization.
Just because there might be some correlation between two variables does not mean that a causal relationship between the two is really plausible. Plausibility means that in order to make the claim that one event, behavior, or belief causes another, the claim has to make sense. It makes sense that people from previous generations would have different attitudes towards marijuana than younger generations. People who grew up in the time of Reefer Madness or the hippies may hold different views than those raised in an era of legalized medicinal and recreational use of marijuana.
Once we’ve established that there is a plausible relationship between the two variables, we also need to establish whether the cause happened before the effect, the criterion of temporality. A person’s age is a quality that appears long before any opinions on drug policy, so temporally the cause comes before the effect. It wouldn’t make any sense to say that support for marijuana legalization makes a person’s age increase. Even if you could predict someone’s age based on their support for marijuana legalization, you couldn’t say someone’s age was caused by their support for legalization.
Finally, scientists must establish nonspuriousness. A spurious relationship is one in which an association between two variables appears to be causal but can in fact be explained by some third variable. For example, we could point to the fact that older cohorts are less likely to have used marijuana. Maybe it is actually use of marijuana that leads people to be more open to legalization, not their age. This is often referred to as the third variable problem, where a seemingly true causal relationship is actually caused by a third variable not in the hypothesis. In this example, the relationship between age and support for legalization could be more about having tried marijuana than the age of the person.
Quantitative researchers are sensitive to the effects of potentially spurious relationships. They are an important form of critique of scientific work. As a result, they will often measure these third variables in their study, so they can control for their effects. These are called control variables, and they refer to variables whose effects are controlled for mathematically in the data analysis process. Control variables can be a bit confusing, but think about it as an argument between you, the researcher, and a critic.
Researcher: “The older a person is, the less likely they are to support marijuana legalization.”
Critic: “Actually, it’s more about whether a person has used marijuana before. That is what truly determines whether someone supports marijuana legalization.”
Researcher: “Well, I measured previous marijuana use in my study and mathematically controlled for its effects in my analysis. The relationship between age and support for marijuana legalization is still statistically significant and is the most important relationship here.”
Let’s consider a few additional, real-world examples of spuriousness. Did you know, for example, that high rates of ice cream sales have been shown to cause drowning? Of course, that’s not really true, but there is a positive relationship between the two. In this case, the third variable that causes both high ice cream sales and increased deaths by drowning is time of year, as the summer season sees increases in both (Babbie, 2010). [4] Here’s another good one: it is true that as the salaries of Presbyterian ministers in Massachusetts rise, so too does the price of rum in Havana, Cuba. Well, duh, you might be saying to yourself. Everyone knows how much ministers in Massachusetts love their rum, right? Not so fast. Both salaries and rum prices have increased, true, but so has the price of just about everything else (Huff & Geis, 1993). [5] Finally, research shows that the more firefighters present at a fire, the more damage is done at the scene. What this statement leaves out, of course, is that as the size of a fire increases so too does the amount of damage caused as does the number of firefighters called on to help (Frankfort-Nachmias & Leon-Guerrero, 2011). [6] In each of these examples, it is the presence of a third variable that explains the apparent relationship between the two original variables.
In sum, the following criteria must be met for a correlation to be considered causal:
• The two variables must vary together.
• The relationship must be plausible.
• The cause must precede the effect in time.
• The relationship must be nonspurious (not due to a third variable).
Once these criteria are met, a researcher can say they have achieved a nomothetic causal explanation, one that is objectively true. It’s a difficult challenge for researchers to meet. You will almost never hear researchers say that they have proven their hypotheses. A statement that bold implies that a relationship has been shown to exist with absolute certainty and that there is no chance that there are conditions under which the hypothesis would not be true. Instead, researchers tend to say that their hypotheses have been supported (or not). This more cautious way of discussing findings allows for the possibility that new evidence or new ways of examining a relationship will be discovered. Researchers may also discuss a null hypothesis. We covered in Chapter 3 that the null hypothesis is one that predicts no relationship between the variables being studied. If a researcher rejects the null hypothesis, she is saying that the variables in question are somehow related to one another.
Idiographic causal relationships
Remember our question, “Are you trying to generalize or nah?” If you answered no, you are trying to establish an idiographic causal relationship. I can guess that if you are trying to establish an idiographic causal relationship, you are likely going to use qualitative methods, reason inductively, and engage in exploratory or descriptive research. We can understand these assumptions by walking through them, one by one.
Researchers seeking idiographic causal relationships are not trying to generalize, so they have no need to reduce phenomena to mathematics. In fact, using the language of mathematics to reduce the social world down is a bad thing, as it robs the causal relationship of its meaning and context. Idiographic causal relationships are bound within people’s stories and interpretations. Usually, these are expressed through words. Not all qualitative studies use word data, as some can use interpretations of visual or performance art, though the vast majority of social science studies do use word data.
But wait, I predicted that an idiographic causal relationship would use descriptive or exploratory research. How can we build causal relationships if we are just describing or exploring a topic? Wouldn’t we need to do explanatory research to build any kind of causal explanation? Explanatory research attempts to establish nomothetic causal relationships—an independent variable is demonstrated to cause changes a dependent variable. Exploratory and descriptive qualitative research contains some causal relationships, but they are actually descriptions of the causal relationships established by the participants in your study. Instead of saying “x causes y,” your participants will describe their experiences with “x,” which they will tell you was caused by and influenced a variety of other factors, depending on time, environment, and subjective experience. As we stated before, idiographic causal explanations are messy. Your job as a social science researcher is to accurately describe the patterns in what your participants tell you.
Let’s consider an example. If I asked you why you decided to become a social worker, what might you say? For me, I would say that I wanted to be a mental health clinician since I was in high school. I was interested in how people thought. At my second internship in my undergraduate program, I got the advice to become a social worker because the license provided greater authority for insurance reimbursement and flexibility for career change. That’s not a simple explanation at all! But it does provide a description of the deeper understanding of the many factors that led me to become a social worker. If we interviewed many social workers about their decisions to become social workers, we might begin to notice patterns. We might find out that many social workers begin their careers based on a variety of factors, such as: personal experience with a disability or social injustice, positive experiences with social workers, or a desire to help others. No one factor is the “most important factor,” like with nomothetic causal relationships. Instead, a complex web of factors, contingent on context, emerge in the dataset when you interpret what people have said.
Finding patterns in data, as you’ll remember from Chapter 6, is what inductive reasoning is all about. A researcher collects data, usually word data, and notices patterns. Those patterns inform the theories we use in social work. In many ways, the idiographic causal relationships you create in qualitative research are like the social theories we reviewed in Chapter 6 (e.g. social exchange theory) and other theories you use in your practice and theory courses. Theories are explanations about how different concepts are associated with each other how that network of relationships works in the real world. While you can think of theories like Systems Theory as Theory (with a capital “T”), inductive causal relationships are like theory with a small “t.” They may apply only to the participants, environment, and moment in time in which you gathered your data. Nevertheless, they contribute important information to the body of knowledge on the topic you studied.
Over time, as more qualitative studies are done and patterns emerge across different studies and locations, more sophisticated theories emerge that explain phenomena across multiple contexts. In this way, qualitative researchers use idiographic causal explanations for theory building or the creation of new theories based on inductive reasoning. Quantitative researchers, on the other hand, use nomothetic causal relationships for theory testing, wherein a hypothesis is created from existing theory (big T or small t) and tested mathematically (i.e., deductive reasoning).
If you plan to study domestic and sexual violence, you will likely encounter the Power and Control Wheel. [6] The wheel is a model of how power and control operate in relationships with physical violence. The wheel was developed based on qualitative focus groups conducted by sexual and domestic violence advocates in Duluth, MN. While advocates likely had some tentative hypotheses about what was important in a relationship with domestic violence, participants in these focus groups provided the information that became the Power and Control Wheel. As qualitative inquiry like this one unfolds, hypotheses get more specific and clear, as researchers learn from what their participants share.
Once a theory is developed from qualitative data, a quantitative researcher can seek to test that theory. For example, a quantitative researcher may hypothesize that men who hold traditional gender roles are more likely to engage in domestic violence. That would make sense based on the Power and Control Wheel model, as the category of “using male privilege” speaks to this relationship. In this way, qualitatively-derived theory can inspire a hypothesis for a quantitative research project.
Unlike nomothetic causal relationships, there are no formal criteria (e.g., covariation) for establishing causality in idiographic causal relationships. In fact, some criteria like temporality and nonspuriousness may be violated. For example, if an adolescent client says, “It’s hard for me to tell whether my depression began before my drinking, but both got worse when I was expelled from my first high school,” they are recognizing that oftentimes it’s not so simple that one thing causes another. Sometimes, there is a reciprocal relationship where one variable (depression) impacts another (alcohol abuse), which then feeds back into the first variable (depression) and also into other variables (school). Other criteria, such as covariation and plausibility still make sense, as the relationships you highlight as part of your idiographic causal explanation should still be plausibly true and it elements should vary together.
Similarly, idiographic causal explanations differ in terms of hypotheses. If you recall from the last section, hypotheses in nomothetic causal explanations are testable predictions based on previous theory. In idiographic research, a researcher likely has hypotheses, but they are more tentative. Instead of predicting that “x will decrease y,” researchers will use previous literature to figure out what concepts might be important to participants and how they believe participants might respond during the study. Based on an analysis of the literature a researcher may formulate a few tentative hypotheses about what they expect to find in their qualitative study. Unlike nomothetic hypotheses, these are likely to change during the research process. As the researcher learns more from their participants, they might introduce new concepts that participants talk about. Because the participants are the experts in idiographic causal relationships, a researcher should be open to emerging topics and shift their research questions and hypotheses accordingly.
Two different baskets
Idiographic and nomothetic causal explanations form the “two baskets” of research design elements pictured in Figure 7.4 below. Later on, they will also determine the sampling approach, measures, and data analysis in your study.
Figure 7.4: Two baskets (or approaches) to research
In most cases, mixing components from one basket with the other would not make sense. If you are using quantitative methods with an idiographic question, you wouldn’t get the deep understanding you need to answer an idiographic question. Knowing, for example, that someone scores 20/35 on a numerical index of depression symptoms does not tell you what depression means to that person. Similarly, qualitative methods are not often used to deductive reasoning because qualitative methods usually seek to understand a participant’s perspective, rather than test what existing theory says about a concept.
However, these are not hard-and-fast rules. There are plenty of qualitative studies that attempt to test a theory. There are fewer social constructionist studies with quantitative methods, though studies will sometimes include quantitative information about participants. Researchers in the critical paradigm can fit into either bucket, depending on their research question, as they focus on the liberation of people from oppressive internal (subjective) or external (objective) forces.
We will explore later on in this chapter how researchers can use both buckets simultaneously in mixed methods research. For now, it’s important that you understand the logic that connects the ideas in each bucket. Not only is this fundamental to how knowledge is created and tested in social work, it speaks to the very assumptions and foundations upon which all theories of the social world are built!
Key Takeaways
• Idiographic research focuses on subjectivity, context, and meaning.
• Nomothetic research focuses on objectivity, prediction, and generalizing.
• In qualitative studies, the goal is generally to understand the multitude of causes that account for the specific instance the researcher is investigating.
• In quantitative studies, the goal may be to understand the more general causes of some phenomenon rather than the idiosyncrasies of one particular instance.
• For nomothetic causal relationships, a relationship must be plausible and nonspurious, and the cause must precede the effect in time.
• In a nomothetic causal relationship, the independent variable causes changes in a dependent variable.
• Hypotheses are statements, drawn from theory, which describe a researcher’s expectation about a relationship between two or more variables.
• Qualitative research may create theories that can be tested quantitatively.
• The choice of idiographic or nomothetic causal relationships requires a consideration of methods, paradigm, and reasoning.
• Depending on whether you seek a nomothetic or idiographic causal explanation, you are likely to employ specific research design components.
Glossary
• Causality-the idea that one event, behavior, or belief will result in the occurrence of another, subsequent event, behavior, or belief
• Control variables- potential “third variables” effects are controlled for mathematically in the data analysis process to highlight the relationship between the independent and dependent variable
• Covariation- the degree to which two variables vary together
• Dependent variable- a variable that depends on changes in the independent variable
• Generalize- to make claims about a larger population based on an examination of a smaller sample
• Hypothesis- a statement describing a researcher’s expectation regarding what she anticipates finding
• Idiographic research- attempts to explain or describe your phenomenon exhaustively, based on the subjective understandings of your participants
• Independent variable- causes a change in the dependent variable
• Nomothetic research- provides a more general, sweeping explanation that is universally true for all people
• Plausibility- in order to make the claim that one event, behavior, or belief causes another, the claim has to make sense
• Spurious relationship- an association between two variables appears to be causal but can in fact be explained by some third variable
• Statistical significance- confidence researchers have in a mathematical relationship
• Temporality- whatever cause you identify must happen before the effect
• Theory building- the creation of new theories based on inductive reasoning
• Theory testing- when a hypothesis is created from existing theory and tested mathematically
Image attributions
Mikado by 3dman_eu CC-0
Weather TV Forecast by mohamed_hassan CC-0
Beatrice Birra Storytelling at African Art Museum by Anthony Cross public domain
1. Uggen, C., & Blackstone, A. (2004). Sexual harassment as a gendered expression of power. AmericanSociological Review, 69, 64–92. ↵
2. In fact, there are empirical data that support this hypothesis. Gallup has conducted research on this very question since the 1960s. For more on their findings, see Carroll, J. (2005). Who supports marijuana legalization? Retrieved from http://www.gallup.com/poll/19561/who-supports-marijuana-legalization.aspx
3. Figures 7.2 and 7.3 were copied from Blackstone, A. (2012) Principles of sociological inquiry: Qualitative and quantitative methods. Saylor Foundation. Retrieved from: https://saylordotorg.github.io/text_...ative-methods/ Shared under CC-BY-NC-SA 3.0 License (https://creativecommons.org/licenses/by-nc-sa/3.0/) ↵
4. Babbie, E. (2010). The practice of social research (12th ed.). Belmont, CA: Wadsworth. ↵
5. Huff, D. & Geis, I. (1993). How to lie with statistics. New York, NY: W. W. Norton & Co. ↵
6. Frankfort-Nachmias, C. & Leon-Guerrero, A. (2011). Social statistics for a diverse society. Washington, DC: Pine Forge Press. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/07%3A_Design_and_causality/7.02%3A_Causal_relationships.txt |
Learning Objectives
• Define units of analysis and units of observation, and describe the two common errors people make when they confuse the two
Another point to consider when designing a research project, and which might differ slightly in qualitative and quantitative studies, has to do with units of analysis and units of observation. These two items concern what you, the researcher, actually observe in the course of your data collection and what you hope to be able to say about those observations. A unit of analysis is the entity that you wish to be able to say something about at the end of your study, probably what you’d consider to be the main focus of your study. A unit of observation is the item (or items) that you actually observe, measure, or collect in the course of trying to learn something about your unit of analysis.
In a given study, the unit of observation might be the same as the unit of analysis, but that is not always the case. For example, a study on electronic gadget addiction may interview undergraduate students (our unit of observation) for the purpose of saying something about undergraduate students (our unit of analysis) and their gadget addiction. Perhaps, if we were investigating gadget addiction in elementary school children (our unit of analysis), we might collect observations from teachers and parents (our units of observation) because younger children may not report their behavior accurately. In this case and many others, units of analysis are not the same as units of observation. What is required, however, is for researchers to be clear about how they define their units of analysis and observation, both to themselves and to their audiences.
More specifically, your unit of analysis will be determined by your research question. Your unit of observation, on the other hand, is determined largely by the method of data collection that you use to answer that research question. We’ll take a closer look at methods of data collection later on in the textbook. For now, let’s consider again a study addressing students’ addictions to electronic gadgets. We’ll consider first how different kinds of research questions about this topic will yield different units of analysis. Then, we’ll think about how those questions might be answered and with what kinds of data. This leads us to a variety of units of observation.
If we were to explore which students are most likely to be addicted to their electronic gadgets, our unit of analysis would be individual students. We might mail a survey to students on campus, and our aim would be to classify individuals according to their membership in certain social groups in order to see how membership in those classes correlated with gadget addiction. For example, we might find that majors in new media, men, and students with high socioeconomic status are all more likely than other students to become addicted to their electronic gadgets. Another possibility would be to explore how students’ gadget addictions differ and how are they similar. In this case, we could conduct observations of addicted students and record when, where, why, and how they use their gadgets. In both cases, one using a survey and the other using observations, data are collected from individual students. Thus, the unit of observation in both examples is the individual.
Another common unit of analysis in social science inquiry is groups. Groups of course vary in size, and almost no group is too small or too large to be of interest to social scientists. Families, friendship groups, and group therapy participants are some common examples of micro-level groups examined by social scientists. Employees in an organization, professionals in a particular domain (e.g., chefs, lawyers, social workers), and members of clubs (e.g., Girl Scouts, Rotary, Red Hat Society) are all meso-level groups that social scientists might study. Finally, at the macro-level, social scientists sometimes examine citizens of entire nations or residents of different continents or other regions.
A study of student addictions to their electronic gadgets at the group level might consider whether certain types of social clubs have more or fewer gadget-addicted members than other sorts of clubs. Perhaps we would find that clubs that emphasize physical fitness, such as the rugby club and the scuba club, have fewer gadget-addicted members than clubs that emphasize cerebral activity, such as the chess club and the women’s studies club. Our unit of analysis in this example is groups because groups are what we hope to say something about. If we had instead asked whether individuals who join cerebral clubs are more likely to be gadget-addicted than those who join social clubs, then our unit of analysis would have been individuals. In either case, however, our unit of observation would be individuals.
Organizations are yet another potential unit of analysis that social scientists might wish to say something about. Organizations include entities like corporations, colleges and universities, and even nightclubs. At the organization level, a study of students’ electronic gadget addictions might explore how different colleges address the problem of electronic gadget addiction. In this case, our interest lies not in the experience of individual students but instead in the campus-to-campus differences in confronting gadget addictions. A researcher conducting a study of this type might examine schools’ written policies and procedures, so her unit of observation would be documents. However, because she ultimately wishes to describe differences across campuses, the college would be her unit of analysis.
In sum, there are many potential units of analysis that a social worker might examine, but some of the most common units include the following:
• Individuals
• Groups
• Organizations
Table 7.1 Units of analysis and units of observation: An example using a hypothetical study of students’ addictions to electronic gadgets
Research question Unit of analysis Data collection Unit of observation Statement of findings
Which students are most likely to be addicted to their electronic gadgets? Individuals Survey of students on campus Individuals New Media majors, men, and students with high socioeconomic status are all more likely than other students to become addicted to their electronic gadgets.
Do certain types of social clubs have more gadget-addicted members than other sorts of clubs? Groups Survey of students on campus Individuals Clubs with a scholarly focus, such as social work club and the math club, have more gadget-addicted members than clubs with a social focus, such as the 100-bottles-of- beer-on-the-wall club and the knitting club.
How do different colleges address the problem of electronic gadget addiction? Organizations Content analysis of policies Documents Campuses without strong computer science programs are more likely than those with such programs to expel students who have been found to have addictions to their electronic gadgets.
Note: Please remember that the findings described here are hypothetical. There is no reason to think that any of the hypothetical findings described here would actually bear out if tested with empirical research.
One common error people make when it comes to both causality and units of analysis is something called the ecological fallacy. This occurs when claims about one lower-level unit of analysis are made based on data from some higher-level unit of analysis. In many cases, this occurs when claims are made about individuals, but only group-level data have been gathered. For example, we might want to understand whether electronic gadget addictions are more common on certain campuses than on others. Perhaps different campuses around the country have provided us with their campus percentage of gadget-addicted students, and we learn from these data that electronic gadget addictions are more common on campuses that have business programs than on campuses without them. We then conclude that business students are more likely than non-business students to become addicted to their electronic gadgets. However, this would be an inappropriate conclusion to draw. Because we only have addiction rates by campus, we can only draw conclusions about campuses, not about the individual students on those campuses. Perhaps the social work majors on the business campuses are the ones that caused the addiction rates on those campuses to be so high. The point is we simply don’t know because we only have campus-level data. By drawing conclusions about students when our data are about campuses, we run the risk of committing the ecological fallacy.
On the other hand, another mistake to be aware of is reductionism. Reductionism occurs when claims about some higher-level unit of analysis are made based on data from some lower-level unit of analysis. In this case, claims about groups or macro-level phenomena are made based on individual-level data. An example of reductionism can be seen in some descriptions of the civil rights movement. On occasion, people have proclaimed that Rosa Parks started the civil rights movement in the United States by refusing to give up her seat to a white person while on a city bus in Montgomery, Alabama, in December 1955. Although it is true that Parks played an invaluable role in the movement, and that her act of civil disobedience gave others courage to stand up against racist policies, beliefs, and actions, to credit Parks with starting the movement is reductionist. Surely the confluence of many factors, from fights over legalized racial segregation to the Supreme Court’s historic decision to desegregate schools in 1954 to the creation of groups such as the Student Nonviolent Coordinating Committee (to name just a few), contributed to the rise and success of the American civil rights movement. In other words, the movement is attributable to many factors—some social, others political and others economic. Did Parks play a role? Of course she did—and a very important one at that. But did she cause the movement? To say yes would be reductionist.
It would be a mistake to conclude from the preceding discussion that researchers should avoid making any claims whatsoever about data or about relationships between levels of analysis. While it is important to be attentive to the possibility for error in causal reasoning about different levels of analysis, this warning should not prevent you from drawing well-reasoned analytic conclusions from your data. The point is to be cautious and conscientious in making conclusions between levels of analysis. Errors in analysis come from a lack of rigor and deviating from the scientific method.
Key Takeaways
• A unit of analysis is the item you wish to be able to say something about at the end of your study while a unit of observation is the item that you actually observe.
• When researchers confuse their units of analysis and observation, they may be prone to committing either the ecological fallacy or reductionism.
Glossary
• Ecological fallacy- claims about one lower-level unit of analysis are made based on data from some higher-level unit of analysis
• Reductionism- when claims about some higher-level unit of analysis are made based on data at some lower-level unit of analysis
• Unit of analysis- entity that a researcher wants to say something about at the end of her study
• Unit of observation- the item that a researcher actually observes, measures, or collects in the course of trying to learn something about her unit of analysis
Image attributions
Binoculars by nightowl CC-0 | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/07%3A_Design_and_causality/7.03%3A_Unit_of_analysis_and_unit_of_observation.txt |
Learning Objectives
• Define sequence and emphasis and describe how they work in qualitative research
• List the five reasons why researchers use mixed methods
So far in this textbook, we have talked about quantitative and qualitative methods as an either/or choice—you can choose quantitative methods or qualitative methods. However, researchers often use both methods inside of their research projects. For example, I recently completed a study with the people who administer state-level services for people with intellectual and developmental disabilities on a program they implemented called self-direction, which allows people with disabilities greater self-determination over their supports. In this study, my research partners and I used a mixed methods approach to understand the implementation of the program. The goal of our project was to describe the implementation of self-direction across the United States. We distributed a short, written survey and also conducted phone interviews with program administrators. While we could have just sent out a questionnaire that asked states to provide basic information on their program (size, qualifications, services offered, etc.), that would not provide us much information about some of the issues administrators faced during implementation of the program. Similarly, we could have interviewed program administrators without the questionnaire, but then we wouldn’t know enough about the programs to ask good questions. Instead, we chose to use both qualitative and quantitative methods.
Sequence and emphasis
There are many different mixed methods designs, each with their own strengths. However, a more simplified synthesis of mixed methods approaches is provided by Engel and Schutt (2016) [1] using two key terms. Sequence refers to the order that each method is used. Researchers can use both methods at the same time or concurrently. Or, they can use one and then the other, or sequentially. For our study of self-direction, we used a sequential design by sending out a questionnaire first, conducing some analysis, and then conducting the interview. We used the quantitative questionnaire to gather basic information about the programs before we began the interviews, so our questions were specific to the features of each program. If we wanted to use a concurrent design for some reason, we could have asked quantitative questions during the interview. However, we felt this would waste the administrators’ time and would break up the conversation and rhythm of the interviews.
The other key term in mixed methods research is emphasis. In our mixed methods study, the qualitative data was the most important data. The quantitative data was mainly used to provide background information for the qualitative interviews, and our write up of the study focused mostly on the qualitative information. Thus, qualitative methods were prioritized in our study. Many times, however, quantitative methods are emphasized. In these studies, qualitative data is used mainly to provide context for the quantitative findings. For example, demonstrating quantitatively that a particular therapy works is important. By adding a qualitative component, researchers could find out how the participants experienced the intervention, how they understood its effects, and the meaning it had on their lives. This data would add depth and context to the findings of the study and allow researchers to improve the therapeutic technique in the future.
A similar practice is when researchers use qualitative methods to solicit feedback on a quantitative scale or measure. The experiences of individuals allow researchers to refine the measure before they do the quantitative component of their study. Finally, it is possible that researchers are equally interested in qualitative and quantitative information. In studies of equal emphasis, researchers consider both methods as the focus of the research project.
Why researchers use mixed methods
Mixed methods research is more than just sticking an open-ended question at the end of a quantitative survey. Mixed methods researchers use mixed methods for both pragmatic and synergistic reasons. That is, they use both methods because it makes sense with their research questions and because they will get the answers they want by combining the two approaches.
Mixed methods also allows you to use both inductive and deductive reasoning. As we’ve discussed, qualitative research follows inductive logic, moving from data to empirical generalizations or theory. In a mixed methods study, a researcher could use the results from a qualitative component to inform a subsequent quantitative component. The quantitative component would use deductive logic, using the theory derived from qualitative data to create and test a hypothesis. In this way, mixed methods use the strengths of both research methods, using each method to understand different parts of the same phenomenon. Quantitative allows the researcher to test new ideas. Qualitative allows the researcher to create new ideas.
With these two concepts in mind, we can start to see why researchers use mixed methods in the real world. I mentioned previously that our research project used a sequential design because we wanted to use our quantitative data to shape what qualitative questions we asked our participants. Mixed methods are often used this way, to initiate ideas with one method to study with another. For example, researchers could begin a mixed methods project by using qualitative methods to interview or conduct a focus group with participants. Based on their responses, the researchers could then formulate a quantitative project to follow up on the results. This is the inverse of what we did in our project, which was use a quantitative survey to inform a more detailed qualitative interview.
In addition to providing information for subsequent investigation, using both quantitative and qualitative information provides additional context for the data. For example, in our questionnaire for the study on self-direction, we asked participants to list what services people could purchase. The qualitative data followed up on that answer by asking whether the administrators had added or taken away any services, how they decided that these services would be covered and not others, and problems that arose around providing these services. With that information, we could analyze what services were offered, why they were offered, and how administrators made those decisions. In this way, we learned the lived experience of program administrators, not just the basic information about their programs.
Finally, another purpose of mixed methods research is corroborating data from both quantitative and qualitative sources. Ideally, your qualitative and quantitative results should support each other. For example, if interviews with participants showed a relationship between two concepts, that relationship should also be present in the qualitative data you collected. Differences between quantitative and qualitative data require an explanation. Perhaps there are outliers or extreme cases that pushed your data in one direction or another, for example.
In summary, these are a few of the many reasons researchers use mixed methods. They are summarized below:
1. Triangulation or convergence on the same phenomenon to improve validity
2. Complementarity, which aims to get at related but different facets of a phenomenon
3. Development or the use of results from one phase or a study to develop another phase
4. Initiation or the intentional analysis of inconsistent qualitative and quantitative findings to derive new insights
5. Expansion or using multiple components to extend the scope of a study (Burnett, 2012, p. 77). [2]
A word of caution
The use of mixed methods has many advantages. However, undergraduate researchers should approach mixed methods with caution. Conducting a mixed methods study may mean doubling or even tripling your work. You must conceptualize how to use one method, another method, and how they fit together. This may mean operationalizing and creating a questionnaire, then writing an interview guide, and thinking through how the data on each measure relate to one another—more work than using one quantitative or qualitative method alone. Similarly, in sequential studies, the researcher must collect and analyze data from one component and then conceptualize and conduct the second component. This may also impact how long a project may take. Before beginning a mixed methods project, you should have a clear vision for what the project will entail and how each methodology will contribute to that vision.
Key Takeaways
• Mixed methods studies vary in sequence and emphasis.
• Mixed methods allow the research to corroborate findings, provide context, follow up on ideas, and use the strengths of each method.
Glossary
• Emphasis- in a mixed methods study, refers to the priority that each method is given
• Sequence- in a mixed methods study, refers to the order that each method is used, either concurrently or sequentially
Image attributions
one two three/ un deux trois by Improulx CC-0
caution by geralt CC-0
1. Rubin, C. & Babbie, S. (2017). Research methods for social work (9th edition). Boston, MA: Cengage. ↵
2. Burnett, D. (2012). Inscribing knowledge: Writing research in social work. In W. Green & B. L. Simon (Eds.), The Columbia guide to social work writing (pp. 65-82). New York, NY: Columbia University Press. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/07%3A_Design_and_causality/7.04%3A_Mixed_Methods.txt |
Creating a research question is an iterative process, one version after another. In the preceding chapters, you started with an initial question and refined it as you learned more about the topic you’re studying. In this chapter, you will finalize your research question, making sure that is it empirical, correctly structured, and feasible to answer. Once this process is completed, you’ll be ready to start answering your question.
This chapter discusses or mentions the following topics: suicide and depression, heterosexism, sexual assault, homelessness, foster care, the criminal justice system, and self-harm.
08: Creating and refining a research question
Learning Objectives
• Define empirical questions and provide an example
• Define ethical questions and provide an example
When it comes to research questions, social workers are best equipped to answer empirical questions—those that can be answered by real experience in the real world—as opposed to ethical questions—questions about which people have moral opinions and that may not be answerable in reference to the real world. While social workers have explicit ethical obligations (e.g., service, social justice), research projects ask empirical questions that help support those ethical principles.
For example, I had a student group who wanted to research the penalties for sexual assault. Their original research question was: “How can prison sentences for sexual assault be so much lower than the penalty for drug possession?” Outside of the research context, that is a darn good question! It speaks to how the War on Drugs and the patriarchy have distorted the criminal justice system towards policing of drug crimes over violent crimes. Unfortunately, it is an ethical question, not an empirical one. How could you answer that question by gathering data about people in the real world? What would an answer to that question even look like?
As the students worked on the project through the semester, they continued to focus on the topic of sexual assault in the criminal justice system. Their research question became more empirical because they read more empirical articles about their topic. One option that they considered was to evaluate intervention programs for perpetrators of sexual assault to see if they reduced the likelihood of committing sexual assault again. Another option they considered was seeing if counties or states with higher than average jail sentences for sexual assault perpetrators had lower rates of re-offense for sexual assault. These projects addressed the ethical question of punishing perpetrators of sexual violence but did so in a way that gathered and analyzed real-world information. Our job as social work researchers is to gather social facts about social work issues, not to judge or determine morality.
In order to help you better understand the difference between ethical and empirical questions, let’s consider a topic about which people have moral opinions. How about SpongeBob SquarePants? [1] In early 2005, members of the conservative Christian group Focus on the Family (2005) [2] denounced this seemingly innocuous cartoon character as “morally offensive” because they perceived his character to be one that promotes a “pro-gay agenda.” Focus on the Family supported their claim that SpongeBob is immoral by citing his appearance in a children’s video designed to promote tolerance of all family forms (BBC News, 2005). [3] They also cited SpongeBob’s regular hand-holding with his male sidekick Patrick as further evidence of his immorality.
So, can we now conclude that SpongeBob SquarePants is immoral? Not so fast. While your mother or a newspaper or television reporter may provide an answer, a social science researcher cannot. Questions of morality are ethical, not empirical. Of course, this doesn’t mean that social work researchers cannot study opinions about or social meanings surrounding SpongeBob SquarePants (Carter, 2010). [4] We study humans after all, and as you will discover in the following chapters of this textbook, we are trained to utilize a variety of scientific data-collection techniques to understand patterns of human beliefs and behaviors. Using these techniques, we could find out how many people in the United States find SpongeBob morally reprehensible, but we could never learn, empirically, whether SpongeBob is in fact morally reprehensible.
Key Takeaways
• Empirical questions are distinct from ethical questions.
• There are usually a number of ethical questions and a number of empirical questions that could be asked about any single topic.
• While social workers may study topics about which people have moral opinions, their job is to gather empirical data that guides action on behalf of clients.
Glossary
• Empirical questions- questions that can be answered by observing experiences in the real world
• Ethical questions- questions that ask about general moral opinions about a topic and cannot be answered through science
Image attributions
Spongebob by InspiredImages CC-0
1. Not familiar with SpongeBob SquarePants? You can learn more about him on Nickelodeon’s site dedicated to all things SpongeBob: http://www.nick.com/spongebob-squarepants/
2. Focus on the Family. (2005, January 26). Focus on SpongeBob. Christianity Today. Retrieved from http://www.christianitytoday.com/ct/2005/januaryweb-only/34.0c.html
3. BBC News. (2005, January 20). US right attacks SpongeBob video. Retrieved from: http://news.bbc.co.uk/2/hi/americas/4190699.stm
4. In fact, an MA thesis examines representations of gender and relationships in the cartoon: Carter, A. C. (2010). Constructing gender andrelationships in “SpongeBob SquarePants”: Who lives in a pineapple under the sea. MA thesis, Department of Communication, University of South Alabama, Mobile, AL. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/08%3A_Creating_and_refining_a_research_question/8.01%3A_Empirical_versus_ethical_questions.txt |
Learning Objectives
• Identify and explain the seven key features of a good research question
• Explain why it is important for social workers to be focused when creating a research question
Now that you’ve thought about what topics interest you and identified a topic that asks an empirical question about a target population, you need to form a research question about that topic. So, what makes a good research question? First, it is generally written in the form of a question. To say that your research question is “the opiate epidemic” or “animal assisted therapy” or “oppression” would not be correct. You need to frame your topic as a question, not a statement. A good research question is also one that is well-focused. A well-focused question helps you tune out irrelevant information and not try to answer everything about the world all at once. You could be the most eloquent writer in your class, or even in the world, but if the research question about which you are writing is unclear, your work will ultimately fall flat.
In addition to being written in the form of a question and being well-focused, a good research question is one that cannot be answered with a simple yes or no. For example, if your interest is in gender norms, you could ask, “Does gender affect a person’s performance of household tasks?” but you will have nothing left to say once you discover your yes or no answer. Instead, why not ask, about the relationship between gender and household tasks. Alternatively, maybe we are interested in how or to what extent gender affects a person’s contributions to housework in a marriage? By tweaking your question in this small way, you suddenly have a much more fascinating question and more to say as you attempt to answer it.
A good research question should also have more than one plausible answer. The student who studied the relationship between gender and household tasks had a specific interest in the impact of gender, but she also knew that preferences might be impacted by other factors. For example, she knew from her own experience that her more traditional and socially conservative friends were more likely to see household tasks as part of the female domain and were less likely to expect their male partners to contribute to those tasks. Thinking through the possible relationships between gender, culture, and household tasks led that student to realize that there were many plausible answers to her questions about how gender affects a person’s contribution to household tasks. Because gender doesn’t exist in a vacuum, she wisely felt that she needed to consider other characteristics that work together with gender to shape people’s behaviors, likes, and dislikes. By doing this, the student considered the third feature of a good research question–she thought about relationships between several concepts. While she began with an interest in a single concept—household tasks—by asking herself what other concepts (such as gender or political orientation) might be related to her original interest, she was able to form a question that considered the relationships among those concepts.
This student had one final component to consider. Social work research questions must contain a target population. Her study would be very different if she were to conduct it on older adults or newly arrived immigrants. The target population is the group of people whose needs your study addresses. If the student noticed issues with household tasks as part of her work with first-generation immigrants, perhaps that would be her target population. Maybe she wants to address the needs of a community of older adults. Whatever the case, the target population should be chosen while keeping in mind social work’s responsibility to work on behalf of marginalized and oppressed groups.
In sum, a good research question generally has the following features:
• It is written in the form of a question
• It is clearly written
• It is not a yes/no
• It has more than one plausible answer
• It considers relationships among multiple variables
• It is specific and clear about the concepts it addresses
• It contains a target population
Key Takeaways
• A poorly focused research question can lead to the demise of an otherwise well-executed study.
• Research questions should address the needs of a target population.
Glossary
• Target population- group of people whose needs your study addresses
Image attributions
Question by johnhain CC-0 | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/08%3A_Creating_and_refining_a_research_question/8.02%3A_Writing_a_good_research_question.txt |
Learning Objectives
• Describe how research questions for exploratory, descriptive, and explanatory quantitative questions differ and how to phrase them
• Identify the differences between and provide examples of strong and weak explanatory research questions
Quantitative descriptive questions
The type of research you are conducting will impact the research question that you ask. Probably the easiest questions to think of are quantitative descriptive questions. For example, “What is the average student debt load of MSW students?” is a descriptive question—and an important one. We aren’t trying to build a causal relationship here. We’re simply trying to describe how much debt MSW students carry. Quantitative descriptive questions like this one are helpful in social work practice as part of community scans, in which human service agencies survey the various needs of the community they serve. If the scan reveals that the community requires more services related to housing, child care, or day treatment for people with disabilities, a nonprofit office can use the community scan to create new programs that meet a defined community need.
Quantitative descriptive questions will often ask for percentage, count the number of instances of a phenomenon, or determine an average. Descriptive questions may only include one variable, such as ours about debt load, or they may include multiple variables. Because these are descriptive questions, we cannot investigate causal relationships between variables. To do that, we need to use a quantitative explanatory question.
Quantitative explanatory questions
Most studies you read in the academic literature will be quantitative and explanatory. Why is that? If you recall from Chapter 7, explanatory research tries to build nomothetic causal relationships. They are generalizable across space and time, so they are applicable to a wide audience. The editorial board of a journal wants to make sure their content will be useful to as many people as possible, so it’s not surprising that quantitative research dominates the academic literature.
Structurally, quantitative explanatory questions must contain an independent variable and dependent variable. Questions should ask about the relationship between these variables. My standard format for an explanatory quantitative research question is: “What is the relationship between [independent variable] and [dependent variable] for [target population]?” You should play with the wording for your research question, revising it as you see fit. The goal is to make the research question reflect what you really want to know in your study.
Let’s take a look at a few more examples of possible research questions and consider the relative strengths and weaknesses of each. Table 8.1 does just that. While reading the table, keep in mind that I have only noted what I view to be the most relevant strengths and weaknesses of each question. Certainly each question may have additional strengths and weaknesses not noted in the table.
Table 8.1 Sample research questions: Strengths and weaknesses
Sample question Question’s strengths Question’s weaknesses Proposed alternative
What are the internal and external effects/problems associated with children witnessing domestic violence? Written as a question Not clearly focused How does witnessing domestic violence impact a child’s romantic relationships in adulthood?
Considers relationships among multiple concepts Not specific and clear about the concepts it addresses
Contains a population
What causes foster children who are transitioning to adulthood to become homeless, jobless, pregnant, unhealthy, etc.? Considers relationships among multiple concepts Concepts are not specific and clear What is the relationship between sexual orientation or gender identity and homelessness for late adolescents in foster care?
