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 @Paper title
 
-Physical and psychological health at adolescence and home care use later in life
+Usability Testing of the BRANCH Smartphone App Designed to Reduce Harmful Drinking in Young Adults
 
 @Section I
 
-All developed societies have been going through major demographic changes in the last decades. Improvements in medical science have led to unprecedented increases in life expectancy. These changes and improvements in conjunction with low birth rates have resulted in a progressively ageing society. The demographic changes increase health care costs and threaten the sustainability of long-term care systems. From both an academic and a policy perspective, it is therefore crucial to understand the determinants of long-term care use.
-A large literature in both economics and epidemiology suggests that conditions experienced early in life may have a long-term effect on health. In particular, adverse early life conditions can have a negative impact on mortality cardiovascular disease and cognition. Many illnesses are inherently chronic and long-lasting, leading to persistent health problems and the need for home care. However, some health problems may be persistent when poor health in youth sets in motion trajectories of health-related disadvantages and health and socio-economic risks that may accumulate over the life course.
-One of the main indicators of later-life poor health is the need for long term care. Despite the potential long-lasting impact of poor health in life, we are not aware of studies that compare health problems in adolescence with home care use at older ages.
-In an earlier study in The Netherlands, we found increased long-term mortality in men who at age 18 were more overweight (BMI >= 25). These men also had lower SES, as indicated by their education level and their fathers had a lower occupation level. We reasoned that the increased mortality in this group could be a reflection of impaired physical health and a greater need for supportive services in later age, prior to increased mortality. This was our main hypothesis. In view of prior findings, we would need to examine if the association was moderated by SES and education, (or IQ) and also control for age. For mental health we had no prior observations for testing as this characteristic had not been examined before in this group in relation to mortality.
-The main contribution of this paper is that we compare findings on standardized military service examinations of men aged 18 to study the association between selected physical health characteristics, in multiple domains, at age 18 and an indicator of mental health, and the utilization of home-based formal care services later in life (around age 60-69), using national Dutch administrative microdata. In the Netherlands, the government encourages people to stay at home for as long as possible by providing formal care in the home setting. A large share of long-term care is provided through formal home care, which has been increasing in recent years. The Netherlands has one of the most extensive public long-term care systems in the world. It has a separate mandatory public insurance system for legal entitlements to formal home care use which covers 100% of the population. This insurance covers all chronic care and included a broad range of home care services for older individuals. Users have to pay a copayment, which depends on the type of care and the amount of care used. The monthly copayment is maximized, depending on income and financial wealth, guaranteeing that long-term care was accessible for all income groups.
-We use administrative microdata on Dutch men who were born in 1944-1947 and were examined for military service between 1961-1965. The records include a standardized recording of demographic and socio-economic characteristics including education, father's occupation, along with a standardized psychometric test battery. At the military examination, all conscripts were scored on seven health aspects of relevance for military service, comprising general health, hearing, eyesight, upper- and lower extremities, intelligence and mental stability. Conscripts deemed unfit on any of these elements were deemed to be unfit for military service. We link these data to national data from the death register and data on persons who received home-based formal care services in the period 2004-2013 to investigate the relationship between measurements of poor health at age 18 and the use of these services.
-This paper contributes to the literature in three main ways. First, our measures of early life conditions include health conditions at the beginning of adult life (around age 18). Second, to the best of our knowledge, we are the first to analyse the relationship between early-life health and home care use later in life. Third, thanks to the availability of data on mortality and the use of home-based formal care services over 10 years, we can account for selective survival in our econometric model. This makes it possible to predict home care use based on health measurements at adolescence.
-We combine several sources of data to arrive at the analytical sample. We start from the universe of male recruits from the nationwide Dutch Military Service Conscription Register for the years 1961-1965 and born in the years 1944-1947 (n 400,000). At the time all men, except those living in psychiatric institutions or in nursing institutes for the blind or for the deaf-mute, were called to the military service induction exam at age 18. These data were previously used for the investigation of the relationship between prenatal famine exposure and obesity in adolescence used a sample to study the relationship between prenatal famine exposure and mortality. This sample included: all the 25,283 men born in the Western Netherlands between November 1944 and March 1946 (famine exposed individuals), a random 15% sample (n = 10,667) of men born before November 1944 or after March 1946 in these same cities, and a random 3% (n = 9,087) of men born between 1944 and 1947 in the remainder of the country. In the analyses we account for this oversampling of famine exposed men through weighting. The final sample extracted from the military examination data for further linkage (via unique personal identification number) included 45,037 men.
-These data were linked to administrative data available through the secured remote data access system of Statistics Netherlands. We were able to link 36,923 men with home care utilization status in 2004, the first year this information was recorded. 8,114 were lost from the sample between the start of the administrative registers in 1999 and 2004 to follow-up. Of the missing individuals 3,442 are known to have died, 487 to have emigrated and 4,185 were lost due to other reasons, see Fig 1.
