abstract: # Background
  .
  The South African health care delivery system has shifted focus to primary health care since 1994. For this purpose the Batho Pele principles were introduced. Nurses claim, however, that since the introduction of these principles patients and their families have been making unnecessary and sometimes impossible demands of nursing staff. This article presents the perceptions of the professional nurses regarding the introduction of the Batho Pele principles in their workplace.
  .
  # Objectives
  .
  To describe the perceptions of professional nurses regarding introduction of the Batho Pele principles and to recommend guidelines to facilitate measures to realise the objects of these principles.
  .
  # Method
  .
  A qualitative, exploratory, descriptive and contexual research design was used. Six audio-taped focus group discussions and field notes were used to collect data from purposively sampled participants who have worked in the outpatient departments of hospitals in the Port Elizabeth Hospital Complex. Guba's model of trustworthiness was used to confirm integrity of the study, whilst the participants were kept anonymous, protected from harm and participated voluntarily. Data analysis was done using Tesch's data analysis spiral and with the involvement of an independent-coder.
  .
  # Results
  .
  Three themes emerged, revealing that the professional nurses perceived the objectives of the Batho Pele principles as difficult to uphold due to the inadequate planning prior to their implementation. Inadequacy of human and material resources aggravated this perception.
  .
  # Conclusion
  .
  Professional nurses are not happy with how things are in terms of introduction of the Batho Pele principles, but are optimistic of a positive change in the near future.
author: Sindiwe James; Thenjiwe M. Miza**Correspondence to:** Sindiwe James **Email:**<email@example.com>, **Postal address:** Department of Nursing Science, Nelson Mandela Metropolitan University, 2nd Floor, R-Block, North Campus, Port Elizabeth 6031, South Africa[^1]
date: 2015-03-09
institute: 1Department of Nursing Science, North Campus, Nelson Mandela Metropolitan University, Port Elizabeth, South Africa; 2Livingstone Hospital, Port Elizabeth, South Africa
references:
title: Perceptions of professional nurses regarding introduction of the Batho Pele principles in State hospitals

# Introduction and background

The quality of care rendered to patients has always been the main focus of health care, and yet this still remains a challenge to State hospitals in South Africa (SA). Quality of care refers to the attributes or characteristics of excellence, with an emphasis on the principles of applicability and acceptability (Muller 2009). If these principles are adhered to, quality healthcare delivery can be achieved. Patients associate 'quality of care' with the quality of care that they receive as well as the amount of empathy shown towards them by nursing staff (Booyens 2008).

In recent years the rendering of quality care in South African State hospitals has been compounded by the resignations of senior and experienced nurses in all sectors, including outpatient departments of different hospital units. This brain and skill 'drain' happened at the same time as inception of primary healthcareopportunities for all in SA. Primary health care was seen as the key element in the Government's plan to transform the health services in SA and to bridge healthcare service delivery gaps where possible (Muller 2009). In order to accomplish this a White Paper on the Batho Pele principles was adopted and published in 1997 as a framework for provision of service delivery by the Department of Health (DoH) (DoH 2001) The core value of these principles, as stated in the English translation, is that people are made a priority. The aim is to ensure that healthcare providers are sensitive to patients' healthcare needs. These principles, which guide healthcare providers to observe standards of consultation, service standards, access, courtesy, information, openness and transparency, redress and value for money (Muller 2009) are discussed next.

## The Batho Pele principles

These prinicples are almost synonymous and therefore difficult to view separately. For the purposes of optimal discussion they will therefore be grouped accordingly.

### Standards of consultation, service, access and courtesy

The above principles insist that citizens should be *consulted* regarding the level and quality of the public service they receive. Should the need arise, they should be further referred to gain *access* to the correct healthcare facility. Here the emphasis is that patients know how healthcare services are classified to ensure that they receive prompt care. As those who have easy access to this information, healthcare workers (for the purposes of this article, professional nurses) should frequently inform the patients in this regard, be tolerant to their inquiries and be respectful of patients as individuals. Such actions will enhance the realisation of effective access to healthcare services.

The principle of access in terms of the Batho Pele principles means that patients should have equal opportunities in terms of resources and facilities (DoH1997, in Muller 2009). In this regard the DoH has vowed to promote and improve access to healthcare facilities through provision of comprehensive healthcare services within a 5 km radius of catchment areas at all times (DoH 2001). However, access may go beyond the designated catchment areas, and hence the need at times for a further referral.

### Information, openness and transparency, redress and value for money

Besides consultation, access and courtesy, the Batho Pele principles also make reference to the provision of fully accurate information to citizens about the public health services to which they are entitled. The public have faith that the professional nurse will give them accurate information regarding health issues; therefore the nurse has the responsibility to ensure that (s)he is aware of all changes and new developments in the healthcare sector. Whilst sharing information with patients, healthcare workers (professional nurses) should observe the culture of openness and transparency. Furthermore, the Batho Pele principles determine that public services should be provided economically and efficiently in order to provide citizens with the best possible service for the value of their money.

Having mentioned the various principles that comprise the notion of Batho Pele, one must also remember that these are informed by three sets of beliefs: care, teamwork and service.

## Care, teamwork and service

Caring for patients in outpatient departments cannot be done in isolation of other healthcare providers and relevant stakeholders. Teamwork and support is of even more importance in an outpatient department for the sake of interdependence and good-quality service. Covey (1989) states that interdependence opens up worlds of possibilities for deep, rich, meaningful associations and increased productivity. As mentioned earlier, some patients will access the healthcare service as referrals from other service centres or will need to be referred to other services. The procedure relating to referral of patients requires consultation of expert knowledge as well as coordination of all processes involved, hence the need for efficient teamwork.

The concept of teamwork becomes more appreciated in health care as it brings with it the experience of interdependence, complementary skills, information sharing and making decisions together towards the set goals of the unit (Muller, Bezuidenhout & Jooste 2011:334). In most hospitals a multidisciplinary team is formed whereby all the health care disciplines meet to discuss the care and referral needs of their patients. Booyens (2008) states that the aim of this teamwork is to determine priorities and clarify roles and responsibilities which, in the context of this article, are significant in promoting quality healthcare service.

In some instances, as is the case in the hospital where the co-author of this article works, the same outpatient department's patients are referred from clinic to clinic to satisfy their healthcare needs. This action may be confusing and annoying to some patients. Explaining the process of referral in a caring manner to patients is therefore a crucial role of professional nurses in identifying patient concerns, problems related to referral systems, possible conflict situations and improvement of communication between team members and community.

Nurses as messengers of either bad or good healthcare-related information are sometimes challenged with being non-caring, especially by patients who do not want to hear the bad news or results related to their health (Huber 2014:120). Patients usually become confused when they do not understand medical instructions, and thus come into conflict with the healthcare person (Huber 2014:120), as in the case of the referral system brought about by introduction of the Batho Pele principles. Doctors and professional nurses should be mindful of the consequences of miscommunication and always try to be as clear in their instructions as possible. Muller (2009) asserts that caring is integral to the ethical and philosophical foundation of nursing. Nurses join the nursing profession with a vision to serve society, this vision being driven by the values of passion and caring which could be enhanced through practising the Batho Pele principles.

Searle (2006) states that when nurses are admitted to the professional register they declare publicly that they are competent and willing to meet the standards of nursing required from them, and that they will dedicate themselves to serving people through meeting their nursing needs. The eight Batho Pele principles and belief sets can easily be applied within patient nursing care by professional nurses working in outpatient departments, as these are also entrenched in the message of caring as translated through the Pledge of Service. Fundamental to adequately serving the patient are the principles of responsibility and accountability, as well as a willingness to go beyond the call of duty, for which the Batho Pele principles chiefly stand. Professional nurses are held responsible for their actions in their day-to-day activities, and despite the conditions under which they serve, their duties include being held accountable for caring for their patients.

## Problem statement

The researcher is exposed to nurses who almost daily express concern that, since introduction of the Batho Pele principles, patients have become abusive towards them, making their work unbearable. According to these nurses, patients seem to have unrealistic demands due to their expectations having been raised by these principles. Some of these nurses feel that it is not easy to uphold the principle of access, for example when there is a shortage of staff, especially skilled staff, and a shortage of medications.

On average, one professional nurse takes care of 20 patients a day in an outpatients department. These patients, as reported by the professional nurses working in the outpatient departments, present themselves to the department as early as 06h00 and might leave between 14h00 and 16h00. This delay is caused mainly by limited material and human resources.