Contains a population
Not written as a yes/no question
How does income inequality predict ambivalence in the Stereo Content Model using major U.S. cities as target populations? Written as a question Unclear wording How does income inequality affect ambivalence in high-density urban areas?
Considers relationships among multiple concepts Population is unclear
Why are mental health rates higher in white foster children then African Americans and other races? Written as a question Concepts are not clear How does race impact rates of mental health diagnosis for children in foster care?
Not written as a yes/no question Does not contain a target population
Making it more specific
A good research question should also be specific and clear about the concepts it addresses. A student investigating gender and household tasks knows what they mean by “household tasks.” You likely also have an impression of what “household tasks” means. But are your definition and the student’s definition the same? A participant in their study may think that managing finances and performing home maintenance are household tasks, but the researcher may be interested in other tasks like childcare or cleaning. The only way to ensure your study stays focused and clear is to be specific about what you mean by a concept. The student in our example could pick a specific household task that was interesting to them or that the literature indicated was important—for example, childcare. Or, the student could have a broader view of household tasks, one that encompasses childcare, food preparation, financial management, home repair, and care for relatives. Any option is probably okay, as long as the researcher is clear on what they mean by “household tasks.”
Table 8.2 contains some “watch words” that indicate you may need to be more specific about the concepts in your research question.
Table 8.2 “Watch words”
Watch words How to get more specific
Factors, Causes, Effects, Outcomes What causes or effects are you interested in? What causes and effects are important, based on the literature in your topic area? Try to choose one or a handful that you consider to be the most important.
Effective, Effectiveness, Useful, Efficient Effective at doing what? Effectiveness is meaningless on its own. What outcome should the program or intervention have? Reduced symptoms of a mental health issue? Better socialization?
Etc., and so forth Get more specific. You need to know enough about your topic to clearly address the concepts within it. Don’t assume that your reader understands what you mean by “and so forth.”
It can be challenging in social work research to be this specific, particularly when you are just starting out your investigation of the topic. If you’ve only read one or two articles on the topic, it can be hard to know what you are interested in studying. Broad questions like “What are the causes of chronic homelessness, and what can be done to prevent it?” are common at the beginning stages of a research project. However, social work research demands that you examine the literature on the topic and refine your question over time to be more specific and clear before you begin your study. Perhaps you want to study the effect of a specific anti-homelessness program that you found in the literature. Maybe there is a particular model to fighting homelessness, like Housing First or transitional housing that you want to investigate further. You may want to focus on a potential cause of homelessness such as LGBTQ discrimination that you find interesting or relevant to your practice. As you can see, the possibilities for making your question more specific are almost infinite.
Quantitative exploratory questions
In exploratory research, the researcher doesn’t quite know the lay of the land yet. If someone is proposing to conduct an exploratory quantitative project, the watch words highlighted in Table 8.2 are not problematic at all. In fact, questions such as “What factors influence the removal of children in child welfare cases?” are good because they will explore a variety of factors or causes. In this question, the independent variable is less clearly written, but the dependent variable, family preservation outcomes, is quite clearly written. The inverse can also be true. If we were to ask, “What outcomes are associated with family preservation services in child welfare?”, we would have a clear independent variable, family preservation services, but an unclear dependent variable, outcomes. Because we are only conducting exploratory research on a topic, we may not have an idea of what concepts may comprise our “outcomes” or “factors.” Only after interacting with our participants will we be able to understand which concepts are important.
Key Takeaways
• Quantitative descriptive questions are helpful for community scans but cannot investigate causal relationships between variables.
• Quantitative explanatory questions must include an independent and dependent variable.
Image attributions
Ask by terimakasih0 CC-0 | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/08%3A_Creating_and_refining_a_research_question/8.03%3A_Quantitative_research_questions.txt |
Learning Objectives
• List the key terms associated with qualitative research questions
• Distinguish between qualitative and quantitative research questions
Qualitative research questions differ from quantitative research questions. Because qualitative research questions seek to explore or describe phenomena, not provide a neat nomothetic explanation, they are often more general and vaguely worded. They may include only one concept, though many include more than one. Instead of asking how one variable causes changes in another, we are instead trying to understand the experiences, understandings, and meanings that people have about the concepts in our research question.
Let’s work through an example from our last section. In Table 8.1, a student asked, “What is the relationship between sexual orientation or gender identity and homelessness for late adolescents in foster care?” In this question, it is pretty clear that the student believes that adolescents in foster care who identify as LGBTQ may be at greater risk for homelessness. This is a nomothetic causal relationship—LGBTQ status causes homelessness.
However, what if the student were less interested in predicting homelessness based on LGBTQ status and more interested in understanding the stories of foster care youth who identify as LGBTQ and may be at risk for homelessness? In that case, the researcher would be building an idiographic causal explanation. The youths whom the researcher interviews may share stories of how their foster families, caseworkers, and others treated them. They may share stories about how they thought of their own sexuality or gender identity and how it changed over time. They may have different ideas about what it means to transition out of foster care.
Because qualitative questions usually look for idiographic causal relationships, they look different than quantitative questions. Table 8.3 below takes the final research questions from Table 8.1 and adapts them for qualitative research. The guidelines for research questions previously described in this chapter still apply, but there are some new elements to qualitative research questions that are not present in quantitative questions. First, qualitative research questions often ask about lived experience, personal experience, understanding, meaning, and stories. These keywords indicate that you will be using qualitative methods. Second, qualitative research questions may be more general and less specific. Instead of asking how one concept causes another, we are asking about how people understand or feel about a concept. They may also contain only one variable, rather than asking about relationships between multiple variables.
Table 8.3 Qualitative research questions
Quantitative Research Questions Qualitative Research Questions
How does witnessing domestic violence impact a child’s romantic relationships in adulthood? How do people who witness domestic violence understand how it affects their current relationships?
What is the relationship between sexual orientation or gender identity and homelessness for late adolescents in foster care? What is the experience of identifying as LGBTQ in the foster care system?
How does income inequality affect ambivalence in high-density urban areas? What does racial ambivalence mean to residents of an urban neighborhood with high income inequality?
How does race impact rates of mental health diagnosis for children in foster care? How do African-Americans experience seeking help for mental health concerns?
Qualitative research questions have one final feature that distinguishes them from quantitative research questions. They can change over the course of a study. Qualitative research is a reflexive process, one in which the researcher adapts her approach based on what participants say and do. The researcher must constantly evaluate whether their question is important and relevant to the participants. As the researcher gains information from participants, it is normal for the focus of the inquiry to shift.
For example, a qualitative researcher may want to study how a new truancy rule impacts youth at risk of expulsion. However, after interviewing some of the youth in her community, a researcher might find that the rule is actually irrelevant to their behavior and thoughts. Instead, her participants will direct the discussion to their frustration with the school administrators or their family’s economic insecurity. This is a natural part of qualitative research, and it is normal for research questions and hypothesis to evolve based on the information gleaned from participants.
Key Takeaways
• Qualitative research questions often contain words like lived experience, personal experience, understanding, meaning, and stories.
• Qualitative research questions can change and evolve as the researcher conducts the study.
Image attributions
Empathy by Sean MacEntee CC-BY-2.0 | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/08%3A_Creating_and_refining_a_research_question/8.04%3A_Qualitative_research_questions.txt |
Learning Objectives
• Identify the aspects of feasibility that shape a researcher’s ability to conduct research
• Analyze the importance of research projects
Now that you have thought about topics that interest you and you’ve learned how to frame those topics as social work research questions, you have probably come up with a few potential research questions—questions to which you are dying to know the answers. However, even if you have identified the most brilliant research question ever, you are still not ready to begin conducting research. First, you’ll need to think about and come up with a plan for your research design, which we discussed in Chapter 7. Once you’ve settled on a research question, your next step is to think about the feasibility of your research question.
There are a few practical matters related to feasibility that all researchers should consider before beginning a research project. Are you interested in better understanding the day-to-day experiences of maximum security prisoners? This sounds fascinating, but unless you plan to commit a crime that lands you in a maximum security prison, gaining access to that facility would be difficult for an undergraduate student project. Perhaps your interest is in the inner workings of toddler peer groups. If you’re much older than four or five, however, it might be tough for you to access that sort of group. Your ideal research topic might require you to live on a chartered sailboat in the Bahamas for a few years, but unless you have unlimited funding, it will be difficult to make even that happen. The point, of course, is that while the topics about which social work questions can be asked may seem limitless, there are limits to which aspects of topics we can study or at least to the ways we can study them.
One of the most important questions in feasibility is whether or not you have access to the people you want to study. For example, let’s say you wanted to better understand students who engaged in self-harm behaviors in middle school. That is a topic of social importance, to be sure. But if you were a principal in charge of a middle school, would you want the parents to hear in the news about students engaging in self-harm at your school? Building a working relationship with the principal and the school administration will be a complicated task, but necessary in order to gain access to the population you need to study. Social work research must often satisfy multiple stakeholders. Stakeholders are individuals or groups who have an interest in the outcome of the study you conduct. Your goal of answering your research question can only be realized when you account for the goals of the other stakeholders. School administrators also want to help their students struggling with self-harm, so they may support your research project. But they may also need to avoid scandal and panic, providing support to students without making the problem worse.
Assuming you can gain approval to conduct research with the population that most interests you, do you know if that population will let you in? Researchers like Barrie Thorne (1993), [1] who study the behaviors of children, sometimes face this dilemma. In the course of her work, Professor Thorne has studied how children teach each other gender norms. She also studied how adults “gender” children, but here we’ll focus on just the former aspect of her work. Thorne had to figure out how to study the interactions of elementary school children when they probably would not accept her as one of their own. They were also unlikely to be able to read and complete a written questionnaire. Since she could not join them or ask them to read and write on a written questionnaire, Thorne’s solution was to watch the children. While this seems like a reasonable solution to the problem of not being able to actually enroll in elementary school herself, there is always the possibility that Thorne’s observations differed from what they might have been had she been able to actually join a class. What this means is that a researcher’s identity, in this case Thorne’s age, might sometimes limit (or enhance) her ability to study a topic in the way that she most wishes to study it. [2]
In addition to personal characteristics, there are also the very practical matters of time and money that shape what you are able to study or how you are able to study it. In terms of time, your personal time frame for conducting research may be the semester during which you are taking your research methods course. Perhaps, one day your employer will give you an even shorter timeline in which to conduct some research—or perhaps longer. By what time a researcher must complete her work may depend on a number of factors and will certainly shape what sort of research that person is able to conduct. Money, as always, is also relevant. For example, your ability to conduct research while living on a chartered sailboat in the Bahamas may be hindered unless you have unlimited funds or win the lottery. And if you wish to conduct survey research, you may have to think about the fact that mailing paper surveys costs not only time but money—from printing them to paying for the postage required to mail them. Interviewing people face to face may require that you offer your research participants a cup of coffee or glass of lemonade while you speak with them—and someone has to pay for the drinks.
In sum, feasibility is always a factor when deciding what, where, when, and how to conduct research. Aspects of your own identity may play a role in determining what you can and cannot investigate, as will the availability of resources such as time and money.
Importance
Another consideration before beginning a research project is whether the question is important enough. For the researcher, answering the question should be important enough to put in the effort, time, and often money required to complete a research project. As we discussed in Chapter 2, you should choose a topic that is important to you, one you wouldn’t mind learning about for at least a few months, if not a few years. Your time and effort are your most precious resources, particularly when you are in school. Make sure you dedicate them to topics and projects you consider important.
Your research question should also be important and relevant to the scientific literature in your topic area. Scientific relevance can be a challenging concept to assess. An example I often provide students is as follows. If you plan to research if cognitive behavioral therapy (CBT) is an effective treatment for depression, you are a little late to be asking that question. Hundreds of scientists have published articles demonstrating its effectiveness at treating depression. If CBT is a therapy of interest to you, perhaps you can consider applying it to a population like older adults for which there may be little evidence for CBT’s effectiveness or to a social problem like mobile phone addiction for which CBT has not been tested. Your project should have something new to say that we don’t already know. For a good reason, Google Scholar’s motto at the bottom of their search page is “stand on the shoulders of giants.” Social science research rests on the work of previous scholars, building off of what they found to learn more about the social world. Ensure that your question will bring our scientific understanding of your topic to new heights.
Finally, your research question should be important to the social world. Social workers conduct research on behalf of target populations. Just as clients in a clinician’s office rely on social workers to help them, target populations rely on social work researchers to help them by illuminating aspects their life. Your research should matter to the people you are trying to help. By helping this client population, your study should be important to society as a whole. In Chapter 4, we discussed the problem statement, which contextualizes your study within a social problem and target population. The purpose of your study is to address this social problem and further social justice. Research projects, obviously, do not need to address all aspects of a problem or fix all of society. Just making a small stride in the right direction is more than enough to make your study of importance to the social world.
If your study requires money to complete, and almost all of them do, you will also have to make the case that your study is important enough to fund. Research grants can be as small as a few hundred or thousand dollars to multi-million dollar grants and anywhere in between. Generally speaking, scientists rarely fund their own research. Instead, they must convince governments, foundations, or others to support their research. Conducting expensive research often involves aligning your research question with what the funder identifies as important. In our previous example on CBT and older adults, you may want to seek funding from an Area Office on Aging or the American Association of Retired Persons. However, you will need to fit your research into their funding priorities or make the case that your study is important enough on its own merits. Perhaps they are interested in reducing suicides or increasing social connectedness. These funding priorities seem like a natural fit for a study on treating depression. If you’re successful, funders become important stakeholders in the research process. Researchers must take great care not to create conflicts of interest in which the funder is able to dictate the outcome of the study before it is even conducted.
Key Takeaways
• When thinking about the feasibility of their research questions, researchers should consider their own identities and characteristics along with any potential constraints related to time and money.
• Your research question should be important to you, social scientists, the target population, and funding sources.
Glossary
• Stakeholders- individuals or groups who have an interest in the outcome of the study a researcher conducts
Image attributions
Man-wearing-black-and-white-stripe-shirt-looking-at-white-printer-papers-on-the-wall by StartupStockPhotos CC-0
important by geralt CC-0
1. Thorne, B. (1993). Gender play: Girls and boys in school. New Brunswick, NJ: Rutgers University Press. ↵
2. Think about Laud Humphreys’s research on the tearoom trade. Would he have been able to conduct this work if he had been a woman? ↵
8.06: Matching question and design
Learning Objectives
• Identify which research designs may be useful for answering your research question
This chapter described how to create a good quantitative and qualitative research question. Starting in Chapter 10, we will detail some of the basic designs that social scientists use to answer their research questions. But which design should you choose?
As with most things, it all depends on your research question. If your research question involves, for example, testing a new intervention, you will likely want to use an experimental design. On the other hand, if you want to know the lived experience of people in a public housing building, you probably want to use an interview or focus group design.
We will learn more about each one of these designs in the remainder of this textbook. We will also learn about using data that already exists, studying an individual client inside clinical practice, and evaluating programs, which are other examples of designs. Below is a list of designs we will cover in this textbook:
• Surveys: online, phone, mail, in-person
• Experiments: classic, pre-experiments, quasi-experiments
• Interviews: in-person or phone
• Focus groups
• Historical analysis
• Content analysis
• Secondary data analysis
• Program evaluation
• Single-subjects
• Action research
The design of your research study determines what you and your participants will do. In an experiment, for example, the researcher will introduce a stimulus or treatment to participants and measure their responses. In contrast, a content analysis may not have participants at all, and the researcher may simply read the marketing materials for a corporation or look at a politician’s speeches to conduct the data analysis for the study.
If you think about your project, I imagine that a content analysis probably seems easier to accomplish than an experiment. As a researcher, you have to choose a research design that makes sense for your question and that is feasible to complete with the resources you have. All research projects require some resources to accomplish. Make sure your design is one you can carry out with the resources (time, money, staff, etc.) that you have.
There are so many different designs that exist in the social science literature that it would be impossible to include them all in this textbook. For example, photovoice is a qualitative method in which participants take photographs of meaningful scenes in their lives and discuss them in focus groups. This qualitative method can be particularly impactful, as pictures can illustrate the meaning behind concepts often better than mere words. I encourage you through your undergraduate and graduate studies in social work to come to know more advanced and specialized designs. The purpose of the subsequent chapters is to help you understand the basic designs upon which these more advanced designs are built.
Key Takeaways
• The design you choose should follow from the research question you ask.
• Research design will determine what the researchers and participants do during the project.
Image attributions
Board by geralt CC-0 | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/08%3A_Creating_and_refining_a_research_question/8.05%3A_Feasibility_and_importance.txt |
This chapter is mainly focused on quantitative research methods, as the level of specificity required to begin quantitative research is far greater than that of qualitative research. In quantitative research, you must specify how you define and plan to measure each concept before you can interact with your participants. In qualitative research, definitions emerge from how participants respond to your questions. Because your participants are the experts, qualitative research does not reach the level of specificity and clarity required for quantitative research. For this reason, we will focus mostly on quantitative measurement and conceptualization in this chapter, with subsections addressing qualitative research.
This chapter discusses or mentions the following topics: mental health diagnoses and depression, masculinity, suicide, juvenile delinquency and the criminal justice system, substance abuse, and shooting guns.
09: Defining and measuring concepts
Learning Objectives
• Define measurement
• Describe Kaplan’s three categories of the things that social scientists measure
Measurement is important. Recognizing that fact, and respecting it, will be of great benefit to you—both in research methods and in other areas of life as well. If, for example, you have ever baked a cake, you know well the importance of measurement. As someone who much prefers rebelling against precise rules over following them, I once learned the hard way that measurement matters. A couple of years ago I attempted to bake my wife a birthday cake without the help of any measuring utensils. I’d baked before, I reasoned, and I had a pretty good sense of the difference between a cup and a tablespoon. How hard could it be? As it turns out, it’s not easy guesstimating precise measures. That cake was the lumpiest, most lopsided cake I’ve ever seen. And it tasted kind of like Play-Doh. Unfortunately for my wife, I did not take measurement seriously and it showed.
Just as measurement is critical to successful baking, it is as important to successfully pulling off a social scientific research project. In social science, when we use the term measurement we mean the process by which we describe and ascribe meaning to the key facts, concepts, or other phenomena that we are investigating. At its core, measurement is about defining one’s terms in as clear and precise a way as possible. Of course, measurement in social science isn’t quite as simple as using a measuring cup or spoon, but there are some basic tenants on which most social scientists agree when it comes to measurement. We’ll explore those, as well as some of the ways that measurement might vary depending on your unique approach to the study of your topic.
What do social scientists measure?
The question of what social scientists measure can be answered by asking yourself what social scientists study. Think about the topics you’ve learned about in other social work classes you’ve taken or the topics you’ve considered investigating yourself. Let’s consider Melissa Milkie and Catharine Warner’s study (2011) [1] of first graders’ mental health. In order to conduct that study, Milkie and Warner needed to have some idea about how they were going to measure mental health. What does mental health mean, exactly? And how do we know when we’re observing someone whose mental health is good and when we see someone whose mental health is compromised? Understanding how measurement works in research methods helps us answer these sorts of questions.
As you might have guessed, social scientists will measure just about anything that they have an interest in investigating. For example, those who are interested in learning something about the correlation between social class and levels of happiness must develop some way to measure both social class and happiness. Those who wish to understand how well immigrants cope in their new locations must measure immigrant status and coping. Those who wish to understand how a person’s gender shapes their workplace experiences must measure gender and workplace experiences. You get the idea. Social scientists can and do measure just about anything you can imagine observing or wanting to study. Of course, some things are easier to observe or measure than others.
In 1964, philosopher Abraham Kaplan (1964) [2] wrote TheConduct of Inquiry, which has since become a classic work in research methodology (Babbie, 2010). [3] In his text, Kaplan describes different categories of things that behavioral scientists observe. One of those categories, which Kaplan called “observational terms,” is probably the simplest to measure in social science. Observational terms are the sorts of things that we can see with the naked eye simply by looking at them. They are terms that “lend themselves to easy and confident verification” (Kaplan, 1964, p. 54). If, for example, we wanted to know how the conditions of playgrounds differ across different neighborhoods, we could directly observe the variety, amount, and condition of equipment at various playgrounds.
Indirect observables, on the other hand, are less straightforward to assess. They are “terms whose application calls for relatively more subtle, complex, or indirect observations, in which inferences play an acknowledged part. Such inferences concern presumed connections, usually causal, between what is directly observed and what the term signifies” (Kaplan, 1964, p. 55). If we conducted a study for which we wished to know a person’s income, we’d probably have to ask them their income, perhaps in an interview or a survey. Thus, we have observed income, even if it has only been observed indirectly. Birthplace might be another indirect observable. We can ask study participants where they were born, but chances are good we won’t have directly observed any of those people being born in the locations they report.
Sometimes the measures that we are interested in are more complex and more abstract than observational terms or indirect observables. Think about some of the concepts you’ve learned about in other social work classes—for example, ethnocentrism. What is ethnocentrism? Well, from completing an introduction to social work class you might know that it has something to do with the way a person judges another’s culture. But how would you measure it? Here’s another construct: bureaucracy. We know this term has something to do with organizations and how they operate, but measuring such a construct is trickier than measuring, say, a person’s income. In both cases, ethnocentrism and bureaucracy, these theoretical notions represent ideas whose meaning we have come to agree on. Though we may not be able to observe these abstractions directly, we can observe the things that they are made up of.
Kaplan referred to these more abstract things that behavioral scientists measure as constructs. Constructs are “not observational either directly or indirectly” (Kaplan, 1964, p. 55), but they can be defined based on observables. For example, the construct of bureaucracy could be measured by counting the number of supervisors that need to approve routine spending by public administrators. The greater the number of administrators that must sign off on routine matters, the greater the degree of bureaucracy. Similarly, we might be able to ask a person the degree to which they trust people from different cultures around the world and then assess the ethnocentrism inherent in their answers. We can measure constructs like bureaucracy and ethnocentrism by defining them in terms of what we can observe.
Thus far, we have learned that social scientists measure what Kaplan called observational terms, indirect observables, and constructs. These terms refer to the different sorts of things that social scientists may be interested in measuring. But how do social scientists measure these things? That is the next question we’ll tackle.
How do social scientists measure?
Measurement in social science is a process. It occurs at multiple stages of a research project: in the planning stages, in the data collection stage, and sometimes even in the analysis stage. Recall that previously we defined measurement as the process by which we describe and ascribe meaning to the key facts, concepts, or other phenomena that we are investigating. Once we’ve identified a research question, we begin to think about what some of the key ideas are that we hope to learn from our project. In describing those key ideas, we begin the measurement process.
Let’s say that our research question is the following: How do new college students cope with the adjustment to college? In order to answer this question, we’ll need some idea about what coping means. We may come up with an idea about what coping means early in the research process, as we begin to think about what to look for (or observe) in our data-collection phase. Once we’ve collected data on coping, we also have to decide how to report on the topic. Perhaps, for example, there are different types or dimensions of coping, some of which lead to more successful adjustment than others. However we decide to proceed, and whatever we decide to report, the point is that measurement is important at each of these phases.
As the preceding example demonstrates, measurement is a process in part because it occurs at multiple stages of conducting research. We could also think of measurement as a process because it involves multiple stages. From identifying your key terms to defining them to figuring out how to observe them and how to know if your observations are any good, there are multiple steps involved in the measurement process. An additional step in the measurement process involves deciding what elements your measures contain. A measure’s elements might be very straightforward and clear, particularly if they are directly observable. Other measures are more complex and might require the researcher to account for different themes or types. These sorts of complexities require paying careful attention to a concept’s level of measurement and its dimensions. We’ll explore these complexities in greater depth at the end of this chapter, but first let’s look more closely at the early steps involved in the measurement process, starting with conceptualization.
Key Takeaways
• Measurement is the process by which we describe and ascribe meaning to the key facts, concepts, or other phenomena that we are investigating.
• Kaplan identified three categories of things that social scientists measure including observational terms, indirect observables, and constructs.
• Measurement occurs at all stages of research.
Glossary
• Constructs- are not observable but can be defined based on observable characteristics
• Indirect observables- things that require indirect observation and inference to measure
• Measurement- the process by which researchers describe and ascribe meaning to the key facts, concepts, or other phenomena they are investigating
• Observational terms- things that we can see with the naked eye simply by looking at them
Image attributions
measuring tape by unknown CC-0
human observer by geralt CC-0
1. Milkie, M. A., & Warner, C. H. (2011). Classroom learning environments and the mental health of first grade children. Journal of Health and SocialBehavior, 52, 4–22. ↵
2. Kaplan, A. (1964). The conduct of inquiry: Methodology for behavioral science. San Francisco, CA: Chandler Publishing Company. ↵
3. Earl Babbie offers a more detailed discussion of Kaplan’s work in his text. You can read it in: Babbie, E. (2010). The practice ofsocial research (12th ed.). Belmont, CA: Wadsworth. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/09%3A_Defining_and_measuring_concepts/9.01%3A_Measurement.txt |
Learning Objectives
• Define concept
• Identify why defining our concepts is important
• Describe how conceptualization works in quantitative and qualitative research
• Define dimensions in terms of social scientific measurement
• Apply reification to conceptualization
In this section, we’ll take a look at one of the first steps in the measurement process, which is conceptualization. This has to do with defining our terms as clearly as possible and also not taking ourselves too seriously in the process. Our definitions mean only what we say they mean—nothing more and nothing less. Let’s talk first about how to define our terms, and then we’ll examine what I mean about not taking ourselves (or our terms, rather) too seriously.
Concepts and conceptualization
So far, the word concept has come up quite a bit, and it would behoove us to make sure we have a shared understanding of that term. A concept is the notion or image that we conjure up when we think of some cluster of related observations or ideas. For example, masculinity is a concept. What do you think of when you hear that word? Presumably, you imagine some set of behaviors and perhaps even a particular style of self-presentation. Of course, we can’t necessarily assume that everyone conjures up the same set of ideas or images when they hear the word masculinity. In fact, there are many possible ways to define the term. And while some definitions may be more common or have more support than others, there isn’t one true, always-correct-in-all-settings definition. What counts as masculine may shift over time, from culture to culture, and even from individual to individual (Kimmel, 2008). [1] This is why defining our concepts is so important.
You might be asking yourself why you should bother defining a term for which there is no single, correct definition. Believe it or not, this is true for any concept you might measure in a research study—there is never a single, always-correct definition. When we conduct empirical research, our terms mean only what we say they mean. There’s a New Yorker cartoon that aptly represents this idea (https://condenaststore.com/featured/it-all-depends-on-how-you-define-chop-tom-cheney.html). It depicts a young George Washington holding an axe and standing near a freshly chopped cherry tree. Young George is looking up at a frowning adult who is standing over him, arms crossed. The caption depicts George explaining, “It all depends on how you define ‘chop.’” Young George Washington gets the idea—whether he actually chopped down the cherry tree depends on whether we have a shared understanding of the term chop.
Without a shared understanding of this term, our understandings of what George has just done may differ. Likewise, without understanding how a researcher has defined her key concepts, it would be nearly impossible to understand the meaning of that researcher’s findings and conclusions. Thus, any decision we make based on findings from empirical research should be made based on full knowledge not only of how the research was designed, as described in Chapter 7 but also of how its concepts were defined and measured.
So, how do we define our concepts? This is part of the process of measurement, and this portion of the process is called conceptualization. The answer depends on how we plan to approach our research. We will begin with quantitative conceptualization and then discuss qualitative conceptualization.
In quantitative research, conceptualization involves writing out clear, concise definitions for our key concepts. Sticking with the previously mentioned example of masculinity, think about what comes to mind when you read that term. How do you know masculinity when you see it? Does it have something to do with men? With social norms? If so, perhaps we could define masculinity as the social norms that men are expected to follow. That seems like a reasonable start, and at this early stage of conceptualization, brainstorming about the images conjured up by concepts and playing around with possible definitions is appropriate. However, this is just the first step.
It would make sense as well to consult other previous research and theory to understand if other scholars have already defined the concepts we’re interested in. This doesn’t necessarily mean we must use their definitions, but understanding how concepts have been defined in the past will give us an idea about how our conceptualizations compare with the predominant ones out there. Understanding prior definitions of our key concepts will also help us decide whether we plan to challenge those conceptualizations or rely on them for our own work. Finally, working on conceptualization is likely to help in the process of refining your research question to one that is specific and clear in what it asks.
If we turn to the literature on masculinity, we will surely come across work by Michael Kimmel, one of the preeminent masculinity scholars in the United States. After consulting Kimmel’s prior work (2000; 2008), [2] we might tweak our initial definition of masculinity just a bit. Rather than defining masculinity as “the social norms that men are expected to follow,” perhaps instead we’ll define it as “the social roles, behaviors, and meanings prescribed for men in any given society at any one time” (Kimmel & Aronson, 2004, p. 503). [3] Our revised definition is both more precise and more complex. Rather than simply addressing one aspect of men’s lives (norms), our new definition addresses three aspects: roles, behaviors, and meanings. It also implies that roles, behaviors, and meanings may vary across societies and over time. To be clear, we’ll also have to specify the particular society and time period we’re investigating as we conceptualize masculinity.
As you can see, conceptualization isn’t quite as simple as merely applying any random definition that we come up with to a term. Sure, it may involve some initial brainstorming, but conceptualization goes beyond that. Once we’ve brainstormed a bit about the images a particular word conjures up for us, we should also consult prior work to understand how others define the term in question. And after we’ve identified a clear definition that we’re happy with, we should make sure that every term used in our definition will make sense to others. Are there terms used within our definition that also need to be defined? If so, our conceptualization is not yet complete. And there is yet another aspect of conceptualization to consider—concept dimensions. We’ll consider that aspect along with an additional word of caution about conceptualization in the next subsection.
Conceptualization in qualitative research proceeds a bit differently than in quantitative research. Because qualitative researchers are interested in the understandings and experiences of their participants, it is less important for the researcher to find one fixed definition for a concept before starting to interview or interact with participants. The researcher’s job is to accurately and completely represent how their participants understand a concept, not to test their own definition of that concept.
If you were conducting qualitative research on masculinity, you would likely consult previous literature like Kimmel’s work mentioned above. From your literature review, you may come up with a working definition for the terms you plan to use in your study, which can change over the course of the investigation. However, the definition that matters is the definition that your participants share during data collection. A working definition is merely a place to start, and researchers should take care not to think it is the only or best definition out there.
In qualitative inquiry, your participants are the experts (sound familiar, social workers?) on the concepts that arise during the research study. Your job as the researcher is to accurately and reliably collect and interpret their understanding of the concepts they describe while answering your questions. Conceptualization of qualitative concepts is likely to change over the course of qualitative inquiry, as you learn more information from your participants. Indeed, getting participants to comment on, extend, or challenge the definitions and understandings of other participants is a hallmark of qualitative research. This is the opposite of quantitative research, in which definitions must be completely set in stone before the inquiry can begin.
A word of caution about conceptualization
Whether you have chosen qualitative or quantitative methods, you should have a clear definition for the term masculinity and make sure that the terms we use in our definition are equally clear—and then we’re done, right? Not so fast. If you’ve ever met more than one man in your life, you’ve probably noticed that they are not all exactly the same, even if they live in the same society and at the same historical time period. This could mean there are dimensions of masculinity. In terms of social scientific measurement, concepts can be said to have multiple dimensions when there are multiple elements that make up a single concept. With respect to the term masculinity, dimensions could be regional (is masculinity defined differently in different regions of the same country?), age-based (is masculinity defined differently for men of different ages?), or perhaps power-based (does masculinity differ based on membership to privileged groups?). In any of these cases, the concept of masculinity would be considered to have multiple dimensions. While it isn’t necessarily required to spell out every possible dimension of the concepts you wish to measure, it may be important to do so depending on the goals of your research. The point here is to be aware that some concepts have dimensions and to think about whether and when dimensions may be relevant to the concepts you intend to investigate.
Before we move on to the additional steps involved in the measurement process, it would be wise to remind ourselves not to take our definitions too seriously. Conceptualization must be open to revisions, even radical revisions, as scientific knowledge progresses. While I’ve suggested that we should consult prior scholarly definitions of our concepts, it would be wrong to assume that just because prior definitions exist that they are more real than the definitions we create (or, likewise, that our own made-up definitions are any more real than any other definition). It would also be wrong to assume that just because definitions exist for some concept that the concept itself exists beyond some abstract idea in our heads. This idea, assuming that our abstract concepts exist in some concrete, tangible way, is known as reification.
To better understand reification, take a moment to think about the concept of social structure. This concept is central to critical thinking. When social scientists talk about social structure, they are talking about an abstract concept. Social structures shape our ways of being in the world and of interacting with one another, but they do not exist in any concrete or tangible way. A social structure isn’t the same thing as other sorts of structures, such as buildings or bridges. Sure, both types of structures are important to how we live our everyday lives, but one we can touch, and the other is just an idea that shapes our way of living.
Here’s another way of thinking about reification: Think about the term family. If you were interested in studying this concept, we’ve learned that it would be good to consult prior theory and research to understand how the term has been conceptualized by others. But we should also question past conceptualizations. Think, for example, about how different the definition of family was 50 years ago. Because researchers from that time period conceptualized family using now outdated social norms, social scientists from 50 years ago created research projects based on what we consider now to be a very limited and problematic notion of what family means. Their definitions of family were as real to them as our definitions are to us today. If researchers never challenged the definitions of terms like family, our scientific knowledge would be filled with the prejudices and blind spots from years ago. It makes sense to come to some social agreement about what various concepts mean. Without that agreement, it would be difficult to navigate through everyday living. But at the same time, we should not forget that we have assigned those definitions, they are imperfect and subject to change as a result of critical inquiry.
Key Takeaways
• Conceptualization is a process that involves coming up with clear, concise definitions.
• Conceptualization in quantitative research comes from the researcher’s ideas or the literature.
• Qualitative researchers conceptualize by creating working definitions which will be revised based on what participants say.
• Some concepts have multiple elements or dimensions.
• Researchers should acknowledge the limitations of their definitions for concepts.
Glossary
• Concept- notion or image that we conjure up when we think of some cluster of related observations or ideas
• Conceptualization- writing out clear, concise definitions for our key concepts, particularly in quantitative research
• Multi-dimensional concepts- concepts that are comprised of multiple elements
• Reification- assuming that abstract concepts exist in some concrete, tangible way
Image attributions
thought by TeroVesalainen CC-0
mindmap by TeroVesalainen CC-0
1. Kimmel, M. (2008). Masculinity. In W. A. Darity Jr. (Ed.), International encyclopedia of the social sciences (2nd ed., Vol. 5, p. 1–5). Detroit, MI: Macmillan Reference USA. ↵
2. Kimmel, M. (2000). Thegendered society. New York, NY: Oxford University Press; Kimmel, M. (2008). Masculinity. In W. A. Darity Jr. (Ed.), Internationalencyclopedia of the social sciences (2nd ed., Vol. 5, p. 1–5). Detroit, MI: Macmillan Reference USA. ↵
3. Kimmel, M. & Aronson, A. B. (2004). Men and masculinities: A-J. Denver, CO: ABL-CLIO. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/09%3A_Defining_and_measuring_concepts/9.02%3A_Conceptualization.txt |
Learning Objectives
• Define and give an example of indicators for a variable
• Identify the three components of an operational definition
• Describe the purpose of multi-dimensional measures such as indexes, scales, and typologies and why they are used
Now that we have figured out how to define, or conceptualize, our terms we’ll need to think about operationalizing them. Operationalization is the process by which researchers conducting quantitative research spell out precisely how a concept will be measured. It involves identifying the specific research procedures we will use to gather data about our concepts. This of course requires that we know what research method(s) we will employ to learn about our concepts, and we’ll examine specific research methods later on in the text. For now, let’s take a broad look at how operationalization works. We can then revisit how this process works when we examine specific methods of data collection in later chapters. Remember, operationalization is only a process in quantitative research. Measurement in qualitative research will be discussed at the end of this section.
Indicators
Operationalization works by identifying specific indicators that will be taken to represent the ideas we are interested in studying. If, for example, we are interested in studying masculinity, indicators for that concept might include some of the social roles prescribed to men in society such as breadwinning or fatherhood. Being a breadwinner or a father might therefore be considered indicators of a person’s masculinity. The extent to which a man fulfills either, or both, of these roles might be understood as clues (or indicators) about the extent to which he is viewed as masculine.
Let’s look at another example of indicators. Each day, Gallup researchers poll 1,000 randomly selected Americans to ask them about their well-being. To measure well-being, Gallup asks these people to respond to questions covering six broad areas: physical health, emotional health, work environment, life evaluation, healthy behaviors, and access to basic necessities. Gallup uses these six factors as indicators of the concept that they are really interested in, which is well-being (http://www.well-beingindex.com/).
Identifying indicators can be even simpler than the examples described thus far. What are the possible indicators of the concept of gender? Most of us would probably agree that “man” and “woman” are both reasonable indicators of gender, but you may want to include other options for people who identify as non-binary or other genders. Political party is another relatively easy concept for which to identify indicators. In the United States, likely indicators include Democrat and Republican and, depending on your research interest, you may include additional indicators such as Independent, Green, or Libertarian as well. Age and birthplace are additional examples of concepts for which identifying indicators is a relatively simple process. What concepts are of interest to you, and what are the possible indictors of those concepts?
Business charts by Pixabay CC-0
We have now considered a few examples of concepts and their indicators, but it is important we don’t make the process of coming up with indicators too arbitrary or casual. One way to avoid taking an overly casual approach in identifying indicators, as described previously, is to turn to prior theoretical and empirical work in your area. Theories will point you in the direction of relevant concepts and possible indicators; empirical work will give you some very specific examples of how the important concepts in an area have been measured in the past and what sorts of indicators have been used. Often, it makes sense to use the same indicators as researchers who have come before you. On the other hand, perhaps you notice some possible weaknesses in measures that have been used in the past that your own methodological approach will enable you to overcome.
Speaking of your methodological approach, another very important thing to think about when deciding on indicators and how you will measure your key concepts is the strategy you will use for data collection. A survey implies one way of measuring concepts, while focus groups imply a quite different way of measuring concepts. Your design choices will play an important role in shaping how you measure your concepts.
Operationalizing your variables
Moving from identifying concepts to conceptualizing them and then to operationalizing them is a matter of increasing specificity. You begin the research process with a general interest, identify a few concepts that are essential for studying that interest you, work to define those concepts, and then spell out precisely how you will measure those concepts. In quantitative research, that final stage is called operationalization.
An operational definition consists of the following components: (1) the variable being measured, (2) the measure you will use, (3) how you plan to interpret the results of that measure.
The first component, the variable, should be the easiest part. By now in quantitative research, you should have a research question that has at least one independent and at least one dependent variable. Remember that variables have to be able to vary. For example, the United States is not a variable. Country of birth is a variable, as is patriotism. Similarly, if your sample only includes men, gender is a constant in your study…not a variable.
Let’s pick a social work research question and walk through the process of operationalizing variables. I’m going to hypothesize that individuals on a residential psychiatric unit who are more depressed are less likely to be satisfied with care. Remember, this would be a negative relationship—as depression increases, satisfaction decreases. In this question, depression is my independent variable (the cause) and satisfaction with care is my dependent variable (the effect). We have our two variables—depression and satisfaction with care—so the first component is done. Now, we move onto the second component–the measure.