-Conscripts were scored (1 = fit; 2 = fairly fit; 5 = unfit) on seven health characteristics of relevance for military service, and were combined into an ABOHZIS score. (A: Algemeen = General health; B: Bovenste extremiteit = Upper extremities; O: Onderste extremiteit = Lower extremities; H: Horen = Hearing; Z: Zien = Eyesight; I: Intelligentie = Intelligence; and S: Stabiliteit = Mental Stability). For each measurement we define as poor health any measurement that was less than fit. These measurements were available for 98% of the conscripts. Conscripts deemed unfit on any of these characteristics were declared to be unfit for military service (the unfit-for-service indicator) The most common characteristics with poor score, were: Poor Eyesight (15.0%), poor general health (10.0%), poor Lower extremities (8.0%), and poor Mental health (4.5%). Poor health indication on other scores were less common: Poor Hearing (2.2%) and poor Upper extremities (0.9%) was less common.
-In the literature excess weight has also been identified as predictor of later health.. We therefore also included an overweight measure (BMI > 25) from the military examination as a possible predictor of late life home care. At the military examination, a standardized recording of demographic and socioeconomic characteristics including education and father's occupation was also completed. The military examination included a standardized Raven Progressive Matrices psychometric test as an indicator of intelligence.
-Requests for formal home care are evaluated by the Centre of indication-setting Health Care (CIZ). The CIZ has divided the Netherlands into 26 regional care purchasing agencies (`Zorgregiokantoor') that assess the eligibility for home care use. The decision is based on functional limitations of the applicant and health status, but not on income or wealth. In the analysis, potential regional differences in the access and financing of home care are taken into account by linking individuals to their regional health care agency and a dummy variable adjustment for region. Statistics Netherlands distinguishes four categories of home care (non-residential care for which the expenditures are covered by the public insurance system): 1) household care: if an individual has received household assistance, such as cleaning and food preparation, which is partly paid through the `Wet Maatschappelijke Ondersteuning (WMO)', the social support act; 2) personal care: if an individual has received personal care for which the expenditures are covered by `Algemene Wet Bijzondere Ziektekosten (AWBZ)', General law on special sickness costs, such as aid with dressing, washing, eating and, drinking; 3) nursing care: if an individual has received nursing care for which the expenditures are covered by `Algemene Wet Bijzondere Ziektekosten (AWBZ)', such as nursing, aid in medication use or injections and 4) total care: if an individual has received any of the three home care categories. For each individual, the use of any home care in a particular year was recorded. At the start of 2004, the first year of home care use observation, we observed that 0.8% of the men received household care, 0.9% personal care, 1.0% nursing care, and 1.7% any of these three categories of home care use (total care). The use increased to 1.6% for household care, 1.9% for personal care, 1.4% for nursing care, and 3.4% for total care in 2013, the final year of observation of home care use. We will analyse the three different home care categories and the total home care use separately. Between 2004 and 2013, 3437 men died and 586 were lost due to other reasons. Table 1 reports the average value of the health indicators and background variables and its relation to home care use.
-Fig 2 clearly shows that the use of home care is increasing over the years (i.e it is increasing with age). The increase is most pronounced for personal care. Fig 3 shows that there is a strong positive correlation between mortality and home care use and that for personal care and nursing care the mortality is increasing with age. This emphasizes the importance to account for selective mortality (see also the S1 Table).
-Based on the home address of each individual, available for every year, we know which care purchasing agency was responsible for the decision to allow provide home care to specific individuals.
+Electronic screening and brief intervention (eSBI), delivered through devices such as computers, tablets and smartphones, is an increasingly popular method to deliver alcohol brief interventions. Meta-analyses demonstrate eSBI to be effective in reducing alcohol consumption by 1 to 2 drinks per week after 6 months compared to controls. However the majority of eSBIs that have been evaluated are Web-based, as opposed to app-based programs. A recent systematic review of mobile interventions for alcohol and substance use reported that while mobile delivery of alcohol interventions is an acceptable and effective communication channel, targeting of interventions to specific populations is required. Another enduring challenge for eSBI development is usability. A recent review of online feedback for existing alcohol apps reported that nonintuitive functionality, software malfunctions, and lack of personalization of content are frequently cited criticisms of existing alcohol apps. While many eSBI apps are available, the majority are not evidence-based. Indeed eSBI is still in its infancy and should be subjected to multiple stages of rigorous development and testing.
+The app "BRANCH" targets harmful drinking in young adults (18-30 year olds). This study reports the second stage of development of the BRANCH app that aims to evaluate the usability of the prototype app to improve its functioning, content, and design. Usability testing is a crucial stage in the app design process as it provides end user feedback about what does and what does not work in the program. This is an important step as the effectiveness of an electronic intervention has been shown to be associated with its level of usability. Conversely, poor usability is associated with nonusage.