Lack of material resources may at times include a lack of medicines to be given to patients, as well as a lack of diagnostic equipment. Nurses are confronted with the anger of patients who are exposed to such supply shortages. As the nursing category that carries the bulk of patient care in the outpatient departments, Professional nurses bear the brunt of the bad behaviour of patients and feel that the authorities do not listen when they report abusive tendencies or behaviour of patients.

Furthermore, there have been many negative reports in the media in recent years regarding the 'bad attitude' of nurses towards patients and their relatives, as well as about the substandard housekeeping and nursing care in State hospitals. Professional nurses expressed concern about these reports.

This study was designed to answer the following research question: What is the perception of professional nurses regarding the introduction of the Batho Pele principles?

### Research objectives

The objectives of the study were to: describe the perceptions of professional nurses regarding the introduction of the Batho Pele principles; and to recommend guidelines to facilitate measures for all parties involved in realisation of the objects of the Batho Pele principles.

# Research design

The research design for the study was qualitative, exploratory, descriptive and contextual in nature. The design suited the study as it allowed the researcher to engage with and to fully understand the lived experiences of the participants (Johnston & Onwuegbuzie 2004:20).

The population for the study was professional nurses who had been working in the outpatient departments of the three hospitals in the Port Elizabeth Hospital Complex within the Nelson Mandela Metropolitan Municipality for at least five years. Specific inclusion criteria were at least five years' experience of working in the outpatients department in a State hospital; work in either the adult or children outpatients department; and knowledge and practical skills which meant that they should possess a better understanding of what nursing stands for, and enhanced the purposive sampling of participants for this study (Parahoo 2006). Forty professional nurses were sampled; only 32 participated as the remaining 8 were either sick or not on duty on the day of data collection.

## Data collection methods

Data were collected through six audio-taped focus group discussions (FGDs) with no less than four participants each, as well as the taking of field notes. Of these six FGDs, two were for the purposes of a pilot study. No errors were identified in the data from the pilot study, and therefore data collected from these two groups were also included in the data analysis and results. Following the discussion with regard to the pilot study, with no major concerns identified, the researcher continued with data collection (Hornby 2005).

The FGDs were scheduled to last no longer than 45 uninterrupted minutes, but at times this schedule was not easy to maintain due to the nature of engagement with the participants, and they would be extended by 5–10 minutes. The interviews were based on one central question, with subsequent questions developing from the responses of the group members, and a set of two predetermined questions.

The central question was: Tell me, how do you feel about the introduction of Batho Pele principles in your institution? The predetermined questions were: What would you tell me about the implementation of the Batho Pele principles?; and What do you think could assist with the implementation of the Batho Pele principles?

The FGDs were conducted over a period of seven days during March 2010. As the researcher had no previous experience in conducting research interviews, the supervisor of the study assisted with facilitation of the FGD with one group for the pilot study and two of the main study FGDs. This facilitation was mainly to teach the researcher how to prepare participants before commencing the interview and to direct a question to a specific participant using the name code before or after the question has been asked, so as to allow individual responses. The researcher was also guided in keeping the focus to the research questions. Data saturation was the indication to discontinue data collection and complete the data analysis process (Burns & Grove 2011; Green & Thorogood 2009).

# Ethical considerations

The researchers were mindful of meeting all ethical considerations (Silverman 2011). A complete research proposal was presented to the research committee of the Nursing Science Department for approval. Written permission to conduct research was obtained from the Research, Technology and Innovation Committee of the Faculty of Health Sciences, with ethical clearance from the Ethical Committee of Nelson Mandela Metropolitan University. Furthermore, the DoH via the Chief Executive Officer of the Port Elizabeth Hospital Complex gave permission to use the hospitals as the site for conducting the study. Informed consent was obtained from the individual participants, as well as permission to identify them using codes such as P1 or P5.

Other ethical issues that were adhered to included preventing harm, no deception of participants, confidentiality and anonymity (De Vos *et al*. 2013). Participants were further assured of anonymity and confidentiality of their information and their privacy. Name codes were used to identify the tapes and transcripts and none of the participants' particulars were divulged. In order not to cause harm, each FGD was conducted in a sensitive manner (Babbie 2010). Participants maintained their right to withdraw at any stage of the study without any penalties.

## Trustworthiness

Babbie and Mouton (1998) state that the eminence of any qualitative study is determined by the level of trustworthiness it 'portrays'. To ensure valid results and trustworthiness, the researcher used Guba's model as described by Krefting (1991). The focus of the model is truth value, applicability, consistency and neutrality. Credibility was assured through member checking and the use of peer examination reflexivity, whilst confirmability was maintained through an audit trail.

Transferability refers to the ability to apply the findings of the study in another context or to other participants. The activities used to enhance transferability include a thick description, achieved by collecting and providing sufficient detailed data within the context of the study, purposive sampling, and data saturation. Dependability was maintained by use of a code-recode procedure and peer examination.

# Results and discussion

Participants were between the ages of 35 and 50years. The participants were all black people with most being Xhosa-speaking, whilst a few were mixed-race. Two groups had one male participant and two groups had one mixed-race participant. The male participants represented 100% of the male professional nurses in the department chosen as the research site.

There were no white employees at these research sites, and hence no white participants. In SA most townships – the environment in which the study was conducted – are predominantly populated by Xhosa families and individuals, whilst the nursing profession is a predominantly female-dominated profession.

Data were analysed using Tesch's method as stated in Creswell (2008:154) and by making use of an independent-coder. Three main themes and several sub-themes and categories emerged from the data analysis.

## Theme 1: Lack of planning with the introduction of Batho Pele

Participants indicated positive and negative emotions regarding introduction of the Batho Pele principles. The participants felt strongly that introduction of the Batho Pele principles lacked a sound foundation to their implementation. Said one participant: 'My experience with Batho Pele principles is that it was designed to transform the health services, the aim was good, but the government fails to do the ground work.'

As a result, the Batho Pele principles could not meet the set positive objectives of providing quality service delivery or of developing competent, committed and professional health workers for whom people or patients come first (DoH 2008).

According to the participants a lack of planning was the chief shortcoming with introduction of the Batho Pele principles: 'No planning was done before implementing the Batho Pele principles'. The participants felt that proper planning to implement the principles would have assisted the authorities to anticipate challenges and devise strategies to deal with such challenges. The experience of limited planning before implementing the principles was expressed as follows: '… without checking on the consequences the patients were informed of the Batho Pele principles. Now the patients want to hear what they want to hear'. Adequate planning would also have afforded well thought-through processes to correctly inform the public of the introduction of the Batho Pele principles.

The Batho Pele principles were meant to bring about a change in the usual manner of healthcare service delivery in the country. The environmental dynamics related to the change process, namely emotional involvement and resistance, were therefore to be observed (Jooste 2009; Huber 2010). Planning allows involvement of all stakeholders, which according to this study are the professional nurses and the community, thus encouraging ownership (Jooste 2009). Planned change enhances productivity and lessens the amount of individual stress resulting from the stakeholders' efforts to cope (Huber 2010).

According to the participants, the patients and the public are largely misinformed about the Batho Pele principles. As one put it: 'Some of these patients are not educated. These principles were read to them then they picked up what they want to hear and interpret it wrongly.'

As a result, they are inclined to make inappropriate demands, such as self-referring to an institution of a higher level of care instead of being referred from a nearby clinic or private doctor. Healthcare services were not rendered previously in terms of different levels; this resulted in duplication of services being the order of the day. Hospitals were providing primary to secondary services simultaneously – thus patients could present for a consultation and then would either be admitted and managed further or referred from one service to another. The professional nurses felt that the newly introduced referral system is not easy for patients and their families to understand.

Availability of medicines and prescriptions are currently categorised according to the level of care of that particular institution, and at times are out of stock. These are demanded by the patients from the professional nurses, although it is a managerial responsibility to order medicines. When the participants explained the impossibility of certain patient demands and informed patients of the correct procedure to be followed, the patients and their relatives became angry – shouting and accusing them of being uncaring and selfish. In this regard one of the participants expressed herself as follows:

> 'Patients shout and threaten us. You become scared and humiliated because patients shout at you in front of colleagues and other patients.'

Some even threatened to channel their dissatisfaction through the media, which would cause even worse conflict between the professional nurses and their patients.