How do you measure depression or satisfaction? Many students begin by thinking that they could look at body language to see if a person were depressed. Maybe they would also verbally express feelings of sadness or hopelessness more often. A satisfied person might be happy around service providers and express gratitude more often. These may indicate depression, but they lack coherence. Unfortunately, what this “measure” is actually saying is that “I know depression and satisfaction when I see them.” While you are likely a decent judge of depression and satisfaction, you need to provide more information in a research study for how you plan to measure your variables. Your judgment is subjective, based on your own idiosyncratic experiences with depression and satisfaction. They couldn’t be replicated by another researcher. They also can’t be done consistently for a large group of people. Operationalization requires that you come up with a specific and rigorous measure for seeing who is depressed or satisfied.
Finding a good measure for your variable can take less than a minute. To measure a variable like age, you would probably put a question on a survey that asked, “How old are you?” To evaluate someone’s length of stay in a hospital, you might ask for access to their medical records and count the days from when they were admitted to when they were discharged. Measuring a variable like income might require some more thought, though. Are you interested in this person’s individual income or the income of their family unit? This might matter if your participant does not work or is dependent on other family members for income. Do you count income from social welfare programs? Are you interested in their income per month or per year? Measures must be specific and clear.
Depending on your research design, your measure may be something you put on a survey or pre/post-test that you give to your participants. For a variable like age or income, one well-worded question may suffice. Unfortunately, most variables in the social world so simple. Depression and satisfaction are multi-dimensional variables, as they each contain multiple elements. Asking someone “Are you depressed?” does not do justice to the complexity of depression, which includes issues with mood, sleeping, eating, relationships, and happiness. Asking someone “Are you satisfied with the services you received?” similarly omits multiple dimensions of satisfaction, such as timeliness, respect, meeting needs, and likelihood of recommending to a friend, among many others.
Checklist by TeroVesalainen CC-0
To account for a variable’s dimensions, a researcher might rely on indexes, scales, or typologies. An index is a type of measure that contains several indicators and is used to summarize some more general concept. An index of depression might ask if the person has experienced any of the following indicators in the past month: pervasive feelings of hopelessness, thoughts of suicide, over- or under-eating, and a lack of enjoyment in normal activities. On their own, some of these indicators like over- or under-eating might not be considered depression, but collectively, the answers to each of these indicators add up to an overall experience of depression. The index allows the researcher in this case to better understand what shape a respondent’s depression experience takes. If the researcher had only asked whether a respondent had ever experienced depression, she wouldn’t know what sorts of behaviors actually made up that respondent’s experience of depression.
Taking things one step further, if the researcher decides to rank order the various behaviors that make up depression, perhaps weighting suicidal thoughts more heavily than eating disturbances, then she will have created a scale rather than an index. Like an index, a scale is also a measure composed of multiple items or questions. But unlike indexes, scales are designed in a way that accounts for the possibility that different items may vary in intensity.
If creating your own scale sounds painful, don’t worry! For most multidimensional variables, you would likely be duplicating work that has already been done by other researchers. You do not need to create a scale for depression because scales such as the Patient Health Questionnaire (PHQ-9) and the Center for Epidemiologic Studies Depression Scale (CES-D) and Beck’s Depression Inventory (BDI) have been developed and refined over dozens of years to measure variables like depression. Similarly, scales such as the Patient Satisfaction Questionnaire (PSQ-18) have been developed to measure satisfaction with medical care. As we will discuss in the next section, these scales have been shown to be reliable and valid. While you could create a new scale to measure depression or satisfaction, a study with rigor would pilot test and refine that scale over time to make sure it measures the concept accurately and consistently. This high level of rigor is often unachievable in undergraduate research projects, so using existing scales is recommended.
Another reason existing scales are preferable is that they can save time and effort. The Mental Measurements Yearbook provides a searchable database of measures for different variables. You can access this database from your library’s list of databases. If you can’t find anything in there, your next stop should be the methods section of the articles in your literature review. The methods section of each article will detail how the researchers measured their variables. In a quantitative study, researchers likely used a scale to measure key variables and will provide a brief description of that scale. A Google Scholar search such as “depression scale” or “satisfaction scale” should also provide some relevant results. As a last resort, a general web search may bring you to a scale for your variable.
Unfortunately, all of these approaches do not guarantee that you will be able to actually see the scale itself or get information on how it is interpreted. Many scales cost money to use and may require training to properly administer. You may also find scales that are related to your variable but would need to be slightly modified to match your study’s needs. Adapting a scale to fit your study is a possibility; however, you should remember that changing even small parts of a scale can influence its accuracy and consistency. Pilot testing is always recommended for adapted scales.
A final way of measuring multidimensional variables is a typology. A typology is a way of categorizing concepts according to particular themes. Probably the most familiar version of a typology is the micro, meso, macro framework. Students classify specific elements of the social world by their ecological relationship with the person. Taking again the example of depression. The lack of sleep would be classified as a micro-level elements while a severe economic recession would be classified as a macro-level elements. Typologies require clearly stated rules on what data will get assigned to what categories, so finding and citing a source on ecological systems theory that provides the rules on what elements are on each level of the ecosystem would be important.
The rules of how the scale works and how the researcher should interpret the results are the final part of operatoinalization. We discussed how ecological systems theory will help give you the rules for interpreting your micro/meso/macro topology. Sometimes, interpreting a measure is incredibly easy. If you ask someone their age, you’ll probably interpret the results by noting the raw number (e.g., 22) someone provides. However, you could also recode that person into age categories (e.g., under 25, 20-29-years-old, etc.). Indexes may also be simple to interpret. If there is a checklist of problem behaviors, one might simply add up the number of behaviors checked off–with a higher total indicating worse behavior. On the other hand, indexes could assign people to categories (e.g., normal, borderline, moderate, significant, severe) based on their total number of checkmarks. As long as the rules are clearly spelled out, you are welcome to interpret in a way that makes sense to you. Theory might guide you to use some categories or you might be influenced by the types of statistical tests you plan to run later on in data analysis.
For more complicated measures like scales, you should look at the information provided by the scale’s authors for how to interpret the scale. If you can’t find enough information from the scale’s creator, look at how the results of that scale are reported in the results section of research articles. For example, Beck’s Depression Inventory (BDI-II) uses 21 questions to measure depression. A person indicates on a scale of 0-3 how much they agree with a statement. The results for each question are added up, and the respondent is put into one of three categories: low levels of depression (1-16), moderate levels of depression (17-30), or severe levels of depression (31 and over).
In sum, operationalization specifies what measure you will be using to measure your variable and how you plan to interpret that measure. Operationalization is probably the trickiest component of basic research methods. Don’t get frustrated if it takes a few drafts and a lot of feedback to get to a workable definition. I’m currently trying operationalize the concept attitudes towards research methods. Originally, I thought I could use the course evaluations students completed at the end of the semester to gauge their attitudes towards research methods. As I looked into the methodological problems with student course evaluations, I reconsidered how I measured attitudes towards research. I used focus groups of students to figure out common beliefs about research. I mentioned these opinions in Chapter 1—including that research is boring, useless, and too difficult. I then created a scale based on these opinions, and plan to pilot test it with another group of students. I expect that after the pilot test I will have to revise it yet again before I can implement the measure in a real social work research project. At the time I’m writing this, I’m still not completely done operationalizing this concept.
Qualitative research and Operationalization
As we discussed in the previous section, qualitative research takes a more open approach towards defining the concepts in your research question. The questions you choose to ask in your interview, focus group, or content analysis will determine what data you end up getting from your participants. For example, if you are researching depression qualitatively, you would not use a scale like the Beck’s Depression Inventory, which is a quantitative measure we described above. Instead, you should start off with a tentative definition of what depression means based on your literature review and use that definition to come up with questions for your participants. We will cover how those questions fit into qualitative research designs later on in the textbook. For now, remember that qualitative researchers use the questions they ask participants to measure their variables and that qualitative researchers can change their questions as they gather more information from participants. Ultimately, the concepts in a qualitative study will be defined by the researcher’s interpretation of what her participants say. Unlike in quantitative research in which definitions must be explicitly spelled out in advance, qualitative research allows the definitions of concepts to emerge during data analysis.
Key Takeaways
• Operationalization involves spelling out precisely how a concept will be measured.
• Operational definitions must include the variable, the measure, and how you plan to interpret the measure.
• Indexes, scales, and typologies are used to measure multi-dimensional concepts.
• It’s a good idea to look at how researchers have measured the concept in previous studies.
Glossary
• Index- measure that contains several indicators and is used to summarize a more general concept
• Indicators- represent the concepts that we are interested in studying
• Operationalization- process by which researchers conducting quantitative research spell out precisely how a concept will be measured and how to interpret that measure
• Scale- composite measure designed in a way that accounts for the possibility that different items on an index may vary in intensity
• Typology- measure that categorizes concepts according to particular themes | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/09%3A_Defining_and_measuring_concepts/9.03%3A_Operationalization.txt |
Learning Objectives
• Define reliability and describe the types of reliability
• Define validity and describe the types of validity
• Analyze the rigor of qualitative measurement using the criteria of trustworthiness and authenticity
In quantitative research, once we’ve managed to define our terms and specify the operations for measuring them, how do we know that our measures are any good? Without some assurance of the quality of our measures, we cannot be certain that our findings have any meaning or, at the least, that our findings mean what we think they mean. When social scientists measure concepts, they aim to achieve reliability and validity in their measures. These two aspects of measurement quality are the focus of this section. We’ll consider reliability first and then take a look at validity. For both aspects of measurement quality, let’s say our interest is in measuring the concepts of alcoholism and alcohol intake. What are some potential problems that could arise when attempting to measure this concept, and how might we work to overcome those problems?
Quality by geralt CC-0
Reliability
First, let’s say we’ve decided to measure alcoholism by asking people to respond to the following question: Have you ever had a problem with alcohol? If we measure alcoholism in this way, it seems likely that anyone who identifies as an alcoholic would respond with a yes to the question. So, this must be a good way to identify our group of interest, right? Well, maybe. Think about how you or others you know would respond to this question. Would responses differ after a wild night out from what they would have been the day before? Might an infrequent drinker’s current headache from the single glass of wine she had last night influence how she answers the question this morning? How would that same person respond to the question before consuming the wine? In each of these cases, if the same person would respond differently to the same question at different points, it is possible that our measure of alcoholism has a reliability problem. Reliability in measurement is about consistency.
One common problem of reliability with social scientific measures is memory. If we ask research participants to recall some aspect of their own past behavior, we should try to make the recollection process as simple and straightforward for them as possible. Sticking with the topic of alcohol intake, if we ask respondents how much wine, beer, and liquor they’ve consumed each day over the course of the past 3 months, how likely are we to get accurate responses? Unless a person keeps a journal documenting their intake, there will very likely be some inaccuracies in their responses. If, on the other hand, we ask a person how many drinks of any kind they have consumed in the past week, we might get a more accurate set of responses.
Reliability can be an issue even when we’re not reliant on others to accurately report their behaviors. Perhaps a researcher is interested in observing how alcohol intake influences interactions in public locations. She may decide to conduct observations at a local pub, noting how many drinks patrons consume and how their behavior changes as their intake changes. But what if the researcher has to use the restroom and misses the three shots of tequila that the person next to her downs during the brief period she is away? The reliability of this researcher’s measure of alcohol intake, counting numbers of drinks she observes patrons consume, depends on her ability to actually observe every instance of patrons consuming drinks. If she is unlikely to be able to observe every such instance, then perhaps her mechanism for measuring this concept is not reliable.
If a measure is reliable, it means that if the measure is given multiple times, the results will be consistent each time. For example, if you took the SATs on multiple occasions before coming to school, your scores should be relatively the same from test to test. This is what is known as test-retest reliability. In the same way, if a person is clinically depressed, a depression scale should give similar (though not necessarily identical) results today that it does two days from now.
Additionally, if your study involves observing people’s behaviors, for example watching sessions of mothers playing with infants, you may also need to assess inter-rater reliability. Inter-rater reliability is the degree to which different observers agree on what happened. Did you miss when the infant offered an object to the mother and the mother dismissed it? Did the other person rating miss that event? Do you both similarly rate the parent’s engagement with the child? Again, scores of multiple observers should be consistent, though perhaps not perfectly identical.
Finally, for scales, internal consistency reliability is an important concept. The scores on each question of a scale should be correlated with each other, as they all measure parts of the same concept. Think about a scale of depression, like Beck’s Depression Inventory. A person who is depressed would score highly on most of the measures, but there would be some variation. If we gave a group of people that scale, we would imagine there should be a correlation between scores on, for example, mood disturbance and lack of enjoyment. They aren’t the same concept, but they are related. So, there should be a mathematical relationship between them. A specific statistical test known as Cronbach’s Alpha provides a way to measure how well each question of a scale is related to the others.
Test-retest, inter-rater, and internal consistency are three important subtypes of reliability. Researchers use these types of reliability to make sure their measures are consistently measuring the concepts in their research questions.
Validity
While reliability is about consistency, validity is about accuracy. What image comes to mind for you when you hear the word alcoholic? Are you certain that the image you conjure up is similar to the image others have in mind? If not, then we may be facing a problem of validity.
For a measure to have validity, we must be certain that our measures accurately get at the meaning of our concepts. Think back to the first possible measure of alcoholism we considered in the previous few paragraphs. There, we initially considered measuring alcoholism by asking research participants the following question: Have you ever had a problem with alcohol? We realized that this might not be the most reliable way of measuring alcoholism because the same person’s response might vary dramatically depending on how they are feeling that day. Likewise, this measure of alcoholism is not particularly valid. What is “a problem” with alcohol? For some, it might be having had a single regrettable or embarrassing moment that resulted from consuming too much. For others, the threshold for “problem” might be different; perhaps a person has had numerous embarrassing drunken moments but still gets out of bed for work every day, so they don’t perceive themselves as having a problem. Because what each respondent considers to be problematic could vary so dramatically, our measure of alcoholism isn’t likely to yield any useful or meaningful results if our aim is to objectively understand, say, how many of our research participants are alcoholics. [1]
In the last paragraph, critical engagement with our measure for alcoholism “Do you have a problem with alcohol?” was shown to be flawed. We assessed its face validity or whether it is plausible that the question measures what it intends to measure. Face validity is a subjective process. Sometimes face validity is easy, as a question about height wouldn’t have anything to do with alcoholism. Other times, face validity can be more difficult to assess. Let’s consider another example.
Perhaps we’re interested in learning about a person’s dedication to healthy living. Most of us would probably agree that engaging in regular exercise is a sign of healthy living, so we could measure healthy living by counting the number of times per week that a person visits their local gym. But perhaps they visit the gym to use their tanning beds or to flirt with potential dates or sit in the sauna. These activities, while potentially relaxing, are probably not the best indicators of healthy living. Therefore, recording the number of times a person visits the gym may not be the most valid way to measure their dedication to healthy living.
Another problem with this measure of healthy living is that it is incomplete. Content validity assesses for whether the measure includes all of the possible meanings of the concept. Think back to the previous section on multidimensional variables. Healthy living seems like a multidimensional concept that might need an index, scale, or typology to measure it completely. Our one question on gym attendance doesn’t cover all aspects of healthy living. Once you have created one, or found one in the existing literature, you need to assess for content validity. Are there other aspects of healthy living that aren’t included in your measure?
Let’s say you have created (or found) a good scale, index, or typology for your measure of healthy living. A valid measure of healthy living would be able to predict, for example, scores of a blood panel test during their annual physical. This is called predictive validity, and it means that your measure predicts things it should be able to predict. In this case, I assume that if you have a healthy lifestyle, a standard blood test done a few months later during an annual checkup would show healthy results. If we were to administer the blood panel measure at the same time as you administer your scale of healthy living, we would be assessing concurrent validity. Concurrent validity is the same as predictive validity—the scores on your measure should be similar to an established measure—except that both measures are given at the same time.
Another closely related concept is convergent validity. In assessing for convergent validity, one should look for existing measures of the same concept, for example the Healthy Lifestyle Behaviors Scale (HLBS). If you give someone your scale and the HLBS at the same time, their scores should be pretty similar. Convergent validity takes an existing measure of the same concept and compares your measure to it. If their scores are similar, then it’s probably likely that they are both measuring the same concept. Discriminant validity is a similar concept, except you would be comparing your measure to one that is entirely unrelated. A participant’s scores on your healthy lifestyle measure shouldn’t be statistically correlated with a scale that measures knowledge of the Italian language.
These are the basic subtypes of validity, though there are certainly others you can read more about. One way to think of validity is to think of it as you would a portrait. Some portraits of people look just like the actual person they are intended to represent. But other representations of people’s images, such as caricatures and stick drawings, are not nearly as accurate. While a portrait may not be an exact representation of how a person looks, what’s important is the extent to which it approximates the look of the person it is intended to represent. The same goes for validity in measures. No measure is exact, but some measures are more accurate than others.
If you are still confused about validity and reliability, Figure 9.2 shows what a validity and reliability look like. On the first target, our shooter’s aim is all over the place. It is neither reliable (consistent) nor valid (accurate). The second (top right) target shows an unreliable or inconsistent shot, but one that is centered around the target (accurate). The third (bottom left) target demonstrates consistency…but it is reliably off-target, or invalid. The fourth and final target (bottom right) represents a reliable and valid result. The person is able to hit the target accurately and consistently. This is what you should aim for in your research.
[2]
Trustworthiness and authenticity
In qualitative research, the standards for measurement quality differ than quantitative research for an important reason. Measurement in quantitative research is done objectively or impartially. That is, the researcher doesn’t have much to do with it. The researcher chooses a measure, applies it, and reads the results. The extent to which the results are accurate and consistent is a problem with the measure, not the researcher.
The same cannot be said for qualitative research. Qualitative researchers are deeply involved in the data analysis process. There is no external measurement tool, like a quantitative scale. Rather, the researcher herself is the measurement instrument. Researchers build connections between different ideas that participants discuss and draft an analysis that accurately reflects the depth and complexity of what participants have said. This is a challenging task for a researcher. It involves acknowledging her own biases, either from personal experience or previous knowledge about the topic, and allowing the meaning that participants shared to emerge as the data is read. It’s not necessarily about being objective, as there is always some subjectivity in qualitative analysis, but more about the rigor with which the individual researcher engages in data analysis.
Trust by Terry Johnston CC-BY-2.0
For this reason, researchers speak of rigor in more personal terms. Trustworthiness refers to the “truth value, applicability, consistency, and neutrality” of the results of a research study (Rodwell, 1998, p. 96). [3] Authenticity refers to the degree to which researchers capture the multiple perspectives and values of participants in their study and foster change across participants and systems during their analysis. Both trustworthiness and authenticity contain criteria that help a researcher gauge the rigor with which the study was conducted.
Most relevant to the discussion of validity and reliability are the trustworthiness criteria of credibility, dependability, and confirmability. Credibility refers to the degree to which the results are accurate and viewed as important and believable by participants. Qualitative researchers will often check with participants before finalizing and publishing their results to make sure participants agree with them. They may also seek out assistance from another qualitative researcher to review or audit their work. As you might expect, it’s difficult to view your own research without bias, so another set of eyes is often helpful. Unlike in quantitative research, the ultimate goal is not to find the Truth (with a capital T) using a predetermined measure, but to create a credible interpretation of the data.
Credibility is seen as akin to validity, as it mainly speaks to the accuracy of the research product. The criteria of dependability, on the other hand, is similar to reliability. As we just reviewed, reliability is the consistency of a measure. If you give the same measure each time, you should get similar results. However, qualitative research questions, hypotheses, and interview questions may change during the research process. How can one achieve reliability under such conditions?
Because emergence is built into the procedures of qualitative data analysis, there isn’t a need for everyone to get the exact same questions each time. Indeed, because qualitative research understands the importance of context, it would be impossible to control all of the things that would make a qualitative measure the same when you give it to each person. The location, timing, or even the weather can and do influence participants to respond differently. Researchers assessing dependability make sure that proper qualitative procedures were followed and that any changes that emerged during the research process are accounted for, justified, and described in the final report. Researchers should document changes to their methodology and the justification for them in a journal or log. In addition, researchers may again use another qualitative researcher to examine their logs and results to ensure dependability.
Finally, the criteria of confirmability refers to the degree to which the results reported are linked to the data obtained from participants. While it is possible that another researcher could view the same data and come up with a different analysis, confirmability ensures that a researcher’s results are actually grounded in what participants said. Another researcher should be able to read the results of your study and trace each point made back to something specific that one or more participants shared. This process is called an audit.
The criteria for trustworthiness were created as a reaction to critiques of qualitative research as unscientific (Guba, 1990). [4] They demonstrate that qualitative research is equally as rigorous as quantitative research. Subsequent scholars conceptualized the dimension of authenticity without referencing the standards of quantitative research at all. Instead, they wanted to understand the rigor of qualitative research on its own terms. What comes from acknowledging the importance of the words and meanings that people use to express their experiences?
While there are multiple criteria for authenticity, the one that is most important for undergraduate social work researchers to understand is fairness. Fairness refers to the degree to which “different constructions, perspectives, and positions are not only allowed to emerge, but are also seriously considered for merit and worth” (Rodwell, 1998, p. 107). Qualitative researchers, depending on their design, may involve participants in the data analysis process, try to equalize power dynamics among participants, and help negotiate consensus on the final interpretation of the data. As you can see from the talk of power dynamics and consensus-building, authenticity attends to the social justice elements of social work research.
After fairness, the criteria for authenticity become more radical, focusing on transforming individuals and systems examined in the study. For our purposes, it is important for you to know that qualitative research and measurement are conducted with the same degree of rigor as quantitative research. The standards may be different, but they speak to the goals of accurate and consistent results that reflect the views of the participants in the study.
Key Takeaways
• Reliability is a matter of consistency.
• Validity is a matter of accuracy.
• There are many types of validity and reliability.
• The criteria that qualitative researchers use to assess rigor are trustworthiness and authenticity.
• Quantitative research is not inherently more rigorous than qualitative research. Both are equally rigorous, though the standards for assessing rigor differ between the two.
Glossary
• Authenticity- the degree to which researchers capture the multiple perspectives and values of participants in their study and foster change across participants and systems during their analysis
• Concurrent validity- if a measure is able to predict outcomes from an established measure given at the same time
• Confirmability- the degree to which the results reported are linked to the data obtained from participants
• Content validity- if the measure includes all of the possible meanings of the concept
• Convergent validity- if a measure is conceptually similar to an existing measure of the same concept
• Credibility- the degree to which the results are accurate and viewed as important and believable by participants
• Dependability- ensures that proper qualitative procedures were followed and that any changes that emerged during the research process are accounted for, justified, and described in the final report
• Discriminant validity- if a measure is not related to measures to which it shouldn’t be statistically correlated
• Face validity- if it is plausible that the measure measures what it intends to
• Fairness- the degree to which “different constructions, perspectives, and positions are not only allowed to emerge, but are also seriously considered for merit and worth” (Rodwell, 1998, p. 107)
• Internal consistency reliability- degree to which scores on each question of a scale are correlated with each other
• Inter-rater reliability- the degree to which different observers agree on what happened
• Predictive validity- if a measure predicts things it should be able to predict in the future
• Reliability- a measure’s consistency.
• Test-retest reliability- if a measure is given multiple times, the results will be consistent each time
• Trustworthiness- the “truth value, applicability, consistency, and neutrality” of the results of a research study (Rodwell, 1998, p. 96)
• Validity- a measure’s accuracy
1. Of course, if our interest is in how many research participants perceive themselves to have a problem, then our measure may be just fine. ↵
2. Figure 9.2 was adapted from Nevit Dilmen’s “Reliability and validity” (2012) Shared under a CC-BY 3.0 license Retrieved from: https://commons.wikimedia.org/wiki/File:Reliability_and_validity.svg I changed the word unvalid to invalid to reflect more commonly used language. ↵
3. Rodwell, M. K. (1998). Social work constructivist research. New York, NY: Garland Publishing. ↵
4. Guba, E. G. (1990). The paradigm dialog. Newbury Park, CA: Sage Publications. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/09%3A_Defining_and_measuring_concepts/9.04%3A_Measurement_quality.txt |
Learning Objectives
• Define and provide examples for the four levels of measurement
• Identify potential sources of error
• Differentiate between systematic and random error
For quantitative methods, you should now have some idea about how conceptualization and operationalization work, and you should also know how to assess the quality of your measures. But measurement is sometimes a complex process, and some concepts are more complex than others. Measuring a person’s political party affiliation, for example, is less complex than measuring their sense of alienation. In this section, we’ll consider some of these complexities in measurement. First, we’ll take a look at the various levels of measurement that exist, and then we’ll consider how measures can be subject to bias and error.
Levels of measurement
When social scientists measure concepts, they sometimes use the language of variables and attributes. A variable refers to a grouping of several characteristics. Attributes are the characteristics that make up a variable. For example, the variable hair color would contain attributes like blonde, brown, black, red, gray, etc. A variable’s attributes determine its level of measurement. There are four possible levels of measurement: nominal, ordinal, interval, and ratio. The first two levels of measurement are categorical, meaning their attributes are categories rather than numbers. The latter two levels of measurement are continuous, meaning their attributes are numbers, not categories.
Hair color is an example of a nominal level of measurement. Nominal measures are categorical, and those categories cannot be mathematically ranked. As a brown-haired person (with some gray), I can’t say for sure that brown-haired people are better than blonde-haired people. There is no ranking order between hair colors. They are simply different. That is what constitutes a nominal level of measurement. Gender and race are also measured at the nominal level.
But what attributes are contained in the variable hair color? Blonde, brown, black, and red are common colors. However, if we listed only these attributes, my wife, who currently has purple hair, wouldn’t fit anywhere. That means our attributes were not exhaustive. Exhaustiveness means that all possible attributes are listed. We may have to list a lot of colors before we can meet the criteria of exhaustiveness. Clearly, there is a point at which exhaustiveness has been reasonably met. If a person insists that their hair color is light burnt sienna, it is not your responsibility to list that as an option. Rather, that person would reasonably be described as brown-haired. Perhaps listing a category for other color would suffice to make our list of colors exhaustive.
What about a person who has multiple hair colors at the same time, such as red and black? They would fall into multiple attributes. This violates the rule of mutual exclusivity, in which a person cannot fall into two different attributes. Instead of listing all of the possible combinations of colors, perhaps you might include a multi-color attribute to describe people with more than one hair color.
The discussion of hair color elides an important point with measurement—reification. You should remember reification from our previous discussion in this chapter. For many years, the attributes for gender were male and female. Now, our understanding of gender has evolved to encompass more attributes including transgender, non-binary, or genderqueer. Children of parents from different races were often classified as one race or another, even if they identified with both cultures equally. The option for bi-racial or multi-racial on a survey not only more accurately reflects the racial diversity in the real world but validates and acknowledges people who identify in that manner.
Unlike nominal-level measures, attributes at the ordinal level can be rank ordered. For example, someone’s degree of satisfaction in their romantic relationship can be ordered by rank. That is, you could say you are not at all satisfied, a little satisfied, moderately satisfied, or highly satisfied. Note that even though these have a rank order to them (not at all satisfied is certainly worse than highly satisfied), we cannot calculate a mathematical distance between those attributes. We can simply say that one attribute of an ordinal-level variable is more or less than another attribute.
This can get a little confusing when using Likertscales. If you have ever taken a customer satisfaction survey or completed a course evaluation for school, you are familiar with Likert scales. “On a scale of 1-5, with one being the lowest and 5 being the highest, how likely are you to recommend our company to other people?” Sound familiar? Likert scales use numbers but only as a shorthand to indicate what attribute (highly likely, somewhat likely, etc.) the person feels describes them best. You wouldn’t say you are “2” more likely to recommend the company. But you could say you are not very likely to recommend the company. Ordinal-level attributes must also be exhaustive and mutually exclusive, as with nominal-level variables.
At the interval level, attributes must also be exhaustive and mutually exclusive. As well, the distance between attributes is known to be equal. Interval measures are also continuous, meaning their attributes are numbers, rather than categories. IQ scores are interval level, as are temperatures. Interval-level variables are not particularly common in social science research, but their defining characteristic is that we can say how much more or less one attribute differs from another. We cannot, however, say with certainty what the ratio of one attribute is in comparison to another. For example, it would not make sense to say that 50 degrees is half as hot as 100 degrees.
Finally, at the ratio level, attributes are mutually exclusive and exhaustive, attributes can be rank ordered, the distance between attributes is equal, and attributes have a true zero point. Thus, with these variables, we can say what the ratio of one attribute is in comparison to another. Examples of ratio-level variables include age and years of education. We know, for example, that a person who is 12 years old is twice as old as someone who is 6 years old. The differences between each level of measurement are visualized in Table 9.1.
Table 9.1 Criteria for Different Levels of Measurement
Nominal Ordinal Interval Ratio
Exhaustive X X X X
Mutually exclusive X X X X
Rank-ordered X X X
Equal distance between attributes X X
True zero point X
Challenges in measurement
Unfortunately, measures never perfectly describe what exists in the real world. Good measures demonstrate validity and reliability but will always have some degree of error. Systematic error causes our measures to consistently output incorrect data, usually due to an identifiable process. Imagine you created a measure of height, but you didn’t put an option for anyone over six feet tall. If you gave that measure to your local college or university, some of the taller members of the basketball team might not be measured accurately. In fact, you would be under the mistaken impression that the tallest person at your school was six feet tall, when in actuality there are likely people taller than six feet at your school. This error seems innocent, but if you were using that measure to help you build a new building, those people might hit their heads!
A less innocent form of error arises when researchers using question wording that might cause participants to think one answer choice is preferable to another. For example, if I were to ask you “Do you think global warming is caused by human activity?” you would probably feel comfortable answering honestly. But what if I asked you “Do you agree with 99% of scientists that global warming is caused by human activity?” Would you feel comfortable saying no, if that’s what you honestly felt? I doubt it. That is an example of a leading question, a question with wording that influences how a participant responds. We’ll discuss leading questions and other problems in question wording in greater detail in Chapter 11.
In addition to error created by the researcher, your participants can cause error in measurement. Some people will respond without fully understanding a question, particularly if the question is worded in a confusing way. That’s one source of error. Let’s consider another. If we asked people if they always washed their hands after using the bathroom, would we expect people to be perfectly honest? Polling people about whether they wash their hands after using the bathroom might only elicit what people would like others to think they do, rather than what they actually do. This is an example of social desirability bias, in which participants in a research study want to present themselves in a positive, socially desirable way to the researcher. People in your study will want to seem tolerant, open-minded, and intelligent, but their true feelings may be closed-minded, simple, and biased. So, they lie. This occurs often in political polling, which may show greater support for a candidate from a minority race, gender, or political party than actually exists in the electorate.
A related form of bias is called acquiescence bias, also known as “yea-saying.” It occurs when people say yes to whatever the researcher asks, even when doing so contradicts previous answers. For example, a person might say yes to both “I am a confident leader in group discussions” and “I feel anxious interacting in group discussions.” Those two responses are unlikely to both be true for the same person. Why would someone do this? Similar to social desirability, people want to be agreeable and nice to the researcher asking them questions or they might ignore contradictory feelings when responding to each question. Respondents may also act on cultural reasons, trying to “save face” for themselves or the person asking the questions. Regardless of the reason, the results of your measure don’t match what the person truly feels.
So far, we have discussed sources of error that come from choices made by respondents or researchers. Usually, systematic errors will result in responses that are incorrect in one direction or another. For example, social desirability bias usually means more people will say they will vote for a third party in an election than actually do. Systematic errors such as these can be reduced, but there is another source of error in measurement that can never be eliminated, and that is random error. Unlike systematic error, which biases responses consistently in one direction or another, random error is unpredictable and does not consistently result in scores that are consistently higher or lower on a given measure. Instead, random error is more like statistical noise, which will likely average out across participants.
Random error is present in any measurement. If you’ve ever stepped on a bathroom scale twice and gotten two slightly different results, maybe a difference of a tenth of a pound, then you’ve experienced random error. Maybe you were standing slightly differently or had a fraction of your foot off of the scale the first time. If you were to take enough measures of your weight on the same scale, you’d be able to figure out your true weight. In social science, if you gave someone a scale measuring depression on a day after they lost their job, they would likely score differently than if they had just gotten a promotion and a raise. Even if the person were clinically depressed, our measure is subject to influence by the random occurrences of life. Thus, social scientists speak with humility about our measures. We are reasonably confident that what we found is true, but we must always acknowledge that our measures are only an approximation of reality.
Humility is important in scientific measurement, as errors can have real consequences. At the time of the writing of this textbook, my wife and I are expecting our first child. Like most people, we used a pregnancy test from the pharmacy. If the test said my wife was pregnant when she was not pregnant, that would be a false positive. On the other hand, if the test indicated that she was not pregnant when she was in fact pregnant, that would be a false negative. Even if the test is 99% accurate, that means that one in a hundred women will get an erroneous result when they use a home pregnancy test. For us, a false positive would have been initially exciting, then devastating when we found out we were not having a child. A false negative would have been disappointing at first and then quite shocking when we found out we were indeed having a child. While both false positives and false negatives are not very likely for home pregnancy tests (when taken correctly), measurement error can have consequences for the people being measured.
Key Takeaways
• In social science, our variables can be one of four different levels of measurement: nominal, ordinal, interval, or ratio.
• Systematic error may arise from the researcher, participant, or measurement instrument.
• Systematic error biases results in a particular direction, whereas random error can be in any direction.
• All measures are prone to error and should interpreted with humility.
Glossary
• Acquiescence bias- when respondents say yes to whatever the researcher asks
• Attributes- are the characteristics that make up a variable
• Categorical measures- a measure with attributes that are categories
• Continuous measures- a measures with attributes that are numbers
• Exhaustiveness- all possible attributes are listed
• False negative- when a measure does not indicate the presence of a phenomenon, when in reality it is present
• False positive- when a measure indicates the presence of a phenomenon, when in reality it is not present
• Interval level- a level of measurement that is continuous, can be rank ordered, is exhaustive and mutually exclusive, and for which the distance between attributes is known to be equal
• Leading question- a question with wording that influences how a participant responds
• Likert scales- ordinal measures that use numbers as a shorthand (e.g., 1=highly likely, 2=somewhat likely, etc.) to indicate what attribute the person feels describes them best
• Mutual exclusivity- a person cannot identify with two different attributes simultaneously
• Nominal- level of measurement that is categorical and those categories cannot be mathematically ranked, though they are exhaustive and mutually exclusive
• Ordinal- level of measurement that is categorical, those categories can be rank ordered, and they are exhaustive and mutually exclusive
• Random error- unpredictable error that does not consistently result in scores that are consistently higher or lower on a given measure
• Ratio level- level of measurement in which attributes are mutually exclusive and exhaustive, attributes can be rank ordered, the distance between attributes is equal, and attributes have a true zero point
• Social desirability bias- when respondents answer based on what they think other people would like, rather than what is true
• Systematic error- measures consistently output incorrect data, usually in one direction and due to an identifiable process
• Variable- refers to a grouping of several characteristics
Image attributions
user satisfaction by mcmurryjulie CC-0
question by jambulboy CC-0
mistake by stevepb CC-0 | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/09%3A_Defining_and_measuring_concepts/9.05%3A_Complexities_in_quantitative_measurement.txt |
Sampling involves selecting a subset of a population and drawing conclusions from that subset. How you sample and who you sample shapes what conclusions you are able to draw. Ultimately, this chapter focuses on questions about the who or the what that you want to be able to make claims about in your research. In the following sections, we’ll define sampling, discuss different types of sampling strategies, and consider how to judge the quality of samples as consumers and creators of social scientific research.
This chapter discusses or mentions the following topics: cancer, substance abuse, homelessness, anti-LGBTQ discrimination, mental health, sexually transmitted infections, and intimate partner violence.
10: Sampling
Learning Objectives
• Differentiate between populations, sampling frames, and samples
• Describe inclusion and exclusion criteria
• Explain recruitment of participants in a research project
In social scientific research, a population is the cluster of people you are most interested in; it is often the “who” that you want to be able to say something about at the end of your study. Populations in research may be rather large, such as “the American people,” but they are more typically a little less vague than that. For example, a large study for which the population of interest really is the American people will likely specify which American people, such as adults over the age of 18 or citizens or legal permanent residents.
As I’ve now said a couple of times, it is quite rare for a researcher to gather data from their entire population of interest. This might sound surprising or disappointing until you think about the kinds of research questions that social workers typically ask. For example, let’s say we wish to answer the following research question: “How does gender impact success in a batterer intervention program?” Would you expect to be able to collect data from all people in batterer intervention programs across all nations from all historical time periods? Unless you plan to make answering this research question your entire life’s work (and then some), I’m guessing your answer is a resounding no. So, what to do? Does not having the time or resources to gather data from every single person of interest mean having to give up your research interest?
Absolutely not. Instead, researchers use what’s called a sampling frame as an intermediate point between the overall population and the sample that is drawn. A sampling frame is a—real or hypothetical—list of people from which you will draw your sample. But where do you find a sampling frame? Answering this question is the first step in conducting human subjects research. Social work researchers must think about locations or groups in which your target population gathers or interacts. For example, a study on quality of care in nursing homes may choose a local nursing home because it’s easy to access. The sampling frame could be all of the patients at the nursing home. You would select your participants for your study from the list of patients at the nursing home. Note that this is a real list. That is, an administrator at the nursing home would give you a list with every resident’s name on it from which you would select your participants. If you decided to include more nursing homes in your study, then your sampling frame could be all of the patients at all of the nursing homes you included.
The nursing home example is perhaps an easy one. Let’s consider some more examples. Unlike nursing home patients, cancer survivors do not live in an enclosed location and may no longer receive treatment at a hospital or clinic. For social work researchers to reach participants, they may consider partnering with a support group that services this population. Perhaps there is a support group at a local church in which survivors may cycle in and out based on need. Without a set list of people, your sampling frame would simply be the people who showed up to the support group on the nights you were there, which is an imaginary list.
More challenging still is recruiting people who are homeless, those with very low income, or people who belong to stigmatized groups. For example, a research study by Johnson and Johnson (2014) [1] attempted to learn usage patterns of “bath salts,” or synthetic stimulants that are marketed as “legal highs.” Users of “bath salts” don’t often gather for meetings, and reaching out to individual treatment centers is unlikely to produce enough participants for a study as use of bath salts is rare. To reach participants, these researchers ingeniously used online discussion boards in which users of these drugs share information. Their sampling frame included everyone who participated in the online discussion boards during the time they collected data. Regardless of whether a sampling frame is easy or challenging, the first rule of sampling is: go where your participants are.
Once you have an idea of where your participants are, you need to recruit your participants into your study. Recruitment refers to the process by which the researcher informs potential participants about the study and attempts to get them to participate. Recruitment comes in many different forms. If you have ever received a phone call asking for you to participate in a survey, someone has attempted to recruit you for their study. Perhaps you’ve seen print advertisements on buses, in student centers, or in a periodical. I’ve received many emails that were passed around my school asking for participants, usually for a graduate student. (As an aside, researchers sometimes speak of “research karma.” If you participate in others’ research studies, they will participate in yours.) As we learn more about specific types of sampling, make sure your recruitment strategy makes sense with your sampling approach. For example, if you put up a flyer in the student health office to recruit for your study, you would likely be using availability or convenience sampling.