+Usability testing is widely used in digital health intervention design, and more recently in the development of digital programs for alcohol harm reduction. A range of methods for usability testing exist including questionnaires, think-aloud observation, and interview-based techniques. For alcohol field, the interview-based techniques are more widely used. Crane et al conducted usability testing on an app designed to reduce alcohol consumption using think aloud testing and semistructured interviews to determine if the features in the app were acceptable and feasible to users and also determine what could be improved. Similarly, Davies assessed the feasibility and acceptability of a digital alcohol harm reduction tool for adolescents, and Dulin conducted usability testing via questionnaires and interviews of a smartphone intervention for adults. These studies highlighted issues of ease-of-use, clarity of information, and appealing design as integral to improvement of the digital tools.
+However, the BRANCH app is different from other alcohol harm reduction apps in that it targets young adults specifically. Young adults' preferences for the usability of apps may differ from other groups who have lower usage rates of apps, such as older population. Indeed, young adults have the highest level of smartphone ownership out of all age groups. Referred to as "digital natives," many are proficient in technology use having grown up being exposed to computers, smartphones, and the Internet . It is therefore critical to optimize usability for apps targeting this age group. Moreover, usability data and experiences may be of use in the development of other apps designed to influence substance use among young adults.
+The aim of the current study was to explore experiences of app usability, in terms of content, functionality, and design of the BRANCH app to improve user experience.
 
 @Section M
 
-The anonymity of the included individuals is guaranteed by Statistics Netherlands. The data can only be analyzed at Statistics Netherlands or through Remote Access. Access to the data is only possible with fingerprint ID and the personal smartcard. The study was reviewed by the Institutional Review Board of the Columbia University Medical Center in New York, NY. The Board determined that studies on this study population do not meet the DHSS definition of 'human subjects research' and are exempt from IRB approval. In the Netherlands, the study does not need approval by Ethical Review Boards or by the National Data Protection Authority (College Bescherming Persoonsgegevens) as all study procedures are in compliance with Dutch privacy legislation and do not need the consent of the data subjects concerned or of their relatives. The study is based on population wide administrative records and not on patient records.
-We seek to find the association between early-life health measurements and home care use later in life. We postulate the following panel probit model for home care use.  where  represents a latent variable of the observed home care indicator; xi is a vector of time-invariant regressors (measured at age 18), betat is a period effect, etai is an unobserved individual effect capturing unobserved heterogeneity and epsilonit denote standard normally distributed, serially uncorrelated error term assumed to be independent of xi. An individual is observed using home care in year t = 2004,...,2013, hit = 1, when .
-An issue is that selective survival/attrition which may depend on home care use in the previous period (see Fig 2) may distort the analyses. We therefore also include a probit model for survival  where  represents a latent variable of the observed mortality indicator; alphah captures the effect of home care use in the preceding period on mortality; alphax captures the effect of time-invariant regressors on mortality, alphat is a period effect and, thetai is an unobserved individual effect, and vit denote standard normally distributed, serially uncorrelated error term assumed to be independent of xi. For the initial period (t = 2003, before home care use is observed,) and the first period, t = 2004, we assume a model including only the time-invariant regressors and a period-specific intercept, alphat. An individual has died in year t when . We have selective survival by allowing the individual heterogeneity terms of the survival equation, thetai, to be correlated with the individual heterogeneity terms of the home care use equation, etai, with rho = Corr(thetai, etai), i.e assuming a bivariate normal distribution for unobserved heterogeneity. The joint likelihood is estimated using the STATA procedure cmp.
-For each of the four home care use categories, we estimate a panel probit model and the bivariate panel probit model accounting for selective survival. We also estimate models that includes an interaction between the health measurements and the binary (manual: self-employed, unskilled and skilled vs non-manual: professional and clerical) indicator of the father's occupation or with the discrete education level indicator (low, middle, high).
-In all analyses we account for oversampling of the famine exposed men using weighted estimation with weights equal to the probability to be sampled, specifically the weight was one for the famine exposed men, 1/0.15 for men born before November 1944 or after March 1946 in the famine region, and 1/0.03 for men born in the remainder of the country.
+Qualitative interviews were chosen as most appropriate to meet the aim of the current project. While other methods such as questionnaires can provide useful overviews of app functioning, the level of fine-grained detail provided can be limited. Qualitative methods provide additional insights as they encourage participants to think about ways to improve usability and identify unanticipated challenges. Focus groups were chosen as the most appropriate method of data collection instead of 1:1 interviews as they allow for views to be developed and discussed, and also for individual opinions to be expressed. As the aim of the study was to identify specific usability issues, the intention was that participants in the focus groups would remind and prompt each other about specific issues they experienced, hence yielding higher identification of usability issues compared to 1:1 interviewing. Ethical approval was obtained from the University Ethics Committee (ref. number HR14/150453).
+Young adults, aged 18-30 years, who lived in South London and scored 16+ on the alcohol use disorders identification test (AUDIT), indicating harmful drinking (AUDIT score between 16-19) or probable dependence (AUDIT score >=20).