Informing and explaining the merits of change to subordinates and followers enhances the process of organisational change (Jooste 2009). Here the 'followers' – the community members – seemed to misunderstand the practical meaning of the 'right to access of health care' due to a lack of adequate explanation regarding the full scope and meaning of this 'right'. Below are examples of expressions bythe participants with regard to limited understanding of the 'right to access of health care' by the community:

> 'Patients are not aware that other things are beyond the control of a nurse.'
>
> 'Patients are rude. They have taken this the wrong way. They think when they shout at a nurse it is their right. They think that these rights are to disrespect and abuse nurses.'

Further mixed emotions were experienced by study participants because they felt that implementation of the policy was further grossly affected by a shortage of human and material resources:

> 'Nurses would like to work and produce good results. When there are no resources I feel disgruntled, fed up. I feel like taking my bag and resign\[*ing*\] and find\[*ing*\] work where there are resources and I can give optimal care.'
>
> 'Another thing that makes us bad to the public is shortage of resources …'
>
> 'You feel embarrassed when you must re-book a patient because of no availability of resources. Some of these patients are poor. At times for most of these patients they have kept that money to come to the hospital; some have borrowed the money, and they must go back without any help because there are no resources.'

Both proper planning and adequate availability of resources are needed to influence achievement of the principles' goals. Despite existing disparities between policy and implementation, healthcare professionals cannot refuse to practice, because they are bound by professional ethics and the Pledge of Service that charges South African nurses to protect the dignity of their patients and families and the community at large, and to protect and maintain a safe and therapeutic health care environment, regardless of colour and creed, based on the human needs of the patient.

### Sub-theme 1.1: Difficulty in upholding the policy of the Batho Pele principles

Participants expressed concern that because of a lack of planning in implementing and incorporating the Batho Pele principles into policy, it is sometimes difficult for them to act in an ethical manner in response to the way in which patients and community members address or treat them:

> 'I can say Batho Pele principles is something good introduced by the government but sometimes it is difficult to uphold.'
>
> 'It is a good tool, but patients use it the wrong way.'

Ethics are vital in nursing practice and any occupation dealing with human life needs, both to regulate the practitioner so as to protect the good name of the profession, and to protect the public (Huber 2010). As aforementioned, at the core of provision of nursing is the value of and respect for human life. Professional nurses found it difficult to uphold this value as introduction of the principles did not fully accommodate issues related to human and material supplies, resulting in negative responses from the patients and community.

Burns and Grove (2009) define ethics as a means of endeavouring towards realistic outcomes where others are involved. Ethics determine that which is 'good' and 'bad', 'right' or 'wrong', or a moral duty and obligation (Pope & May 2005).

In this regard Burns and Grove (2009) maintain that problems of ethics relate to conscience, justice and responsibility, amongst others. The BathoPele principles were formulated to ensure that patients are treated with respect and consideration, and that the healthcare providers show courtesy and respect when interacting with patients. With this understanding in mind, professional nurses often have to keep quiet and ignore abusive behaviour from their patients, despite feeling heartbroken.

### Sub-theme 1.2: Batho Pele principles not planned properly

Change is complicated and should therefore be planned and implemented properly. If proper planning is not done, it leads to frustration, confusion and resistance amongst employees (Tomey 2009). Planning, according to Booyens (2008), is the cornerstone of good management and is grounded in the vision, mission, goals, philosophy and objectives of the organisation. Therefore, when planning for change the manager should not settle on a change approach before first examining the problem, the personal environment, time constraints, resources and goals to be achieved (Hellriegel *et al*. 2002). In the opinion of the participants this approach should have been adopted by the health authorities before their implementation of the Batho Pele principles:

> 'No planning was done before implementing the Batho Pele principles.'
>
> '… without checking on the consequences the patients were informed of the Batho Pele principles. Now the patients want to hear what they want to hear.'

Planning affords an organisation a formal structure which will lead to better coordination of activities and, in the context of this article, better service delivery. In a study of cross-sectional surveys of nurses and patients to explore patient safety, satisfaction and quality hospital care in 12 countries of Europe and the United States of America, conducted and published by Aiken *et al*. (2012), results show that an organised healthcare worker environment is closely assosciated with quality care and patient and nurse satisfaction. For this reason the participants felt that the Batho Pele principles needed to be revisited.

### Sub-theme 1.3: Introduction of Batho Pele principles affected by shortage of human and material resources

The participants indicated that besides the lack of planning by the relevant authorities, there were also human and material resource constraints which made it difficult for them to achieve the goals of the Batho Pele principles. Inadequate resources can have a negative impact on provision of care, leading to delays and deaths of patients. When there are no resources nurses are unable to render quality care and give of their best (Yoder–Wise 2007). The participants reported that they often have to rely on crisis management. In the patients' eyes this is often perceived as non-caring inefficiency. A lack of resources, such as staff shortages, means patients might not always get their treatment on time or are sent home to return to collect outstanding medication later.

Aiken *et al*. (2012) argue that provision of resources (staffing and materials) improves patient outcomes as there is less occurence of staff burnout and patient complaints. Furthermore, Hellriegel *et al*. 2002) state that managers need to identify and commit the organisation's resources to achieving its goals. In view of Hellriegel's statement, Benjamin (2008) recommends that managers develop project management Gantt charts to help them focus on tracking tasks and allocating resources, thus identifying shortcomings and providing the necessary help. The following are some of the statements made by participants in relation to inadequacy of material resources:

> 'Most of the time we nurses we improvise or go round borrowing from other departments or hospitals because there are no resources.'
>
> 'Nurses would like to work and produce good results. When there are no resources I feel disgruntled, fed up. I feel like taking my bag and resign\[*ing*\] and find\[*ing*\] work where there are resources and I can give optimal care.'

Caring promotes patient satisfaction. For patients, caring denotes positive connectedness, being instructed and taught, and having a nurse spending time with them and being patient with them (Palese *et al*. 2011:341). In the current study participants perceived themselves as not fulfilling this expectation due to limited materials, resulting in conflict between themselves and their patients.

## Theme 2: Owing to introduction of the Batho Pele principles, nurse-managers are letting the professional nurses down

Participants felt that they were not receiving enough support from their managers, expressed in statements such as that below:

> 'To report a patient or even a staff member who threatens you, you will be wasting time. Nothing happens.'

Dessler (2004) argues that a manager is a person who plans, organises, leads and controls the work of others so that the organisation can achieve its goals. If the manager fails to adhere to these attributes the department will be chaotic and nursing care will be compromised (Dessler 2004).

In their recent study Aiken *et al*. (2012) found that managerial support of nursing care, nurse participation in decision-making and organisational priorities on care quality were directly associated with nurse-workforce outcomes and nurses who were intent on leaving or remaining in their nursing jobs. This is in keeping with the perceptions of the participants in this study. The finding of that study can be applied in this current study, as the participants perceived the nurse-managers as not supportive of their actions, and at times were embarrassed in front of the patients as the nurse-managers took sides with the patients.

### Sub-theme 2.2: Batho Pele principles cause the nurse managers to lack discipline in their leadership

In the participants' opinion challenges to introduction of the Batho Pele principles were further aggravated by inconsistencies in the application of disciplinary measures by nurse managers – yet there were appropriate policies and guidelines in place. The participants reported that such policies and guidelines were not adhered to:

> 'The disciplinary policies are there but they are not implemented, especially if that person is a shop steward nothing is done. They do as they please. They are rewarded for their behaviour, like they will be promoted or sent for courses.'
>
> 'There is no discipline in our hospitals, everyone does what he/she likes, and even if you report that person nothing happens.'

Owing to this lack of disciplinary consistency, everyone could do as they pleased. This finding is similar to what was found in a similar study conducted in Ekurhuleni District of Gauteng Province, SA. That study revealed that nurse managers are to be blamed at times for non-supervision of staff performance, lack of role-modelling, and ineffective planning and control of their nursing units, all of which negatively affects implementation of the Batho Pele principles (Khoza, Du Toit & Roos 2010). However, ill-discipline was not only related to inadequately upheld disciplinary measures but also to matters concerning professionalism.

## Theme 3: Doctors are not committed to implementation of the Batho Pele principles

Doctors have the same responsibility as the nurses with regards to upholding the Batho Pele principles; however participants felt that sometimes their actions belied this.

**Sub-theme 3.1:** Doctors perceived as being impolite to patients and nurses.

Most of the participants felt that some doctors were extremely impolite and sarcastic. Participants had experienced doctors shouting at them in front of patients when they queried their behaviour or prescription. Participants felt that some doctors ignore the fact that a nurse is part of the health team:

> 'Batho Pele is for all categories, not only for nurses.'
>
> 'Doctors must get lectures on the upholding of the Batho Pele principles.'