As you think about sampling frame and recruitment, another level of specificity that researchers add at this stage is deciding if there are certain characteristics or attributes that individuals must have if they participate in your study. These are known as inclusion and exclusion criteria. Inclusion criteria are the characteristics a person must possess in order to be included in your sample. If you were conducting a survey on LGBTQ discrimination at your agency, you might want to sample only clients who identify as LGBTQ. In that case, your inclusion criteria for your sample would be that individuals have to identify as LGBTQ. Comparably, exclusion criteria are characteristics that disqualify a person from being included in your sample. In the previous example, you could think of heterosexuality as one of your exclusion criteria because no person who identifies as heterosexual would be included in your sample. Exclusion criteria are often like the mirror image of inclusion criteria. However, there may be other criteria by which we want to exclude people from our sample. For example, we may exclude clients who were recently discharged or those who have just begun to receive services.
Once you find a sampling frame from which you can recruit your participants, you end up with a sample. A sample is the group of people you successfully recruit from your sampling frame to participate in your study. If you are a participant in a research project—answering survey questions, participating in interviews, etc.—you are part of the sample of that research project. Some research projects social workers may engage in don’t use people at all. Instead of people, the elements selected for inclusion into a sample are documents, including client records, blog entries, or television shows. A researcher conducting this kind of analysis, described in detail in Chapter 14, still goes through the stages of sampling—identifying a sampling frame, applying inclusion criteria, and gathering the sample.
Applying sampling terms
Sampling terms can be a bit daunting at first. However, with some practice, they will become second nature. Let’s walk through an example from a research project of mine. I am currently collecting data for a research project on how much it costs to become a licensed clinical social worker or LCSW. An LCSW is necessary for private clinical practice and is used by supervisors in human service organizations to sign off on clinical charts from less credentialed employees, as well as provide clinical supervision. If you are interested in providing clinical services as a social worker, you should become familiar with the licensing laws in your state.
Figure 10.1 Sampling terms by size
Using Figure 10.1 as a guide, my population is clearly clinical social workers, as these are the people about whom I want to draw conclusions. The next step inward would be a sampling frame. Unfortunately, there is no list of every licensed clinical social worker in the United States. I could write to each state’s social work licensing board and ask for a list of names and addresses, perhaps even using a Freedom of Information Act request if they were unwilling to share the information. That option sounds time-consuming and has a low likelihood of success. Instead, I tried to figure out where social workers are likely to congregate. I considered setting up a booth at a National Association of Social Workers (NASW) conference and asking people to participate in my survey. Ultimately, this would prove too costly, and I wouldn’t be able to draw a truly random sample. I finally discovered the NASW membership email list, which is available to advertisers, including researchers advertising for research projects. While the NASW list does not contain every social worker, it reaches over one hundred thousand social workers via email regularly through its monthly newsletter.
My sampling frame became the members of the NASW membership list. I decided to recruit 5000 participants because I knew that email advertisements don’t have the best return rates. I sent a recruitment email to the 5000 participants and specified that I only wanted to hear from social workers who were either currently or recently received clinical supervision for licensure—my inclusion criteria. This was important because many of the people on the NASW membership list may not be licensed. While I would love it if my sample were all 5000 participants I attempted to recruit, my actual sample contained only 150 people. These are the people I successfully recruited using my email advertisement—the people who filled out my survey on licensure.
From this example, you can see that sampling is a process. The process flows sequentially from figuring out your target population to thinking about where to find people from your target population to finding a real or imaginary list of people in your population to recruiting people from that list to be a part of your sample. Through the sampling process, you must consider where people in your target population are likely to be and how best to get their attention for your study. Sampling can be an easy process, like calling every 100th name from the phone book one afternoon, or challenging, like standing every day for a few weeks in an area in which people who are homeless gather for shelter. In either case, your goal is to recruit enough people who will participate in your study so you can learn about your population.
In the next two sections of this chapter, we will discuss sampling approaches, also known as sampling techniques or types of samples. Sampling approach determines how a researcher selects people from the sampling frame to recruit into her sample. Because the goals of qualitative and quantitative research differ, so too does the sampling approach. Quantitative approaches allow researchers to make claims about populations that are much larger than their actual sample with a fair amount of confidence. Qualitative approaches are designed to allow researchers to make conclusions that are specific to one time, place, context, and group of people. We will review both of these approaches to sampling in the coming sections of this chapter. First, we examine sampling types and techniques used in qualitative research. After that, we’ll look at how sampling typically works in quantitative research.
Key Takeaways
• A population is the group who is the main focus of a researcher’s interest; a sample is the group from whom the researcher actually collects data.
• Sampling involves selecting the observations that you will analyze.
• To conduct sampling, a researcher starts by going where your participants are.
• Sampling frames can be real or imaginary.
• Recruitment involves informing potential participants about your study and seeking their participation.
Glossary
• Exclusion criteria- characteristics that disqualify a person from being included in a sample
• Inclusion criteria- the characteristics a person must possess in order to be included in a sample
• Population- the cluster of people about whom a researcher is most interested
• Recruitment- the process by which the researcher informs potential participants about the study and attempts to get them to participate
• Sample- the group of people you successfully recruit from your sampling frame to participate in your study
• Sampling frame- a real or hypothetical list of people from which a researcher will draw her sample
Image attributions
crowd by mwewering CC-0
job interview by styles66 CC-0
1. Johnson, P. S., & Johnson, M. W. (2014). Investigation of “bath salts” use patterns within an online sample of users in the United States. Journal of psychoactive drugs, 46(5), 369-378. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/10%3A_Sampling/10.01%3A_Basic_concepts_of_sampling.txt |
Learning Objectives
• Define nonprobability sampling, and describe instances in which a researcher might choose a nonprobability sampling technique
• Describe the different types of nonprobability samples
Qualitative researchers typically make sampling choices that enable them to achieve a deep understanding of whatever phenomenon it is that they are studying. In this section, we’ll examine the techniques that qualitative researchers typically employ when sampling as well as the various types of samples that qualitative researchers are most likely to use in their work.
Nonprobability sampling
Nonprobability sampling refers to sampling techniques for which a person’s likelihood of being selected for membership in the sample is unknown. Because we don’t know the likelihood of selection, we don’t know with nonprobability samples whether a sample is truly representative of a larger population. But that’s okay. Generalizing to a larger population is not the goal with nonprobability samples or qualitative research. That said, the fact that nonprobability samples do not represent a larger population does not mean that they are drawn arbitrarily or without any specific purpose in mind (that would mean committing one of the errors of informal inquiry discussed in Chapter 1). We’ll take a closer look at the process of selecting research elements when drawing a nonprobability sample. But first, let’s consider why a researcher might choose to use a nonprobability sample.
When are nonprobability samples ideal? One instance might be when we’re starting a big research project. For example, if we’re conducting survey research, we may want to administer a draft of our survey to a few people who seem to resemble the folks we’re interested in studying in order to help work out kinks in the survey. We might also use a nonprobability sample if we’re conducting a pilot study or some exploratory research. This can be a quick way to gather some initial data and help us get some idea of the lay of the land before conducting a more extensive study. From these examples, we can see that nonprobability samples can be useful for setting up, framing, or beginning research, even quantitative research. But it isn’t just early stage research that relies on and benefits from nonprobability sampling techniques. Researchers also use nonprobability samples in full-blown research projects. These projects are usually qualitative in nature, where the researcher’s goal is in-depth, idiographic understanding rather than more general, nomothetic understanding.
Types of nonprobability samples
There are several types of nonprobability samples that researchers use. These include purposive samples, snowball samples, quota samples, and convenience samples. While the latter two strategies may be used by quantitative researchers from time to time, they are more typically employed in qualitative research, and because they are both nonprobability methods, we include them in this section of the chapter.
To draw a purposive sample, a researcher selects participants from their sampling frame because they have characteristics that the researcher desires. A researcher begins with specific characteristics in mind that she wishes to examine and then seeks out research participants who cover that full range of characteristics. For example, if you are studying mental health supports on your campus, you may want to be sure to include not only students, but mental health practitioners and student affairs administrators. You might also select students who currently use mental health supports, those who dropped out of supports, and those who are waiting to receive supports. The purposive part of purposive sampling comes from selecting specific participants on purpose because you already know they have characteristics—being an administrator, dropping out of mental health supports—that you need in your sample.
Note that these are different than inclusion criteria, which are more general requirements a person must possess to be a part of your sample. For example, one of the inclusion criteria for a study of your campus’ mental health supports might be that participants had to have visited the mental health center in the past year. That is different than purposive sampling. In purposive sampling, you know characteristics of individuals and recruit them because of those characteristics. For example, I might recruit Jane because she stopped seeking supports this month, JD because she has worked at the center for many years, and so forth.
Also, it’s important to recognize that purposive sampling requires you to have prior information about your participants before recruiting them because you need to know their perspectives or experiences before you know whether you want them in your sample. This is a common mistake that many students make. What I often hear is, “I’m using purposive sampling because I’m recruiting people from the health center,” or something like that. That’s not purposive sampling. Purposive sampling is recruiting specific people because of the various characteristics and perspectives they bring to your sample. Imagine we were creating a focus group. A purposive sample might gather clinicians, patients, administrators, staff, and former patients together so they can talk as a group. Purposive sampling would seek out people that have each of those attributes.
Quota sampling is another nonprobability sampling strategy that takes purposive sampling one step further. When conducting quota sampling, a researcher identifies categories that are important to the study and for which there is likely to be some variation. Subgroups are created based on each category, and the researcher decides how many people to include from each subgroup and collects data from that number for each subgroup. Let’s consider a study of student satisfaction with on-campus housing. Perhaps there are two types of housing on your campus: apartments that include full kitchens and dorm rooms where residents do not cook for themselves and instead eat in a dorm cafeteria. As a researcher, you might wish to understand how satisfaction varies across these two types of housing arrangements. Perhaps you have the time and resources to interview 20 campus residents, so you decide to interview 10 from each housing type. It is possible as well that your review of literature on the topic suggests that campus housing experiences vary by gender. If that is that case, perhaps you’ll decide on four important subgroups: men who live in apartments, women who live in apartments, men who live in dorm rooms, and women who live in dorm rooms. Your quota sample would include five people from each of the four subgroups.
In 1936, up-and-coming pollster George Gallup made history when he successfully predicted the outcome of the presidential election using quota sampling methods. The leading polling entity at the time, The Literary Digest, predicted that Alfred Landon would beat Franklin Roosevelt in the presidential election by a landslide, but Gallup’s polling disagreed. Gallup successfully predicted Roosevelt’s win and subsequent elections based on quota samples, but in 1948, Gallup incorrectly predicted that Dewey would beat Truman in the US presidential election. [1] Among other problems, the fact that Gallup’s quota categories did not represent those who actually voted (Neuman, 2007) [2] underscores the point that one should avoid attempting to make statistical generalizations from data collected using quota sampling methods. [3] While quota sampling offers the strength of helping the researcher account for potentially relevant variation across study elements, it would be a mistake to think of this strategy as yielding statistically representative findings. For that, you need probability sampling, which we will discuss in the next section.
Qualitative researchers can also use snowball sampling techniques to identify study participants. In snowball sampling, a researcher identifies one or two people she’d like to include in her study but then relies on those initial participants to help identify additional study participants. Thus, the researcher’s sample builds and becomes larger as the study continues, much as a snowball builds and becomes larger as it rolls through the snow. Snowball sampling is an especially useful strategy when a researcher wishes to study a stigmatized group or behavior. For example, a researcher who wanted to study how people with genital herpes cope with their medical condition would be unlikely to find many participants by posting a call for interviewees in the newspaper or making an announcement about the study at some large social gathering. Instead, the researcher might know someone with the condition, interview that person, and ask the person to refer others they may know with the genital herpes to contact you to participate in the study. Having a previous participant vouch for the researcher may help new potential participants feel more comfortable about being included in the study.
Snowball sampling is sometimes referred to as chain referral sampling. One research participant refers another, and that person refers another, and that person refers another—thus a chain of potential participants is identified. In addition to using this sampling strategy for potentially stigmatized populations, it is also a useful strategy to use when the researcher’s group of interest is likely to be difficult to find, not only because of some stigma associated with the group, but also because the group may be relatively rare. This was the case for Steven Kogan and colleagues (Kogan, Wejnert, Chen, Brody, & Slater, 2011) [4] who wished to study the sexual behaviors of non-college-bound African American young adults who lived in high-poverty rural areas. The researchers first relied on their own networks to identify study participants, but because members of the study’s target population were not easy to find, access to the networks of initial study participants was very important for identifying additional participants. Initial participants were given coupons to pass on to others they knew who qualified for the study. Participants were given an added incentive for referring eligible study participants; they received \$50 for participating in the study and an additional \$20 for each person they recruited who also participated in the study. Using this strategy, Kogan and colleagues succeeded in recruiting 292 study participants.
Finally, convenience sampling is another nonprobability sampling strategy that is employed by both qualitative and quantitative researchers. To draw a convenience sample, a researcher simply collects data from those people or other relevant elements to which she has most convenient access. This method, also sometimes referred to as availability sampling, is most useful in exploratory research or in student projects in which probability sampling is too costly or difficult. If you’ve ever been interviewed by a fellow student for a class project, you have likely been a part of a convenience sample. While convenience samples offer one major benefit—convenience—they do not offer the rigor needed to make conclusions about larger populations. That is the subject of our next section on probability sampling.
Table 10.1 Types of nonprobability samples
Sample type Description
Purposive Researcher seeks out participants with specific characteristics.
Snowball Researcher relies on participant referrals to recruit new participants.
Quota Researcher selects cases from within several different subgroups.
Convenience Researcher gathers data from whatever cases happen to be convenient.
Key Takeaways
• Nonprobability samples might be used when researchers are conducting qualitative (or idiographic) research, exploratory research, student projects, or pilot studies.
• There are several types of nonprobability samples including purposive samples, snowball samples, quota samples, and convenience samples.
Glossary
• Convenience sample- researcher gathers data from whatever cases happen to be convenient
• Nonprobability sampling- sampling techniques for which a person’s likelihood of being selected for membership in the sample is unknown
• Purposive sample- when a researcher seeks out participants with specific characteristics
• Quota sample- when a researcher selects cases from within several different subgroups
• Snowball sample- when a researcher relies on participant referrals to recruit new participants
Image attributions
business by helpsg CC-0
network by geralt CC-0
1. For more information about the 1948 election and other historically significant dates related to measurement, see the PBS timeline of “The first measured century” at [1]http://www.pbs.org/fmc/timeline/e1948election.htm. ↵
2. Neuman, W. L. (2007). Basics of social research: Qualitative and quantitative approaches (2nd ed.). Boston, MA: Pearson. ↵
3. If you are interested in the history of polling, I recommend reading Fried, A. (2011). Pathways to polling: Crisis, cooperation, and the making of public opinion professions. New York, NY: Routledge. ↵
4. Kogan, S. M., Wejnert, C., Chen, Y., Brody, G. H., & Slater, L. M. (2011). Respondent-driven sampling with hard-to-reach emerging adults: An introduction and case study with rural African Americans. Journal of Adolescent Research, 26, 30–60. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/10%3A_Sampling/10.02%3A_Sampling_in_qualitative_research.txt |
Learning Objectives
• Describe how probability sampling differs from nonprobability sampling
• Define generalizability, and describe how it is achieved in probability samples
• Identify the various types of probability samples, and describe why a researcher may use one type over another
Quantitative researchers are often interested in making generalizations about groups larger than their study samples; they seek nomothetic causal explanations. While there are certainly instances when quantitative researchers rely on nonprobability samples (e.g., when doing exploratory research), quantitative researchers tend to rely on probability sampling techniques. The goals and techniques associated with probability samples differ from those of nonprobability samples. We’ll explore those unique goals and techniques in this section.
Probability sampling
Unlike nonprobability sampling, probability sampling refers to sampling techniques for which a person’s likelihood of being selected from the sampling frame is known. You might ask yourself why we should care about a potential participant’s likelihood of being selected for the researcher’s sample. The reason is that, in most cases, researchers who use probability sampling techniques are aiming to identify a representative sample from which to collect data. A representative sample is one that resembles the population from which it was drawn in all the ways that are important for the research being conducted. If, for example, you wish to be able to say something about differences between men and women at the end of your study, you better make sure that your sample doesn’t contain only women. That’s a bit of an oversimplification, but the point with representativeness is that if your population varies in some way that is important to your study, your sample should contain the same sorts of variation.
Obtaining a representative sample is important in probability sampling because of generalizability. In fact, generalizability is perhaps the key feature that distinguishes probability samples from nonprobability samples. Generalizability refers to the idea that a study’s results will tell us something about a group larger than the sample from which the findings were generated. In order to achieve generalizability, a core principle of probability sampling is that all elements in the researcher’s sampling frame have an equal chance of being selected for inclusion in the study. In research, this is the principle of random selection. Researchers use a computer’s random number generator to determine who from the sampling frame gets recruited into the sample.
Using random selection does not mean that your sample will be perfect. No sample is perfect. The only way to come with a perfect result would be to include everyone in the population in your sample, which defeats the whole point of sampling. Generalizing from a sample to a population always contains some degree of error. This is referred to as sampling error, a statistical calculation of the difference between results from a sample and the actual parameters of a population.
Generalizability is a pretty easy concept to grasp. Imagine a professor were to take a sample of individuals in your class to see if the material is too hard or too easy. The professor, however, only sampled individuals whose grades were over 90% in the class. Would that be a representative sample of all students in the class? That would be a case of sampling error—a mismatch between the results of the sample and the true feelings of the overall class. In other words, the results of the professor’s study don’t generalize to the overall population of the class.
Taking this one step further, imagine your professor is conducting a study on binge drinking among college students. The professor uses undergraduates at your school as her sampling frame. Even if that professor were to use probability sampling, perhaps your school differs from other schools in important ways. There are schools that are “party schools” where binge drinking may be more socially accepted, “commuter schools” at which there is little nightlife, and so on. If your professor plans to generalize her results to all college students, she will have to make an argument that her sampling frame (undergraduates at your school) is representative of the population (all undergraduate college students).
Types of probability samples
There are a variety of probability samples that researchers may use. These include simple random samples, systematic samples, stratified samples, and cluster samples. Let’s build on the previous example. Imagine we were concerned with binge drinking and chose the target population of fraternity members. How might you go about getting a probability sample of fraternity members that is representative of the overall population?
Simple random samples are the most basic type of probability sample. A simple random sample requires a real sampling frame—an actual list of each person in the sampling frame. Your school likely has a list of all of the fraternity members on campus, as Greek life is subject to university oversight. You could use this as your sampling frame. Using the university’s list, you would number each fraternity member, or element, sequentially and then randomly select the elements from which you will collect data.
True randomness is difficult to achieve, and it takes complex computational calculations to do so. Although you think you can select things at random, human-generated randomness is actually quite predictable, as it falls into patterns called heuristics. To truly randomly select elements, researchers must rely on computer-generated help. Many free websites have good pseudo-random number generators. A good example is the website Random.org, which contains a random number generator that can also randomize lists of participants. Sometimes, researchers use a table of numbers that have been generated randomly. There are several possible sources for obtaining a random number table. Some statistics and research methods textbooks offer such tables as appendices to the text.
As you might have guessed, drawing a simple random sample can be quite tedious. Systematic sampling techniques are somewhat less tedious but offer the benefits of a random sample. As with simple random samples, you must possess a list of everyone in your sampling frame. Once you’ve done that, to draw a systematic sample you’d simply select every kth element on your list. But what is k, and where on the list of population elements does one begin the selection process? k is your selection interval or the distance between the elements you select for inclusion in your study. To begin the selection process, you’ll need to figure out how many elements you wish to include in your sample. Let’s say you want to interview 25 fraternity members on your campus, and there are 100 men on campus who are members of fraternities. In this case, your selection interval, or k, is 4. To arrive at 4, simply divide the total number of population elements by your desired sample size. This process is represented in Figure 10.2.
Figure 10.2 Formula for determining selection interval for systematic sample
To determine where on your list of population elements to begin selecting the names of the 25 men you will interview, select a number between 1 and k, and begin there. If we select 3 as our starting point, we’d begin by selecting the third fraternity member on the list and then select every fourth member from there. This might be easier to understand if you can see it visually. Table 10.2 lists the names of our hypothetical 100 fraternity members on campus. You’ll see that the third name on the list has been selected for inclusion in our hypothetical study, as has every fourth name after that. A total of 25 names have been selected.
Table 10.2 Systematic sample of 25 fraternity members
Number Name Include in study? Number Name Include in study?
1 Jacob 51 Blake Yes
2 Ethan 52 Oliver
3 Michael Yes 53 Cole
4 Jayden 54 Carlos
5 William 55 Jaden Yes
6 Alexander 56 Jesus
7 Noah Yes 57 Alex
8 Daniel 58 Aiden
9 Aiden 59 Eric Yes
10 Anthony 60 Hayden
11 Joshua Yes 61 Brian
12 Mason 62 Max
13 Christopher 63 Jaxon Yes
14 Andrew 64 Brian
15 David Yes 65 Mathew
16 Logan 66 Elijah
17 James 67 Joseph Yes
18 Gabriel 68 Benjamin
19 Ryan Yes 69 Samuel
20 Jackson 70 John
21 Nathan 71 Jonathan Yes
22 Christian 72 Liam
23 Dylan Yes 73 Landon
24 Caleb 74 Tyler
25 Lucas 75 Evan Yes
26 Gavin 76 Nicholas
27 Isaac Yes 77 Braden
28 Luke 78 Angel
29 Brandon 79 Jack
30 Isaiah 80 Jordan
31 Owen Yes 81 Carter
32 Conner 82 Justin
33 Jose 83 Jeremiah Yes
34 Julian 84 Robert
35 Aaron Yes 85 Adrian
36 Wyatt 86 Kevin
37 Hunter 87 Cameron Yes
38 Zachary 88 Thomas
39 Charles Yes 89 Austin
40 Eli 90 Chase
41 Henry 91 Sebastian Yes
42 Jason 92 Levi
43 Xavier Yes 93 Ian
44 Colton 94 Dominic
45 Juan 95 Cooper Yes
46 Josiah 96 Luis
47 Ayden Yes 97 Carson
48 Adam 98 Nathaniel
49 Brody 99 Tristan Yes
50 Diego 100 Parker
In case you’re wondering how I came up with 100 unique names for this table, I’ll let you in on a little secret: lists of popular baby names can be great resources for researchers. I used the list of top 100 names for boys based on Social Security Administration statistics for this table. I often use baby name lists to come up with pseudonyms for field research subjects and interview participants. See Family Education. (n.d.). Name lab. Retrieved from baby-names.familyeducation.com/popular-names/boys.
There is one clear instance in which systematic sampling should not be employed. If your sampling frame has any pattern to it, you could inadvertently introduce bias into your sample by using a systemic sampling strategy. (Bias will be discussed in more depth in the next section.) This is sometimes referred to as the problem of periodicity. Periodicity refers to the tendency for a pattern to occur at regular intervals. Let’s say, for example, that you wanted to observe binge drinking on campus each day of the week. Perhaps you need to have your observations completed within 28 days and you wish to conduct four observations on randomly chosen days. Table 10.3 shows a list of the population elements for this example. To determine which days we’ll conduct our observations, we’ll need to determine our selection interval. As you’ll recall from the preceding paragraphs, to do so we must divide our population size, in this case 28 days, by our desired sample size, in this case 4 days. This formula leads us to a selection interval of 7. If we randomly select 2 as our starting point and select every seventh day after that, we’ll wind up with a total of 4 days on which to conduct our observations. You’ll see how that works out in the following table.
Table 10.3 Systematic sample of observation days
Day # Day Drinking Observe? Day # Day Drinking Observe?
1 Monday Low 15 Monday Low
2 Tuesday Low Yes 16 Tuesday Low Yes
3 Wednesday Low 17 Wednesday Low
4 Thursday High 18 Thursday High
5 Friday High 19 Friday High
6 Saturday High 20 Saturday High
7 Sunday Low 21 Sunday Low
8 Monday Low 22 Monday Low
9 Tuesday Low Yes 23 Tuesday Low Yes
10 Wednesday Low 24 Wednesday Low
11 Thursday High 25 Thursday High
12 Friday High 26 Friday High
13 Saturday High 27 Saturday High
14 Sunday Low 28 Sunday Low
Do you notice any problems with our selection of observation days in Table 1? Apparently, we’ll only be observing on Tuesdays. Moreover, Tuesdays may not be an ideal day to observe binge drinking behavior. Unless alcohol consumption patterns have changed significantly since I was in my undergraduate program, I would assume binge drinking is more likely to happen over the weekend.
In cases such as this, where the sampling frame is cyclical, it would be better to use a stratified sampling technique. In stratified sampling, a researcher will divide the study population into relevant subgroups and then draw a sample from each subgroup. In this example, we might wish to first divide our sampling frame into two lists: weekend days and weekdays. Once we have our two lists, we can then apply either simple random or systematic sampling techniques to each subgroup.
Stratified sampling is a good technique to use when, as in our example, a subgroup of interest makes up a relatively small proportion of the overall sample. In our example of a study of binge drinking, we want to include weekdays and weekends in our sample, but because weekends make up less than a third of an entire week, there’s a chance that a simple random or systematic strategy would not yield sufficient weekend observation days. As you might imagine, stratified sampling is even more useful in cases where a subgroup makes up an even smaller proportion of the sampling frame—for example, if we want to be sure to include in our study students who are in year five of their undergraduate program but this subgroup makes up only a small percentage of the population of undergraduates. There’s a chance simple random or systematic sampling strategy might not yield any fifth-year students, but by using stratified sampling, we could ensure that our sample contained the proportion of fifth-year students that is reflective of the larger population.
In this case, class year (e.g., freshman, sophomore, junior, senior, and fifth-year) is our strata, or the characteristic by which the sample is divided. In using stratified sampling, we are often concerned with how well our sample reflects the population. A sample with too many freshmen may skew our results in one direction because perhaps they binge drink more (or less) than students in other class years. Using stratified sampling allows us to make sure our sample has the same proportion of people from each class year as the overall population of the school.
Up to this point in our discussion of probability samples, we’ve assumed that researchers will be able to access a list of population elements in order to create a sampling frame. This, as you might imagine, is not always the case. Let’s say, for example, that you wish to conduct a study of binge drinking across fraternity members at each undergraduate program in your state. Just imagine trying to create a list of every single fraternity member in the state. Even if you could find a way to generate such a list, attempting to do so might not be the most practical use of your time or resources. When this is the case, researchers turn to cluster sampling. Cluster sampling occurs when a researcher begins by sampling groups (or clusters) of population elements and then selects elements from within those groups.
Let’s work through how we might use cluster sampling in our study of binge drinking. While creating a list of all fraternity members in your state would be next to impossible, you could easily create a list of all undergraduate colleges in your state. Thus, you could draw a random sample of undergraduate colleges (your cluster) and then draw another random sample of elements (in this case, fraternity members) from within the undergraduate college you initially selected. Cluster sampling works in stages. In this example, we sampled in two stages— (1) undergraduate colleges and (2) fraternity members at the undergraduate colleges we selected. However, we could add another stage if it made sense to do so. We could randomly select (1) undergraduate colleges (2) specific fraternities at each school and (3) individual fraternity members. As you might have guessed, sampling in multiple stages does introduce the possibility of greater error (each stage is subject to its own sampling error), but it is nevertheless a highly efficient method.
Jessica Holt and Wayne Gillespie (2008) [2] used cluster sampling in their study of students’ experiences with violence in intimate relationships. Specifically, the researchers randomly selected 14 classes on their campus and then drew a random subsample of students from those classes. But you probably know from your experience with college classes that not all classes are the same size. So, if Holt and Gillespie had simply randomly selected 14 classes and then selected the same number of students from each class to complete their survey, then students in the smaller of those classes would have had a greater chance of being selected for the study than students in the larger classes. Keep in mind, with random sampling the goal is to make sure that each element has the same chance of being selected. When clusters are of different sizes, as in the example of sampling college classes, researchers often use a method called probability proportionate to size (PPS). This means that they take into account that their clusters are of different sizes. They do this by giving clusters different chances of being selected based on their size so that each element within those clusters winds up having an equal chance of being selected.
To summarize, probability samples allow a researcher to make conclusions about larger groups. Probability samples require a sampling frame from which elements, usually human beings, can be selected at random from a list. The use of random selection reduces the error and bias present in nonprobability samples reviewed in the previous section, though some error will always remain. In relying on a random number table or generator, researchers can more accurately state that their sample represents the population from which it was drawn. This strength is common to all probability sampling approaches summarized in Table 10.4.
Table 10.4 Types of probability samples
Sample type Description
Simple random Researcher randomly selects elements from sampling frame.
Systematic Researcher selects every kth element from sampling frame.
Stratified Researcher creates subgroups then randomly selects elements from each subgroup.
Cluster Researcher randomly selects clusters then randomly selects elements from selected clusters.
In determining which probability sampling approach makes the most sense for your project, it helps to know more about your population. A simple random sample and systematic sample are relatively similar to carry out. They both require a list all elements in your sampling frame. Systematic sampling is slightly easier in that it does not require you to use a random number generator, instead using a sampling interval that is easy to calculate by hand.
The relative simplicity of both approaches is counterweighted by their lack of sensitivity to characteristics in of your population. Stratified samples can better account for periodicity by creating strata that reduce or eliminate the effects of periodicity. Stratified samples also ensure that smaller subgroups are included in your sample, thus making your sample more representative of the overall population. While these benefits are important, creating strata for this purpose requires knowing information about your population before beginning the sampling process. In our binge drinking example, we would need to know how many students are in each class year to make sure our sample contained the same proportions. We would need to know that, for example, fifth-year students make up 5% of the student population to make sure 5% of our sample is comprised of fifth-year students. If the true population parameters are unknown, stratified sampling becomes significantly more challenging.
Common to each of the previous probability sampling approaches is the necessity of using a real list of all elements in your sampling frame. Cluster sampling is different. It allows a researcher to perform probability sampling in cases for which a list of elements is not available or pragmatic to create. Cluster sampling is also useful for making claims about a larger population, in our example, all fraternity members within a state. However, because sampling occurs at multiple stages in the process, in our example at the university and student level, sampling error increases. For many researchers, this weakness is outweighed by the benefits of cluster sampling.
Key Takeaways
• In probability sampling, the aim is to identify a sample that resembles the population from which it was drawn.
• There are several types of probability samples including simple random samples, systematic samples, stratified samples, and cluster samples.
• Probability samples usually require a real list of elements in your sampling frame, though cluster sampling can be conducted without one.
Glossary
• Cluster sampling- a sampling approach that begins by sampling groups (or clusters) of population elements and then selects elements from within those groups
• Generalizability – the idea that a study’s results will tell us something about a group larger than the sample from which the findings were generated
• Periodicity- the tendency for a pattern to occur at regular intervals
• Probability proportionate to size- in cluster sampling, giving clusters different chances of being selected based on their size so that each element within those clusters has an equal chance of being selected
• Probability sampling- sampling approaches for which a person’s likelihood of being selected from the sampling frame is known
• Random selection- using a randomly generated numbers to determine who from the sampling frame gets recruited into the sample
• Representative sample- a sample that resembles the population from which it was drawn in all the ways that are important for the research being conducted
• Sampling error- a statistical calculation of the difference between results from a sample and the actual parameters of a population
• Simple random sampling- selecting elements from a list using randomly generated numbers
• Strata- the characteristic by which the sample is divided
• Stratified sampling- dividing the study population into relevant subgroups and then draw a sample from each subgroup
• Systematic sampling- selecting every kth element from a list
Image attributions
crowd men women by DasWortgewand CC-0
roll the dice by 955169 CC-0
1. Figure 10.2 copied from Blackstone, A. (2012) Principles of sociological inquiry: Qualitative and quantitative methods. Saylor Foundation. Retrieved from: https://saylordotorg.github.io/text_...ative-methods/ Shared under CC-BY-NC-SA 3.0 License (https://creativecommons.org/licenses/by-nc-sa/3.0/) ↵
2. Holt, J. L., & Gillespie, W. (2008). Intergenerational transmission of violence, threatened egoism, and reciprocity: A test of multiple psychosocial factors affecting intimate partner violence. AmericanJournal of Criminal Justice, 33, 252–266. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/10%3A_Sampling/10.03%3A_Sampling_in_quantitative_research.txt |
Learning Objectives
• Identify three questions you should ask about samples when reading research results
• Describe how bias impacts sampling
We read and hear about research results so often that we might sometimes overlook the need to ask important questions about where the research participants came from and how they are identified for inclusion. It is easy to focus only on findings when we’re busy and when the really interesting stuff is in a study’s conclusions, not its procedures. But now that you have some familiarity with the variety of procedures for selecting study participants, you are equipped to ask some very important questions about the findings you read and to be a more responsible consumer of research.
Who sampled, how, and for what purpose?
Have you ever been a participant in someone’s research? If you have ever taken an introductory psychology or sociology class at a large university, that’s probably a silly question to ask. Social science researchers on college campuses have a luxury that researchers elsewhere may not share—they have access to a whole bunch of (presumably) willing and able human guinea pigs. But that luxury comes at a cost—sample representativeness. One study of top academic journals in psychology found that over two-thirds (68%) of participants in studies published by those journals were based on samples drawn in the United States (Arnett, 2008). [1] Further, the study found that two-thirds of the work that derived from US samples published in the Journal of Personality and Social Psychology was based on samples made up entirely of American undergraduates taking psychology courses.
These findings certainly raise the question: What do we actually learn from social scientific studies and about whom do we learn it? That is exactly the concern raised by Joseph Henrich and colleagues (Henrich, Heine, & Norenzayan, 2010), [2] authors of the article “The Weirdest People in the World?” In their piece, Henrich and colleagues point out that behavioral scientists very commonly make sweeping claims about human nature based on samples drawn only from WEIRD (Western, Educated, Industrialized, Rich, and Democratic) societies, and often based on even narrower samples, as is the case with many studies relying on samples drawn from college classrooms. As it turns out, many robust findings about the nature of human behavior when it comes to fairness, cooperation, visual perception, trust, and other behaviors are based on studies that excluded participants from outside the United States and sometimes excluded anyone outside the college classroom (Begley, 2010). [3] This certainly raises questions about what we really know about human behavior as opposed to US resident or US undergraduate behavior. Of course, not all research findings are based on samples of WEIRD folks like college students. But even then, it would behoove us to pay attention to the population on which studies are based and the claims that are being made about to whom those studies apply.
In the preceding discussion, the concern is with researchers making claims about populations other than those from which their samples were drawn. A related, but slightly different, potential concern is sampling bias. Bias in sampling occurs when the elements selected for inclusion in a study do not represent the larger population from which they were drawn. For example, if you were to sample people walking into the social work building on campus during each weekday, your sample would include too many social work majors and not enough non-social work majors. Furthermore, you would completely exclude graduate students whose classes are at night. Bias may be introduced by the sampling method used or due to conscious or unconscious bias introduced by the researcher (Rubin & Babbie, 2017). [4] A researcher might select people who “look like good research participants,” in the process transferring their unconscious biases to their sample.
Another thing to keep in mind is that just because a sample may be representative in all respects that a researcher thinks are relevant, there may be aspects that are relevant that didn’t occur to the researcher when she was drawing her sample. You might not think that a person’s phone would have much to do with their voting preferences, for example. But had pollsters making predictions about the results of the 2008 presidential election not been careful to include both cell phone-only and landline households in their surveys, it is possible that their predictions would have underestimated Barack Obama’s lead over John McCain because Obama was much more popular among cell-only users than McCain (Keeter, Dimock, & Christian, 2008). [5]
So how do we know when we can count on results that are being reported to us? While there might not be any magic or always-true rules we can apply, there are a couple of things we can keep in mind as we read the claims researchers make about their findings.
First, remember that sample quality is determined only by the sample actually obtained, not by the sampling method itself. A researcher may set out to administer a survey to a representative sample by correctly employing a random selection technique, but if only a handful of the people sampled actually respond to the survey, the researcher will have to be very careful about the claims she can make about her survey findings.
Another thing to keep in mind, as demonstrated by the preceding discussion, is that researchers may be drawn to talking about implications of their findings as though they apply to some group other than the population actually sampled. Though this tendency is usually quite innocent and does not come from a place of malice, it is all too tempting a way to talk about findings; as consumers of those findings, it is our responsibility to be attentive to this sort of (likely unintentional) bait and switch.
Finally, keep in mind that a sample that allows for comparisons of theoretically important concepts or variables is certainly better than one that does not allow for such comparisons. In a study based on a nonrepresentative sample, for example, we can learn about the strength of our social theories by comparing relevant aspects of social processes. We talked about this as theory-testing in Chapter 7.
At their core, questions about sample quality should address who has been sampled, how they were sampled, and for what purpose they were sampled. Being able to answer those questions will help you better understand, and more responsibly read, research results.
Key Takeaways
• Sometimes researchers may make claims about populations other than those from whom their samples were drawn; other times they may make claims about a population based on a sample that is not representative. As consumers of research, we should be attentive to both possibilities.
• A researcher’s findings need not be generalizable to be valuable; samples that allow for comparisons of theoretically important concepts or variables may yield findings that contribute to our social theories and our understandings of social processes.
Glossary
• Bias- in sampling, when the elements selected for inclusion in a study do not represent the larger population from which they were drawn due to sampling method or thought processes of the researcher
Image attributions
men women apparel couple by 5688709 CC-0
ignorance by Rilsonav CC-0
1. Arnett, J. J. (2008). The neglected 95%: Why American psychology needs to become less American. American Psychologist, 63, 602–614. ↵
2. Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world? Behavioral and Brain Sciences, 33, 61–135. ↵
3. Newsweek magazine published an interesting story about Henrich and his colleague’s study: Begley, S. (2010). What’s really human? The trouble with student guinea pigs. Retrieved from http://www.newsweek.com/2010/07/23/what-s-really-human.html
4. Rubin, C. & Babbie, S. (2017). Research methods for social work (9th edition). Boston, MA: Cengage. ↵
5. Keeter, S., Dimock, M., & Christian, L. (2008). Calling cell phones in ’08 pre-election polls. The Pew Research Center for the People and the Press. Retrieved from people-press.org/files/legacy-pdf/cell-phone-commentary.pdf↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/10%3A_Sampling/10.04%3A_A_word_of_caution-_Questions_to_ask_about_samples.txt |
In 2008, the voters of the United States elected our first African American president, Barack Obama. It may not surprise you to learn that when President Obama was coming of age in the 1970s, one-quarter of Americans reported they would not vote for a qualified African American presidential nominee. Three decades later, when President Obama ran for the presidency, fewer than 8% of Americans still held that position, and President Obama won the election (Smith, 2009). [1] We know about these trends in voter opinion because the General Social Survey (http://www.norc.uchicago.edu/GSS+Website), a nationally representative survey of American adults, included questions about race and voting over the years described here. Without survey research, we may not know how Americans’ perspectives on race and the presidency shifted over these years.
This chapter discusses or mentions the following topics: racism, mental health, terrorism and 9/11, substance use, and sexism and ageism in the workplace.
1. Smith, T. W. (2009). Trends in willingness to vote for a black and woman for president, 1972–2008. GSS Social Change Report No. 55. Chicago, IL: National Opinion Research Center.