+The app "BRANCH" targeted harmful drinking in young adults. Prototype development was informed by 3 studies: (1) a systematic review of engagement promoting strategies for online substance use interventions, (2) a review of user-reviews of existing alcohol eSBI apps available on iTunes and Google Play stores, and (3) focus groups with young adults drinking at harmful levels and residing in South London exploring their preferences for content features and style for an alcohol brief intervention app. The prototype was designed iteratively, using a user-centered design approach (UCD). This involved collaboration between the program developers, research team, and target population. The core functions of BRANCH were based on the FRAMES model (feedback, responsibility, advice, menu of options, empathy, and self-efficacy) of alcohol brief interventions, which has been previously adapted for eSBI. The FRAMES model is based upon the principles of motivational interviewing, an established and evidence based method to reduce alcohol harm. The core functions included a drinking diary for recording alcohol consumption (see Multimedia Appendix 1) and a goal setting function where users could set weekly goals based on cost, calories, and alcohol units as well as setting a drink free day (see Multimedia Appendix 2). Users monitored their drinking over time and received feedback on it, both descriptively and graphically. Information on drinking risks and cutting down was available to users (see Multimedia Appendix 2).
+In addition to the core components, several strategies to optimize engagement with the app were incorporated. In order to tailor the app to young adults, these strategies were developed in collaboration with a user group recruited from the target population. The two main components young adults requested were social features and tailoring of the app to broader wellbeing issues associated with alcohol use. Consequently, the app included a Twitter-style newsfeed enabling interaction between app users, as well as providing personalized notifications, motivational messaging, and reminders based on goals (see Multimedia Appendix 3). The research team could also upload relevant material for young adults, such as links to Web-based articles, YouTube videos, and photos. There was also a personalization feature in which the app users selected their motivations for cutting down drinking when signing up. These motivations were chosen by the user group and included options such as mental health, sugar intake, appearance, and weight. Personalized feedback and targeted information was delivered to users based on their selection of motivators. For example, if a user selected "fitness" as their primary motivator, they would receive tailored messaging on their newsfeed on this topic as well as feedback on how much exercise would be needed to burn off the alcohol calories they had consumed over the last week. Additionally, users were allocated to a team based on these motivators. Users could compare their progress against other users in their team and were awarded points for engaging with the app (see Multimedia Appendix 3). The app was Web-based, and could therefore be accessed from all devices.
+Participants were recruited through Gumtree, an online classified and social community website. Potential participants were invited to take part in a focus group interview to test the app designed to support young adults reducing their alcohol use. A link was provided to an online screening questionnaire where they completed the AUDIT and provided their contact and basic demographic data. Eligible participants were invited to take part. Participants who attended a focus group interview were compensated $30 for their time.
+The focus group participants were provided with the BRANCH app 1 week before and instructed to use it daily over the course of the week to monitor their drinking. Participants were provided with the following specific tasks to complete: (1) set up the app, (2) fill out a weeks' worth of drinking in the drinks diary, (3) set a goal and 3 drink free days, and (4) join a team and review team feedback (See Multimedia Appendices 1-).
+A topic guide was designed to explore the extent to which the participants found the different features acceptable, in terms of content, features, and design. Participants were asked to give their views on their experience of using the different features in the app, focusing around what did and what did not work well. Written informed consent was obtained before commencement of the focus group. The focus group was facilitated by 3 researchers (JM, JD, and RD). They were introduced to participants as researchers who were developing an app to reduce harmful drinking. JM led the group; JD and RD took notes of key themes.
+Focus group interviews were recorded and transcribed verbatim by a professional transcription company. All data were coded using NVivo qualitative data analysis software (QSR International Pty Ltd. Version 10, 2012). JM coded the transcripts and JD double-coded. Any discrepancies that arose were discussed until a consensus was reached.
+A thematic analysis was undertaken as outlined by Braun and Clarke. A deductive approach was used. Usability issues were coded into categories of (1) App content, (2) Functionality, or (3) Design. Each of these categories was considered in terms of being a barrier or an enabler to use or a suggested improvement. Themes were systematically refined by going back and forth between the data and the coding framework.
 
 @Section R
 
-First, we investigate whether the unfit-for-service indicator at the military examination predicts home care use later in life, taking into account other characteristics that may influence home care use: father's occupation (in six categories), IQ measurement at age 18, a dummy for the care purchasing agency region and, a quadratic trend in the month of birth. Father's occupation measures the socio-economic position of the household at age 18. Intelligence, as measured by an IQ-test, affects both health and the take-up rate of home care use. We do not include the education level, because education is likely to be an endogenous variable. The quadratic trend in the month of birth is included to capture the age effect on home care use (together with the period effect). The estimated odds ratios are reported in Table 2. The full estimation results are available upon request. This unfit-for-service indicator clearly predicts home care use later in life. Accounting for selective survival hardly influence the estimation results.
-Next, we estimate models which include the seven health indicators measured at age 18,: overweight (BMI > = 25), poor general health, poor eyesight, poor mental health, poor upper extremity, poor lower extremity, and poor hearing. Again, we also include in our models father's occupation, IQ measurement at age 18, care purchasing agency region, and a quadratic trend in the month of birth.