Searle (2006:172) contends that nurses act in the interests of the patient and have a joint responsibility with the doctor for ensuring that the patient receives the correct prescribed diagnostic and therapeutic treatment. It is therefore important for doctors to familiarise themselves with the contents of this policy.

## Reaching the research goals

The research conducted was guided by two objectives, which were accomplished at the end of the study. Participants shared their perceptions relating to introduction of the Batho Pele principles. Through the use of exploratory questions, participants were able to provide in-depth information related to their perceptions, that could be both described and analysed. Findings revealed that professional nurses are overwhelmed by challenges resulting from the introduction of these principles. According to the participants, the objective of introduction of these principles was good, but implementation of the introduction of the Batho Pele principles lacked proper planning.

Data were analysed and the findings were used to develop guidelines that will be recommended to hospital managers as a means to facilitate realisation of the objectives of the Batho Pele principles within State hospitals.

# Limitations of the study

The concept of the Batho Pele principles is fairly new in the South African healthcare system and, like any other change introduced in a system, it has been confronted with some challenges. The researcher experienced it as being limiting to having to only interview professional nurses who work in outpatients' departments, excluding professional nurses from other departments and wards of the hospitals in the study.

# Recommendations

A second objective of this study was to recommend measures that could be used for facilitation of all the parties involved in the realisation of the objectives of the Batho Pele principles. Based on the findings of the study, the guidelines outlined below are recommended to facilitate effective implementation of the Batho Pele principles.

## Guideline 1: Planning of health services

The researcher believes that the staff would be eager supporters of the Batho Pele principles if:

-   they could be assured of their access to the necessary human and material resources, as well as to an adequate and reliable public and emergency services transport system for the purpose of speedy referrals;

-   the hospitals have fully functional Accident and Emergency Departments to allow for direct referrals;

-   all the hospitals are provided with the necessary security measures to safeguard the environment for both patients and staff; and

-   all stakeholders are provided with educational programmes and other formal means to inform them about the standards of care they will receive.

## Guideline 2: Effective leadership and management

The hospital and nurse managers should and are to:

-   be sensitive to employees' problems and show genuine concern;

-   create an environment in which employees are able to render optimal care, a non-threatening environment characterised by safety and security, where discipline is the order of the day;

-   ensure orientation of new personnel to the policies of the institution, basing all punitive discipline on accepted legal prescriptions and remaining uninfluenced by other staff members or unions in consistency in implementing discipline; and

-   be exemplary and keep to issues related to punctuality and work attendance, in keeping with the necessary institutional policies.

## Guideline 3: Availability of human and material resources

There are never enough resources for the work that needs to be done. In order to overcome this gap managers need to be:

-   well-versed in financial management and budgetary control; and

-   able to prioritise and be cost-effective without compromising quality care.

To achieve the clinical-related recommendations the researchers provide a further guide, based on the principles informed by the article 'Healthcare in a land called People Power: nothing about me without me' (Delbanco *et al*. 2001:144). A summary of those principles is listed below:

-   Collaborative partnerships with relevant stakeholders.

-   Approach the groups identified and inform them of the intentions of the collaboration.

-   The groups should be represented by non-governmental organisations, lay persons, patients, doctors, multi-disciplinary teams, nurse managers and, where possible, legal staff.

-   Allow involvement at decision-making level, as this allows for stakeholder commitment and ownership.

-   Share information with interested groups.

-   Identified groups are to be informed of the changes and interpretation of the changes so as to allow them to take that information to the masses.

-   Information should also relate to the objectives of (in this instance) the Batho Pele principles.

-   Collaborations with community-based leaders.

-   Lay, retired and other well-respected, experienced people in the community could be approached for assistance in dealing with misinformation and incorrect perceptions of the introduction of the Batho Pele principles.

-   In-service education.

-   Nurse managers or persons in these positions should be continuously guided in their roles.

-   Nurse managers need also to be guided as to how to motivate surbordinates, for example by using incentives.

-   Nurse managers should be trained on how to be adequate role models.

# Conclusion

Batho Pele is a well-founded strategy towards a quality healthcare service, but is posing a challenge in the South African healthcare context. A revised strategy is needed to encourage ownership and uptake of these principles by key stakeholders, namely professional nurses, managers and the community.

The Batho Pele principles are intended for empowerement of the community through developing responsible attitudes towards health care and usage of healthcare services. From the findings of this study it is evident that this objective has not yet been achieved, owing to the diverse factors discussed in this article. The implication is that funds are still not being adequately channelled or used correctly. It is possible that because of the funds not being used correctly, some patients are still not getting the care they need and, as a result, are prone to complications that could lead to either chronic conditions or longer stays in hospital. Both of the latter ultimately lead to the hospital losing more funds.

Notwithstanding the perceptions of participants with regard to introduction of the Batho Pele principles, the researcher saw it necessary to recommend measures that could facilitate enhancement of implementation of these principles. Three guidelines were developed from the study, in the hope of ultimately developing permanent policies to guide implementation of the Batho Pele principles.

## Acknowledgements

We thank Jean Morrissey for assisting with the editorial requirements of this article.

### Competing interests

The authors declare that they have no financial or personal relationship(s) that may have inappropriately influenced them in writing this article.

### Authors' contributions

S.J. (Nelson Mandela Metropolitan University) was supervisor and co-researcher for this study, as well as being responsible for conceptualisation, responding to the reviewers' comments and finalising the manuscript. T.M.M. (Livingstone Hospital) conducted the research and approved the initial draft article.

# References

[^1]: **How to cite this article:** James, S. & Miza, T.M., 2015, 'Perceptions of professional nurses regarding introduction of the Batho Pele principles in State hospitals', *Curationis* 38(1), Art. \#1128, 9 pages. <http://dx.doi.org/10.4102/curationis.v38i1.1128>


abstract: Three tools for simulating genome evolution are presented: for neutrally evolving DNA, for phylogenetic context-free grammars and for richly structured syntenic blocks of genome sequence.
author: Avinash Varadarajan; Robert K Bradley; Ian H Holmes
date: 2008
institute: 1Computer Science Division, University of California, Berkeley, CA 94720-1776, USA; 2Biophysics Graduate Group, University of California, Berkeley, CA 94720-3200, USA; 3Department of Bioengineering, University of California, Berkeley, CA 94720-1762, USA
references:
title: Tools for simulating evolution of aligned genomic regions with integrated parameter estimation

# Rationale

Almost every kind of genome annotation tool has, at some point in its lifecycle, been benchmarked on simulated data. Exceptions occur when the data are too poorly understood to be simulated, or so well understood that simulation is unnecessary. For the regime in between, generation of synthetic datasets is a nontrivial task. To accurately predict the strengths and weaknesses of a tool, one needs to generate simulated data with the same underlying statistics as the real data on which the tool will eventually be used. Relevant statistics include compositional bias (including local deviations from randomness like microsatellites or inverted repeats), phylogenetic correlations (including tree topology and branch lengths), hetergeneous substitution and indel rates, structured and conserved features (such as genes or binding sites) and context-dependence of mutational parameters. All the above factors lead to fluctuations in information density that can reduce the effectiveness of an annotation tool in practice.

A few concrete examples of applications that have been critically evaluated using simulated data are protein-coding genefinding \[1\], identification of transcription factor binding sites \[2\] and other functional non-coding DNA \[3\], phylogenetic reconstruction using distances based on substitutions \[4,5\] or indels \[6\], protein homology detection \[7\] and protein multiple alignment \[8\]. This list is a gross under-sampling from recent years, based on a citation search using the simulators described below; since simulation is almost a prerequisite for any new tool, the full list is much longer than this.

A number of tools address different aspects of the sequence simulation problem over long evolutionary timescales. Some of these tools are primarily protein-coding simulators; some handle DNA, and some do both. ROSE \[9\] is a canonical model for neutral sequence that implements substitution and indel events. DAWG \[10\] implements similar mutations to ROSE but is based on a deeper theoretical analysis of the underlying model, which is somewhat similar to the 'long indel' model of statistical alignment \[11\]. Several programs simulate substitution processes without indels; a recent example, which generates data of a given dinucleotide content (with a somewhat constrained choice of substitution model), is SISSIz \[12\]. Protein simulators include SimProt \[13\], Indel-Seq-Gen \[14\] and EvolveAGene \[15\]; of these, Indel-Seq-Gen offers the most realism, with rate heterogeneity and a diverse set of mutations. Simulators for genomic sequence (including conserved features) include EvolSimulator \[16\], which simulates gene family dynamics, and PSPE \[17\], which simulates turnover in promoter regions.