11: Survey Research
Learning Objectives
• Define survey research
• Identify when it is appropriate to employ survey research as a data-collection strategy
Most of you have probably taken a survey at one time or another, so you probably have a pretty good idea of what a survey is. Sometimes students in my research methods classes feel that understanding what a survey is and how to write one is so obvious there’s no need to dedicate any class time to learning about it. This feeling is understandable—surveys are very much a part of our everyday lives—we’ve probably all taken one, we hear about their results in the news, and perhaps we’ve even administered one ourselves. What students quickly learn is that there is more to constructing a good survey than meets the eye. Survey design takes a great deal of thoughtful planning and often a great many rounds of revision. But it is worth the effort. As we’ll learn in this chapter, there are many benefits to choosing survey research as one’s method of data collection. We’ll take a look at what a survey is exactly, what some of the benefits and drawbacks of this method are, how to construct a survey, and what to do with survey data once one has it in hand.
Survey research is a quantitative method in which a researcher poses a set of predetermined questions to an entire group, or sample, of individuals. Survey research is an especially useful approach when a researcher aims to describe or explain features of a very large group or groups. This method may also be used as a way of quickly gaining some general details about one’s population of interest to help prepare for a more focused, in-depth study using time-intensive methods such as in-depth. In this case, a survey may help a researcher identify specific individuals or locations from which to collect additional data.
As is true of all methods of data collection, survey research is better suited to answering some kinds of research questions more than others. In addition, as you’ll recall from Chapter 9, operationalization works differently with different research methods. If your interest is in political activism, for example, you likely operationalize that concept differently in a survey than you would for an experimental study of the same topic.
Key Takeaways
• Survey research is often used by researchers who wish to explain trends or features of large groups. It may also be used to assist those planning some more focused, in-depth study.
Glossary
• Survey research- a quantitative method whereby a researcher poses some set of predetermined questions to a sample
Image attributions
survey by andibreit CC-0 | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/11%3A_Survey_Research/11.01%3A_Survey_research-_What_is_it_and_when_should_it_be_used%3F.txt |
Learning Objectives
• Identify and explain the strengths of survey research
• Identify and explain the weaknesses of survey research
Survey research, as with all methods of data collection, comes with both strengths and weaknesses. We’ll examine both in this section.
Strengths of survey methods
Researchers employing survey methods to collect data enjoy a number of benefits. First, surveys are an excellent way to gather lots of information from many people. In a study of older people’s experiences in the workplace, researchers were able to mail a written questionnaire to around 500 people who lived throughout the state of Maine at a cost of just over \$1,000. This cost included printing copies of a seven-page survey, printing a cover letter, addressing and stuffing envelopes, mailing the survey, and buying return postage for the survey. I realize that \$1,000 is nothing to sneeze at, but just imagine what it might have cost to visit each of those people individually to interview them in person. You would have to dedicate a few weeks of your life at least, drive around the state, and pay for meals and lodging to interview each person individually. We could double, triple, or even quadruple our costs pretty quickly by opting for an in-person method of data collection over a mailed survey. Thus, surveys are relatively cost-effective.
Related to the benefit of cost-effectiveness is a survey’s potential for generalizability. Because surveys allow researchers to collect data from very large samples for a relatively low cost, survey methods lend themselves to probability sampling techniques, which we discussed in Chapter 10. Of all the data collection methods described in this textbook, survey research is probably the best method to use when one hopes to gain a representative picture of the attitudes and characteristics of a large group.
Survey research also tends to be a reliable method of inquiry. This is because surveys are standardized in that the same questions, phrased in exactly the same way, are posed to participants. Other methods, such as qualitative interviewing, which we’ll learn about in Chapter 13, do not offer the same consistency that a quantitative survey offers. This is not to say that all surveys are always reliable. A poorly phrased question can cause respondents to interpret its meaning differently, which can reduce that question’s reliability. Assuming well-constructed questions and survey design, one strength of this methodology is its potential to produce reliable results.
The versatility of survey research is also an asset. Surveys are used by all kinds of people in all kinds of professions. The versatility offered by survey research means that understanding how to construct and administer surveys is a useful skill to have for all kinds of jobs. Lawyers might use surveys in their efforts to select juries, social service and other organizations (e.g., churches, clubs, fundraising groups, activist groups) use them to evaluate the effectiveness of their efforts, businesses use them to learn how to market their products, governments use them to understand community opinions and needs, and politicians and media outlets use surveys to understand their constituencies.
In sum, the following are benefits of survey research:
• Cost-effectiveness
• Generalizability
• Reliability
• Versatility
Weaknesses of survey methods
As with all methods of data collection, survey research also comes with a few drawbacks. First, while one might argue that surveys are flexible in the sense that we can ask any number of questions on any number of topics in them, the fact that the survey researcher is generally stuck with a single instrument for collecting data, the questionnaire. Surveys are in many ways rather inflexible. Let’s say you mail a survey out to 1,000 people and then discover, as responses start coming in, that your phrasing on a particular question seems to be confusing a number of respondents. At this stage, it’s too late for a do-over or to change the question for the respondents who haven’t yet returned their surveys. When conducting in-depth interviews, on the other hand, a researcher can provide respondents further explanation if they’re confused by a question and can tweak their questions as they learn more about how respondents seem to understand them.
Depth can also be a problem with surveys. Survey questions are standardized; thus, it can be difficult to ask anything other than very general questions that a broad range of people will understand. Because of this, survey results may not be as valid as results obtained using methods of data collection that allow a researcher to more comprehensively examine whatever topic is being studied. Let’s say, for example, that you want to learn something about voters’ willingness to elect an African American president, as in our opening example in this chapter. General Social Survey respondents were asked, “If your party nominated an African American for president, would you vote for him if he were qualified for the job?” Respondents were then asked to respond either yes or no to the question. But what if someone’s opinion was more complex than could be answered with a simple yes or no? What if, for example, a person was willing to vote for an African American woman but not an African American man? [1]
In sum, potential drawbacks to survey research include the following:
• Inflexibility
• Lack of depth
Key Takeaways
• Strengths of survey research include its cost effectiveness, generalizability, reliability, and versatility.
• Weaknesses of survey research include inflexibility and issues with depth.
Image attributions
experience by mohamed_hassan CC-0
1. I am not at all suggesting that such a perspective makes any sense. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/11%3A_Survey_Research/11.02%3A_Strengths_and_weaknesses_of_survey_research.txt |
Learning Objectives
• Define cross-sectional surveys, provide an example of a cross-sectional survey, and outline some of the drawbacks of cross-sectional research
• Describe the three types of longitudinal surveys
• Describe retrospective surveys and identify their strengths and weaknesses
• Discuss the benefits and drawbacks of the various methods of administering surveys
There is immense variety when it comes to surveys. This variety comes both in terms of time—when or with what frequency a survey is administered—and in terms of administration—how a survey is delivered to respondents. In this section, we’ll look at what types of surveys exist when it comes to both time and administration.
Time
In terms of time, there are two main types of surveys: cross-sectional and longitudinal. Cross-sectional surveys are those that are administered at just one point in time. These surveys offer researchers a snapshot in time and offer an idea about how things are for the respondents at the particular point in time that the survey is administered.
An example of a cross-sectional survey comes from Aniko Kezdy and colleagues’ study (Kezdy, Martos, Boland, & Horvath-Szabo, 2011) [1] of the association between religious attitudes, religious beliefs, and mental health among students in Hungary. These researchers administered a single, one-time-only, cross-sectional survey to a convenience sample of 403 high school and college students. The survey focused on how religious attitudes impact various aspects of one’s life and health. The researchers found from analysis of their cross- sectional data that anxiety and depression were highest among those who had both strong religious beliefs and some doubts about religion.
Yet another recent example of cross-sectional survey research can be seen in Bateman and colleagues’ study (Bateman, Pike, & Butler, 2011) [2] of how the perceived publicness of social networking sites influences users’ self-disclosures. These researchers administered an online survey to undergraduate and graduate business students. They found that even though revealing information about oneself is viewed as key to realizing many of the benefits of social networking sites, respondents were less willing to disclose information about themselves as their perceptions of a social networking site’s publicness rose. That is, there was a negative relationship between perceived publicness of a social networking site and plans to self-disclose on the site.
One problem with cross-sectional surveys is that the events, opinions, behaviors, and other phenomena that such surveys are designed to assess don’t generally remain stagnant. They change over time. Thus, generalizing from a cross-sectional survey about the way things are can be tricky; perhaps you can say something about the way things were in the moment that you administered your survey, but it is difficult to know whether things remained that way for long after you administered your survey. Think, for example, about how Americans might have responded if administered a survey asking for their opinions on terrorism on September 10, 2001. Now imagine how responses to the same set of questions might differ were they administered on September 12, 2001. The point is not that cross-sectional surveys are useless; they have many important uses. But researchers must remember what they have captured by administering a cross-sectional survey—that is, as previously noted, a snapshot of life as it was at the time that the survey was administered.
One way to overcome this sometimes-problematic aspect of cross-sectional surveys is to administer a longitudinal survey. Longitudinal surveys are those that enable a researcher to make observations over some extended period of time. There are several types of longitudinal surveys, including trend, panel, and cohort surveys. We’ll discuss all three types here, along with retrospective surveys. Retrospective surveys fall somewhere in between cross-sectional and longitudinal surveys.
The first type of longitudinal survey is called a trend survey. The main focus of a trend survey is, perhaps not surprisingly, trends. Researchers conducting trend surveys are interested in how people in a specific group change over time. Each time the researchers gather data, they ask different people from the group they are describing because their concern is the group, not the individual people they survey. Let’s look at an example.
The Monitoring the Future Study (http://www.monitoringthefuture.org/) is a trend study that described the substance use of high school children in the United States. It’s conducted annually by the National Institute on Drug Abuse (NIDA). Each year, the NIDA distributes surveys to children in high schools around the country to understand how substance use and abuse in that population changes over time. Perhaps surprisingly, fewer high school children reported using alcohol in the past month than at any point over the last 20 years. Recent data also reflected an increased use of e-cigarettes and the popularity of e-cigarettes with no nicotine over those with nicotine. The data points provide insight into targeting substance abuse prevention programs towards the current issues facing the high school population.
Unlike in a trend survey, in a panel survey the same people participate in the survey each time it is administered. As you might imagine, panel studies can be difficult and costly. Imagine trying to administer a survey to the same 100 people every year for, say, 5 years in a row. Keeping track of where people live, when they move, and when they die takes resources that researchers often don’t have. When they do, however, the results can be quite powerful. The Youth Development Study (YDS), administered from the University of Minnesota, offers an excellent example of a panel study. You can read more about the Youth Development Study at its website: https://cla.umn.edu/sociology/graduate/collaboration-opportunities/youth-development-study.
Since 1988, YDS researchers have administered an annual survey to the same 1,000 people. Study participants were in ninth grade when the study began, and they are now in their thirties. Several hundred papers, articles, and books have been written using data from the YDS. One of the major lessons learned from this panel study is that work has a largely positive impact on young people (Mortimer, 2003). [3] Contrary to popular beliefs about the impact of work on adolescents’ performance in school and transition to adulthood, work in fact increases confidence, enhances academic success, and prepares students for success in their future careers. Without this panel study, we may not be aware of the positive impact that working can have on young people.
Another type of longitudinal survey is a cohort survey. In a cohort survey, the participants have a defining characteristic that the researcher is interested in studying. The same people don’t necessarily participate from year to year, but all participants must meet whatever categorical criteria fulfill the researcher’s primary interest. Common cohorts that may be of interest to researchers include people of particular generations or those who were born around the same time period, graduating classes, people who began work in a given industry at the same time, or perhaps people who have some specific historical experience in common.
An example of this sort of research can be seen in Christine Percheski’s work (2008) [4] on cohort differences in women’s employment. Percheski compared women’s employment rates across seven different generational cohorts, from Progressives born between 1906 and 1915 to Generation Xers born between 1966 and 1975. She found, among other patterns, that professional women’s labor force participation had increased across all cohorts. She also found that professional women with young children from Generation X had higher labor force participation rates than similar women from previous generations, concluding that mothers do not appear to be opting out of the workforce as some journalists have speculated (Belkin, 2003). [5]
All three types of longitudinal surveys share the strength that they permit a researcher to make observations over time. This means that if whatever behavior or other phenomenon the researcher is interested in changes, either because of some world event or because people age, the researcher will be able to capture those changes. Table 11.1 summarizes these three types of longitudinal surveys.
Table 11.1 Types of longitudinal surveys
Sample type Description
Trend Researcher examines changes in trends over time; the same people do not necessarily participate in the survey more than once.
Panel Researcher surveys the exact same sample several times over a period of time.
Cohort Researcher identifies a defining characteristic and then regularly surveys people who have that characteristic.
Finally, retrospective surveys are similar to other longitudinal studies in that they deal with changes over time, but like a cross-sectional study, they are administered only once. In a retrospective survey, participants are asked to report events from the past. By having respondents report past behaviors, beliefs, or experiences, researchers are able to gather longitudinal-like data without actually incurring the time or expense of a longitudinal survey. Of course, this benefit must be weighed against the possibility that people’s recollections of their pasts may be faulty. Imagine, for example, that you’re asked in a survey to respond to questions about where, how, and with whom you spent last Valentine’s Day. As last Valentine’s Day can’t have been more than 12 months ago, chances are good that you might be able to respond accurately to any survey questions about it. But now let’s say the researcher wants to know how last Valentine’s Day compares to previous Valentine’s Days, so she asks you to report on where, how, and with whom you spent the preceding six Valentine’s Days. How likely is it that you will remember? Will your responses be as accurate as they might have been had you been asked the question each year over the past 6 years, rather than asked to report on all years today?
In sum, when or with what frequency a survey is administered will determine whether your survey is cross-sectional or longitudinal. While longitudinal surveys are certainly preferable in terms of their ability to track changes over time, the time and cost required to administer a longitudinal survey can be prohibitive. As you may have guessed, the issues of time described here are not necessarily unique to survey research. Other methods of data collection can be cross-sectional or longitudinal—these are really matters of research design. But we’ve placed our discussion of these terms here because they are most commonly used by survey researchers to describe the type of survey administered. Another aspect of survey administration deals with how surveys are administered. We’ll examine that next.
Administration
Surveys vary not just in terms of when they are administered but also in terms of how they are administered. One common way to administer surveys is in the form of self-administered questionnaires. This means that a research participant is given a set of questions, in writing, to which they are asked to respond. Self-administered questionnaires can be delivered in hard copy format, typically via mail, or increasingly more commonly, online. We’ll consider both modes of delivery here.
Hard copy self-administered questionnaires may be delivered to participants in person or via snail mail. Perhaps you’ve take a survey that was given to you in person; on many college campuses, it is not uncommon for researchers to administer surveys in large social science classes (as you might recall from the discussion in our chapter on sampling). If you are ever asked to complete a survey in a similar setting, it might be interesting to note how your perspective on the survey and its questions could be shaped by the new knowledge you’re gaining about survey research in this chapter.
Researchers may also deliver surveys in person by going door-to-door and either asking people to fill them out right away or making arrangements for the researcher to return to pick up completed surveys. Though the advent of online survey tools has made door-to-door delivery of surveys less common, I still see an occasional survey researcher at my door, especially around election time. This mode of gathering data is apparently still used by political campaign workers, at least in some areas of the country.
If you are not able to visit each member of your sample personally to deliver a survey, you might consider sending your survey through the mail. While this mode of delivery may not be ideal (imagine how much less likely you’d probably be to return a survey that didn’t come with the researcher standing on your doorstep waiting to take it from you), sometimes it is the only available or the most practical option. As mentioned, though, this may not be the most ideal way of administering a survey because it can be difficult to convince people to take the time to complete and return your survey.
Often survey researchers who deliver their surveys via snail mail may provide some advance notice to respondents about the survey to get people thinking about and preparing to complete it. They may also follow up with their sample a few weeks after their survey has been sent out. This can be done not only to remind those who have not yet completed the survey to please do so but also to thank those who have already returned the survey. Most survey researchers agree that this sort of follow-up is essential for improving mailed surveys’ return rates (Babbie, 2010). [6] Other helpful tools to increase response rate are to create an attractive and professional survey, offer monetary incentives, and provide a pre-addressed, stamped return envelope.
Earlier, I mentioned online delivery as another way to administer a survey. This delivery mechanism is becoming increasingly common, no doubt because it is easy to use, relatively cheap, and may be quicker than knocking on doors or waiting for mailed surveys to be returned. To deliver a survey online, a researcher may subscribe to a service that offers online delivery or use some delivery mechanism that is available for free. SurveyMonkey offers both free and paid online survey services (https://www.surveymonkey.com). One advantage to using a service like SurveyMonkey, aside from the advantages of online delivery already mentioned, is that results can be provided to you in formats that are readable by data analysis programs such as SPSS. This saves you, the researcher, the step of having to manually enter data into your analysis program, as you would if you administered your survey in hard copy format.
Many of the suggestions provided for improving the response rate on a hard copy questionnaire apply to online questionnaires as well. One difference of course is that the sort of incentives one can provide in an online format differ from those that can be given in person or sent through the mail. But this doesn’t mean that online survey researchers cannot offer completion incentives to their respondents. I’ve taken a number of online surveys; many of these did not come with an incentive other than the joy of knowing that I’d helped a fellow social scientist do their job. However, for participating in one survey, I was given a coupon code to use for \$30 off any order at a major online retailer. I’ve taken other online surveys where on completion I could provide my name and contact information if I wished to be entered into a lottery together with other study participants to win a larger gift, such as a \$50 gift card or an iPad.
Online surveys, however, may not be accessible to individuals with limited, unreliable, or no access to the internet or less skill at using a computer. If those issues are common in your target population, online surveys may not work as well for your research study. While online surveys may be faster and cheaper than mailed surveys, mailed surveys are more likely to reach your entire sample but also more likely to be lost and not returned. The choice of which delivery mechanism is best depends on a number of factors, including your resources, the resources of your study participants, and the time you have available to distribute surveys and wait for responses. Understanding the characteristics of your study’s population is key to identifying the appropriate mechanism for delivering your survey.
Sometimes surveys are administered by having a researcher poses questions verbally to respondents rather than having respondents read the questions on their own. Researchers using phone or in-person surveys use an interview schedule which contains the list of questions and answer options that the researcher will read to respondents. Consistency in the way that questions and answer options are presented is very important with an interview schedule. The aim is to pose every question-and-answer option in the very same way to every respondent. This is done to minimize interviewer effect, or possible changes in the way an interviewee responds based on how or when questions and answer options are presented by the interviewer. In-person surveys may be recorded, but because questions tend to be closed ended, taking notes during the interview is less disruptive than it can be during a qualitative interview.
Interview schedules are used in phone or in-person surveys and are also called quantitative interviews. Phone surveys are often conducted by political polling firms to understand how the electorate feels about certain candidates or policies. In both cases, researchers pose questions verbally to participants. As someone who has poor research karma, I often decline to participate in phone studies when I am called. It is easy, socially acceptable even, to hang up abruptly on an unwanted caller. Additionally, a distracted participant who is cooking dinner, tending to troublesome children, or driving may not provide accurate answers to your questions. Phone surveys make it difficult to control the environment in which a person answers your survey. Another challenge comes from the increasing number of people who only have cell phones and do not use landlines (Pew Research, n.d.). [7] Unlike landlines, cell phone numbers are portable across carriers, associated with individuals, not households, and do not change their first three numbers when people move to a new geographical area. Computer-assisted telephone interviewing (CATI) programs have also been developed to assist quantitative survey researchers. These programs allow an interviewer to enter responses directly into a computer as they are provided, thus saving hours of time that would otherwise have to be spent entering data into an analysis program by hand.
Quantitative interviews must also be administered in such a way that the researcher asks the same question the same way each time. While questions on hard copy questionnaires may create an impression based on the way they are presented, having a person administer questions introduces a slew of additional variables that might influence a respondent. Even a slight shift in emphasis on a word may bias the respondent to answer differently. As I’ve mentioned earlier, consistency is key with quantitative data collection—and human beings are not necessarily known for their consistency. Quantitative interviews can also help reduce a respondent’s confusion. If a respondent is unsure about the meaning of a question or answer option on a self-administered questionnaire, they probably won’t have the opportunity to get clarification from the researcher. An interview, on the other hand, gives the researcher an opportunity to clarify or explain any items that may be confusing. If a participant asks for clarification, the researcher must use pre-determined responses to make sure each quantitative interview is exactly the same as the others.
In-person surveys are conducted in the same way as phone surveys but must also account for non-verbal expressions and behaviors. In-person surveys do carry one distinct benefit—they are more difficult to say “no” to. Because the participant is already in the room and sitting across from the researcher, they are less likely to decline than if they clicked “delete” for an emailed online survey or pressed “hang up” during a phone survey. In-person surveys are also much more time consuming and expensive than mailing questionnaires. Thus, quantitative researchers may opt for self-administered questionnaires over in-person surveys on the grounds that they will be able to reach a large sample at a much lower cost than were they to interact personally with each and every respondent.
Key Takeaways
• Time is a factor in determining what type of survey researcher administers; cross-sectional surveys are administered at one time, and longitudinal surveys are administered over time.
• Retrospective surveys offer some of the benefits of longitudinal research but also come with their own drawbacks.
• Self-administered questionnaires may be delivered in hard copy form to participants in person or via snail mail or online.
• Interview schedules are used in in-person or phone surveys.
• Each method of survey administration comes with benefits and drawbacks.
Glossary
• Cohort survey- describes how people with a defining characteristic change over time
• Cross-sectional surveys- surveys that are administered at just one point in time
• Interview schedules- a researcher poses questions verbally to respondents
• Longitudinal surveys- surveys in which a researcher to make observations over some extended period of time
• Panel survey- describes how people in a specific group change over time, asking the same people each time the survey is administered
• Retrospective surveys- describe changes over time but are administered only once
• Self-administered questionnaires- a research participant is given a set of questions, in writing, to which they are asked to respond
• Trend survey- describes how people in a specific group change over time, asking different people each time the survey is administered
Image attributions
company social networks by Hurca CC-0
posts submit searching by mohamed_hassan CC-0
talk telephone by MelanieSchwolert CC-0
1. Kezdy, A., Martos, T., Boland, V., & Horvath-Szabo, K. (2011). Religious doubts and mental health in adolescence and young adulthood: The association with religious attitudes. Journal of Adolescence, 34, 39–47. ↵
2. Bateman, P. J., Pike, J. C., & Butler, B. S. (2011). To disclose or not: Publicness in social networking sites. Information Technology & People, 24, 78–100. ↵
3. Mortimer, J. T. (2003). Working and growing up in America. Cambridge, MA: Harvard University Press. ↵
4. Percheski, C. (2008). Opting out? Cohort differences in professional women’s employment rates from 1960 to 2005. American Sociological Review, 73, 497–517. ↵
5. Belkin, L. (2003, October 26). The opt-out revolution. New York Times, pp. 42–47, 58, 85–86. ↵
6. Babbie, E. (2010). The practice of social research (12th ed.). Belmont, CA: Wadsworth. ↵
7. Pew Research (n.d.) Sampling. Retrieved from: http://www.pewresearch.org/methodology/u-s-survey-research/sampling/ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/11%3A_Survey_Research/11.03%3A_Types_of_surveys.txt |
Learning Objectives
• Identify the steps one should take to write effective survey questions
• Describe some of the ways that survey questions might confuse respondents and how to overcome that possibility
• Apply mutual exclusivity and exhaustiveness to writing closed-ended questions
• Define fence-sitting and floating
• Describe the steps involved in constructing a well-designed questionnaire
• Discuss why pretesting is important
Up to this point, we’ve considered several general points about surveys, including when to use them, some of their strengths and weaknesses, and how often and in what ways to administer surveys. In this section, we’ll get more specific and take a look at how to pose understandable questions that will yield useable data and how to present those questions on your questionnaire.
Asking effective questions
The first thing you need to do to write effective survey questions is identify what exactly you wish to know. As silly as it sounds to state what seems so completely obvious, I can’t stress enough how easy it is to forget to include important questions when designing a survey. Begin by looking at your research question. Perhaps you wish to identify the factors that contribute to students’ ability to transition from high school to college. To understand which factors shaped successful students’ transitions to college, you’ll need to include questions in your survey about all the possible factors that could contribute. How do you know what to ask? Consulting the literature on the topic will certainly help, but you should also take the time to do some brainstorming on your own and to talk with others about what they think may be important in the transition to college. Time and space limitations won’t allow you to include every single item you’ve come up with, so you’ll also need to think about ranking your questions so that you can be sure to include those that you view as most important. In your study, think back to your work on operationalization. How did you plan to measure your variables? If you planned to ask specific questions or use a scale, those should be in your survey.
Although I have stressed the importance of including questions on all topics you view as important to your overall research question, you don’t want to take an everything-but-the-kitchen-sink approach by uncritically including every possible question that occurs to you. Doing so puts an unnecessary burden on your survey respondents. Remember that you have asked your respondents to give you their time and attention and to take care in responding to your questions; show them your respect by only asking questions that you view as important.
Once you’ve identified all the topics about which you’d like to ask questions, you’ll need to actually write those questions. Questions should be as clear and to the point as possible. This is not the time to show off your creative writing skills; a survey is a technical instrument and should be written in a way that is as direct and concise as possible. As I’ve mentioned earlier, your survey respondents have agreed to give their time and attention to your survey. The best way to show your appreciation for their time is to not waste it. Ensuring that your questions are clear and concise will go a long way toward showing your respondents the gratitude they deserve.
Related to the point about not wasting respondents’ time, make sure that every question you pose will be relevant to every person you ask to complete it. This means two things: first, that respondents have knowledge about whatever topic you are asking them about, and second, that respondents have experience with whatever events, behaviors, or feelings you are asking them to report. You probably wouldn’t want to ask a sample of 18-year-old respondents, for example, how they would have advised President Reagan to proceed when news of the United States’ sale of weapons to Iran broke in the mid-1980s. For one thing, few 18-year-olds are likely to have any clue about how to advise a president. Furthermore, the 18-year-olds of today were not even alive during Reagan’s presidency, so they have had no experience with Iran-Contra affair about which they are being questioned. In our example of the transition to college, heeding the criterion of relevance would mean that respondents must understand what exactly you mean by “transition to college” if you are going to use that phrase in your survey and that respondents must have actually experienced the transition to college themselves.
If you decide that you do wish to pose some questions about matters with which only a portion of respondents will have had experience, it may be appropriate to introduce a filter question into your survey. A filter question is designed to identify some subset of survey respondents who are asked additional questions that are not relevant to the entire sample. Perhaps in your survey on the transition to college you want to know whether substance use plays any role in students’ transitions. You may ask students how often they drank during their first semester of college. But this assumes that all students drank. Certainly, some may have abstained from using alcohol, and it wouldn’t make any sense to ask the nondrinkers how often they drank. Nevertheless, it seems reasonable that drinking frequency may have an impact on someone’s transition to college, so it is probably worth asking this question even if doing means the question will not be relevant for some respondents. This is just the sort of instance when a filter question would be appropriate. You may pose the question as it is presented in Figure 11.1.
Figure 11.1 Filter question
There are some ways of asking questions that are bound to confuse many survey respondents. Survey researchers should take great care to avoid these kinds of questions. These include questions that pose double negatives, those that use confusing or culturally specific terms, and those that ask more than one question but are posed as a single question. Any time respondents are forced to decipher questions that use double negatives, confusion is bound to ensue. Taking the previous question about drinking as our example, what if we had instead asked, “Did you not abstain from drinking during your first semester of college?” This example is obvious, but hopefully it drives home the point to be careful about question wording so that respondents are not asked to decipher double negatives. In general, avoiding negative terms in your question wording will help to increase respondent understanding.
You should also avoid using terms or phrases that may be regionally or culturally specific (unless you are absolutely certain all your respondents come from the region or culture whose terms you are using). When I first moved to southwest Virginia, I didn’t know what a holler was. Where I grew up in New Jersey, to holler means to yell. Even then, it wasn’t used very much. In New Jersey, we shouted and screamed, but we didn’t holler much. In southwest Virginia, my current home, a holler also means a small valley in between the mountains. If I used holler in that way on my survey, people who live near me may understand, but almost everyone else would be totally confused.
A similar issue arises when you use jargon, or technical language, that people do not commonly know. For example, if you asked adolescents how they experience imaginary audience, they likely would not be able to link that term to the concepts from David Elkind’s theory. [2] The questions on your study must be understandable to the participants. Instead, you would need to break down that term into language that is easier to understand and common to adolescents.
Asking multiple questions as though they are a single question can also confuse survey respondents. There’s a specific term for this sort of question; it is called a double-barreled question. Using our example of the transition to college, Figure 11.2 shows a double-barreled question.
Figure 11.2 Double-barreled question
Do you see what makes the question double-barreled? How would someone respond if they felt their college classes were more demanding but also more boring than their high school classes? Or less demanding but more interesting? Because the question combines “demanding” and “interesting,” there is no way to respond yes to one criterion but no to the other.
Another thing to avoid when constructing survey questions is the problem of social desirability. We all want to look good, right? And we all probably know the politically correct response to a variety of questions whether we agree with the politically correct response or not. In survey research, social desirability refers to the idea that respondents will try to answer questions in a way that will present them in a favorable light. (You may recall we covered social desirability bias in Chapter 9.) Let’s go back to our example about transitioning to college to explore this concept further.
Perhaps we decide that to understand the transition to college, we need to know whether respondents ever cheated on an exam in high school or college. We all know that cheating on exams is generally frowned upon (at least I hope we all know this). So, it may be difficult to get people to admit to cheating on a survey. But if you can guarantee respondents’ confidentiality, or even better, their anonymity, chances are much better that they will be honest about having engaged in this socially undesirable behavior. Another way to avoid problems of social desirability is to try to phrase difficult questions in the most benign way possible. Earl Babbie (2010) [3] offers a useful suggestion for helping you do this—simply imagine how you would feel responding to your survey questions. If you would be uncomfortable, chances are others would as well.
Finally, it is important to get feedback on your survey questions from as many people as possible, especially people who are like those in your sample. Now is not the time to be shy. Ask your friends for help, ask your mentors for feedback, ask your family to take a look at your survey as well. The more feedback you can get on your survey questions, the better the chances that you will come up with a set of questions that are understandable to a wide variety of people and, most importantly, to those in your sample.
In sum, in order to pose effective survey questions, researchers should do the following:
• Identify what it is they wish to know.
• Keep questions clear and succinct.
• Make questions relevant to respondents.
• Use filter questions when necessary.
• Avoid questions that are likely to confuse respondents—including those that use double negatives, use culturally specific terms or jargon, and pose more than one question at a time.
• Imagine how respondents would feel responding to questions.
• Get feedback, especially from people who resemble those in the researcher’s sample.
Response options
While posing clear and understandable questions in your survey is certainly important, so too is providing respondents with unambiguous response options. Response options are the answers that you provide to the people taking your survey. Generally, respondents will be asked to choose a single (or best) response to each question you pose, though certainly it makes sense in some cases to instruct respondents to choose multiple response options. One caution to keep in mind when accepting multiple responses to a single question, however, is that doing so may add complexity when it comes to tallying and analyzing your survey results.
Offering response options assumes that your questions will be closed-ended questions. In a quantitative written survey, which is the type of survey we’ve been discussing here, chances are good that most, if not all, your questions will be closed-ended. This means that you, the researcher, will provide respondents with a limited set of options for their responses. To write an effective closed-ended question, there are a couple of guidelines worth following. First, be sure that your response options are mutually exclusive. Look back at Figure 11.1, which contains questions about how often and how many drinks respondents consumed. Do you notice that there are no overlapping categories in the response options for these questions? This is another one of those points about question construction that seems fairly obvious but that can be easily overlooked. Response options should also be exhaustive. In other words, every possible response should be covered in the set of response options that you provide. For example, note that in question 10a in Figure 11.1, we have covered all possibilities—those who drank, say, an average of once per month can choose the first response option (“less than one time per week”) while those who drank multiple times a day each day of the week can choose the last response option (“7+”). All the possibilities in between these two extremes are covered by the middle three response options.
Surveys need not be limited to closed-ended questions. Sometimes survey researchers include open-ended questions in their survey instruments as a way to gather additional details from respondents. An open-ended question does not include response options; instead, respondents are asked to reply to the question in their own way, using their own words. These questions are generally used to find out more about a survey participant’s experiences or feelings about whatever they are being asked to report in the survey. If, for example, a survey includes closed-ended questions asking respondents to report on their involvement in extracurricular activities during college, an open-ended question could ask respondents why they participated in those activities or what they gained from their participation. While responses to such questions may also be captured using a closed-ended format, allowing participants to share some of their responses in their own words can make the experience of completing the survey more satisfying to respondents and can also reveal new motivations or explanations that had not occurred to the researcher.
Earlier in this section, we discussed double-barreled questions, but response options can also be double barreled, and this should be avoided. Figure 11.3 is an example of a question that uses double-barreled response options.
Figure 11.3 Double-barreled response options
Other things to avoid when it comes to response options include fence-sitting and floating. Fence-sitters are respondents who choose neutral response options, even if they have an opinion. This can occur if respondents are given, say, five rank-ordered response options, such as strongly agree, agree, no opinion, disagree, and strongly disagree. You’ll remember this is called a Likert scale. Some people will be drawn to respond, “no opinion” even if they have an opinion, particularly if their true opinion is the not a socially desirable opinion. Floaters, on the other hand, are those that choose a substantive answer to a question when really, they don’t understand the question or don’t have an opinion. If a respondent is only given four rank-ordered response options, such as strongly agree, agree, disagree, and strongly disagree, those who have no opinion have no choice but to select a response that suggests they have an opinion.
As you can see, floating is the flip side of fence-sitting. Thus, the solution to one problem is often the cause of the other. How you decide which approach to take depends on the goals of your research. Sometimes researchers specifically want to learn something about people who claim to have no opinion. In this case, allowing for fence-sitting would be necessary. Other times researchers feel confident their respondents will all be familiar with every topic in their survey. In this case, perhaps it is okay to force respondents to choose an opinion. There is no always-correct solution to either problem.
Finally, using a matrix is a nice way of streamlining response options. A matrix is a question type that that lists a set of questions for which the answer categories are all the same. If you have a set of questions for which the response options are the same, it may make sense to create a matrix rather than posing each question and its response options individually. Not only will this save you some space in your survey but it will also help respondents progress through your survey more easily. A sample matrix can be seen in Figure 11.4.
Figure 11.4 Survey questions utilizing matrix format
Designing questionnaires
In addition to constructing quality questions and posing clear response options, you’ll also need to think about how to present your written questions and response options to survey respondents. Questions are presented on a questionnaire, which is the document (either hard copy or online) that contains all your survey questions that respondents read and provide their responses. Designing questionnaires takes some thought.
One of the first things to do once you’ve come up with a set of survey questions you feel confident about is to group those questions thematically. In our example of the transition to college, perhaps we’d have a few questions asking about study habits, others focused on friendships, and still others on exercise and eating habits. Those may be the themes around which we organize our questions. Or perhaps it would make more sense to present any questions we had about pre-college life and then present a series of questions about life after beginning college. The point here is to be deliberate about how you present your questions to respondents.
Once you have grouped similar questions together, you’ll need to think about the order in which to present those question groups. Most survey researchers agree that it is best to begin a survey with questions that will want to make respondents continue (Babbie, 2010; Dillman, 2000; Neuman, 2003). [5] In other words, don’t bore respondents, but don’t scare them away either. There’s some disagreement over where on a survey to place demographic questions, such as those about a person’s age, gender, and race. On the one hand, placing them at the beginning of the questionnaire may lead respondents to think the survey is boring, unimportant, and not something they want to bother completing. On the other hand, if your survey deals with some very sensitive or difficult topic, such as child sexual abuse or other criminal activity, you don’t want to scare respondents away or shock them by beginning with your most intrusive questions.
In truth, the order in which you present questions on a survey is best determined by the unique characteristics of your research—only you, the researcher, hopefully in consultation with people who are willing to provide you with feedback, can determine how best to order your questions. To do so, think about the unique characteristics of your topic, your questions, and most importantly, your sample. Keeping in mind the characteristics and needs of the people you will ask to complete your survey should help guide you as you determine the most appropriate order in which to present your questions.
You’ll also need to consider the time it will take respondents to complete your questionnaire. Surveys vary in length, from just a page or two to a dozen or more pages, which means they also vary in the time it takes to complete them. How long to make your survey depends on several factors. First, what is it that you wish to know? Wanting to understand how grades vary by gender and year in school certainly requires fewer questions than wanting to know how people’s experiences in college are shaped by demographic characteristics, college attended, housing situation, family background, college major, friendship networks, and extracurricular activities. Keep in mind that even if your research question requires a sizable number of questions be included in your questionnaire, do your best to keep the questionnaire as brief as possible. Any hint that you’ve thrown in a bunch of useless questions just for the sake of it will turn off respondents and may make them not want to complete your survey.
Second, and perhaps more important, how long are respondents likely to be willing to spend completing your questionnaire? If you are studying college students, asking them to use their precious fun time away from studying to complete your survey may mean they won’t want to spend more than a few minutes on it. But if you have the endorsement of a professor who is willing to allow you to administer your survey in class, students may be willing to give you a little more time (though perhaps the professor will not). The time that survey researchers ask respondents to spend on questionnaires varies greatly. Some researchers advise that surveys should not take longer than about 15 minutes to complete (as cited in Babbie 2010), [4] whereas others suggest that up to 20 minutes is acceptable (Hopper, 2010). [5] As with question order, there is no clear-cut, always-correct answer about questionnaire length. The unique characteristics of your study and your sample should be considered to determine how long to make your questionnaire.
A good way to estimate the time it will take respondents to complete your questionnaire is through pretesting. Pretesting allows you to get feedback on your questionnaire so you can improve it before you actually administer it. Pretesting can be quite expensive and time consuming if you wish to test your questionnaire on a large sample of people who very much resemble the sample to whom you will eventually administer the finalized version of your questionnaire. But you can learn a lot and make great improvements to your questionnaire simply by pretesting with a small number of people to whom you have easy access (perhaps you have a few friends who owe you a favor). By pretesting your questionnaire, you can find out how understandable your questions are, get feedback on question wording and order, find out whether any of your questions are boring or offensive, and learn whether there are places where you should have included filter questions. You can also time pretesters as they take your survey. This will give you a good idea about the estimate to provide respondents when you administer your survey and whether you have some wiggle room to add additional items or need to cut a few items.
Perhaps this goes without saying, but your questionnaire should also have an attractive design. A messy presentation style can confuse respondents or, at the very least, annoy them. Be brief, to the point, and as clear as possible. Avoid cramming too much into a single page. Make your font size readable (at least 12 point or larger, depending on the characteristics of your sample), leave a reasonable amount of space between items, and make sure all instructions are exceptionally clear. Think about books, documents, articles, or web pages that you have read yourself—which were relatively easy to read and easy on the eyes and why? Try to mimic those features in the presentation of your survey questions.
Key Takeaways
• Brainstorming and consulting the literature are two important early steps to take when preparing to write effective survey questions.
• Make sure your survey questions will be relevant to all respondents and that you use filter questions when necessary.