-The reported estimated odds ratios of health measurements on homecare use in Table 3 suggest that healthy ageing starts early in life. The estimated odd's ratios of other control variables can be found in the S2 Table and the full table with coefficients in the S3 Table and the S4 Table. Poor mental health at age 18 increases the probability of all types of home care use: males scoring a 'fair' or 'unfit' have a 1.5 times higher probability to receive total care 50 years later compared to men scoring `fit' on mental health and 3 times higher probability to receive household care. Being overweight at age 18 increased the risk of later life home care use by 30%. General health problems early in life and problems with legs or feet increase the probability of home care use only somewhat (1.1 times). Other smaller effects are seen for Poor eyesight at age 18 which increases the probability of the need for household and personal care and for poor hearing at age 18 which increases the need for nursing care. Comparing the results in the upper panel of Table 3 with the results in the lower panel shows that accounting for selective survival lowers the estimated impact of the health measurements at age 18 on home care use later in life.
-Socioeconomic status early in life has a long-lasting effect on health leading to changes in home care use later in life. This is reflected in the statistical significance of the marginal effects of father's occupation on home care use (S1 Table). However, the socioeconomic status is also directly related to health early in life, the health measurements at age 18 we use. We therefore also estimate a model that includes an interaction between the health measurements and the binary (manual: self-employed, unskilled and skilled vs non-manual: professional and clerical) indicator of the father's occupation The resulting odd's ratios of the health measurements on home care later in life, shown in Table 4 indicate that the impact of early health measurements on home care use differs substantially by socioeconomic status. Whereas the impact of poor general health on home care use is larger for men from lower socioeconomic background (father with manual occupation), the impact of overweight and poor mental health is larger for men from higher socioeconomic background (father with non-manual occupation).
-It is well known that the education level of an individual is an important factor in predicting home care use later in life. However, education is also likely to be endogenous, as poor health limits educational progress and because confounding factors may influence both education choice and health later in life. For this reason, we did not include education in the control variables and did not estimate a model with interaction between the education level and the health measurements, similar to the interaction model for father's occupation. A separate analysis by education level suffers less from this endogeneity.
-Educational attainment is observed at the military examination at age 18 for each individual and we group the individuals into three levels: low, medium and high education, depending on the type of high school they attended. At the time the individuals in the study went to school the education system in the Netherlands was characterised by a minimum school-leaving age of 14.
-The resulting odds ratios of the health measurements on home care use later in life, reported in Table 5, indicate substantial differences by education level. The impact of poor mental health in adolescence on home care use later in life seems much larger for the high educated. Note that poor mental health is very rare amongst the high educated men. Being overweight and poor general health have the largest impact on home care use for the less educated men. Problems with upper extremities, arms or hands, and lower extremities, legs or feet, only affect the home care probability of the less educated.
+A total of 70 people completed the online screening survey. Of these, 32 (46%) scored 16 or more on the AUDIT, were between 18-30 years of age, and lived in South London.
+A total of 20 participants attended 1 of the 3 focus groups with 6 to 7 participants in each over a 1-month period in August 2016. These numbers in each group allowed for meaningful discussions to take place between participants. Of the 20 participants, 18 were female (90%), 10 (50%) were employed, 1 (5%) was unemployed, and 9 (45%) were students. The mean age was 23 years (SD 3.9). The mean AUDIT score across the participants was 21 (SD 5.7).
+This theme reflected how all the participants wanted simple and fast functionality, with features that would minimize the amount of effort, input, and time required from them. Features that had efficient and automated functionality were praised as enablers to usability. For example, being able to quickly complete functions in the app such as posting a newsfeed message, setting up the app, or adding data to the drinking diary via a guided walkthrough.
+However, while participants typically appreciated features of the app that functioned well, some still expressed views that there were scopes for improvements. When discussing their experiences of using the app, several participants reported becoming quickly frustrated when a feature was hard-to-use or took too much time. Some expressed strong views that their time was precious and that they did not want to spend unnecessary time inputting data, such as when entering drinks into the drinking diary:
+Generally when I'm having a cocktail I can't put in a brand so it's difficult...for example, a Long Island Iced Tea...has five different variants of alcohol in it...
+And if you had a double, like a double gin and tonic, I had to put in a single and then a shot because you can't put in a double.
+Many participants also wanted push notifications (ie, reminders) on their phone to prompt them to use the app. A few wanted reduced scrolling to find information on the newsfeed and a help feature to facilitate app usage. Functionality requests were typically related to increasing the level of "automation" in the app, subsequently reducing the amount of time required to use it. For the majority of the participants, increasing automation seemed to improve usability and make the app more valued.
+Another important finding that arose was related to the impact that the quality of the functionality of an app can have on a user's intentions to interact with it. There was a consensus for deleting apps that did not immediately function as expected:
+The NHS Change for Life? Was it yellow?
+Yes, it was that and I hated it. The notifications were awful, it just wouldn't let me do anything so I was like what's the point of you? Just delete.
+I really hate apps that do that when they send you notifications as well and you still get emails.