Many of these model-based simulation tools share a fundamental deficiency in their treatment of missing parameters and data. Specifically, they often lack robust functionality for: direct measurement of the model parameters from data; or integrated inference of missing information (gene boundaries, evolutionary histories, and so on) via the underlying model. The first aspect is important because the properties of the synthetic dataset may be parameter-dependent; the second aspect is important because even with direct measurement, the parameters measured may be strongly biased by the annotation of the training data.

Equally seriously, few of these models capture even a fraction of the true variety of genome features. At the mutational level, context-dependent substitution and indel rates (within which category we include microsatellite expansion and contraction) can have a significant impact on prediction accuracy \[18\]. At the level of selection for particular genomic features, a realistic simulator should model all the commonly encountered features of genomes, including protein-coding genes, non-coding RNA genes, conserved elements (such as binding sites), pseudogenes and transposons. All of these can bias different predictors in different ways.

There are notable exceptions to the above sweeping critique. DAWG does include a Perl script to estimate indel rates directly from data. SISSIz offers some heuristics for estimating parameters, without proof of the convergence or accuracy of these estimates. EvolSimulator does combine evolution of gene families and intergenic regions, but does not model the other genomic features mentioned above; nor does it provide tools to measure rate parameters. Indel-Seq-Gen is restricted to protein sequences; it offers domain-specific mutational parameters and includes events such as indels and domain shuffling but, again, does not offer a way to estimate these parameters. PSPE simulates promoter turnover, including loss-of-function mutations; the PSPE paper also describes ways to estimate parameters for promoter turnover directly from data, though it does not provide software to do this.

We have developed three related simulation engines: GSIMULATOR, SIMGRAM and SIMGENOME. The first, GSIMULATOR, models substitutions and indels in neutrally evolving DNA, with context-dependent rates for those events. The second, SIMGRAM, samples paths from a generic class of models called 'phylo-grammars', which include a broad class of models for proteins, coding DNA sequences, RNA genes, promoters and other features. The third, SIMGENOME, combines the previous tools with a rich diversity of genomic features (proteins, RNAs, pseudogenes, promoters and transposons) backed by a comprehensive repository of empirically measured substitution and indel rates, drawn from previously published analyses of large datasets such as PANDIT \[19\] and the 12 sequenced *Drosophila* genomes \[20\], and collected for the first time in a single place.

All three tools are based on generative models that offer efficient algorithms for parameter inference, annotation and/or ancestral reconstruction. The particular generative models used are transducers \[21\] and phylo-grammars \[22\], which both may be viewed as subsets of the set of mutational grammars. The theoretical advantages are several. One can learn parameters directly from data: for phylo-grammars we use the previously published XRATE program \[22\], while GSIMULATOR has a transducer estimator built-in. Generative grammars also offer parametric modularity: one can isolate important or repeated parameters, and place these conveniently at the top of the grammar file so that they can easily be edited or replaced with re-estimated parameters. Equally significantly, our grammars offer structural modularity. All the tools described here use documented file formats for representing their models. One can easily break down the grammar into sub-models, add new features or modify existing ones, without the need for directly modifying or re-compiling the underlying program code.

The present work is addressed at the problem of simulating syntenic blocks of genome sequence. We did not attempt to model genome rearrangements or duplications in this first release of our simulator, despite a clear need for benchmarking of genome rearrangement algorithms \[23-30\]. This was primarily because (at the time of writing) we lacked a unified framework for measurement in such models, or for dealing with missing data. In contrast, each simulation tool that we describe here is consistently complemented by robust measurement and reconstruction tools \[22,31\]. Adding rearrangement or duplication events would, however, be a natural future extension to our work. Another related but distinct area that we have omitted is evolution at the population level. Theoretical frameworks for populations exist, such as the coalescent \[32\] and super-processes \[33\], but exact inference in those frameworks is a significantly more challenging problem. Several recent simulators have addressed evolution at the shorter timescales associated with population genetics, incorporating effects like recombination, geographic migration, demography and ecology \[34-36\].

# Results

The fundamental component models of our simulator each have applications in training, simulation and inference. We propose that a single coherent evolutionary theory, encompassing and unifying these three aspects, is an extremely desirable feature for a simulation framework. There can be no simulation without parameters, which must be measured using some model; the parameters are typically measured from data that must have been aligned or annotated, using some model; and the alignment or annotation tools must be benchmarked using simulations, also using some model. The common feature of all the approaches described here, which we seek to emphasize, is that all three of these models are the same: parameter estimation, annotation and simulation can all be conducted using the same probabilistic model.

We now describe three tools. GSIMULATOR randomly generates alignments of neutrally evolving DNA; SIMGRAM randomly generates alignments of generically structured features under selection; and SIMGENOME combines these to randomly generate alignments of syntenic regions in genomes, using a reasonably detailed model of the genomic feature landscape. All three of these programs, together with examples of input/output files and command-line usage, may be accessed via the webpage \[37\].

## GSIMULATOR: a transducer-based simulator for neutrally evolving DNA

The GSIMULATOR tool simulates the neutral evolution of DNA on a phylogenetic tree. Along each branch, substitution and insertion-deletion mutations are modeled, using a context-dependent transducer. The theory of transducers is described in previous work \[21\] and summarized in the Materials and methods (see 'Sampling from lexicalized transducers'). Essentially, a transducer is a finite-state machine, similar to a Pair hidden Markov model ('Pair-HMM'), that mutates a sequence by introducing random substitutions and indels.

The GSIMULATOR transducer is context-dependent, meaning that the substitution and indel 'rates' are dependent on the past *K* absorbed and emitted symbols, where *K* is a parameter that can be configured. The purpose of allowing context-dependence is to model local sequence-dependent fluctuations in substitution and indel rates, such as methylation-dependent CpG deamination, microsatellite expansion and contraction, and 'micro-duplications' or 'micro-inversions' corresponding to *K* nucleotides or fewer.

GSIMULATOR also permits flexible modeling of gap length distributions, by allowing *N* multiple degenerate insertion and deletion states, where *N* is a configurable parameter. In the absence of context-dependence (that is, when *K* = 0), this yields a mixture of geometric distributions for the lengths of gaps. The distribution is more complicated for context-dependent transducers (*K* ≥ 1), since the gap length depends on the inserted (or deleted) sequence.

As with all the methods described in this paper, GSIMULATOR is a trainable simulator, meaning that the parameters can be directly estimated from pairwise alignment data (and need not be 'guesstimated' by a user). Compositional biases of gene predictors, aligners, motif finders and other annotation tools can be exquisitely sensitive to the underlying evolutionary statistics, so this feature is extremely important for a robust simulator.

## SIMGRAM: a phylo-grammar simulation tool

The SIMGRAM tool generates sample alignments from a user-specified phylogenetic context-free grammar, or 'phylo-grammar'. In contrast to the transducers used by GSIMULATOR, the phylo-grammars of SIMGRAM can model genome features under finely structured selection, including co-ordination of the relative layout of these features (analogously to the way in which a human-language grammar specifies the layout of the various parts of speech). Examples of features that can be so modeled include protein-coding genes \[1,18\], non-coding RNA genes \[22,38,39\], protein binding sites \[40\], protein domains \[41,42\] and protein secondary structure \[22,43\]. The full theory of phylo-grammars has been widely described (see the above-cited applications by ourselves and others); a brief introduction can be found in the Materials and methods (see 'Sampling from phylo-grammars').

The phylo-grammar format used by SIMGRAM is the same as that of the XRATE program, a previously described tool that uses the Expectation Maximization algorithm to estimate the rate and probability parameters of any custom phylo-grammar \[22\]. Therefore, XRATE can be used to estimate simulation parameters directly from training data, then SIMGRAM can be used to generate synthetic data with similar properties, but no direct homology (excluding cases where the phylo-grammar itself encodes homology information \[41,42\]). This represents a new application of XRATE: the SIMGRAM program has not been previously described, and previous uses of XRATE have involved using the phylo-grammar to annotate sequence, or to measure substitution rates that are themselves of direct interest. (Thus, as with all the methods here, the generative model underpinning SIMGRAM can readily be trained on data and used for annotation and inference.)