• Getting feedback on your survey questions is a crucial step in the process of designing a survey.
• When it comes to creating response options, the solution to the problem of fence-sitting might cause floating, whereas the solution to the problem of floating might cause fence sitting.
• Pretesting is an important step for improving one’s survey before actually administering it.
Glossary
• Closed-ended questions- questions for which the researcher offers response options
• Double-barreled question- a question that asks two different questions at the same time, making it difficult to respond accurately
• Fence-sitters- respondents who choose neutral response options, even if they have an opinion
• Filter question- question that identifies some subset of survey respondents who are asked additional questions that are not relevant to the entire sample
• Floaters- respondents that choose a substantive answer to a question when really, they don’t understand the question or don’t have an opinion
• Matrix question- lists a set of questions for which the answer categories are all the same
• Open-ended questions- questions for which the researcher does not include response options
1. All figures in this chapter were copied from Blackstone, A. (2012) Principles of sociological inquiry: Qualitative and quantitative methods. Saylor Foundation. Retrieved from: https://saylordotorg.github.io/text_...ative-methods/ Shared under CC-BY-NC-SA 3.0 License (https://creativecommons.org/licenses/by-nc-sa/3.0/) ↵
2. See https://en.Wikipedia.org/wiki/Imaginary_audience for more information on the theory of imaginary audience. ↵
3. Babbie, E. (2010). The practice of social research (12th ed.). Belmont, CA: Wadsworth. ↵
4. All figures in this chapter were copied from Blackstone, A. (2012) Principles of sociological inquiry: Qualitative and quantitative methods. Saylor Foundation. Retrieved from: https://saylordotorg.github.io/text_...ative-methods/ Shared under CC-BY-NC-SA 3.0 License (https://creativecommons.org/licenses/by-nc-sa/3.0/) ↵
5. Babbie, E. (2010). The practice of social research (12th ed.). Belmont, CA: Wadsworth; Dillman, D. A. (2000). Mail and Internet surveys: The tailored design method (2nd ed.). New York, NY: Wiley; Neuman, W. L. (2003). Social research methods: Qualitative and quantitative approaches (5th ed.). Boston, MA: Pearson. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/11%3A_Survey_Research/11.04%3A_Designing_effective_questions_and_questionnaires.txt |
When you think of the term experiment, what comes to mind? Perhaps you thought about trying a new soda or changing your cat’s litter to a different brand. We all design informal experiments in our life. We try new things and seek to learn how those things changed us or how they compare to other things we might try. We even create entertainment programs like Mythbusters whose hosts use experimental methods to test whether common myths or bits of folk knowledge are actually true. It’s likely you’ve already developed an intuitive sense of how experiments work. The content of this chapter will increase your existing competency about using experiments to learn about the social world.
This chapter discusses or mentions the following topics: substance abuse, eating disorders, prejudice, hurricane Katrina, domestic violence, racism, poverty, and trauma.
12: Experimental Design
Learning Objectives
• Define experiment
• Identify the core features of true experimental designs
• Describe the difference between an experimental group and a control group
• Identify and describe the various types of true experimental designs
Experiments are an excellent data collection strategy for social workers wishing to observe the effects of a clinical intervention or social welfare program. Understanding what experiments are and how they are conducted is useful for all social scientists, whether they actually plan to use this methodology or simply aim to understand findings from experimental studies. An experiment is a method of data collection designed to test hypotheses under controlled conditions. Students in my research methods classes often use the term experiment to describe all kinds of research projects, but in social scientific research, the term has a unique meaning and should not be used to describe all research methodologies.
Experiments have a long and important history in social science. Behaviorists such as John Watson, B. F. Skinner, Ivan Pavlov, and Albert Bandura used experimental design to demonstrate the various types of conditioning. Using strictly controlled environments, behaviorists were able to isolate a single stimulus as the cause of measurable differences in behavior or physiological responses. The foundations of social learning theory and behavior modification are found in experimental research projects. Moreover, behaviorist experiments brought psychology and social science away from the abstract world of Freudian analysis and towards empirical inquiry, grounded in real-world observations and objectively-defined variables. Experiments are used at all levels of social work inquiry, including agency-based experiments that test therapeutic interventions and policy experiments that test new programs.
Several kinds of experimental designs exist. In general, designs considered to be true experiments contain three key features: independent and dependent variables, pretesting and posttesting, and experimental and control groups. In a true experiment, the effect of an intervention is tested by comparing two groups: one that is exposed to the intervention (the experimentalgroup, also known as the treatment group) and another that does not receive the intervention (the controlgroup).
In some cases, it may be immoral to withhold treatment from a control group within an experiment. If you recruited two groups of people with severe addiction and only provided treatment to one group, the other group would likely suffer. For these cases, researchers use a comparison group that receives “treatment as usual.” Experimenters must clearly define what treatment as usual means. For example, a standard treatment in substance abuse recovery is attending Alcoholics Anonymous or Narcotics Anonymous meetings. A substance abuse researcher conducting an experiment may use twelve-step programs in their comparison group and use their experimental intervention in the experimental group. The results would show whether the experimental intervention worked better than normal treatment, which is useful information. However, using a comparison group is a deviation from true experimental design and is more associated with quasi-experimental designs.
Importantly, participants in a true experiment need to be randomly assigned to either the control or experimental groups. Random assignment uses a random number generator or some other random process to assign people into experimental and control groups. Random assignment is important in experimental research because it helps to ensure that the experimental group and control group are comparable and that any differences between the experimental and control groups are due to random chance. We will address more of the logic behind random assignment in the next section.
In an experiment, the independent variable is the intervention being tested—for example, a therapeutic technique, prevention program, or access to some service or support. It is less common in of social work research, but social science research may also have a stimulus, rather than an intervention as the independent variable. For example, an electric shock or a reading about death might be used as a stimulus to provoke a response.
The dependent variable is usually the intended effect the researcher wants the intervention to have. If the researcher is testing a new therapy for individuals with binge eating disorder, their dependent variable may be the number of binge eating episodes a participant reports. The researcher likely expects her intervention to decrease the number of binge eating episodes reported by participants. Thus, she must measure the number of episodes that existed prior to the intervention, which is the pretest, and after the intervention, which is the posttest.
Let’s put these concepts in chronological order so we can better understand how an experiment runs from start to finish. Once you’ve collected your sample, you’ll need to randomly assign your participants to the experimental group and control group. You will then give both groups your pretest, which measures your dependent variable, to see what your participants are like before you start your intervention. Next, you will provide your intervention, or independent variable, to your experimental group. Many interventions last a few weeks or months to complete, particularly therapeutic treatments. Finally, you will administer your posttest to both groups to observer any changes in your dependent variable. Together, this is known as the classic experimental design and is the simplest type of true experimental design. All of the designs we review in this section are variations on this approach. Figure 12.1 visually represents these steps.
Figure 12.1 Steps in classic experimental design
An interesting example of experimental research can be found in Shannon K. McCoy and Brenda Major’s (2003) [1] study of peoples’ perceptions of prejudice. In one portion of this multifaceted study, all participants were given a pretest to assess their levels of depression. No significant differences in depression were found between the experimental and control groups during the pretest. Participants in the experimental group were then asked to read an article suggesting that prejudice against their own racial group is severe and pervasive, while participants in the control group were asked to read an article suggesting that prejudice against a racial group other than their own is severe and pervasive. Clearly, these were not meant to be interventions or treatments to help depression, but were stimuli designed to elicit changes in people’s depression levels. Upon measuring depression scores during the posttest period, the researchers discovered that those who had received the experimental stimulus (the article citing prejudice against their same racial group) reported greater depression than those in the control group. This is just one of many examples of social scientific experimental research.
In addition to classic experimental design, there are two other ways of designing experiments that are considered to fall within the purview of “true” experiments (Babbie, 2010; Campbell & Stanley, 1963). [2] The posttest-only control group design is almost the same as classic experimental design, except it does not use a pretest. Researchers who use posttest-only designs want to eliminate testing effects, in which a participant’s scores on a measure change because they have already been exposed to it. If you took multiple SAT or ACT practice exams before you took the real one you sent to colleges, you’ve taken advantage of testing effects to get a better score. Considering the previous example on racism and depression, participants who are given a pretest about depression before being exposed to the stimulus would likely assume that the intervention is designed to address depression. That knowledge can cause them to answer differently on the posttest than they otherwise would. Participants are not stupid. They are actively trying to figure out what your study is about.
In theory, as long as the control and experimental groups have been determined randomly and are therefore comparable, no pretest is needed. However, most researchers prefer to use pretests so they may assess change over time within both the experimental and control groups. Researchers wishing to account for testing effects but also gather pretest data can use a Solomon four-group design. In the Solomon four-group design, the researcher uses four groups. Two groups are treated as they would be in a classic experiment—pretest, experimental group intervention, and posttest. The other two groups do not receive the pretest, though one receives the intervention. All groups are given the posttest. Table 12.1 illustrates the features of each of the four groups in the Solomon four-group design. By having one set of experimental and control groups that complete the pretest (Groups 1 and 2) and another set that does not complete the pretest (Groups 3 and 4), researchers using the Solomon four-group design can account for testing effects in their analysis.
Table 12.1 Solomon four-group design
Pretest Stimulus Posttest
Group 1 X X X
Group 2 X X
Group 3 X X
Group 4 X
Solomon four-group designs are challenging to implement in the real world because they are time- and resource-intensive. Researchers must recruit enough participants to create four groups and implement interventions in two of them. Overall, true experimental designs are sometimes difficult to implement in a real-world practice environment. It may be impossible to withhold treatment from a control group or randomly assign participants in a study. In these cases, pre-experimental and quasi-experimental designs can be used. However, the differences in rigor from true experimental designs leave their conclusions more open to critique.
Key Takeaways
• True experimental designs require random assignment.
• Control groups do not receive an intervention, and experimental groups receive an intervention.
• The basic components of a true experiment include a pretest, posttest, control group, and experimental group.
• Testing effects may cause researchers to use variations on the classic experimental design.
Glossary
• Classic experimental design- uses random assignment, an experimental and control group, as well as pre- and posttesting
• Comparison group- a group in quasi-experimental designs that receives “treatment as usual” instead of no treatment
• Control group- the group in an experiment that does not receive the intervention
• Experiment- a method of data collection designed to test hypotheses under controlled conditions
• Experimental group- the group in an experiment that receives the intervention
• Posttest- a measurement taken after the intervention
• Posttest-only control group design- a type of experimental design that uses random assignment, and an experimental and control group, but does not use a pretest
• Pretest- a measurement taken prior to the intervention
• Random assignment-using a random process to assign people into experimental and control groups
• Solomon four-group design- uses random assignment, two experimental and two control groups, pretests for half of the groups, and posttests for all
• Testing effects- when a participant’s scores on a measure change because they have already been exposed to it
• True experiments- a group of experimental designs that contain independent and dependent variables, pretesting and post testing, and experimental and control groups
Image attributions
exam scientific experiment by mohamed_hassan CC-0
1. McCoy, S. K., & Major, B. (2003). Group identification moderates emotional response to perceived prejudice. Personality and Social Psychology Bulletin, 29, 1005–1017. ↵
2. Babbie, E. (2010). The practice of social research (12th ed.). Belmont, CA: Wadsworth; Campbell, D., & Stanley, J. (1963). Experimental and quasi-experimental designs for research. Chicago, IL: Rand McNally. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/12%3A_Experimental_Design/12.01%3A_Experimental_design-_What_is_it_and_when_should_it_be_used%3F.txt |
Learning Objectives
• Identify and describe the various types of quasi-experimental designs
• Distinguish true experimental designs from quasi-experimental and pre-experimental designs
• Identify and describe the various types of quasi-experimental and pre-experimental designs
As we discussed in the previous section, time, funding, and ethics may limit a researcher’s ability to conduct a true experiment. For researchers in the medical sciences and social work, conducting a true experiment could require denying needed treatment to clients, which is a clear ethical violation. Even those whose research may not involve the administration of needed medications or treatments may be limited in their ability to conduct a classic experiment. When true experiments are not possible, researchers often use quasi-experimental designs.
Quasi-experimental designs are similar to true experiments, but they lack random assignment to experimental and control groups. The most basic of these quasi-experimental designs is the nonequivalent comparison groups design (Rubin & Babbie, 2017). [1] The nonequivalent comparison group design looks a lot like the classic experimental design, except it does not use random assignment. In many cases, these groups may already exist. For example, a researcher might conduct research at two different agency sites, one of which receives the intervention and the other does not. No one was assigned to treatment or comparison groups. Those groupings existed prior to the study. While this method is more convenient for real-world research, researchers cannot be sure that the groups are comparable. Perhaps the treatment group has a characteristic that is unique–for example, higher income or different diagnoses–that make the treatment more effective.
Quasi-experiments are particularly useful in social welfare policy research. Social welfare policy researchers like me often look for what are termed natural experiments, or situations in which comparable groups are created by differences that already occur in the real world. For example, Stratmann and Wille (2016) [2] were interested in the effects of a state healthcare policy called Certificate of Need on the quality of hospitals. They clearly cannot assign states to adopt one set of policies or another. Instead, researchers used hospital referral regions, or the areas from which hospitals draw their patients, that spanned across state lines. Because the hospitals were in the same referral region, researchers could be pretty sure that the client characteristics were pretty similar. In this way, they could classify patients in experimental and comparison groups without affecting policy or telling people where to live.
There are important examples of policy experiments that use random assignment, including the Oregon Medicaid experiment. In the Oregon Medicaid experiment, the wait list for Oregon was so long, state officials conducted a lottery to see who from the wait list would receive Medicaid (Baicker et al., 2013). [3] Researchers used the lottery as a natural experiment that included random assignment. People selected to be a part of Medicaid were the experimental group and those on the wait list were in the control group. There are some practical complications with using people on a wait list as a control group—most obviously, what happens when people on the wait list are accepted into the program while you’re still collecting data? Natural experiments aren’t a specific kind of experiment like quasi- or pre-experimental designs. Instead, they are more like a feature of the social world that allows researchers to use the logic of experimental design to investigate the connection between variables.
Matching is another approach in quasi-experimental design to assigning experimental and comparison groups. Researchers should think about what variables are important in their study, particularly demographic variables or attributes that might impact their dependent variable. Individual matching involves pairing participants with similar attributes. When this is done at the beginning of an experiment, the matched pair is split—with one participant going to the experimental group and the other to the control group. An ex post facto control group, in contrast, is when a researcher matches individuals after the intervention is administered to some participants. Finally, researchers may engage in aggregate matching, in which the comparison group is determined to be similar on important variables.
There are many different quasi-experimental designs in addition to the nonequivalent comparison group design described earlier. Describing all of them is beyond the scope of this textbook, but one more design is worth mentioning. The time series design uses multiple observations before and after an intervention. In some cases, experimental and comparison groups are used. In other cases where that is not feasible, a single experimental group is used. By using multiple observations before and after the intervention, the researcher can better understand the true value of the dependent variable in each participant before the intervention starts. Additionally, multiple observations afterwards allow the researcher to see whether the intervention had lasting effects on participants. Time series designs are similar to single-subjects designs, which we will discuss in Chapter 15.
When true experiments and quasi-experiments are not possible, researchers may turn to a pre-experimental design (Campbell & Stanley, 1963). [4] Pre-experimental designs are called such because they often happen before a true experiment is conducted. Researchers want to see if their interventions will have some effect on a small group of people before they seek funding and dedicate time to conduct a true experiment. Pre-experimental designs, thus, are usually conducted as a first step towards establishing the evidence for or against an intervention. However, this type of design comes with some unique disadvantages, which we’ll describe as we review the pre-experimental designs available.
If we wished to measure the impact of a natural disaster, such as Hurricane Katrina for example, we might conduct a pre-experiment by identifying an experimental group from a community that experienced the hurricane and a control group from a similar community that had not been hit by the hurricane. This study design, called a static group comparison, has the advantage of including a comparison group that did not experience the stimulus (in this case, the hurricane). Unfortunately, it is difficult to know those groups are truly comparable because the experimental and control groups were determined by factors other than random assignment. Additionally, the design would only allow for posttests, unless one were lucky enough to be gathering the data already before Katrina. As you might have guessed from our example, static group comparisons are useful in cases where a researcher cannot control or predict whether, when, or how the stimulus is administered, as in the case of natural disasters.
In cases where the administration of the stimulus is quite costly or otherwise not possible, a one-shot case study design might be used. In this instance, no pretest is administered, nor is a control group present. In our example of the study of the impact of Hurricane Katrina, a researcher using this design would test the impact of Katrina only among a community that was hit by the hurricane and would not seek a comparison group from a community that did not experience the hurricane. Researchers using this design must be extremely cautious about making claims regarding the effect of the stimulus, though the design could be useful for exploratory studies aimed at testing one’s measures or the feasibility of further study.
Finally, if a researcher is unlikely to be able to identify a sample large enough to split into control and experimental groups, or if she simply doesn’t have access to a control group, the researcher might use a one-group pre-/posttest design. In this instance, pre- and posttests are both taken, but there is no control group to which to compare the experimental group. We might be able to study of the impact of Hurricane Katrina using this design if we’d been collecting data on the impacted communities prior to the hurricane. We could then collect similar data after the hurricane. Applying this design involves a bit of serendipity and chance. Without having collected data from impacted communities prior to the hurricane, we would be unable to employ a one- group pre-/posttest design to study Hurricane Katrina’s impact.
As implied by the preceding examples where we considered studying the impact of Hurricane Katrina, experiments do not necessarily need to take place in the controlled setting of a lab. In fact, many applied researchers rely on experiments to assess the impact and effectiveness of various programs and policies. You might recall our discussion of arresting perpetrators of domestic violence in Chapter 6, which is an excellent example of an applied experiment. Researchers did not subject participants to conditions in a lab setting; instead, they applied their stimulus (in this case, arrest) to some subjects in the field and they also had a control group in the field that did not receive the stimulus (and therefore were not arrested).
Key Takeaways
• Quasi-experimental designs do not use random assignment.
• Comparison groups are often used in quasi-experiments.
• Matching is a way of improving the comparability of experimental and comparison groups.
• Quasi-experimental designs and pre-experimental designs are often used when experimental designs are impractical.
• Quasi-experimental and pre-experimental designs may be easier to carry out, but they lack the rigor of true experiments.
Glossary
• Aggregate matching- when the comparison group is determined to be similar to the experimental group along important variables
• Ex post facto control group- a control group created when a researcher matches individuals after the intervention is administered
• Individual matching- pairing participants with similar attributes for the purpose of assignment to groups
• Natural experiments- situations in which comparable groups are created by differences that already occur in the real world
• Nonequivalent comparison group design- a quasi-experimental design similar to a classic experimental design but without random assignment
• One-group pre-/posttest design- a pre-experimental design that applies an intervention to one group but also includes a pretest
• One-shot case study- a pre-experimental design that applies an intervention to only one group without a pretest
• Pre-experimental designs- a variation of experimental design that lacks the rigor of experiments and is often used before a true experiment is conducted
• Quasi-experimental design- designs lack random assignment to experimental and control groups
• Static group design- uses an experimental group and a comparison group, without random assignment and pretesting
• Time series design- a quasi-experimental design that uses multiple observations before and after an intervention
Image attributions
1. Rubin, C. & Babbie, S. (2017). Research methods for social work (9th edition). Boston, MA: Cengage. ↵
2. Stratmann, T. & Wille, D. (2016). Certificate-of-need laws and hospital quality. Mercatus Center at George Mason University, Arlington, VA. Retrieved from: https://www.mercatus.org/system/files/mercatus-stratmann-wille-con-hospital-quality-v1.pdf
3. Baicker, K., Taubman, S. L., Allen, H. L., Bernstein, M., Gruber, J. H., Newhouse, J. P., ... & Finkelstein, A. N. (2013). The Oregon experiment—effects of Medicaid on clinical outcomes. New England Journal of Medicine, 368(18), 1713-1722. ↵
4. Campbell, D., & Stanley, J. (1963). Experimental and quasi-experimental designs for research. Chicago, IL: Rand McNally. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/12%3A_Experimental_Design/12.02%3A_Pre-experimental_and_quasi-experimental_design.txt |
Learning Objectives
• Apply the criteria of causality to experimental design
• Define internal validity and external validity
• Identify threats to validity
As we discussed at the beginning of this chapter, experimental design is commonly understood and implemented informally in everyday life. Trying out a new restaurant, dating a new person—we often term these experiments. As you’ve learned over the past two sections, in order for something to be a true experiment, or even a quasi- or pre-experiment, you must rigorously apply the various components of experimental design. A true experiment for trying a new restaurant would include recruitment of a large enough sample, random assignment to control and experimental groups, pretesting and posttesting, as well as using clearly and objectively defined measures of satisfaction with the restaurant.
Social scientists use this level of rigor and control because they try to maximize the internal validity of their experiment. Internal validity is the confidence researchers have about whether their intervention produced variation in their dependent variable. Thus, experiments are attempts to establish causality between two variables—your treatment and its intended outcome. As we talked about in Chapter 7, nomothetic causal relationships must establish four criteria: covariation, plausibility, temporality, and nonspuriousness.
The logic and rigor experimental design allows for causal relationships to be established. Experimenters can assess covariation on the dependent variable through pre- and posttests. The use of experimental and control conditions ensures that some people receive the intervention and others do not, providing variation in the independent variable. Moreover, since the researcher controls when the intervention is administered, she can be assured that changes in the independent variable (the treatment) happened before changes the dependent variable (the outcome). In this way, experiments assure temporality. In our restaurant experiment, we would know through assignment experimental and control groups that people varied in the restaurant they attended. We would also know whether their level of satisfaction changed, as measured by the pre- and posttest. We would also know that changes in our diners’ satisfaction occurred after they left the restaurant, not before they walked in because of the pre- and posttest.
Experimenters will also have a plausible reason why their intervention would cause changes in the dependent variable. Usually, a theory or previous empirical evidence should indicate the potential for a causal relationship. Perhaps we found a national poll that found the type of food our experimental restaurant served, let’s say pizza, is the most popular food in America. Perhaps this restaurant has good reviews on Yelp or Google. This evidence would give us a plausible reason to establish our restaurant as causing satisfaction.
While you may not need a clean suit like these scientists, you need to similarly control for threats to the validity of your experiment.
One of the most important features of experiments is that they allow researchers to eliminate spurious variables. True experiments are usually conducted under strictly controlled laboratory conditions. The intervention must be given in the same way to each person, with a minimal number of other variables that might cause their posttest scores to change. In our restaurant example, this level of control might prove difficult. We cannot control how many people are waiting for a table, whether participants saw someone famous there, or if there is bad weather. Any of these factors might cause a diner to be less satisfied with their meal. These spurious variables may cause changes in satisfaction that have nothing to do with the restaurant itself, an important problem in real-world research. For this reason, experiments use the laboratory environment try to control as many aspects of the research process as possible. Researchers in large experiments often employ clinicians or other research staff to help them. Researchers train their staff members exhaustively, provide pre-scripted responses to common questions, and control the physical environment of the lab so each person who participates receives the exact same treatment.
Experimental researchers also document their procedures, so that others can review how well they controlled for spurious variables. My favorite example of this concept is Bruce Alexander’s Rat Park (1981) experiments because it spoke directly to my practice as a substance abuse and mental health social worker. [1] Much of the early research conducted on addictive drugs, like heroin and cocaine, was conducted on animals other than humans, usually mice or rats. While this may seem strange, the systems of our mammalian relatives are similar enough to humans that causal inferences can be made from animal studies to human studies. It is certainly unethical to deliberately cause humans to become addicted to cocaine and measure them for weeks in a laboratory, but it is currently more ethically acceptable to do so with animals. There are specific ethical processes for animal research, similar to an IRB review.
The scientific consensus up until Alexander’s experiments was that cocaine and heroin were so addictive that rats, if offered the drugs, would consume them repeatedly until they perished. Researchers claimed this behavior explained how addiction worked in humans, but Alexander was not so sure. He knew rats were social animals and the experimental procedure from previous experiments did not allow them to socialize. Instead, rats were kept isolated in small cages with only food, water, and metal walls. To Alexander, social isolation was a spurious variable, causing changes in addictive behavior not due to the drug itself. Alexander created an experiment of his own, in which rats were allowed to run freely in an interesting environment, socialize and mate with other rats, and of course, drink from a solution that contained an addictive drug. In this environment, rats did not become hopelessly addicted to drugs. In fact, they had little interest in the substance.
To Alexander, the results of his experiment demonstrated that social isolation was more of a causal factor for addiction than the drug itself. This makes intuitive sense to me. If I were in solitary confinement cell for most of my life, the escape of an addictive drug would seem more tempting than if I were in my natural environment with friends, family, and activities. One challenge with Alexander’s findings is that subsequent researchers have had mixed success replicating his findings (e.g., Petrie, 1996; Solinas, Thiriet, El Rawas, Lardeux, & Jaber, 2009). [2] Replication involves conducting another researcher’s experiment in the same manner and seeing if it produces the same results. If the causal relationship is real, it should occur in all (or at least most) replications of the experiment.
One of the defining features of experiments is that they report their procedures diligently, which allows for easier replication. Recently, researchers at the Reproducibility Project have caused a significant controversy in social science fields like psychology (Open Science Collaboration, 2015). [3] In one study, researchers attempted reproduce the results of 100 experiments published in major psychology journals between 2008 and the present. What they found was shocking. The results of only 36% of the studies were reproducible. Despite coordinating closely with the original researchers, the Reproducibility Project found that nearly two-thirds of psychology experiments published in respected journals were not reproducible. The implications of the Reproducibility Project are staggering, and social scientists are coming up with new ways to ensure researchers do not cherry-pick data or change their hypotheses, simply to get published.
Returning to Alexander’s Rat Park study, consider what the implications of his experiment were to a substance abuse professional such as myself. The conclusions he drew from his experiments on rats were meant to generalize to the population of people with substance use disorders with whom I worked. Experiments seek to establish external validity, which is the degree to which their conclusions generalize to larger populations and different situations. Alexander argues his conclusions about addiction and social isolation help us understand why people living in deprived, isolated environments will often become addicted to drugs more often than those in more enriching environments. Similarly, earlier rat researchers argued their results showed these drugs were instantly addictive, often to the point of death.
Neither study will match up perfectly with real life. I met in my practice many individuals who may have fit into Alexander’s social isolation model, but social isolations for humans is complex. My clients lived in environments with other sociable humans, worked jobs, and had romantic relationships, so how isolated were they? On the other hand, many faced structural racism, poverty, trauma, and other challenges that may contribute to social isolation. Alexander’s work helped me understand part of my clients’ experiences, but the explanation was incomplete. The real world was much more complicated than the experimental conditions in Rat Park, just as humans are more complex than rats.
Social workers are especially attentive to how social context shapes social life. So, we are likely to point out a specific disadvantage of experiments. They are rather artificial. How often do real-world social interactions occur in the same way that they do in a lab? Experiments that are conducted in community settings may not be as subject to artificiality, though then their conditions are less easily controlled. This relationship demonstrates the tension between internal and external validity. The more researchers tightly control the environment to ensure internal validity, the less they can claim external validity and that their results are applicable to different populations and circumstances. Correspondingly, researchers whose settings are just like the real world will be less able to ensure internal validity, as there are many factors that could pollute the research process. This is not to suggest that experimental research cannot have external validity, but experimental researchers must always be aware that external validity problems can occur and be forthcoming in their reports of findings about this potential weakness.
Threats to validity
Internal validity and external validity are conceptually linked. Internal validity refers to the degree to which the intervention causes its intended outcomes, and external validity refers to how well that relationship applies to different groups and circumstances. There are a number of factors that may influence a study’s validity. You might consider these threats to all be spurious variables, as we discussed at the beginning of this section. Each threat proposes another factor that is changing the relationship between intervention and outcome. The threats introduce error and bias into the experiment.
Throughout this chapter, we reviewed the importance of experimental and control groups. These groups must be comparable in order for experimental design to work. Comparable groups are groups that are similar across factors important for the study. Researchers can help establish comparable groups by using probability sampling, random assignment, or matching techniques. Control or comparison groups provide a counterfactual—what would have happened to my experimental group had I not given them my intervention? Two very different groups would not allow you to answer that question. Intuitively, we all know that no two people are exactly the same. So, no groups are ever perfectly comparable. What’s important is ensuring groups are comparable along the variables relevant to the research project.
In our restaurant example, if one of my groups had far more vegetarians or people with gluten issues, it might influence how satisfied they were with my restaurant. My groups, in that case, would not be comparable. Researchers also account for this by measuring other variables, like dietary preference, and controlling for their effects statistically, after the data are collected. We discussed control variables like these in Chapter 7. Similarly, if I were to pick out people I thought would “really like” my restaurant and assign them to the experimental group, I would be introducing selection bias into my sample. This is another reason experimenters use random assignment, so conscious and unconscious bias do not influence to which group a participant is assigned.
Experimenters themselves are often the source of threats to validity. They may choose measures that do not accurately measure participants or implement the measure in a way that biases participant responses in one direction or another. Researchers may, just by the very act of conducting an experiment, influence participants to perform differently. Experiments are different from participants’ normal routines. The novelty of a research environment or experimental treatment may cause them to expect to feel differently, independently of the actual intervention. You have likely heard of the placebo effect, in which a participant feels better, despite having received no intervention at all.
Researchers may also introduce error by expecting participants in each group to behave differently. For the experimental group, researchers may expect them to feel better and may give off conscious or unconscious cues to participants that influence their outcomes. Control groups will be expected to fare worse, and research staff could cue participants that they should feel worse than they otherwise would. For this reason, researchers often use double-blind designs wherein research staff interacting with participants are unaware of who is in the control or experimental group. Proper training and supervision are also necessary to account for these and other threats to validity. If proper supervision is not applied, research staff administering the control group may try to equalize treatment or engage in a rivalry with research staff administering the experimental group (Engel & Schutt, 2016). [4]
No matter how tightly the researcher controls the experiment, participants are humans and are therefore curious, problem-solving creatures. Participants who learn they are in the control group may react by trying to outperform the experimental group or by becoming demoralized. In either case, their outcomes in the study would be different had they been unaware of their group assignment. Participants in the experimental group may begin to behave differently or share insights from the intervention with individuals in the control group. Whether through social learning or conversation, participants in the control group may receive parts of the intervention of which they were supposed to be unaware. Experimenters, as a result, try to keep experimental and control groups as separate as possible. Inside a laboratory study, this is significantly easier as the researchers control access and timing at the facility. In agency-based research, this problem is more complicated. If your intervention is good, your participants in the experimental group may impact the control group by behaving differently and sharing the insights they’ve learned with their peers. Agency-based researchers may locate experimental and control conditions at separate offices with separate treatment staff to minimize the interaction between their participants.
Key Takeaways
• Experimental design provides researchers with the ability to best establish causality between their variables.
• Experiments provide strong internal validity but may have trouble achieving external validity.
• Experimental deigns should be reproducible by future researchers.
• Threats to validity come from both experimenter and participant reactivity.
Glossary
• Comparable groups- groups that are similar across factors important for the study
• Double-blind- when researchers interact with participants are unaware of who is in the control or experimental group
• External validity- the degree to which experimental conclusions generalize to larger populations and different situations
• Internal validity- the confidence researchers have about whether their intervention produced variation in their dependent variable
• Placebo effect- when a participant feels better, despite having received no intervention at all
• Replication- conducting another researcher’s experiment in the same manner and seeing if it produces the same results
• Selection bias- when a researcher consciously or unconsciously influences assignment into experimental and control groups
Image attributions
One of Juno’s solar panels before illumination test by NASA/Jack Pfaller public domain
mistake by Tumisu CC-0
1. Alexander, B. (2010). Addiction: The view from rat park. Retrieved from: http://www.brucekalexander.com/articles-speeches/rat-park/148-addiction-the-view-from-rat-park
2. Petrie, B. F. (1996). Environment is not the most important variable in determining oral morphine consumption in Wistar rats. Psychological reports, 78(2), 391-400.; Solinas, M., Thiriet, N., El Rawas, R., Lardeux, V., & Jaber, M. (2009). Environmental enrichment during early stages of life reduces the behavioral, neurochemical, and molecular effects of cocaine. Neuropsychopharmacology, 34(5), 1102. ↵
3. Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349(6251), aac4716. ↵
4. Engel, R. J. & Schutt, R. K. (2016). The practice of research in social work (4th ed.). Washington, DC: SAGE Publishing. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/12%3A_Experimental_Design/12.03%3A_The_logic_of_experimental_design.txt |
Learning Objectives
• Define response rate, and discuss some of the current thinking about response rates
• Describe what a codebook is and what purpose it serves
• Define univariate, bivariate, and multivariate analysis
• Identify and apply each of the measures of central tendency
• Describe what a contingency table displays
This textbook is primarily focused on designing research, collecting data, and becoming a knowledgeable and responsible consumer of research. We won’t spend as much time on data analysis or what to do with our data once we’ve designed a study and collected it, but I will spend some time describing some important basics of data analysis that are unique to each method. Entire textbooks could be (and have been) written entirely on data analysis. In fact, if you’ve ever taken a statistics class, you already know much about how to analyze quantitative survey data. Here we’ll go over a few basics that can get you started as you begin to think about turning data from surveys and experiences into findings that you can share.
Who responds to your questionnaire?
It can be very exciting to receive those first few completed questionnaires back from respondents. Hopefully you’ll even get more than a few back, and once you have a handful of completed questionnaires, your feelings may go from initial euphoria to dread. Data are fun and can also be overwhelming. The goal with data analysis is to be able to condense large amounts of information into usable and understandable chunks.
In an experiment, as long as no one drops out, you can be assured that everyone in your sample will complete your questionnaires as part of their pretest and posttest. For surveys, it is much less likely that everyone will complete your questionnaire. The hope is that you will receive a good portion of the questionnaires you distributed back in a completed and readable format. The number of completed questionnaires you receive divided by the number of questionnaires you distributed is your response rate. Let’s say your sample included 100 people and you sent questionnaires to each of those people. It would be wonderful if all 100 returned completed questionnaires, but the chances of that happening are about zero. If you’re lucky, perhaps 75 or so will return completed questionnaires. In this case, your response rate would be 75%. The response rate is calculated by dividing the number of surveys returned by the number of surveys distributed.
Though response rates vary, and researchers don’t always agree about what makes a good response rate, having 75% of your surveys returned would be considered good—even excellent—by most survey researchers. There has been a lot of research done on how to improve a survey’s response rate. We covered some of these previously, but suggestions include personalizing questionnaires by, for example, addressing them to specific respondents rather than to some generic recipient, such as “madam” or “sir”; enhancing the questionnaire’s credibility by providing details about the study, contact information for the researcher, and perhaps partnering with agencies likely to be respected by respondents such as universities, hospitals, or other relevant organizations; sending out pre-questionnaire notices and post-questionnaire reminders; and including some token of appreciation with mailed questionnaires even if small, such as a \$1 bill.
The major concern with response rates is that a low rate of response may introduce nonresponse bias into a study’s findings. What if only those who have strong opinions about your study topic return their questionnaires? If that is the case, we may well find that our findings don’t at all represent how things really are or, at the very least, we are limited in the claims we can make about patterns found in our data. While high return rates are certainly ideal, a recent body of research shows that concern over response rates may be overblown (Langer, 2003). [1] Several studies have shown that low response rates did not make much difference in findings or in sample representativeness (Curtin, Presser, & Singer, 2000; Keeter, Kennedy, Dimock, Best, & Craighill, 2006; Merkle & Edelman, 2002). [2] For now, the jury may still be out on what makes an ideal response rate and on whether, or to what extent, researchers should be concerned about response rates. Nevertheless, certainly no harm can come from aiming for as high a response rate as possible.
Building a codebook
Regardless of your response rate, a major concern of quantitative researchers once they have their big stack of completed questionnaires is condensing their data into manageable and analyzable, bits. One major advantage of quantitative methods such as surveys and experiments, as you may recall from Chapter 1, is that they enable researchers to describe large amounts of data because they can be represented by and condensed into numbers.
In order to condense your completed surveys into analyzable numbers, you’ll first need to create a codebook. A codebook is a document that outlines how a survey researcher has translated her data from words into numbers. An excerpt from a codebook can be seen in Table 12.2. As you’ll see in the table, in addition to converting response options into numerical values, a short variable name is given to each question. This shortened name comes in handy when entering data into a computer program for analysis.
Table 12.2 Codebook excerpt from survey of older workers
Variable # Variable Name Question Options
11 FINSEC In general, how financially secure would you say you are? 1 = Not at all secure
2 = Between not at all and moderately secure
3 = Moderately secure
4 = Between moderately secure and very secure
5 = Very secure
12 FINFAM Since age 62, have you ever received money from family members or friends to help make ends meet? 0 = No
1 = Yes
13 FINFAMT If yes, how many times? 1 = 1 or 2 times
2 = 3 or 4 times
3 = 5 times or more
14 FINCHUR Since age 62, have you ever received money from a church or other organization to help make ends meet? 0 = No
1 = Yes
15 FINCHURT If yes, how many times? 1 = 1 or 2 times
2 = 3 or 4 times
3 = 5 times or more
16 FINGVCH Since age 62, have you ever donated money to a church or other organization? 0 = No
1 = Yes
17 FINGVFAM Since age 62, have you ever given money to a family member or friend to help them make ends meet? 0 = No
1 = Yes
The next task after creating your codebook is data entry. If you’ve utilized an online tool such as SurveyMonkey to administer your questionnaire, here’s some good news—most online survey tools come with the capability of importing survey results directly into a data analysis program. Trust me—this is excellent news. (If you don’t believe me, I highly recommend administering hard copies of your questionnaire next time around. You’ll surely then appreciate the wonders of online survey administration!)
For those who will be conducting manual data entry, there probably isn’t much I can say about this task that will make you want to perform it other than pointing out the reward of having a data set of your very own ready to analyze. At best, it is a Zen-like practice akin to raking sand. At worst, it is mind-numbingly boring. While you can pay someone else to do your data entry for you, a common practice with undergraduate and graduate research assistants, you should ask yourself whether you trust someone else to make no errors in entering your data. If errors are made in data entry, it can jeopardize the results of your project. You may want to consider whether it is worth your time and effort to do your data entry yourself.
We won’t get into too many of the details of data entry, but I will mention a few programs that survey researchers may use to analyze data once it has been entered. The first is SPSS or the Statistical Package for the Social Sciences (http://www.spss.com). SPSS is a statistical analysis computer program designed to analyze just the sort of data quantitative survey researchers collect. It can perform everything from very basic descriptive statistical analysis to more complex inferential statistical analysis. SPSS is touted by many for being highly accessible and relatively easy to navigate (with practice). Other programs that are known for their accessibility include MicroCase (www.microcase.com/index.html), which includes many of the same features as SPSS, and Excel, which is far less sophisticated in its statistical capabilities but is relatively easy to use and suits some researchers’ purposes just fine.
Identifying patterns
Data analysis is about identifying, describing, and explaining patterns. Univariate analysis is the most basic form of analysis that quantitative researchers conduct. In this form, researchers describe patterns across just one variable. Univariate analysis includes frequency distributions and measures of central tendency. A frequency distribution is a way of summarizing the distribution of responses on a single survey question. Let’s look at the frequency distribution for just one variable from a survey of older workers. We’ll analyze the item mentioned first in the codebook excerpt given earlier, which is on respondents’ self-reported financial security.