+This underlines a difficult balance between too little and too much output, both of which impact usability. As this quotation suggests, it is not a case of providing users with as much content as possible, instead carefully tailoring the content to the requirements of the individual user. Overall, what participants appeared to want from the functionality of BRANCH were features "at their fingertips," pressing as few buttons as possible, in a fast and seamless interaction. If this was not achieved then there was a risk of losing the user entirely.
+The design of the app was the usability issue most discussed in all the focus groups. Participants frequently commented on the need for the app to have a well-considered design, with short pieces of clearly presented text and features that were easily distinguishable from one another. An aesthetically displeasing app seemed to be considered to be a major usability barrier. For instance, many participants commented on how the newsfeed was too text heavy, with large blocks of text, not separated by pictures or colors, which made the information difficult to absorb and certain core features not clearly distinguishable:
+Did anyone get any goal related messaging?
+I got something like 'you went to a barbeque this weekend'...
+No, it wouldn't have been that, it would have had a star next to it here on the newsfeed...
+Oh yeah, look, oh dear...didn't achieve your goals.
+This is a critical issue as participants were not aware that certain integral features aimed at reducing alcohol-related harm even existed, as the buttons and tabs through which they were advertised were not easily discernible from other newsfeed content.
+While participants seemed to express the view that too much text and a poor design hindered usability, the use of multimedia in the "information about drinking" section was the preferred style of most of the participants. This section had been especially designed with an infographic style, which aims to present complex information in easy-to-digest, short components in a colorful, succinct presentation with lots of pictures (see Multimedia Appendix 2):
+I like that, I think that would be better, that style, on the Newsfeed. Because I think I'd be more inclined to read it with the pictures and bits and bobs. Cause that looks more...like if you clicked on that and then there's something in different colours and...Yeah, looks really good.
+From this extract, it is apparent that the design of the app can impact the level of engagement a user has with it; in this case, motivating the user to read through information provided. Appealing designs seemed to promote usage while those which were difficult to digest or read through discouraged usage.
+Another significant finding about the design of the app was the importance of consistency in style. While efforts were made to present a consistent and coherent theme throughout the design of BRANCH, many participants still expressed a desire for a greater level of consistency. However, it appeared from the views expressed in the focus groups that while participants unanimously agreed that a consistent and appealing design was integral to app usability, participants could not necessarily agree on the type of design which was the most appealing, with many different opinions being expressed. This identifies another usability barrier for BRANCH, ie, providing an aesthetic that is agreeable to all.
+It looks a bit like it was maybe made on Word. So it just needs to be a bit more like corporate.
+It was very green.
+I didn't find it that exciting and fun to go into like other apps...they're colourful and, you know, didn't find it that...found it quite bland.
+Overall, this theme highlights how important a well-considered design is to the usability of an app. Participants reported that to promote usability and subsequent motivation to engage with the app, information must be clearly and succinctly provided, with standout features and a consistent design throughout.
+Maximized personalization of app content emerged as an important usability issue. Personalization was presented as a two-fold concept where participants wanted the app to be both automatically personalized to them as much as possible, but they also wanted the autonomy to personalize the app by themselves. Providing autonomy gave participants a sense of empowerment over their interactions with the app, and made them feel in control of their drinking.
+While participants commonly enjoyed the personalization of the motivators and feedback features, there were aspects of the app that some reported could be improved. A particular issue was the daily newsfeed messages. These messages were sent to the entire user-base each day and were generic and not targeted to the individual. The majority said that these messages were not relatable (See Multimedia Appendix 4). Indeed, participants appeared to adeptly identify any area of the app that was not specifically tailored to each user. Surprisingly, this is in spite of the messages being written by the user-group of young adults with whom the app was developed. For the focus group participants, it seemed that personalization to every aspect of the individual, such as motivations for use, preferences for style and content, and even targeting geographical area, were usability enablers.
+Equally, while participants wanted maximum automated personalization, they also wanted independence and autonomy to personalize the app by themselves. For example they wanted to be able to select whose posts were visible on their newsfeed and to be able to personalize the colors and content in the app. Having the option to personalize the app made them feel that the app was unique, belonging to them, and tailored specifically to their own preferences, which made the app more relatable and appeared to increase the usability of the app:
+Cause if it was personalise...you could say that I don't like this kind of tip or I don't like certain things, and then you could kind of have it specific to you...
+Or you [could] save it for later. 'Cause a lot of these things...could be something you might not need now but in a month's time you might think, oh, let me have a look on that app.
+A novel feature of the app was the "social" component, where participants could post messages and interact with other users through the newsfeed and a "teams" page where users collected points for engaging with the app (see Multimedia Appendix 3). The majority of participants found the newsfeed feature a useful way to connect with other users, which made them feel like they were part of a community of like-minded others. Participants compared the newsfeed feature with other social media apps they enjoyed using, like Facebook, and reflected on how the newsfeed elevated using the app from an isolated, solitary activity to something that is shared with and connected to others. Participants also found it a useful tool to be able to compare their experiences with that of others, which enabled participants to normalize their experiences and motivated them to both continue using the app and to continue their drinking goals.