An appealing feature of phylo-grammars for simulating an evolving and feature-rich genome sequence is that it is extremely easy to combine several sub-models into an all-encompassing model. Furthermore, the XRATE format allows several features that are useful for simulation. One such feature is parametric models, where the rates and probabilities are constrained to have a particular functional form that depends on a smaller parameter set. This is useful to construct models that have desired symmetry properties, such as strand-symmetric substitution processes, or *K*~*a*~/*K*~*s*~ codon models. The XRATE format can also approximate context-dependent substitution rate models, using the technique of \[44\]. Finally, a powerful macro language exists that can be used to compactly describe grammars with many states, or to model lineage-specific parameterizations.

The DART (DNA, Amino Acid and RNA Tests) package, in which SIMGRAM is distributed, includes reproductions of several previously published phylo-grammars that can be simulated using SIMGRAM. Examples include models of secondary structure for proteins \[43\] and RNA \[38\], as well as a number of point substitution models for protein and nucleic acid sequences. The phylo-grammar format is described in full online \[45\].

## SIMGENOME: a feature-rich phylo-grammar for genome alignments

So far, we have described the GSIMULATOR program for context-dependent mutation of neutral DNA, and the SIMGRAM program for mutation of structured features under selection. Each model has its strengths and weaknesses: GSIMULATOR richly models neutral DNA, but not features under selection, whereas SIMGRAM has better models for such features but lacks GSIMULATOR's context-dependent rates or sophisticated indel model. We now describe a program that combines these approaches, using a modular framework that can easily be extended to incorporate future, specialized feature-simulators.

The combined simulator, SIMGENOME, starts by generating a multiple alignment from a template phylo-grammar that includes a rich array of genome features. The features are described below in more detail, together with outlines of how the template can be extended by an expert user to incorporate new features.

In the generated alignment, certain columns are flagged as intergenic. The SIMGENOME program then repeatedly calls GSIMULATOR to generate alignments of neutral DNA corresponding to these intergenic regions, and splices them into the main alignment. This process is extensible: the template phylo-grammar can be edited to add new features or change the underlying parameters of the model. Furthermore, other external feature simulators can be specified in the template grammar, and their output alignments will be spliced into the main alignment in exactly the same way as GSIMULATOR's output is.

The features modeled by the template phylo-grammar include protein-coding genes (with a rough approximation to exon-intron-untranslated region (UTR) structure that includes exon length distributions), non-coding RNA genes, conserved elements (such as transcription factor binding sites), pseudogenes and DNA transposons with terminal inverted repeats. Features can appear on forward or reverse strands. All features are annotated in the generated alignment, so that their recovery in automated benchmarks can be assessed.

The sub-models that generate these features use substitution rate parameters that all were estimated directly from the following experimental datasets, using the XRATE program (and could be re-estimated from alternative datasets).

### The protein-coding gene model

The protein-coding gene model uses an empirical, fully reversible and otherwise unconstrained 61×61 rate matrix over codons, estimated in previous work \[46\]. Frame-preserving deletions are allowed. The training set for this model was the PANDIT database consisting of DNA-level alignments of protein domain families \[19\].

### The non-coding RNA gene model

The non-coding RNA gene model treats gaps as a fifth character and therefore uses (4 + 1) × (4 + 1) single-stranded nucleotide and (4 + 1)^2^ × (4 + 1)^2^ double-stranded base-pair rate matrices that are fully reversible and otherwise unconstrained, and were estimated separately. The training set for this model consisted of alignments provided with the program CONSAN \[47\], which in turn were derived from the European large subunit rRNA database \[48\]. The initial probability distribution over base-pairs in double-stranded regions was also used to generate the terminal inverted repeats in simulated DNA transposons (although these features subsequently evolve under a neutral model, so that they do not display the compensatory mutations characteristic of non-coding RNA (ncRNA) genes under selection).

### The strand-symmetric neutral substitution model

The strand-symmetric neutral substitution model that underpins the pseudogene and transposon models treats gaps as a fifth character and was trained on a random 1% of alignments of 12 *Drosophila* genomes \[20,49\]. The alignments themselves were made using the PECAN program \[50\]. The model was constrained to be strand-symmetric and reversible using XRATE's parameterization functionality. A slower, ungapped version of this substitution rate matrix is also used to model conserved features.

### The transducer model

The transducer model used by GSIMULATOR to simulate intergenic sequence evolving under a neutral context-dependent model was trained on a set of pairwise alignments drawn from a subset of twelve-species *Drosophila* alignments, which were made using the PECAN program \[50\]. The subset was drawn from approximately 5% of the original multiple alignment data, to which a 95% minimum percentage identity threshold was applied.

### The frequencies and length distributions

The frequencies and length distributions of genomic features were estimated from the *Drosophila* genome literature \[20,51,52\] using *Minos* as a model for DNA transposons \[53,54\].

The underlying template phylo-grammar is written using the publicly documented XRATE format and can be readily edited. High-level parameters, such as the frequencies with which genes or other features appear, are declared at the top level of the grammar and may be easily changed. We invite users to try adding sub-models representing new features of relevance to benchmarking (or to consult with us in this process). New sub-models can be parameterized directly from data using XRATE, and the parameters copied and pasted into SIMGENOME's grammar; this also applies to the existing models, which can be re-trained and/or re-parameterized (for example, to reflect differing codon usage or GC content). Even greater extensibility is afforded by the modular plug-in architecture that allows the use of third-party programs to generate features that cannot currently be simulated by SIMGENOME's phylo-grammars or transducers; such as tandem arrays, long-range duplications, and so on.

The following are examples of features that are not currently included in the SIMGENOME model, but are possible using SIMGRAM and could be incorporated by modifying SIMGENOME's grammar file.

### Codon frequencies

The PANDIT dataset that was used to estimate the SIMGENOME codon model spans a wide spectrum of compositional and codon usage biases. In terms of overall patterns of conservation and suppressed mutation rates, we consider it an acceptable general model of codon substitution. For example, if one is benchmarking a motif-finding tool, the coding regions generated by SIMGENOME will result in more false positives than non-coding regions (because the level of conservation is higher) and this may be adequate for the purposes of that benchmark. However, for other purposes, one might conceivably want a richer parametric model that takes account of genome-specific effects such as compositional bias, codon bias, transition-transversion ratios or CpG methylation-induced deamination. Using such a parametric model is a simple case of swapping out the relevant rate matrix in the SIMGENOME grammar file. The model can be fit to data using XRATE in the normal way. We are preparing a manuscript describing a direct comparison between XRATE and PAML for these purposes, including Perl code for generating such richer parametric models (Heger A, Ponting C and Holmes IH, in preparation).

### Lineage-specific parameterizations

The SIMGRAM macro language allows for different parameters on different branches of the tree. We have not made use of this feature in the SIMGENOME grammar, since its usage is somewhat dependent on the phylogenetic clade under investigation: one may (for example) want to use different parameters on every branch, on a single internal branch, or within a specific clade. With reference to the XRATE documentation, it is quite possible to design grammars that make use of this feature, so that the model may (for example) use different codon frequencies or compositional biases in different parts of the tree.

### Loss-of-function mutations

The SIMGRAM format also allows for lineage-specific evolution of whole features, in the manner of the DLESS program by Pollard *et al.* \[55\]. Internally, we have developed phylo-grammars modeling loss-of-function mutations in protein-coding genes, for investigations of pseudogene evolution. We have not included loss-of-function mutations in this first release of SIMGENOME, but it would be quite feasible to extend it without needing to write new code.

### Splice sites, initial methionines, UTRs and other aspects of protein-coding gene structure

The grammar of SIMGENOME currently includes a crude semblance of exon and intron structure, in order to reproduce the broad compositional fluctuations associated with protein-coding genes. This currently includes slow-evolving sequence at the exon-intron boundaries, as a mock-up of splice site conservation. The current release does not, however, model protein-coding genes at a sufficient level of detail to be used as positive examples for a protein-coding gene predictor. One could readily modify the simulator to do this, modeling splice sites as GT-AG and perhaps even AT-AC donor-acceptor pairs, and including other features such as poly-A signals, initial ATGs, TATA boxes and UTRs. These sorts of feature are straightforward to add to a phylo-grammar framework.