Table 12.3 Frequency distribution of older workers’ financial security
In general, how financially secure would you say you are? Value Frequency Percentage
Not at all secure 1 46 25.6
Between not at all and moderately secure 2 43 23.9
Moderately secure 3 76 42.2
Between moderately and very secure 4 11 6.1
Very secure 5 4 2.2
Total valid cases = 180; no response = 3
As you can see in the frequency distribution on self-reported financial security, more respondents reported feeling “moderately secure” than any other response category. We also learn from this single frequency distribution that fewer than 10% of respondents reported being in one of the two most secure categories.
Another form of univariate analysis that survey researchers can conduct on single variables is measures of central tendency. Measures of central tendency can be taken for variables at any level of measurement we reviewed in Chapter 9—from nominal to ratio. There are three measures of central tendency: modes, medians, and means. Mode refers to the most common response given to a question. Modes are most appropriate for nominal-level variables. A median is the middle point in a distribution of responses. In the previous example, if you wrote out all 180 responses to the question, side by side, from smallest to largest (1,1,1….5,5,5), the median would be the middle number. Finally, the measure of central tendency used for interval- and ratio-level variables is the mean. More commonly known as an average, means can be obtained by adding the value of all responses on a given variable and then dividing that number of the total number of responses.
Median is the appropriate measure of central tendency for ordinal-level variables, though it is sometimes used for interval or ratio variables whose distribution contains outliers or extreme scores that would skew the mean higher than the true center of the distribution. For example, if you asked your four friends about how much money they have in their wallets and one of them just won the lottery, the mean would be quite high, even though most of you do not have near that amount. The median value would be closer to the true center, in this case, than the mean.
In the previous example of older workers’ self-reported levels of financial security, the appropriate measure of central tendency would be the median, as this is an ordinal-level variable. If we were to list all responses to the financial security question in order and then choose the middle point in that list, we’d have our median.
In Figure 12.2, the value of each response to the financial security question is noted, and the middle point within that range of responses is highlighted. To find the middle point, we simply divide the number of valid cases by two. The number of valid cases, 180, divided by 2 is 90, so we’re looking for the 90th value on our distribution to discover the median. As you’ll see in Figure 12.2, that value is 3; thus, the median on our financial security question is 3 or “moderately secure.”
Figure 12.2 Distribution of responses and median value on workers’ financial security
As you can see, we can learn a lot about our respondents simply by conducting univariate analysis of measures on our survey. We can learn even more, of course, when we begin to examine relationships across multiple variables. Either we can analyze the relationships between two variables, called bivariate analysis, or we can examine relationships among more than two variables. This latter type of analysis is known as multivariate analysis.
Bivariate analysis allows us to assess covariation among two variables. We reviewed covariation in Chapter 7. This means we can find out whether changes in one variable occur together with changes in another. If two variables do not covary, they are said to have independence. This means simply that there is no relationship between the two variables in question. To learn whether a relationship exists between two variables, a researcher may cross-tabulate the two variables and present their relationship in a contingency table. A contingency table shows how variation on one variable may be contingent on variation on the other.
Let’s take a look at a contingency table. In Table 12.4, I have cross-tabulated two questions from an older worker survey: respondents’ reported gender and their self-rated financial security.
Table 12.4 Financial security among men and women workers age 62 and up
Men Women
Not financially secure (%) 44.1 51.8
Moderately financially secure (%) 48.9 39.2
Financially secure (%) 7.0 9.0
Total N = 43 N = 135
You’ll see in Table 12.4 that I collapsed a couple of the financial security response categories (recall there were five categories presented in Table 12.3). Researchers sometimes collapse response categories on items such as this in order to make it easier to read results in a table. You’ll also see that I placed the variable “gender” in the table’s columns and “financial security” in its rows. Typically, values that are contingent on other values (dependent variables) are placed in rows, while independent variables are placed in columns. This makes comparing across categories of ourindependentvariableprettysimple.
Reading across the top row of our table, we can see that around 44% of men in the sample reported that they are not financially secure while almost 52% of women reported the same. In other words, more women than men reported they are not financially secure. You’ll also see in the table that I reported the total number of respondents for each category of the independent variable in the table’s bottom row. This is also standard practice in a bivariate table, as is including a table heading describing what is presented in the table.
Researchers interested in simultaneously analyzing relationships among more than two variables conduct multivariate analysis. If I hypothesized that financial security declines for women as they age but increases for men as they age, I might consider adding age to the preceding analysis. To do so would require multivariate, rather than bivariate, analysis. This is common in studies with multiple independent or dependent variables. It is also necessary for studies that include control variables, which almost all studies do. We won’t go into detail here about how to conduct multivariate analysis of quantitative survey items here. If you are interested in learning more about the analysis of quantitative survey data, I recommend checking out your campus’s offerings in statistics classes. The quantitative data analysis skills you will gain in a statistics class could serve you quite well should you find yourself seeking employment one day.
Key Takeaways
• While survey researchers should always aim to obtain the highest response rate possible, some recent research argues that high return rates on surveys may be less important than we once thought.
• There are several computer programs designed to assist quantitative researchers with analyzing their data include SPSS, MicroCase, and Excel.
• Data analysis is about identifying, describing, and explaining patterns.
• Contingency tables show how, or whether, one variable covaries with another.
Glossary
• Bivariate analysis- quantitative analysis that examines relationships among two variables
• Codebook- a document that outlines how a survey researcher has translated her data from words into numbers
• Contingency table- shows how variation on one variable may be contingent on variation on the other
• Frequency distribution- summarizes the distribution of responses on a single survey question
• Independence- there is no relationship between the two variables in question
• Mean- also known as the average, this is the sum of the value of all responses on a given variable divided by the total number of responses
• Median- the value that lies in the middle of a distribution of responses
• Mode- the most common response given to a question
• Multivariate analysis- quantitative analysis that examines relationships among more than two variables
• Nonresponse bias- bias reflected differences between people who respond to your survey and those who do not respond
• Response rate- the number of people who respond to your survey divided by the number of people to whom the survey was distributed
• Univariate analysis- quantitative analysis that describes patterns across just one variable
Image attributions
website by JuralMin CC-0
1. Langer, G. (2003). About response rates: Some unresolved questions. Public Perspective, May/June, 16–18. Retrieved from: https://www.aapor.org/AAPOR_Main/media/MainSiteFiles/Response_Rates_-_Langer.pdf
2. Curtin, R., Presser, S., & Singer, E. (2000). The effects of response rate changes on the index of consumer sentiment. Public Opinion Quarterly, 64, 413–428; Keeter, S., Kennedy, C., Dimock, M., Best, J., & Craighill, P. (2006). Gauging the impact of growing nonresponse on estimates from a national RDD telephone survey. Public Opinion Quarterly, 70, 759–779; Merkle, D. M., & Edelman, M. (2002). Nonresponse in exit polls: A comprehensive analysis. In M. Groves, D. A. Dillman, J. L. Eltinge, & R. J. A. Little (Eds.), Survey nonresponse (pp. 243–258). New York, NY: John Wiley and Sons. ↵
3. Figure 12.2 copied from Blackstone, A. (2012). Principles of sociological inquiry: Qualitative and quantitative methods. Saylor Foundation. Retrieved from: https://saylordotorg.github.io/text_...ative-methods/ Shared under CC-BY-NC-SA 3.0 License (https://creativecommons.org/licenses/by-nc-sa/3.0/) ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/12%3A_Experimental_Design/12.04%3A_Analyzing_quantitative_data.txt |
What is it like to be a young man entering adulthood? According to sociologist Michael Kimmel, they are “totally confused”; “cannot commit to their relationships, work, or lives”; and are “obsessed with never wanting to grow up.” [1] If that sounds like a bunch of malarkey to you, hold on a minute. Kimmel interviewed 400 young men, ages 16 to 26, over the course of four years across the United States to learn how young men made the transition from adolescence into adulthood. Since the results of Kimmel’s research were published in 2008, [2] his book Guyland made quite a splash. Whatever your take on Kimmel’s research, one thing remains true—we surely would not know nearly as much as we now do about the lives of many young American men were it not for interview research.
This chapter discusses or mentions the following topics: childfree adults, sexual harassment, juvenile delinquency, drunk driving, racist hate groups, ageism, sexism, and police interviews.
1. These quotes come from a summary of reviews on the website dedicated to Kimmel’s book, Guyland: www.guyland.net. ↵
2. Kimmel, M. (2008). Guyland: The perilous world where boys become men. New York, NY: Harper Collins. ↵
13: Interviews and Focus Groups
Learning Objectives
• Define interviews from the social scientific perspective
• Identify when it is appropriate to employ interviews as a data-collection strategy
Knowing how to create and conduct a good interview is an essential skill. Interviews are used by market researchers to learn how to sell their products, and journalists use interviews to get information from a whole host of people from VIPs to random people on the street. Police use interviews to investigate crimes. It seems everyone who’s anyone knows how to conduct an interview.
In social science, interviews are a method of data collection that involves two or more people exchanging information through a series of questions and answers. The questions are designed by a researcher to elicit information from interview participants on a specific topic or set of topics. These topics are informed by the author’s research questions. Typically, interviews involve an in-person meeting between two people—an interviewer and an interviewee– but interviews need not be limited to two people, nor must they occur in-person.
The question of when to conduct an interview might be on your mind. Interviews are an excellent way to gather detailed information. They also have an advantage over surveys—they can change as you learn more information. In a survey, you cannot change what questions you ask if a participant’s response sparks some follow-up question in your mind. All participants must get the same questions. The questions you decided to put on your survey during the design stage determine what data you get. In an interview, however, you can follow up on new and unexpected topics that emerge during the conversation. Trusting in emergence and learning from your participants are hallmarks of qualitative research. In this way, interviews are a useful method to use when you want to know the story behind responses you might receive in a written survey.
Interviews are also useful when the topic you are studying is rather complex, requires lengthy explanation, or needs a dialogue between two people to thoroughly investigate. Also, if people will describe the process by which a phenomenon occurs, like how a person makes a decision, then interviews may be the best method for you. For example, you could use interviews to gather data about how people reach the decision not to have children and how others in their lives have responded to that decision. To understand these “how’s” you would need to have some back-and-forth dialogue with respondents. When they begin to tell you their story, inevitably new questions that hadn’t occurred to you from prior interviews would come up because each person’s story is unique. Also, because the process of choosing not to have children is complex for many people, describing that process by responding to closed-ended questions on a survey wouldn’t work particularly well.
In sum, interview research is especially useful when the following are true:
• You wish to gather very detailed information
• You anticipate wanting to ask respondents follow-up questions based on their responses
• You plan to ask questions that require lengthy explanation
• You are studying a complex or potentially confusing topic to respondents
• You are studying processes, such as how people make decisions
Key Takeaways
• Understanding how to design and conduct interview research is a useful skill to have.
• In a social scientific interview, two or more people exchange information through a series of questions and answers.
• Interview research is often used when detailed information is required and when a researcher wishes to examine processes.
Glossary
• Interviews- a method of data collection that involves two or more people exchanging information through a series of questions and answers
Image attributions
interview restaurant a pair by alda2 CC-0 | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/13%3A_Interviews_and_Focus_Groups/13.01%3A_Interview_research-_What_is_it_and_when_should_it_be_used%3F.txt |
Learning Objectives
• Identify the primary aim of in-depth interviews
• Describe what makes qualitative interview techniques unique
• Define the term interview guide and describe how to construct an interview guide
• Outline the guidelines for constructing good qualitative interview questions
• Describe how writing field notes and journaling function in qualitative research
• Identify the strengths and weaknesses of interviews
Qualitative interviews are sometimes called intensive or in-depth interviews. These interviews are semi-structured; the researcher has a particular topic about which she would like to hear from the respondent, but questions are open-ended and may not be asked in exactly the same way or in exactly the same order to each and every respondent. For in-depth interviews, the primary aim is to hear from respondents about what they think is important about the topic at hand and to hear it in their own words. In this section, we’ll take a look at how to conduct qualitative interviews, analyze interview data, and identify some of the strengths and weaknesses of this method.
Constructing an interview guide
Qualitative interviews might feel more like a conversation than an interview to respondents, but the researcher is in fact usually guiding the conversation with the goal in mind of gathering information from a respondent. Qualitative interviews use open-ended questions, which are questions that a researcher poses but does not provide answer options for. Open-ended questions are more demanding of participants than closed-ended questions for they require participants to come up with their own words, phrases, or sentences to respond.
In a qualitative interview, the researcher usually develops a guide in advance that she then refers to during the interview (or memorizes in advance of the interview). An interview guide is a list of topics or questions that the interviewer hopes to cover during the course of an interview. It is called a guide because it is simply that—it is used to guide the interviewer, but it is not set in stone. Think of an interview guide like your agenda for the day or your to-do list—both probably contain all the items you hope to check off or accomplish, though it probably won’t be the end of the world if you don’t accomplish everything on the list or if you don’t accomplish it in the exact order that you have it written down. Perhaps new events will come up that cause you to rearrange your schedule just a bit, or perhaps you simply won’t get to everything on the list.
Interview guides should outline issues that a researcher feels are likely to be important. Because participants are asked to provide answers in their own words and to raise points they believe are important, each interview is likely to flow a little differently. While the opening question in an in-depth interview may be the same across all interviews, from that point on, what the participant says will shape how the interview proceeds. This, I believe, is what makes in-depth interviewing so exciting–and rather challenging. It takes a skilled interviewer to be able to ask questions; listen to respondents; and pick up on cues about when to follow up, when to move on, and when to simply let the participant speak without guidance or interruption.
I’ve said that interview guides can list topics or questions. The specific format of an interview guide might depend on your style, experience, and comfort level as an interviewer or with your topic. Figure 13.1 provides an example of an interview guide for a study of how young people experience workplace sexual harassment. The guide is topic-based, rather than a list of specific questions. The ordering of the topics is important, though how each comes up during the interview may vary.
Figure 13.1 Interview guide displaying topics rather than questions
In my interviews with state administrators of developmental disabilities departments, the interview guide contained 15 questions all of which were asked to each participant. Sometimes, participants would cover the answer to one question before it was read. When I came to that question later on in the interview, I would acknowledge that they already addressed part of this question and ask them if they had anything to add to their response. Underneath some of the questions were more specific words or phrases for follow-up in case the participant did not mention those topics in their responses. These probes, as well as the questions, were based on our review of their department’s documentation about their programs. Our study was a challenging one in that administrators may have thought that since we were studying a particular kind of program, we may have an agenda to try and convince administrators to expand or better fund that program. We had to be very objective in how we worded questions to avoid the appearance of bias. Some of these questions are depicted in Figure 13.2.
Figure 13.2 Interview guide displaying questions rather than topics
As you might have guessed, interview guides do not appear out of thin air. They are the result of thoughtful and careful work on the part of a researcher. As you can see in both of the preceding guides, the topics and questions have been organized thematically and in the order in which they are likely to proceed (though keep in mind that the flow of a qualitative interview is in part determined by what a respondent has to say). Sometimes qualitative interviewers may create two versions of the interview guide: one version contains a very brief outline of the interview, perhaps with just topic headings, and another version contains detailed questions underneath each topic heading. In this case, the researcher might use the very detailed guide to prepare and practice in advance of actually conducting interviews and then just bring the brief outline to the interview. Bringing an outline, as opposed to a very long list of detailed questions, to an interview encourages the researcher to actually listen to what a participant is telling her. An overly detailed interview guide will be difficult to navigate during an interview and could give respondents the misimpression the interviewer is more interested in her questions than in the participant’s answers.
When beginning to construct an interview guide, brainstorming is usually the first step. There are no rules at the brainstorming stage—simply list all the topics and questions that come to mind when you think about your research question. Once you’ve got a pretty good list, you can begin to pare it down by cutting questions and topics that seem redundant and group like questions and topics together. If you haven’t done so yet, you may also want to come up with question and topic headings for your grouped categories. You should also consult the scholarly literature to find out what kinds of questions other interviewers have asked in studies of similar topics and what theory indicates might be important. As with quantitative survey research, it is best not to place very sensitive or potentially controversial questions at the very beginning of your qualitative interview guide. You need to give participants the opportunity to warm up to the interview and to feel comfortable talking with you. Finally, get some feedback on your interview guide. Ask your friends, other researchers, and your professors for some guidance and suggestions once you’ve come up with what you think is a strong guide. Chances are they’ll catch a few things you hadn’t noticed. Your participants may also suggest revisions or improvements, once you begin your interviews.
In terms of the specific questions you include in your guide, there are a few guidelines worth noting. First, avoid questions that can be answered with a simple yes or no. Try to rephrase your questions in a way that invites longer responses from your interviewees. If you choose to include yes or no questions, be sure to include follow-up questions. Remember, one of the benefits of qualitative interviews is that you can ask participants for more information—be sure to do so. While it is a good idea to ask follow-up questions, try to avoid asking “why” as your follow-up question, as this particular question can come off as confrontational, even if that is not your intent. Often people won’t know how to respond to “why,” perhaps because they don’t even know why themselves. Instead of “why,” I recommend that you say something like, “Could you tell me a little more about that?” This allows participants to explain themselves further without feeling that they’re being doubted or questioned in a hostile way.
Also, try to avoid phrasing your questions in a leading way. For example, rather than asking, “Don’t you think most people who don’t want kids are selfish?” you could ask, “What comes to mind for you when you hear someone doesn’t want kids?” Or rather than asking, “What do you think about juvenile offenders who drink and drive?” you could ask, “How do you feel about underage drinking?” or “What do you think about drinking and driving?” Finally, remember to keep most, if not all, of your questions open-ended. The key to a successful qualitative interview is giving participants the opportunity to share information in their own words and in their own way. Documenting decisions that you make along the way regarding which questions are used, thrown out, or revised can help a researcher remember during analysis the thought process behind the interview guide. Additionally, it promotes the rigor of the qualitative project as a whole, ensuring the researcher is proceeding in a reflective and deliberate manner that can be checked by others reviewing her study.
Recording qualitative data
Even after the interview guide is constructed, the interviewer is not yet ready to begin conducting interviews. The researcher next has to decide how to collect and maintain the information that is provided by participants. Researchers keep field notes or written recordings produced by the researcher during the data collection process, including before, during, and after interviews. Field notes help researchers document what they observe, and in so doing, they form the first draft of data analysis. Field notes may contain many things—observations of body language or environment, reflections on whether interview questions are working well, and connections between ideas that participants share.
Unfortunately, even the most diligent researcher cannot write down everything that is seen or heard during an interview. In particular, it is difficult for a researcher to be truly present and observant if she is also writing down everything the participant is saying. For this reason, it is quite common for interviewers to create audio recordings of the interviews they conduct. Recording interviews allows the researcher to focus on her interaction with the interview participant rather than being distracted by trying to write down every word that is said.
Of course, not all participants will feel comfortable being recorded and sometimes even the interviewer may feel that the subject is so sensitive that recording would be inappropriate. If this is the case, it is up to the researcher to balance excellent note-taking with exceptional question-asking and even better listening. I don’t think I can understate the difficulty of managing all these feats simultaneously. Whether you will be recording your interviews or not (and especially if not), practicing the interview in advance is crucial. Ideally, you’ll find a friend or two willing to participate in a couple of trial runs with you. Even better, you’ll find a friend or two who are similar in at least some ways to your sample. They can give you the best feedback on your questions and your interview demeanor.
Another issue interviewers face is documenting the decisions made during the data collection process. Qualitative research is open to new ideas that emerge through the data collection process. For example, a participant might suggest a new concept you hadn’t thought of before or define a concept in a new way. This may lead you to create new questions or ask questions in a different way to future participants. These processes should be documented in a process called journaling or memoing. Journal entries are notes to yourself about reflections or methodological decisions that emerge during the data collection process. Documenting these decisions is important, as you’d be surprised how quickly you can forget what happened. Journaling makes sure that when it comes time to analyze your data, you remember how, when, and why certain changes were made. The discipline of journaling in qualitative research helps to ensure the rigor of the research process—that is its trustworthiness and authenticity. We covered these standards of qualitative rigor in Chapter 9.
Strengths and weaknesses of qualitative interviews
As we’ve mentioned in this section, qualitative interviews are an excellent way to gather detailed information. Any topic can be explored in much more depth with interviews than with almost any other method. Not only are participants given the opportunity to elaborate in a way that is not possible with other methods such as survey research, but they also are able share information with researchers in their own words and from their own perspectives. Whereas, quantitative research asks participants to fit their perspectives into the limited response options provided by the researcher. And because qualitative interviews are designed to elicit detailed information, they are especially useful when a researcher’s aim is to study social processes or the “how” of various phenomena. Yet another, and sometimes overlooked, benefit of qualitative interviews that occurs in person is that researchers can make observations beyond those that a respondent is orally reporting. A respondent’s body language, and even their choice of time and location for the interview, might provide a researcher with useful data.
Of course, all these benefits come with some drawbacks. As with quantitative survey research, qualitative interviews rely on respondents’ ability to accurately and honestly recall specific details about their lives, circumstances, thoughts, opinions, or behaviors. As Esterberg (2002) puts it, “If you want to know about what people actually do, rather than what they say they do, you should probably use observation [instead of interviews].” [2] Further, as you may have already guessed, qualitative interviewing is time-intensive and can be quite expensive. Creating an interview guide, identifying a sample, and conducting interviews are just the beginning. Writing out what was said in interviews and analyzing the qualitative are time consuming processes. Keep in mind you are also asking for more of participants’ time than if you’d simply mailed them a questionnaire containing closed-ended questions. Conducting qualitative interviews is not only labor-intensive but can also be emotionally taxing. Seeing and hearing the impact that social problems have on respondents is difficult. Researchers embarking on a qualitative interview project should keep in mind their own abilities to receive stories that may be difficult to hear.
Key Takeaways
• In-depth interviews are semi-structured interviews where the researcher has topics and questions in mind to ask, but questions are open-ended and flow according to how the participant responds to each.
• Interview guides can vary in format but should contain some outline of the topics you hope to cover during the course of an interview.
• Qualitative interviews allow respondents to share information in their own words and are useful for gathering detailed information and understanding social processes.
• Field notes and journaling document decisions and thoughts the researcher has that influence the research process.
• Drawbacks of qualitative interviews include reliance on respondents’ accuracy and their intensity in terms of time, expense, and possible emotional strain.
Glossary
• Field notes- written notes produced by the researcher during the data collection process
• In-depth interviews- interviews in which researchers hear from respondents about what they think is important about the topic at hand in the respondent’s own words
• Interview guide- a list of topics or questions that the interviewer hopes to cover during the course of an interview
• Journaling- making notes of emerging issues and changes during the research process
• Semi-structured interviews- questions are open ended and may not be asked in exactly the same way or in exactly the same order to each and every respondent
Image attributions
questions by geralt CC-0
writing by StockSnap CC-0
1. Figure 13.1 is copied from Blackstone, A. (2012) Principles of sociological inquiry: Qualitative and quantitative methods. Saylor Foundation. Retrieved from: https://saylordotorg.github.io/text_...ative-methods/ Shared under CC-BY-NC-SA 3.0 License (https://creativecommons.org/licenses/by-nc-sa/3.0/) ↵
2. Esterberg, K. G. (2002). Qualitativemethods in social research. Boston, MA: McGraw-Hill. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/13%3A_Interviews_and_Focus_Groups/13.02%3A_Qualitative_interview_techniques.txt |
Learning Objectives
• Identify the three main issues that interviewers should consider
• Describe how interviewers can address power imbalances
• Describe and define rapport
• Define the term probe
Qualitative researchers are attentive to the complexities that arise during the interview process. Interviews are intimate processes. Your participants will share with you how they view the world, how they understand themselves, and how they cope with events that happened to them. Conscientious researchers should keep in mind the following topics to ensure the authenticity and trust necessary for successful interviews.
Power
First and foremost, interviewers must be aware of and attentive to the power differential between themselves and interview participants. The interviewer sets the agenda and leads the conversation. Qualitative interviewers aim to allow participants to have some control over which or to what extent various topics are discussed, but at the end of the day, it is the researcher who is in charge of the interview and how the data are reported to the public. The participant loses the ability to shape the narrative after the interview is over because it is the researcher who tells the story to the world. As the researcher, you are also asking someone to reveal things about themselves they may not typically share with others. Researchers do not reciprocate by revealing much or anything about themselves. All these factors shape the power dynamics of an interview.
A number of excellent pieces have been written dealing with issues of power in research and data collection. Feminist researchers in particular paved the way in helping researchers think about and address issues of power in their work (Oakley, 1981). [1] Suggestions for overcoming the power imbalance between researcher and respondent include having the researcher reveal some aspects of her own identity and story so that the interview is a more reciprocal experience rather than one-sided, allowing participants to view and edit interview transcripts before the researcher uses them for analysis, and giving participants an opportunity to read and comment on analysis before the researcher shares it with others through publication or presentation (Reinharz, 1992; Hesse-Biber, Nagy, & Leavy, 2007). [2] On the other hand, some researchers note that sharing too much with interview participants can give the false impression there is no power differential, when in reality researchers can analyze and present participants’ stories in whatever way they see fit (Stacey, 1988). [3]
However you feel about sharing details about your background with an interview participant, another way to balance the power differential between yourself and your interview participants is to make the intent of your research very clear to the subjects. Share with them your rationale for conducting the research and the research question(s) that frame your work. Be sure that you also share with participants how the data you gather will be used and stored. Also, explain to participants how their confidentiality will be protected including who will have access to the data you gather from them and what procedures, such as using pseudonyms, you will take to protect their identities. Social workers also must disclose the reasons why confidentiality may be violated to prevent danger to self or others. Many of these details will be covered by your IRB’s informed consent procedures and requirements. However, even if they are not, as researchers we should be attentive to how informed consent can help balance the power differences between ourselves and those who participate in our research.
There are no easy answers when it comes to handling the power differential between the researcher and researched. Even social scientists do not agree on the best approach. Because qualitative research involves interpersonal interactions and building a relationship with research participants, power is a particularly important issue.
Location, location, location
One way to address the power between researcher and respondent is to conduct the interview in a location of the participant’s choosing, where they will feel most comfortable answering your questions. Interviews can take place in any number of locations—in respondents’ homes or offices, researchers’ homes or offices, coffee shops, restaurants, public parks, or hotel lobbies, to name just a few possibilities. Each location comes with its own set of benefits and its own challenges. While I would argue that allowing the respondent to choose the location that is most convenient and most comfortable for them is of utmost importance, identifying a location where there will be few distractions is also important. For example, some coffee shops and restaurants are so loud that recording the interview can be a challenge. Other locations may present different sorts of distractions. For example, if you conduct interviews with parents in their home, they may out of necessity spend more time attending to their children during an interview than responding to your questions (of course, depending on the topic of your research, the opportunity to observe such interactions could be invaluable). As an interviewer, you may want to suggest a few possible locations, and note the goal of avoiding distractions, when you ask your respondents to choose a location.
Of course, the extent to which a respondent should be given complete control over choosing a location must also be balanced by accessibility of the location to you, the interviewer, and by your safety and comfort level with the location. You may not feel comfortable conducting an interview in an area with posters for hate groups on the wall. Not only might you fear for your safety, you may be too distracted to conduct a good interview. While it is important to conduct interviews in a location that is comfortable for respondents, doing so should never come at the expense of your safety.
Researcher-respondent relationship
A unique feature of interviews is that they require some social interaction, which means that a relationship is formed between interviewer and interviewee. One essential element in building a productive relationship is respect. You should respect the person’s time and their story. Demonstrating respect will help interviewees feel comfortable sharing with you.
There are no big secrets or tricks for how to show respect for research participants. At its core, the interview interaction should not differ from any other social interaction in which you show gratitude for a person’s time and respect for a person’s humanity. It is crucial that you, as the interviewer, conduct the interview in a way that is culturally sensitive. In some cases, this might mean educating yourself about your study population and even receiving some training to help you learn to effectively communicate with your research participants. Do not judge your research participants; you are there to listen to them, and they have been kind enough to give you their time and attention. Even if you disagree strongly with what a participant shares in an interview, your job as the researcher is to gather the information being shared with you, not to make personal judgments about it.
Respect provides a solid foundation for rapport. Rapport is the sense of connection you establish with a participant. Some argue that this term is too clinical, and perhaps it implies that a researcher tricks a participant into thinking they are closer than they really are (Esterberg, 2002). [4] The responsibilities that a social work clinician has to a person differ significantly from those of a researcher, as clinicians provide services whereas researchers do not. The participant is not your client, and your goals for the interaction are different than those of a clinical relationship.
Developing good rapport requires good listening. In fact, listening during an interview is an active, not a passive, practice. Active listening means that you, the researcher, participate with the respondent by showing you understand and follow whatever it is that they are telling you (Devault, 1990). [5] The questions you ask respondents should indicate you’ve actually heard what they’ve just said.
Active listening means you will probe the respondent for more information from time to time throughout the interview. A probe is a request for more information. Probes are used because qualitative interviewing techniques are designed to go with the flow and take whatever direction the respondent goes during the interview. It is worth your time to come up with helpful probes in advance of an interview. You certainly do not want to find yourself stumped or speechless after a respondent has just said something about which you’d like to hear more. This is another reason why practicing your interview in advance with people who are similar to those in your sample is a good idea.
Key Takeaways
• All interviewers should take into consideration the power differential between themselves and their respondents.
• Attend to the location of an interview and the relationship that forms between the interviewer and interviewee.
• Feminist researchers paved the way for helping interviewers think about how to balance the power differential between themselves and interview participants.
• Interviewers must always be respectful of interview participants.
Glossary
• Probe- a request for more information in qualitative research
Image attributions
punch fist by PublicDomainPictures CC-0
action collaborate by rawpixel CC-0
1. Oakley, A. (1981). Interviewing women: A contradiction in terms. In H. Roberts (Ed.), Doing feminist research (pp. 30–61). London, UK: Routledge & Kegan Paul. ↵
2. Reinharz, S. (1992). Feminist methods in social research. New York, NY: Oxford University Press; Hesse-Biber, S. N., & Leavy, P. L. (Eds.). (2007). Feminist research practice: A primer. Thousand Oaks, CA: Sage. ↵
3. Stacey, J. (1988). Can there be a feminist ethnography? Women’s Studies International Forum, 11, 21–27. ↵
4. Esterberg, K. G. (2002). Qualitative methods in social research. Boston, MA: McGraw-Hill. ↵
5. For more on the practice of listening, especially in qualitative interviews, see Devault, M. (1990). Talking and listening from women’s standpoint: Feminist strategies for interviewing and analysis. Social Problems, 37, 96–116. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/13%3A_Interviews_and_Focus_Groups/13.03%3A_Issues_to_consider_for_all_interview_types.txt |
Learning Objectives
• Define focus groups and outline how they differ from one-on-one interviews
• Describe how to determine the best size for focus groups
• Identify the important considerations in focus group composition
• Discuss how to moderate focus groups
• Identify the strengths and weaknesses of focus group methodology
Focus groups resemble qualitative interviews in that a researcher may prepare a guide in advance and interact with participants by asking them questions. But anyone who has conducted both one-on-one interviews and focus groups knows that each is unique. In an interview, usually one member (the research participant) is most active while the other (the researcher) plays the role of listener, conversation guider, and question-asker. Focus groups, on the other hand, are planned discussions designed to elicit group interaction and “obtain perceptions on a defined area of interest in a permissive, nonthreatening environment” (Krueger & Casey, 2000, p. 5). [1] In this case, the researcher may play a less active role than in a one-on-one interview. The researcher’s aim is to get participants talking to each other and to observe interactions among participants.
There are numerous examples of focus group research. In their 2008 study, for example, Amy Slater and Marika Tiggemann (2010) [2] conducted six focus groups with 49 adolescent girls between the ages of 13 and 15 to learn more about girls’ attitudes towards’ participation in sports. In order to get focus group participants to speak with one another rather than with the group facilitator, the study’s interview guide contained just two questions: “Can you tell me some of the reasons that girls stop playing sports or other physical activities?” and “Why do you think girls don’t play as much sport/physical activity as boys?” In another focus group study, Virpi Ylanne and Angie Williams (2009) [3] held nine focus group sessions with adults of different ages to gauge their perceptions of how older characters are represented in television commercials. Among other considerations, the researchers were interested in discovering how focus group participants position themselves and others in terms of age stereotypes and identities during the group discussion. In both examples, the researchers’ core interest in group interaction could not have been assessed had interviews been conducted on a one-on-one basis; thus, the focus group method was the ideal choice in each instance.
The preceding examples come from the work of academics who have used focus groups as their method of data collection. But focus groups have proven quite useful for those outside of academia as well. In fact, this method is especially popular among researchers. Market researchers use focus groups to gather information about the products or services they aim to sell. Government officials and political campaign workers use them to learn how members of the public feel about a particular issue or candidate. One of the earliest documented uses of focus groups comes from World War II when researchers used them to assess the effectiveness of troop training materials and of various propaganda efforts (Merton & Kendall, 1946; Morgan, 1997). [4] Market researchers quickly adopted this method of collecting data to learn about human beliefs and behaviors. Within social science, the use of focus groups did not really take off until the 1980s, when demographers and communication researchers began to appreciate their use in understanding knowledge, attitudes, and communication (Morgan, 1997).
Who should be in your focus group?
In some ways, focus groups require more planning than other qualitative methods of data collection, such as one-on-one interviews in which a researcher may be better able to the dialogue. Researchers must take care to form focus groups with members who will want to interact with one another and to control the timing of the event so that participants are not asked nor expected to stay for a longer time than they’ve agreed to participate. The researcher should also be prepared to inform focus group participants of their responsibility to maintain the confidentiality of what is said in the group. But while the researcher can and should encourage all focus group members to maintain confidentiality, she should also clarify to participants that the unique nature of the group setting prevents her from being able to promise that confidentiality will be maintained by other participants. Once focus group members leave the research setting, researchers cannot control what they say to other people.
Group size should be determined in part by the topic of the interview and your sense of the likelihood that participants will have much to say without much prompting. If the topic is one about which you think participants feel passionately and will have much to say, I think a group of 3–5 makes sense. Groups larger than that, especially for heated topics, can easily become unmanageable. Some researchers say that a group of about 6–10 participants is the ideal size for focus group research (Morgan, 1997); others recommend that groups should include 3–12 participants (Adler & Clark, 2008). [5] The size of the focus group is ultimately your decision as the researcher. When forming groups and deciding how large or small to make them, take into consideration what you know about the topic and participants’ potential interest in, passion for, and feelings about the topic. Also consider your comfort level and experience in conducting focus groups. These factors will help you decide which size is right in your particular case.
It may seem counterintuitive, but in general, it is better to form focus groups consisting of participants who do not know one another than to create groups consisting of friends, relatives, or acquaintances (Agar & MacDonald, 1995). [6] The reason for this is that group members who know each other may share some taken-for-granted knowledge or assumptions. In research, it is precisely the knowledge taken-for-granted that is often of interest; thus, the focus group researcher should avoid setting up interactions where participants may be discouraged to question or raise issues that they take for granted. However, groups should not be so heterogeneous that participants will be unlikely to feel comfortable talking with one another.
Focus group researchers must carefully consider the composition of the groups they put together. In his text on conducting focus groups, Morgan suggests that “homogeneity in background and not homogeneity in attitudes” (p. 36) should be the goal, since participants must feel comfortable speaking up but must also have enough differences to facilitate a productive discussion (1997). [7] Whatever composition a researcher designs for her focus groups, the important point to keep in mind is that focus group dynamics are shaped by multiple social contexts (Hollander, 2004). [8] Participants’ silences as well as their speech may be shaped by gender, race, class, sexuality, age, or other background characteristics or social dynamics—all of which might be suppressed or exacerbated depending on the composition of the group. Hollander suggests that researchers must pay careful attention to group composition, must be attentive to group dynamics during the focus group discussion, and should use multiple methods of data collection in order to “untangle participants’ responses and their relationship to the social contexts of the focus group” (p. 632).
The role of the moderator
In addition to the importance of group composition, focus groups also require skillful moderation. A moderator is the researcher tasked with facilitating the conversation in the focus group. Participants may ask each other follow-up questions, agree or disagree with one another, display body language that tells us something about their feelings about the conversation, or even come up with questions not previously conceived of by the researcher. It is just these sorts of interactions and displays that are of interest to the researcher. A researcher conducting focus groups collects data on more than people’s direct responses to her question, as in interviews.
The moderator’s job is not to ask questions to each person individually, but to stimulate conversation between participants. It is important to set ground rules for focus groups at the outset of the discussion. Remind participants you’ve invited them to participate because you want to hear from all of them. Therefore, the group should aim to let just one person speak at a time and avoid letting just a couple of participants dominate the conversation. One way to do this is to begin the discussion by asking participants to briefly introduce themselves or to provide a brief response to an opening question. This will help set the tone of having all group members participate. Also, ask participants to avoid having side conversations; thoughts or reactions to what is said in the group are important and should be shared with everyone.
As the focus group gets rolling, the moderator will play a less active role as participants talk to one another. There may be times when the conversation stagnates or when you, as moderator, wish to guide the conversation in another direction. In these instances, it is important to demonstrate that you’ve been paying attention to what participants have said. Being prepared to interject statements or questions such as “I’d really like to hear more about what Sunil and Joe think about what Dominick and Jae have been saying” or “Several of you have mentioned X. What do others think about this?” will be important for keeping the conversation going. It can also help redirect the conversation, shift the focus to participants who have been less active in the group, and serve as a cue to those who may be dominating the conversation that it is time to allow others to speak. Researchers may choose to use multiple moderators to make managing these various tasks easier.
Moderators are often too busy working with participants to take diligent notes during a focus group. Researchers may recruit a note-taker who can record participants’ responses (Liamputtong, 2011). [9] The note-taker creates, in essence, the first draft of interpretation for the data in the study. They note themes in responses, nonverbal cues, and other information to be included in the analysis later on. Focus groups are analyzed in a similar way as interviews; however, the interactive dimension between participants adds another element to the analytical process. Researchers must attend to the group dynamics of each focus group, as “verbal and nonverbal expressions, the tactical use of humour, interruptions in interaction, and disagreement between participants” are all data that vital to include in analysis (Liamputtong, 2011, p. 175). Note-takers record these elements in field notes, which allows moderators to focus on the conversation.
Strengths and weaknesses of focus groups
Focus groups share many of the strengths and weaknesses of one-on-one qualitative interviews. Both methods can yield very detailed, in-depth information; are excellent for studying social processes; and provide researchers with an opportunity not only to hear what participants say but also to observe what they do in terms of their body language. Focus groups offer the added benefit of giving researchers a chance to collect data on human interaction by observing how group participants respond and react to one another. Like one-on-one qualitative interviews, focus groups can also be quite expensive and time-consuming. However, there may be some time savings with focus groups as it takes fewer group events than one-on-one interviews to gather data from the same number of people. Another potential drawback of focus groups, which is not a concern for one-on-one interviews, is that one or two participants might dominate the group, silencing other participants. Careful planning and skillful moderation on the part of the researcher are crucial for avoiding, or at least dealing with, such possibilities. The various strengths and weaknesses of focus group research are summarized in Table 13.1.