+However, not all participants had a positive view on connecting with other users on the newsfeed. As the newsfeed connected users together who did not know each other, some participants reported that connecting with strangers was irrelevant to them. Participants held conflicting views on this issue and discussed how they had different ways of using online social tools, with no single model being suitable for everybody. Some users liked to be very active, while others did not want to be involved at all. In general, participants wanted the flexibility to be able to choose how involved they were with the social features:
+You've got the danger of weirdoes and all that kind of stuff...
+I mean I don't care what Steve from Birmingham has got...it's irrelevant for me...I would opt out of other people's comments.
+I liked hearing other people's struggle and I liked hearing about other people's triumphs. I didn't feel so bad when I kind of, you know, fell off the wagon myself, okay, it's not just me.
+While the social feature of the newsfeed was highly praised by the participants, the teams section of the app was one of the most criticized areas. Participants reported that the teams concept was underdeveloped and not engaging to use. In particular, most of the participants mentioned that the objective of joining a team and the benefits of the feature, (which provided points for using the app) were not clear. However, participants generally still thought the feature had merit but that it needed to be improved. One method participants suggested to improve the usability of the Teams section, was to make it more socially interactive, and have a live feed where users could interact specifically with people in their team. However, as mentioned above, some participants were hesitant about interacting with people they did not know, and that interactions with friends would be more meaningful:
+I think what needs to be really clear is once you've picked a team and once you're in a team what can you do?
+What do you get for winning? Otherwise it all just seems a bit pointless.
+I'd just quite like to...go with my six or seven mates who all play football...and then your newsfeed is based around the team that you choose, so you see what your mates are saying.
+Overall, the option for social connectivity within the app was a highly praised feature, which participants strongly believed improved the usability by fostering an engaging and interesting user experience that could be shared with others. However, participants also highlighted the need for improvement in the teams section, making the objectives and concepts clearer to understand and also increasing the level of social connectivity.
 
 @Section D
 
-This paper is the first to study the relationship between health indicators at age 18 and the use of formal home care later in life at age 57-69. In the empirical analysis, we use administrative data on a sample of Dutch men born in 1944-1947 to estimate bivariate panel probit models that account for unobserved heterogeneity and selective survival. As a further strength of the current analysis we note that home care use was evaluated taking regional variation in home care access and financing into account.
-Our results indicate that poor health early in life, especially having poor mental health or being overweight at age 18, is associated with problems that require home-based formal care services later in life. Having poor general health or problems with legs or feet early in life increase the probability of health problems later in life to a much smaller degree. We show that the impact of poor lower extremities on home care use is mostly seen among men from a lower socioeconomic background (fathers with manual occupation). We also show that, for less educated men, both being overweight or being rated with poor general health at age 18 has a larger impact on home care use later in life than for medium or higher educated men.
-Some specific conditions that lead to a poor health rating on physical characteristic included congenital malformations, blindness, deafness and conditions acquired during childhood (paralytic polio, bone fractures cardiac and other infections). Much progress has been made since the 1960's on the prevention of many of these conditions.
-In recent years there has been a continued policy debate about the sustainability of national long-term care provisions, due to the ageing of the population in all developed countries. In the Netherlands. Starting in 2013, several reforms have shifted an increasing part of the financial burden to households, these now have to face higher medical out of pocket expenditures for long-term care. Our results highlight the potential of interventions to diagnose and treatment of adults with mental health problems and to educate them about the long term impact of weight problems on later health.
-Our study has some limitations. First, large data sets for similar analyses among women are not available in the Netherlands. Second, although the follow-up time in this study is close to 50 years, the utilization of home care at age 70 was still relatively low. Continued follow-up of the cohort will therefore be needed to monitor the utilization of home care with further aging of the study cohort. Third, we describe relations between early-life health measurements and later life home in an observational study, subject to unmeasured sources of bias. Although suggestive, the reported relations therefore fall short of providing measures of causal effects.
+The aim of this study was to explore the experiences of enablers and barriers to usability for a prototype eSBI app called BRANCH targeting harmful drinking in young adults. The study found that an easy-to-use interface, with minimum required user-input and high levels of automated functioning were the most important usability requirements for participants. It also found that clear, consistent, and visually appealing design was integral to the level of usability. The option for social connectivity was important to participants, as were high levels of personalization. Poor functionality, text heavy content, high user-burden costs in time and effort, and unappealing design were considered major usability barriers. This study showed how focus group interviews can be used to get detailed feedback on the usability of an alcohol app, which can then be used to improve its effectiveness and ultimately increase its potential for reducing drinking among users.
+The findings of this study are consistent with previous research, which found that difficulties in inputting data were among the most frequently criticized functionality issues in existing eSBI alcohol apps. High data entry burden costs, which were considered a usability barrier by participants using BRANCH, have been reported to be a primary reason why people stop using health apps. Participants wanted features that reduced the amount of time and effort required from them. They suggested that reminders, guided walkthroughs, and reduced scrolling were all features that could improve usability. The level of data participants are expected to enter into self-monitoring apps should be carefully considered in future app development. Indeed, frustration with poor performance is one of the most common complaints of app users and results in apps being deleted entirely.