### Higher-order correlations between codons

The SIMGRAM distribution includes example phylo-HMMs demonstrating higher-order correlations between amino acids in protein alignments. For example, there is a replica of the Thorne-Goldman-Jones 3-state phylo-HMM for modeling secondary structure \[43\]. Given a suitable parameterization to map from amino-acid substitution rate matrices to codon matrices, it would be straightforward to use something like this to model higher-level correlations between codons in SIMGENOME's coding-DNA regions. One may reasonably ask why we have not included such higher-order dependencies in the first release of SIMGENOME, when we have included higher-order context-dependencies in the intergenic regions. The answer is that intergenic features (such as microsatellites or conserved regions) may include strong compositional biases extending over tens of bases and so generally contribute more to fluctuations in information density than correlations between codons, which are typically weak, local and often detectable only at the level of the encoded amino acids \[43\].

### Detailed length distributions

Most of the length distributions of features modeled in SIMGENOME are geometric (the simplest kind of distribution that one can model with an HMM). By chaining together duplicate states, it is possible to generate more complex (realistic) length distributions. For example, the SIMGENOME grammar file includes functions for generating a peaked 'negative binomial' distribution (also known as the 'Pascal' distribution) for exon lengths; so there are examples that can be used to do this. However, a straightforward geometric distribution was empirically found to be a better fit to exon length data in *Drosophila*.

## Evaluation: benchmarking a non-coding RNA predictor

Evaluating a simulation tool is a slightly different problem from evaluating an annotation tool, such as a gene predictor. When benchmarking a predictor, one is typically interested in minimizing the number of false positives that the predictor finds in a null dataset at a given threshold of the prediction score cutoff. One can eliminate all false positives by setting the score threshold arbitrarily high, but at the cost of also missing all the real genes in the dataset. To get a true picture of the predictor's performance, one must therefore consider how the number of false positives varies as a function of this threshold; or (more meaningfully) as a function of the sensitivity of the predictor, that is, the number of real genes that it correctly detects at a particular score threshold.

A common practice is to use a set of real genes to evaluate the sensitivity of the predictor, but to use simulated null data to evaluate the false positive rate. The reason for using simulated null data, instead of a real DNA sequence that does not contain any genes, is the paucity of negative annotations: it is difficult to demonstrate experimentally that a particular sequence of DNA definitively does not contain any genes. This is particularly true of hard-to-identify genes, such as RNA genes or short open reading frames.

A good simulator, therefore, is one that closely reproduces the statistics of real DNA, and generates a similar number of false positives to real DNA. In practice, the second criterion rests on the choice of statistics for the first criterion In general, if the statistical model is too simplistic (for example, omitting low-complexity regions), then the complexity of the simulated DNA will be more than it should be, leading to fewer false positives. To take a specific example: a DNA simulator that randomly emits a sequence of independent, identically distributed symbols will match the nucleotide-level composition of real DNA, but will not reproduce the short-range fluctuations in information content that can be found in real DNA, and so will generate fewer false positives in a motif-finding benchmark than a simulator that includes short-range complexity fluctuation phenomena (such as microsatellites).

On this basis, we argue that a measure of a good probabilistic simulator is that its model (after being fit to real DNA) should maximize the number of false positives for a given predictor at a given sensitivity. Another way of putting this is that the simulator should provide the most stringent possible benchmark for the gene predictor, by minimizing the area under the receiver operating characteristic (ROC) curve over the range of interest (see below).

To evaluate the simulation engines described here, we used them to estimate the false positive rate (FPR) for a computational whole-genome screen for conserved structural RNA genes, conducted using XRATE \[22\]. We chose RNA gene prediction as a test case because it has an extremely high FPR, whose actual extent is still unknown \[39,56,57\]; and because the estimated FPR for this screen is highly sensitive to the underlying properties of the simulation engine, making it a good motivator of increased realism \[12,58\].

Specifically, the FPR was estimated by sliding a window across the simulated alignments, and running XRATE on each window using an RNA gene-prediction grammar. This grammar models the distinct patterns of nucleotide substitution in RNA genes, including covariation of base-paired nucleotides, and is closely related to the EVOFOLD program for comparative RNA gene prediction \[39\] and the PFOLD program for comparative RNA folding \[59\]. The grammar itself, along with detailed instructions for reproducing the screen, can be found online \[37\]. The full rationale underlying the development of the grammar, and its critical evaluation (as a genefinder) and comparison to related grammars, will be described elsewhere (Bradley RK, Uzilov AV, Skinner M, Bendaña YR, Barquist L and Holmes I, submitted).

The plots show ROC curves where the FPR is plotted against the sensitivity of the screen (as measured using annotations of known ncRNAs in *Drosophila melanogaster*), as a parametric function of the score threshold for the screen. Since ncRNAs represent positive results for this screen, and we already have a set of known curated ncRNAs for *D. melanogaster*, we omitted the ncRNA submodel from the SIMGENOME grammar for these tests.

The results are shown in Figure <a href="#F1" data-ref-type="fig">1</a>. The general conclusion is that increased realism makes for a higher FPR. In the case of GSIMULATOR, increasing either *N* or *K* radically increases the FPR; in the case of SIMGENOME, inclusion of conserved genomic features with slower evolutionary rates markedly increases the FPR relative to both a pure point substitution model as well as the most realistic GSIMULATOR model.

We also compared our simulation methods, GSIMULATOR and SIMGENOME, to DAWG \[10\], a widely cited program for simulation of neutral substitution and indel events. We chose DAWG because it most closely exemplifies the goals we have identified here: it is clearly based on an underlying evolutionary model and provides tools for estimating the parameters of the indel model directly from sequence data. It appears to be the leading general-purpose simulator at the time of writing. Other simulators (such as PSPE) are richer, but do not provide the parameter-estimation functionality that DAWG does.

The parameters for DAWG were as follows. We used the same general-time reversible substitution model (REV) that we estimated from PECAN alignments of *Drosophila* genomes. DAWG's 'geometric' indel model (that is, geometrically distributed indel lengths) was parameterized using the script provided with the program. Although the 'power-law' model for indel lengths gave a better fit, it produced alignments that were mostly gaps. DAWG allows for heterogeneous rates and invariant sites using the Γ + *I* model for rate heterogeneity \[60\], also providing some example parameters for this model (γ = 1, ι = 0.1), which we used for these simulations.

Figure <a href="#F2" data-ref-type="fig">2</a> compares DAWG with the most realistic GSIMULATOR and richest SIMGENOME models. The figure shows that the context-dependence modeled by GSIMULATOR and the genomic features modeled by SIMGENOME result in much tighter false-positive estimates than DAWG produced.

Since DAWG's example γ and ι parameters (which determine the rate heterogeneity and conserved-site density) were manually adjusted for human-chimp alignments by the program's author, they may be an underestimate for *Drosophila* (where conserved elements are more closely spaced than in primates, due to smaller genomes and a higher deletion rate of nonfunctional DNA). However, there is no automated method for setting these parameters in DAWG; nor does the DAWG package or paper provide explicit guidance on how to relate these parameters to straightforward statistics on genomic feature density. (The SIMGENOME grammar file, in contrast, includes comments that outline the derivation of the feature distribution parameters from published *Drosophila* annotations.) Further, the GSIMULATOR program includes a fully automated training procedure, has no model for conserved sites or rate heterogeneity (other than context-dependent substitution) and nevertheless generates a higher false prediction rate than DAWG, even when these features are enabled in DAWG (Figure <a href="#F2" data-ref-type="fig">2</a>). Since SIMGENOME, in turn, generates a higher FPR than GSIMULATOR (Figure <a href="#F1" data-ref-type="fig">1</a>), we reason transitively that SIMGENOME is also a more realistic simulator than DAWG. Correspondingly, we note that this argument strongly motivates an automated tool (or even a simple heuristic) for estimating the γ and ι parameters of DAWG's heterogeneous-rate model. There is considerable analysis of such models \[60\], so this may be a reasonable goal of future study.

# Discussion

We have described an extensible system for genome simulation that includes a rich array of features and parameters, together with integrated methods for estimating those parameters, and comes with a comprehensive repository of mutation rate measurements for genomic features and intergenic DNA. Features modeled by our simulator include protein-coding and non-coding RNA genes, pseudogenes, transposons, conserved elements, microsatellite expansion/contraction and other context-sensitive substitutions and indels in neutrally evolving regions.