Table 13.1 Strengths and weaknesses of focus group research
Strengths Weaknesses
Yield detailed, in-depth data Expensive
Less time-consuming than one-on-one interviews May be more time-consuming than survey research
Useful for studying social processes Minority of participants may dominate entire group
Allow researchers to observe body language in addition to self-reports Some participants may not feel comfortable talking in groups
Allow researchers to observe interaction between multiple participants Cannot ensure confidentiality
Key Takeaways
• In terms of focus group composition, homogeneity of background among participants is recommended while diverse attitudes within the group are ideal.
• The goal of a focus group is to get participants to talk with one another, a conversation the researcher moderates.
• Like one-on-one qualitative interviews, focus groups can yield very detailed information, are excellent for studying social processes, and provide researchers with an opportunity to observe participants’ body language; they also allow researchers to observe social interaction.
• Focus groups can be expensive and time-consuming, as are one-on-one interviews; there is also the possibility that a few participants will dominate the group and silence others in the group.
Glossary
• Focus groups- planned discussions designed to elicit group interaction and “obtain perceptions on a defined area of interest in a permissive, nonthreatening environment” (Krueger & Casey, 2000, p. 5)
• Moderator- the researcher tasked with facilitating the conversation in the focus group
Image attributions
target group by geralt CC-0
workplace team by Free-Photos CC-0
1. Krueger, R. A., & Casey, M. A. (2000). Focus groups: A practical guide for applied research (3rd ed.). Thousand Oaks, CA: Sage. ↵
2. Slater, A., & Tiggemann, M. (2010). “Uncool to do sport”: A focus group study of adolescent girls’ reasons for withdrawing from physical activity. Psychology of Sport and Exercise, 11, 619–626. ↵
3. Ylanne, V., & Williams, A. (2009). Positioning age: Focus group discussions about older people in TV advertising. International Journal of the Sociology of Language, 200, 171–187. ↵
4. Morgan, D. L. (1997). Focus groups as qualitative research (2nd ed.). Thousand Oaks, CA: Sage. ↵
5. Adler, E. S., & Clark, R. (2008). How it’s done: An invitation to social research (3rd ed.). Belmont, CA: Thomson Wadsworth. ↵
6. Agar, M., & MacDonald, J. (1995). Focus groups and ethnography. Human Organization, 54,78–86. ↵
7. Morgan, D. L. (1997). Focus groups as qualitative research (2nd ed.). Thousand Oaks, CA: Sage. ↵
8. Hollander, J. A. (2004). The social context of focus groups. Journal of Contemporary Ethnography, 33, 602–637. ↵
9. Liamputtong, P. (2011). Focus group methodology: Principles and practice. Washington, DC: Sage. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/13%3A_Interviews_and_Focus_Groups/13.04%3A_Focus_groups.txt |
Learning Objectives
• Describe how to transcribe qualitative data
• Identify and describe the two types of coding in qualitative research
Analysis of qualitative data typically begins with a set of transcripts of the interviews or focus groups conducted. Obtaining these transcripts requires having either taken exceptionally good notes or, preferably, having recorded the interview or focus group and then transcribed it. Transcribing audio recordings is usually the first step toward analyzing qualitative data. Researchers create a complete, written copy, or transcript, of the recording by playing it back and typing in each word that is spoken, noting who spoke which words. In general, it is best to aim for a verbatim transcript, one that reports word for word exactly what was said in the recording. If possible, it is also best to include nonverbals in a transcript. Gestures made by participants should be noted, as should the tone of voice and notes about when, where, and how spoken words may have been emphasized by participants. Because these are difficult to capture via audio, it is important to have a note-taker in focus groups and to write useful field notes during interviews.
If you have the time (or if you lack the resources to hire others), I think it is best to transcribe your qualitative data yourself. I never cease to be amazed by the things I recall from an interview or focus group when I transcribe it myself. If the researcher who conducted the interview or focus group transcribes it herself, that person will also be able to make a note of nonverbal behaviors and interactions that may be relevant to analysis but that could not be picked up by audio recording. Participants might roll their eyes, wipe tears from their face, and even make obscene gestures. These nonverbals speak volumes about participants’ feelings. Unless you write them down in your field notes or include them in your transcript, those details cannot inform your analysis.
The goal of qualitative data analysis is to reach some inferences, lessons, or conclusions by condensing large amounts of data into relatively smaller, more manageable bits of understandable information. Analysis of qualitative data often works inductively (Glaser & Strauss, 1967; Charmaz, 2006). [1] To move from the specific observations a researcher collects to identifying patterns across those observations, qualitative researchers will often begin by reading through transcripts and trying to identify codes. A code is a shorthand representation of some more complex set of issues or ideas. In this usage, the word code is a noun. But it can also be a verb. The process of identifying codes in one’s qualitative data is often referred to as coding. Coding involves identifying themes across qualitative data by reading and rereading (and rereading again) transcripts until the researcher has a clear idea about what themes emerge.
Qualitative researcher and textbook author Kristin Esterberg (2002) [2] describes coding as a multistage process. Esterberg suggests that there are two types of coding: open coding and focused coding. To analyze qualitative data, one can begin by open coding transcripts. This means that you read through each transcript, line by line, and make a note of whatever categories or themes jump out to you. At this stage, it is important that you not let your original research question or tentative hypotheses cloud your ability to see categories or themes. It’s called open coding for a reason—keep an open mind. You may have even noted some ideas for coding in your field notes or journal entries.
Open coding will probably require multiple rounds. That is, you will read through all of your transcripts multiple times. As you do, it is likely that you’ll begin to see some commonalities across the categories or themes that you’ve jotted down. Once you have completed a few passes and started noticing commonalities, you might begin focused coding. Focused coding is a multistage process. First, collapse or narrow down themes and categories identified in open coding by reading through the notes you made while conducting open coding. Identify themes or categories that seem to be related, perhaps merging some. Once you come up with a final list of codes, make sure each one has a definition that clearly spells out what the code means. Finally, you recode the dataset using the final list of codes, making sure to apply the definition of the code consistently throughout each transcript.
Defining codes is a way of making meaning of your data and of developing a way to talk about your findings. Researchers must ensure that codes are applied in a uniform way in the entire data set during focused coding. In open coding, new codes and shifts in definitions for codes are common. The researcher should keep an open mind and allow the definitions of codes to emerge from reading (and re-reading) the data. However, once focused coding begins, the definitions should not change for any reason. Any deviation will make the data analysis less trustworthy. If there are pieces of data that do not fit with your definition, then it is important to note those deviant cases in your final report.
Using multiple researchers to code the same dataset can be quite helpful. You may miss something a participant said that another coder catches. Similarly, you may shift your understanding of what a code means and not realize it until another coder asks you about it. If multiple researchers are coding the dataset simultaneously, researchers must come to a consensus about the meaning of each code and ensure that codes are applied consistently by each researcher. We discussed this previously in Chapter 9 as inter-rater reliability. Even if only one person will code the dataset, it is important to work with other researchers. If other researchers have the time, you may be able to have them check your work for trustworthiness and authenticity. We discussed these standards for methodological rigor in Chapter 9. Remember, in qualitative data analysis, the researcher is the measurement instrument, determining what is true, what is connected to what, and what it all means.
As tedious and laborious as it might seem to read through hundreds of pages of transcripts multiple times, sometimes getting started with the coding process is actually the hardest part. If you find yourself struggling to identify themes at the open coding stage, ask yourself some questions about your data. The answers should give you a clue about what sorts of themes or categories you are reading. In their text on analyzing qualitative data, Lofland and Lofland (1995) [3] identify a set of questions I find very useful when coding qualitative data. They suggest asking the following:
• Of what topic, unit, or aspect is this an instance?
• What question about a topic does this item of data suggest?
• What sort of answer to a question about a topic does this item of data suggest (i.e., what proposition is suggested)?
Asking yourself these questions about the passages of data that you’re reading can help you begin to identify and name potential themes and categories.
Still feeling uncertain about how this process works? Sometimes it helps to see how qualitative data translate into codes. In Table 13.2, I present two codes that emerged from an inductive analysis of transcripts from interviews with child-free adults. I also include a brief description of each code and a few (of many) interview excerpts from which each code was developed.
Table 13.2 Interview coding example
Code Code definition Interview excerpts
Reify gender Participants reinforce heteronormative ideals in two ways: (a) by calling up stereotypical images of gender and family and (b) by citing their own “failure” to achieve those ideals. “The woman is more involved with taking care of the child. [As a woman] I’d be the one waking up more often to feed the baby and more involved in the personal care of the child, much more involved. I would have more responsibilities than my partner. I know I would feel that burden more than if I were a man.”
“I don’t have that maternal instinct.”
“I look at all my high school friends on Facebook, and I’m the only one who isn’t married and doesn’t have kids. I question myself, like if there’s something wrong with me that I don’t have that.”
“I feel badly that I’m not providing my parents with grandchildren.”
Resist Gender Participants resist gender norms in two ways: (a) by pushing back against negative social responses and (b) by redefining family for themselves in a way that challenges normative notions of family. “Am I less of a woman because I don’t have kids? I don’t think so!”
“I think if they’re gonna put their thoughts on me, I’m putting it back on them. When they tell me, ‘Oh, Janet, you won’t have lived until you’ve had children. It’s the most fulfilling thing a woman can do!’ then I just name off the 10 fulfilling things I did in the past week that they didn’t get to do because they have kids.”
“Family is the group of people that you want to be with. That’s it.”
As you might imagine, wading through all these data is quite a process. Just as quantitative researchers rely on the assistance of special computer programs designed to help with sorting through and analyzing their data, so too do qualitative researchers. Where quantitative researchers have SPSS and MicroCase (and many others), qualitative researchers have programs such as NVivo (http://www.qsrinternational.com) and Atlas.ti (http://www.atlasti.com). These are programs specifically designed to assist qualitative researchers with organizing, managing, sorting, and analyzing large amounts of qualitative data. The programs work by allowing researchers to import transcripts contained in an electronic file and then label or code passages, cut and paste passages, search for various words or phrases, and organize complex interrelationships among passages and codes. They even include advanced features that allow researchers to code multimedia files, visualize relationships between a network of codes, and count the number of times a code was applied. Having completed a handwritten coding process as part of a class project with a rather old-school professor, I’m happy I can use qualitative data analysis software to save myself time and hassle.
To summarize, the following excerpt, from my paper analyzing the implementation of self-directed supports for individuals with intellectual and developmental disabilities summarizes how the process of analyzing qualitative data can work:
Transcribed interviews were analyzed using Atlas.ti 7.5 (2014) qualitative data analysis software, a commonly used program in qualitative social science. The researchers approached data analysis from an inductive perspective, allowing themes to emerge from the data. As described by Braun and Clarke (2006), the thematic analysis proceeded along six sequential phases: (a) familiarizing with the data set, (b) generating initial codes, (c) searching for themes, (d) reviewing themes, (e) defining and naming themes, (f) and reporting data. One member of the research team conducted the coding and thematic analysis, consulting with a peer reviewer at the end of each of the three passes of coding and the entire research team after the coding process was complete. The peer reviewer reviewed each phase of coding for consistency, and worked with the primary coder to identify, review, and name themes. At the end of coding, the entire research team reviewed the themes and established a shared meaning that best reflected the narratives of participants, based on a series of dialogues. The themes were organized into a thematic map which was refined through consultation with the research team to ensure homogeneity within each theme and heterogeneity between themes. The analysis contained within this paper used co-occurrence counts as a guideline for the prevalence of themes within the data set. Thus, the analysis is limited to the most prevalent themes that answer each research question, while attending to exceptional or divergent cases. Methodological journaling related to coding and peer review helped to ensure the dependability, confirmability, and trustworthiness of the final research product (DeCarlo, Bogenschutz, Hall-Lande, & Hewitt, in press). [4]
Key Takeaways
• Open coding involves allowing codes to emerge from the dataset.
• Codes must be clearly defined before focused coding can begin, so the researcher applies them in the same way to each unit of data.
• NVivo and Atlas.ti are computer programs that qualitative researchers use to help with organizing, sorting, and analyzing their data.
Glossary
• Code- a shorthand representation of some more complex set of issues or ideas
• Coding- identifying themes across qualitative data by reading transcripts
• Focused coding- collapsing or narrowing down codes, defining codes, and recoding each transcript using a final code list
• Open coding- reading through each transcript, line by line, and make a note of whatever categories or themes seem to jump out to you
• Transcript- a complete, written copy of the recorded interview or focus group containing each word that is spoken on the recording, noting who spoke which words
Image attributions
Compact Cassette by Petr Kvashin CC-0
concept of learning by unknown CC-0
1. If you would like to learn more about inductive qualitative data analysis, I recommend two titles: Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. Chicago, IL: Aldine; Charmaz, K. (2006). Constructing grounded theory:A practical guide through qualitative analysis. Thousand Oaks, CA: Sage. ↵
2. Esterberg, K. G. (2002). Qualitative methods in social research. Boston, MA: McGraw-Hill. ↵
3. Lofland, J., & Lofland, L. H. (1995). Analyzing social settings: A guide to qualitative observation and analysis (3rd ed.) Belmont, CA: Wadsworth. ↵
4. DeCarlo, M., Bogenschutz, M., Hall-Lane, J., & Hewitt, A. (in press). Implementation of self-directed supports for individuals with intellectual and developmental disabilities in the United States. Journal of disability policy studies. | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/13%3A_Interviews_and_Focus_Groups/13.05%3A_Analyzing_qualitative_data.txt |
Are female and male athletes at the professional and college levels treated equally? You might think 40 years since the passing of Title IX (the civil rights law that prohibits sex discrimination in education including athletics) and with the growing visibility of women athletes in sports, such as golf, basketball, hockey, and tennis, that the answer would be an easy yes. But Professor Michael Messner’s (2002) [1] unobtrusive research shows otherwise, as does Professors Jo Ann M. Buysse and Melissa Sheridan Embser-Herbert’s (2004) [2] content analysis of college athletics media guide photographs.
In fact, Buysse and Embser-Herbert’s unobtrusive research shows that traditional definitions of femininity are fiercely maintained through colleges’ visual representations of women athletes as passive and overtly feminine (as opposed to strong and athletic). In addition, Messner and colleagues’ (Messner, Duncan, & Jensen, 1993) [3] content analysis of verbal commentary in televised coverage of men’s and women’s sports shows that announcers’ comments vary depending on an athlete’s gender identity. Such commentary not only infantilizes women athletes but also asserts an ambivalent stance toward their accomplishments. Without unobtrusive research we might be inclined to think that more has changed for women athletes over the past 40 years than actually has changed.
This chapter discusses or mentions the following topics: sexism, racism, depression, and suicide.
1. Messner, M. A. (2002). Taking the field: Women, men, and sports. Minneapolis: University of Minnesota Press.
2. Buysse, J. A. M., & Embser-Herbert, M. S. (2004). Constructions of gender in sport: An analysis of intercollegiate media guide cover photographs. Gender & Society, 18, 66–81.
3. Messner, M. A., Duncan, M. C., & Jensen, K. (1993). Separating the men from the girls: The gendered language of televised sports. Gender & Society, 7, 121–137.
14: Unobtrusive Research
Learning Objectives
• Define unobtrusive research and describe why it is used
In this chapter, we will explore unobtrusive methods of collecting data. Unobtrusive research refers to methods of collecting data that don’t interfere with the subjects under study (because these methods are not obtrusive). Both qualitative and quantitative researchers use unobtrusive research methods. Unobtrusive methods share the unique quality that they do not require the researcher to interact with the people she is studying. It may seem strange that social work, a discipline dedicated to helping people, would employ a methodology that requires no interaction with human beings. But humans create plenty of evidence of their behaviors—they write letters to the editor of their local paper, they create various sources of entertainment for themselves such as movies and televisions shows, they consume goods, they walk on sidewalks, and they lie on the grass in public parks. All these activities leave something behind—worn paths, trash, recorded shows, and printed papers. These are all potential sources of data for the unobtrusive researcher.
Social workers interested in history are likely to use unobtrusive methods, which are also well suited to comparative research. Historical comparative research is “research that focuses either on one or more cases over time (the historical part) or on more than one nation or society at one point in time (the comparative part)” (Esterberg, 2002, p. 129). [1] While not all unobtrusive researchers necessarily conduct historical, comparative, or even some combination of historical and comparative work, unobtrusive methods are well suited to such work. As an example, Melissa Weiner (2010) [2] used a historical comparative approach to study racial barriers historically experienced by Jewish people and African Americans in New York City public schools. Weiner analyzed public records from several years of newspapers, trial transcripts, and several organizations as well as private manuscript collections to understand how parents, children, and other activists responded to inequality and worked to reform schools. Not only did this work inform readers about the little-known similarities between Jewish and African American experiences, but it also informs current debates over inequalities experienced in public schools today.
In this chapter, we’ll examine content analysis as well as analysis of data collected by others. Both types of analysis have in common their use of data that do not require direct interaction with human subjects, but the particular type and source of data for each type of analysis differs. We’ll explore these similarities and differences in the following sections, after we look at some of the pros and cons of unobtrusive research methods.
Key Takeaways
• Unobtrusive methods allow researchers to collect data without interfering with the subjects under study.
• Historical comparative methods, which are unobtrusive, focus on changes in multiple cases over time or on more than one nation or society at a single point in time.
Glossary
• Unobtrusive research- methods of collecting data that don’t interfere with the subjects under study
Image attributions
office business by rawpixel CC-0
1. Esterberg, K. G. (2002). Qualitative methods in social research. Boston, MA: McGraw-Hill. ↵
2. Weiner, M. (2010). Power, protest, and the public schools: Jewish and African American struggles in New York City. Piscataway, NJ: Rutgers University Press. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/14%3A_Unobtrusive_Research/14.01%3A_Unobtrusive_research-_What_is_it_and_when_should_it_be_used%3F.txt |
Learning Objectives
• Identify the major strengths of unobtrusive research
• Identify the major weaknesses of unobtrusive research
• Define the Hawthorne effect
As is true of the other research designs examined in this text, unobtrusive research has a number of strengths and weaknesses.
Strengths of unobtrusive research
Researchers who seek evidence of what people actually do, as opposed to what they say they do (as in survey and interview research), might wish to consider using unobtrusive methods. Researchers often, as a result of their presence, have an impact on the participants in their study simply because they measure and observe them. For example, compare how you would behave at work if you knew someone was watching you versus a time when you knew you were alone. Because researchers conducting unobtrusive research do not alert participants to their presence, they do not need to be concerned about the effect of the research on their subjects. This effect, known as the Hawthorne effect, is not a concern for unobtrusive researchers because they do not interact directly with their research participants. In fact, this is one of the major strengths of unobtrusive research.
Another benefit of unobtrusive research is that it can be relatively low-cost compared to some of the other methods we’ve discussed. Because “participants” are generally inanimate objects (e.g., web journal entries, television shows, historical speeches) as opposed to human beings, researchers may be able to access data without having to worry about paying participants for their time (though certainly travel to or access to some documents and archives can be costly).
Unobtrusive research is also pretty forgiving. It is far easier to correct mistakes made in data collection when conducting unobtrusive research than when using any of the other methods described in this textbook. Imagine what you would do, for example, if you realized at the end of conducting 50 in-depth interviews that you’d accidentally omitted two critical questions from your interview guide. What are your options? Re-interview all 50 participants? Try to figure out what they might have said based on their other responses? Reframe your research question? Scratch the project entirely? Obviously, none of these options is ideal. The same problems arise if a mistake is made in survey research. Fortunately for unobtrusive researchers, going back to the source of the data to gather more information or correct some problem in the original data collection is a relatively straightforward prospect.
Finally, as described in the previous section, unobtrusive research is well suited to studies that focus on processes that occur over time. While longitudinal surveys and long-term field observations are also suitable ways of gathering such information, they cannot examine processes that occurred decades before data collection began, nor are they the most cost-effective ways to examine long-ranging processes. Unobtrusive methods, on the other hand, enable researchers to investigate events and processes that have long since passed. They also do not rely on retrospective accounts, which may be subject to errors in memory, as some longitudinal surveys do.
In sum, the strengths of unobtrusive research include the following:
• There is no possibility for the Hawthorne effect.
• The method is cost-effective.
• It is easier in unobtrusive research than with other methods to correct mistakes.
• Unobtrusive methods are conducive to examining processes that occur over time or in the past.
Weaknesses of unobtrusive research
While there are many benefits to unobtrusive research, this method also comes with a unique set of drawbacks. Because unobtrusive researchers analyze data that may have been created or gathered for purposes entirely different from the researcher’s aim, problems of validity sometimes arise in such projects. It may also be the case that data sources measuring whatever a researcher wishes to examine simply do not exist. This means that unobtrusive researchers may be forced to tweak their original research interests or questions to better suit the data that are available to them. Finally, it can be difficult in unobtrusive research projects to account for context. In an interview, for example, the researcher can ask what events lead up to some occurrence, but this level of personal interaction is impossible in unobtrusive research. So, while it can be difficult to ascertain why something occurred in unobtrusive research, we can gain a good understanding of what has occurred.
In sum, the weaknesses of unobtrusive research include the following:
• There may be potential problems with validity.
• The topics or questions that can be investigated are limited by data availability.
• It can be difficult to see or account for social context.
Key Takeaways
• Unobtrusive research is cost effective and allows for easier correction of mistakes than other methods of data collection do.
• The Hawthorne effect, which occurs when research subjects alter their behaviors because they know they are being studied, is not a risk in unobtrusive research as it is in other methods of data collection.
• Weaknesses of unobtrusive research include potential problems with validity, limitations in data availability, and difficulty in accounting for social context.
Glossary
• Hawthorne effect- participants in a study will behave differently because they know they are being observed
Image attributions
man paris traffic by whitfieldink CC-0 | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/14%3A_Unobtrusive_Research/14.02%3A_Strengths_and_weaknesses_of_unobtrusive_research.txt |
Learning Objectives
• Define content analysis
• Describe the kinds of texts that content analysts analyze
• Outline the differences between manifest content and latent content
• Discuss the differences between qualitative and quantitative content analysis
• Describe code sheets and their purpose
This section focuses on how to gather data unobtrusively and what to do with those data once they have been collected. There are two main ways of gathering data unobtrusively: conducting a content analysis of existing texts and analyzing physical traces of human behavior. We’ll explore both approaches.
Content analysis
One way of conducting unobtrusive research is to analyze texts. Texts come in all kinds of formats. At its core, content analysis addresses the questions of “Who says what, to whom, why, how, and with what effect?” (Babbie, 2010, pp. 328–329). [1] Content analysis is a type of unobtrusive research that involves the study of texts and their meaning. Here we use a more liberal definition of text than you might find in your dictionary. The text that content analysts investigate includes such things as actual written copy (e.g., newspapers or letters) and content that we might see or hear (e.g., speeches or other performances). Content analysts might also investigate more visual representations of human communication, such as television shows, advertisements, or movies. The following table provides a few specific examples of the kinds of data that content analysts have examined in prior studies. Which of these sources of data might be of interest to you?
Table 14.1 Content analysis examples
Data Research question Author(s) (year)
Spam e-mails What is the form, content, and quantity of unsolicited e- mails? Berzins (2009) [2]
James Bond films How are female characters portrayed in James Bond films, and what broader lessons can be drawn from these portrayals? Neuendorf, Gore, Dalessandro, Janstova, and Snyder-Suhy (2010) [3]
Console video games How is male and female sexuality portrayed in the best-selling console video games? Downs and Smith (2010) [4]
Newspaper articles How do newspapers cover closed-circuit television surveillance in Canada, and what are the implications of coverage for public opinion and policymaking? Greenberg and Hier (2009) [5]
Pro-eating disorder websites What are the features of pro-eating disorder websites, and what are the messages to which users may be exposed? Borzekowski, Schenk, Wilson, and Peebles (2010) [6]
One thing you might notice about Table 14.1 is that the data sources represent primary sources. That is, they are the original documents written by people who observed the event or analyzed the data. Secondary sources, on the other hand, are those that have already been analyzed. Often, secondary sources are created by looking at primary sources and analyzing their contents. We reviewed the difference between primary and secondary sources in Chapter 2.
Shulamit Reinharz offers a helpful way of distinguishing between these two types of sources in her methods text. She explains that while primary sources represent the “‘raw’ materials of history,” secondary sources are the “‘cooked’ analyses of those materials” (1992, p. 155). [7] The distinction between primary and secondary sources is important for many aspects of social science, but it is especially important to understand when conducting content analysis. While there are certainly instances of content analysis in which secondary sources are analyzed, I think it is safe to say that it is more common for content analysts to analyze primary sources.
In those instances where secondary sources are analyzed, the researcher’s focus is usually on the process by which the original analyst or presenter of data reached his conclusions or on the choices that were made in terms of how and in what ways to present the data. For example, James Loewen (2007) [8] conducted a content analysis of high school history textbooks. His aim was not to learn about history, but to understand how students are taught American history in high school. The results of his inquiry uncovered that the books often glossed over issues of racism, leaving students with an incomplete understanding of the trans-Atlantic slave trade, the extermination of Indigenous peoples, and the civil rights movement.
Sometimes students new to research methods struggle to grasp the difference between a content analysis of secondary sources and a literature review, discussed in Chapter 4. In a literature review, researchers analyze theoretical, practical, and empirical sources to try to understand what we know and what we don’t know about a particular topic. The sources used to conduct a scholarly review of the literature are typically peer-reviewed sources, written by trained scholars, published in some academic journal or press. These sources are culled in a literature review to arrive at some conclusion about our overall knowledge about a topic. Findings from sources are generally taken at face value.
Conversely, a content analysis of scholarly literature would raise questions not addressed in a literature review. A content analyst who examines scholarly articles would try to learn something about the authors (e.g., who publishes what and where), publication outlets (e.g., how well do different journals represent the diversity of the discipline), or topics (e.g., how has the popularity of topics shifted over time). A content analysis of scholarly articles would be a “study of the studies” as opposed to a “review of studies.” Perhaps, for example, a researcher wishes to know whether more men than women authors are published in the top-ranking journals in the discipline. The researcher could conduct a content analysis of different journals and count authors by gender (though this may be a tricky prospect if relying only on names to indicate gender). Or perhaps a researcher would like to learn whether or how various topics of investigation go in and out of style. She could investigate changes over time in topical coverage in various journals. In these latter two instances, the researcher is not aiming to summarize the content of the articles, as in a literature review, but instead is looking to learn something about how, why, or by whom particular articles came to be published.
Content analysis can be qualitative or quantitative, and often researchers will use both strategies to strengthen their investigations. In qualitative content analysis, the aim is to identify themes in the text being analyzed and to identify the underlying meaning of those themes. For example, Alyssa Goolsby (2007) [9] conducted qualitative content analysis in her study of national identity in the United States. To understand how the boundaries of citizenship were constructed in the United States, she conducted a qualitative content analysis of key historical congressional debates focused on immigration law.
Quantitative content analysis, on the other hand, involves assigning numerical values to raw data so that it can be analyzed statistically. Jason Houle (2008) conducted a quantitative content analysis of song lyrics. Inspired by an article on the connections between fame, chronic self- consciousness (as measured by frequent use of first-person pronouns), and self-destructive behavior (Schaller, 1997), [10] Houle counted first-person pronouns in Elliott Smith song lyrics. Houle found that Smith’s use of self-referential pronouns increased steadily from the time of his first album release in 1994 until his suicide in 2003 (2008). [11] We’ll elaborate on how qualitative and quantitative researchers collect, code, and analyze unobtrusive data in the final portion of this section.
Indirect measures
Texts are not the only sort of data that researchers can collect unobtrusively. Unobtrusive researchers might also be interested in analyzing the evidence that humans leave behind that tells us something about who they are or what they do. This kind evidence includes the physical traces left by humans and the material artifacts that tell us something about their beliefs, values, or norms. Physical traces include such things as worn paths across campus, the materials in a landfill or in someone’s trash can (a data source William Rathje and colleagues [Rathje, 1992; Rathje & Murthy, 1992] [12] have used), indentations in furniture, or empty shelves in the grocery store. Examples of material artifacts include video games and video game equipment, sculptures, mementos left on gravestones, housing structures, flyers for an event, or even kitchen utensils. What kinds of physical traces or material artifacts might be of interest to you?
The original author of this text, Dr. Blackstone, relates the following example of material artifacts:
I recently visited the National Museum of American History in Washington, DC. While there I saw an exhibit displaying chef Julia Child’s home kitchen, where she filmed many of her famous cooking shows. Seeing the kitchen made me wonder how cooking has changed over the past few decades since Child’s shows were on air. I wondered how the layout of our kitchens and the utensils and appliances they contain might influence how we entertain guests, how much time we spend preparing meals, and how much time we spend cleaning up afterward. Our use of particular kitchen gadgets and utensils might even indicate something about our social class identities. [13] Answers to these questions have bearing on our norms and interactions as humans; thus, they are just the sorts of questions researchers using unobtrusive methods might be interested in answering. I snapped a few photos of the kitchen while at the museum. Though the glass surrounding the exhibit prevents ideal picture taking, I hope the photos in Figure 14.1 give you an idea of what I saw. Might the organizational scheme used in this kitchen, or the appliances that are either present or missing from it, shape the answers to the questions I pose above about human behaviors and interactions? (Blackstone, n.d.)
Figure 14.1 A visit to chef Julia Child’s kitchen at the National Museum of American History
One challenge with analyzing physical traces and material artifacts is that you generally don’t have access to the people who left the traces or created the artifacts that you are analyzing. (And if you did find a way to contact them, then your research would no longer qualify as unobtrusive!) It can be especially tricky to analyze meanings of these materials if they come from some historical or cultural context other than your own. Situating the traces or artifacts you wish to analyze both in their original contexts and in your own is not always easy and can lead to problems during data analysis. How do you know that you are viewing an object or physical trace in the way that it was intended to be viewed? Do you have the necessary understanding or knowledge about the background of its original creators or users to understand where they were coming from when they created it?
Imagine an alien trying to understand some aspect of Western human culture simply by examining our artifacts. Cartoonist Mark Parisi demonstrates the misunderstanding that could ensue in his drawing featuring three very small aliens standing atop a toilet. One alien says, “Since water is the life-blood on this planet, this must be a temple of some sort…Let’s stick around and see how they show their respect” (1989). [15] Without a contextual understanding of Western human culture, the aliens have misidentified the purpose of the toilet, and they will be in for quite a surprise when someone shows up to use it!
The point is that while physical traces and material artifacts make excellent sources of data, analyzing their meaning takes more than simply trying to understand them from your own contextual position. You must also be aware of who caused the physical trace or created the artifact, when they created it, why they created, and for whom they created it. Answering these questions will require accessing materials in addition to the traces or artifacts themselves. It may require accessing historical documents or, if analyzing a contemporary trace or artifact, perhaps another method of data collection such as interviews with its creators.
Analysis of unobtrusive data collected by you
Once you have identified the set of texts, physical traces, or artifacts that you would like to analyze, the next step is to figure out how you’ll analyze them. This step requires that you determine your procedures for coding, differentiate between manifest and latent content, and understand how to identify patterns across your coded data. We’ll begin by discussing procedures for coding.
You might recall being introduced to coding procedures in Chapter 13, where we discussed the coding of qualitative interview data. While the coding procedures used for written documents obtained unobtrusively may resemble those used to code interview data, many sources of unobtrusive data differ dramatically from written documents or transcripts. What if your data are sculptures or paths in the snow? The idea of conducting open coding and focused coding on these sources as you would for a written document sounds a little silly, not to mention impossible. So how do we begin to identify patterns across the sculptures or worn paths or utensils we wish to analyze? One option is to take field notes as we observe our data and then code patterns in those notes. Let’s say, for example, that we’d like to analyze how people the use of kitchen utensils, as in Figure 14.1. Taking field notes might be a useful approach were we conducting observations of people actually using utensils in a documentary or on a television program. (Remember, if we’re observing people in-person then our method is no longer unobtrusive.)
If, rather than observing people in documentaries or television shows, our data include a collection of actual utensils, note-taking may not be the most effective way to record our observations. Instead, we could create a code sheet to record details about the utensils in our sample. A code sheet, sometimes referred to as a tally sheet in quantitative coding, is the instrument an unobtrusive researcher uses to record observations.
In the example of kitchen utensils, perhaps we’re interested in how utensils have changed over time. If we had access to sales records for utensils over the past 50 years, we could analyze the top-selling utensil for each year. To do so, we’d want to make some notes about each of the 50 utensils included in our sample. For each top-rated utensil, we might note its name, its purpose, and perhaps its price in current dollar amounts. We might also want to make some assessment about how easy or difficult it is to use or some other qualitative assessment about the purpose of the utensil. To rate the difficulty of use we could use a 5-point scale, with 1 being very easy to use and 5 being very difficult to use. We could even record other notes or observations about the utensils that may not occur to us until we actually see the utensils. Our code sheet might look something like the sample shown in Table 14.2.
Note that the sample sheet contains columns only for 10 years’ worth of utensils. If you were to conduct this project, obviously you’d need to create a code sheet that allows you to record observations for each of the 50 items in your sample.
Table 14.2 Sample code sheet for study of kitchen utensil popularity over time
1961 1962 1963 1964 1965 1966 1967 1968 1969 1970
Utensil name
Utensil purpose
Price (in 2011 \$)
Ease of use (1-5 scale)
Other notes
As you can see, our code sheet will contain both qualitative and quantitative data. Our “ease of use” rating is a quantitative assessment; we can therefore conduct some statistical analysis of the patterns here, perhaps noting the mean value on ease of use for each decade we’ve observed. We could do the same thing with the data collected in the row labeled “price,” which is also quantitative. The final row of our sample code sheet, containing notes about our impressions of the utensils we observe, will contain qualitative data. We may conduct open and focused coding on these notes to identify patterns across those notes. In both cases, whether the data being coded are quantitative or qualitative, the aim is to identify patterns across the coded data.
The “purpose” row in our sample code sheet provides an opportunity for assessing both manifest and latent content. Manifest content is the content we observe that is most apparent; it is the surface content. This is in contrast to latent content, which is less obvious. Latent content refers to the underlying meaning of the surface content we observe. In the example of utensil purpose, we might say a utensil’s manifest content is the stated purpose of the utensil. The latent content would be our assessment of what it means that a utensil with a particular purpose is top-rated. Perhaps after coding the manifest content in this category we see some patterns that tell us something about the meanings of utensil purpose. Perhaps we conclude, based on the meanings of top-rated utensils across five decades, that the shift from an emphasis on utensils designed to facilitate entertaining in the 1960s to those designed to maximize efficiency and minimize time spent in the kitchen in the 1980s reflects a shift in how (and how much) people spend time in their homes.
Kathleen Denny’s (2011) [16] study of scouting manuals offers another excellent example of the differences between manifest and latent content. Denny compared Boy Scout and Girl Scout handbooks to understand gender socializing among scouts. By counting activity types described in the manuals, Denny learned from this manifest content that boys are offered more individual-based and more scientific activities, while girls are offered more group-based and more artistic activities. Denny also analyzed the latent meaning of the messages that scouting handbooks portray about gender; she found that girls were encouraged to become “up-to- date traditional women” while boys were urged to adopt “an assertive heteronormative masculinity” (Denny, 2011, p. 27).
Key Takeaways
• Content analysts interpret texts.
• The texts that content analysts analyze include actual written texts such as newspapers or journal entries, as well as visual and auditory sources such as television shows, advertisements, or movies.
• Content analysts most typically analyze primary sources, though in some instances they may analyze secondary sources.
• Indirect measures that content analysts examine include physical traces and material artifacts.
• Manifest content is apparent; latent content is underlying.
• Content analysts use code sheets to collect data.
Glossary
• Code sheet- the instrument an unobtrusive researcher uses to record observations
• Content analysis- a type of unobtrusive research that involves the study of texts and their meaning
• Latent content- the underlying meaning of the surface content
• Manifest content- the most apparent and surface-level content in a communication
1. Babbie, E. (2010). The practice of social research (12th ed.). Belmont, CA: Wadsworth. ↵
2. Berzins, M. (2009). Spams, scams, and shams: Content analysis of unsolicited email. International Journal of Technology, Knowledge, and Society, 5, 143–154. ↵
3. Neuendorf, K. A., Gore, T. D., Dalessandro, A., Janstova, P., & Snyder-Suhy, S. (2010). Shaken and stirred: A content analysis of women’s portrayals in James Bond films. SexRoles, 62, 747–761. ↵
4. Downs, E., & Smith, S. L. (2010). Keeping abreast of hypersexuality: A video game character content analysis. Sex Roles, 62, 721–733. ↵
5. Greenberg, J., & Hier, S. (2009). CCTV surveillance and the poverty of media discourse: A content analysis of Canadian newspaper coverage. Canadian Journal of Communication, 34, 461–486. ↵
6. Borzekowski, D. L. G., Schenk, S., Wilson, J. L., & Peebles, R. (2010). e-Ana and e-Mia: A content analysis of pro-eating disorder Web sites. AmericanJournal of Public Health, 100, 1526–1534. ↵
7. Reinharz, S. (1992). Feminist methods in social research. New York, NY: Oxford University Press. ↵
8. Loewen, J. W. (2007). Lies my teacher told me: Everything your American history textbook got wrong. Grenwich, CT: Touchstone. ↵
9. Goolsby, A. (2007). U.S. immigration policy in the regulatory era: Meaning and morality in state discourses of citizenship (Unpublished master’s thesis). Department of Sociology, University of Minnesota, Minneapolis, MN. ↵
10. Schaller, M. (1997). The psychological consequences of fame: Three tests of the self-consciousness hypothesis. Journal of Personality, 65, 291– 309. ↵
11. Houle, J. (2008). Elliott Smith’s self-referential pronouns by album/year. Prepared for teaching SOC 207, Research Methods, at Pennsylvania State University, Department of Sociology. ↵
12. Rathje, W. (1992). How much alcohol do we drink? It’s a question…so to speak. Garbage, 4, 18–19; Rathje, W., & Murthy, C. (1992). Garbage demographics. American Demographics, 14, 50–55. ↵
13. Watch the following clip, featuring satirist Joe Queenan, from the PBS documentary People Like Us on social class in the United States: [1]http://www.youtube.com/watch?v=j_Rtl3Y4EuI. The clip aptly demonstrates the sociological relevance of kitchen gadgets. ↵
14. Figure 14.1 copied from Blackstone, A. (2012) Principles of sociological inquiry: Qualitative and quantitative methods. Saylor Foundation. Retrieved from: https://saylordotorg.github.io/text_...ative-methods/ Shared under a CC-BY-NC-SA 3.0 license (https://creativecommons.org/licenses/by-nc-sa/3.0/) ↵
15. Parisi, M. (1989). Alien cartoon 6. Off the Mark. Retrieved from: http://www.offthemark.com/System/2006-05-30. ↵
16. Denny, K. (2011). Gender in context, content, and approach: Comparing gender messages in Girl Scout and Boy Scout handbooks. Gender & Society, 25, 27–47. ↵ | textbooks/socialsci/Social_Work_and_Human_Services/Scientific_Inquiry_in_Social_Work_(DeCarlo)/14%3A_Unobtrusive_Research/14.03%3A_Unobtrusive_data_collected_by_you.txt |
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