+A well-conceived visual design was integral to the usability of BRANCH. Participants wanted clear, concise presentation of information which was not text heavy, a finding which is consistent with previous research. Poor design, such as features and buttons not standing out, inhibit use as users are unable to distinguish between features. This has implications not only for usability but also for the potential effectiveness of the intervention. If an eSBI user cannot identify that a particular feature is available, then the user will not be exposed to the targeted alcohol harm reduction intervention. Furthermore, visual design influences the credibility of an app and users are more likely to rate consumer health information on the web as credible if it is presented in an aesthetic style.
+An issue closely related to usability was engagement. Engagement refers both to how a user interacts with a technology and their emotional response to it. For BRANCH, participants often stated how positive experiences of usability made them engage more with the app, making them more likely to keep on using it. For example, participants praised the newsfeed feature as one which enhanced their experience of app usability, as it provided them with meaningful interactions with other users and a sense of community. Participants also praised how personalization made the app feel more tailored to their own needs, providing a positive user experience. This is consistent with the elaboration likelihood model (ELM), which proposes that people are more motivated to engage with and process information more thoroughly if the message is personally relevant and meaningful. The theoretical model of user engagement by Short et al proposes that an individual's characteristics and personal circumstances may influence their user experience of the app. It may be that future applications can enhance usability by targeting features and increasing personalization to target specific user characteristics.
+Not improving usability would result in frustrating features and boredom is associated with disengagement with online programs. The teams section in BRANCH, where participants were awarded points for engaging with the app, was criticized for being a major usability barrier because the objective of the feature came across as confusing to participants. While gamification methods (the use of gaming design in nongaming contexts) are popular and effective methods with which to improve engagement, it is apparent from the present study that the design of such features needs to be carefully considered in the context of the intervention, otherwise its relevance will be challenged.
+Engagement is an ongoing issue for health app development. Issues such as low login rates and limited use of intervention features are consistently reported in literature. Findings from the online intervention "Down Your Drink" reported that only 6% of users stayed with the program until the end of the 6 week program. Enhancing the usability of engagement features is crucial to the effectiveness of an eSBI app. The more usable an app is, the more likely an individual is to revisit it and repeatedly use the program intervention features. Indeed, higher engagement through logins and repeated use is associated with better participant health outcomes.
+Optimizing usability for eSBI apps is a critical step in the development process. Consumer expectations for digital products are high and if products do not meet their expectations, then they may cease to use them. A recent survey demonstrated that peoples' tolerance for poor performing apps has reduced, with approximately 50% of people reporting that they are less tolerant of problems in apps they use compared to a few years ago. In case of young adults, the age group with the highest use of health apps, if an app does not function as they want it to, regardless of its objective, they will delete it. It is not good enough to have only a strong evidence-based core intervention, the whole package of delivery, including design, aesthetics, usability, and functionality needs to be iteratively refined and improved. As there are high demands on apps such as BRANCH that target skilled technology users such as young adults, the development of future eSBI apps that allows for usability testing with representative users may help support the effectiveness of eSBI to reduce harmful drinking. The BRANCH app is currently being evaluated as part of a randomized controlled trial with results expected in early 2018.
+Significant efforts were made to recruit a sample of young adults, both male and female; however, the majority of participants (90%) were female. This is consistent with a previous study for a Web-based alcohol intervention, which also reported a high sample of females (73%). The advertisement was designed for both men and women, however more females replied to the advert and requested to bring along more female friends, creating a multiplying effect. While potentially introducing bias, there is research to suggest that women are more motivated to use the Internet for seeking health information and are more likely to use eHealth interventions as recommended. Therefore, the sample in the current study may represent the type of individuals more likely to engage with the Web-based BRANCH app. Future studies may wish to explore these differences in more detail, examining how males and females engage with eSBI, informing how interventions can be tailored to gender. Participants were not screened on their intention to cut down their alcohol use. Consequently, there may have been differences between the participants in the current study and some end-users in terms of how motivated they would be to engage with the app. However, BRANCH was not designed exclusively for those wishing to cut down, but also for those wanting to monitor their use or learn more about the risks of drinking. While this data was not collected, there were 20 participants in the present study who would have likely held a range of reasons for wanting to participate in the study, reflecting the target end-user of the app. Future studies should be further improved by specifically targeting at recruitment stage the types of end users the app is designed for. Focus groups can be subject to response bias, where participants provide answers based on what they think the researchers want to hear. However the findings in the current research reflect those in previous research both from the alcohol field and from usability testing research in the computer science disciplines, suggesting that the results have meaning across different populations. Focus groups may also limit the full range of views due to convergence of ideas. Future research may wish to conduct both 1:1 as well as focus group interviews. The participants in the focus group scored high on the AUDIT. Alcohol is a topic seen as sensitive and stigmatizing, therefore participants may not have been comfortable sharing all of their experiences of using the app, as this may reveal details about their level of drinking.
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