There are several obvious extensions to this work. We did not include large duplications or rearrangements in our simulator because, at the time of writing, we lacked up-to-date methods for measuring the frequencies of these events in evolution (although see \[61\]). However, such events would be an obvious extra layer to add to our system. A variant on this would be to simulate gene family dynamics using a birth-death model \[62,63\] for benchmarking of orthology/paralogy prediction methods. This might also be achieved by constructing gene features from explicit models of protein domains, for example, based on HMMs from the PFAM database. Likewise, we could generate ncRNA features based on explicit families (such as tRNAs).

The power of efficient generative probabilistic models is that they provide a common framework for measuring parameters, simulating from those parameters, and reconstructing missing information such as ancestral genotypes or gene boundaries. Another strong advantage, which we have used for this work, is the ease with which such models can be extended to incorporate new features or variations on existing features. The technologies that we have used to build our simulator (phylo-grammars and transducers) can, in fact, be viewed as overlapping subsets of a larger set of mutational grammars. With the inevitable trend of richer prediction tools whose dependence on the intricate structure of sequence evolution becomes ever harder to predict, the future of such generative grammatical models is as bright in computational biology as it is in linguistics.

# Materials and methods

## Sampling from phylo-grammars

A phylo-grammar is a stochastic context-free grammar whose every state generates alignment columns (or groups of alignment columns). The residues in each row of such a column are related by an underlying phylogenetic tree (whose topology remains constant), using a continuous-time Markov chain subsitution model (which is allowed to vary from state to state). Each state in the grammar is allowed to generate several columns simultaneously; these sites then evolve co-ordinately, so that a state can (for example) emit three columns that evolve together as a codon triplet, or two distantly separated columns that evolve as a base-pair in a non-coding RNA alignment.

One can vary the evolutionary rate throughout the tree, and for this behavior to be state-dependent, so that different states in the grammar can have trees with different branch lengths. However, SIMGRAM requires that the tree topology stay constant throughout the alignment. (While it is mathematically straightforward to construct phylo-grammars with alternative tree topologies in the various states, such models are not implemented by SIMGRAM.)

Sampling from the phylo-grammar proceeds in two stages. First, a parse tree is sampled by repeated application of randomized grammar rules. Next, a Gillespie algorithm is used to simulate continuous-time Markov chain trajectories for each set of co-evolving columns \[64\].

## Sampling from lexicalized transducers

A transducer is a finite state machine, similar to a 'Pair-HMM', but conditionally normalized; thus, instead of emitting two sequences (as does a Pair-HMM), the transducer absorbs one sequence (*X*) as an input and emits the second sequence (*Y*) as an output. Practically, a transducer looks very similar to a Pair-HMM: it has match, delete and insert states, and the training and alignment algorithms are almost identical. The key difference is the probabilistic normalization: a transducer's emission and transition probabilities are normalized such that the likelihood of any state path π corresponds to the conditional probability *P*(π,*Y*\|*X*), whereas in a Pair-HMM the state path likelihood corresponds to the joint probability *P*(π,*X*,*Y*). Conceptually, a transducer absorbs a symbol on the input, then decides (randomly) what state to go into, then emits a symbol (or symbols) on the output; in contrast, a Pair-HMM first changes state, then emits symbol(s) on either or both outputs.

A transducer models random changes in a sequence, as might occur on an individual branch of a phylogenetic tree. It is also convenient to introduce a special type of transducer, located at the root of the tree, that only emits sequence (that is, it has only 'insert' states, and lacks 'match' or 'delete' states to absorb an input sequence). Such a transducer is referred to as a 'singleton' transducer and is exactly equivalent to a single sequence-emitting HMM. The composition of an (emitting) singleton transducer with an (absorbing-and-emitting) branch transducer yields a machine that is exactly equivalent to a Pair-HMM.

A lexicalized transducer is one in which the probability parameters for making transitions between states, and for absorbing or emitting various symbols within states, are dependent on the last few symbols that were emitted or absorbed. This dependence allows the root transducer to generate higher-order compositional statistics of DNA (such as dinucleotide or trinucleotide frequencies). It also allows the branch transducers to model phenomena such as increased rates of indels and substitutions in low-complexity regions, such as microsatellites.

The lexicalized transducer underlying GSIMULATOR is a discrete mutator that introduces substitutions and indels at a frequency corresponding to a finite span τ of evolutionary time, corresponding (typically) to a short branch on a phylogenetic tree. For example, the pre-trained transducers that are distributed with GSIMULATOR, and parameterized from *Drosophila* alignments, correspond to a branch length of τ ≈ 0.07 substitutions per site. Longer branches of the tree, with length *T* \> τ, are simulated by iterated application of the transducer (for example, a branch of length *T* = 0.35 corresponds to five repeated applications of an evolutionary transducer with branch length τ ≈ 0.07); branches of length *T* \< τ are rounded up (if *T* ≥ τ/2) or down (if *T* \< τ/2).

In other words, evolutionary time *T* is treated as a discrete parameter, corresponding to some integer multiple of τ. This contrasts with many point substitution models that are used in molecular evolution (and in previous evolutionary simulators), which are based on continuous-time Markov chains. This behavior is deliberate and justified on the grounds of realism, as follows: it is extremely difficult to obtain closed-form matrix exponential solutions to the transition probabilities for context-dependent substitution and indel models of the kind used by GSIMULATOR. Indeed, only approximate solutions currently exist for context-dependent substitution models \[44,65\], and there is currently no good theory at all for context-dependent indels. We argue that the increased realism of context-dependence is easily worth a small reduction in granularity of the evolutionary time parameter. In cases where fine-grained time distinctions are critical, the SIMGRAM phylo-grammar simulator described here can be used instead.

The training procedure for GSIMULATOR is straightforward. The algorithm for estimating the parameters is essentially the same as the Baum-Welch algorithm for training a Pair-HMM from a pairwise sequence alignment \[66\]. The corresponding inference algorithms are not detailed here, but there exist a range of dynamic programming algorithms, from exhaustive inference to Markov Chain Monte Carlo algorithms \[31,67-69\] that can be used to impute alignments and evolutionary histories, to reconstruct ancestral sequences, or to annotate sequences in alignment-free (as well as alignment-dependent) ways. The particular algorithm used by GSIMULATOR to infer parameters is a variant on the Baum-Welch algorithm \[66\]. During training, GSIMULATOR finds the branch length τ from the underlying data using a Jukes-Cantor distance estimate \[70\].

For the four symbols of the DNA alphabet, order-*K* context-dependence multiplies the number of transducer parameters by a factor of 4^2*K*^. In practice, the quantity of training data (and potentially runtime and/or memory considerations) will limit the value of *K*. We find that a value of *K* = 3 yields a transducer that can reasonably be trained from eukaryotic genome alignments of the approximate size of *Drosophila*, but that this transducer takes a long time to train (especially if the degeneracy *N* of the indel states is greater than 1).

We do not currently have a specialized ancestral reconstruction tool for lexicalized transducers; instead, we have a more general tool. The previously published Handel program \[68\] is a Gibbs sampler for multiple alignments and ancestral sequence reconstructions under the TKF91 model \[71\]. More recently, it has been extended to model affine indel-length distributions (unpublished). Handel can also be coupled to any external program that implements a probabilistic scoring function for alignments; that is, given any ancestral reconstruction *A* in Stockholm alignment format \[72\], the program must compute and then output *P*(*A*,*S*\|*M*) for some model *M*, where *S* represents the observed sequences at leaf nodes. (GSIMULATOR is itself one such program.) Handel then accepts the Markov Chain Monte Carlo move from *A* → *A'* with probability:

$$\min\left( {1,\frac{\left. P(A^{\prime},S \middle| M)P(A,S \middle| T^{\prime}) \right.}{\left. P(A,S \middle| M)P(A^{\prime},S \middle| T) \right.}} \right)$$

where *T* represents the TKF91 model; this is a Hastings ratio \[73\]. Asymptotically, this yields a direct sample from *P*(*A*\|*S*,*M*).

## Generative model features

Most features of the SIMGENOME phylo-grammar are self-explanatory, either from this paper or by inspection of the commented grammar file (located in the subdirectory `dart/grammars/SIMGENOME.eg`). The length distribution of exons is a negative binomial distribution, or Pascal distribution, obtained by serial chaining of left-regular states, each of which emits a geometrically distributed number of codons. (The Pascal distribution is that of the sum of independent, geometrically distributed random variables.) This results in far fewer unrealistically shorter exons than would be generated by a geometric distribution, while allowing easy parameterization of the mean exon length.

The default GSIMULATOR model used by SIMGENOME has two insert states and two delete states, and uses three nucleotides of both input and output context. Roughly speaking, this corresponds to a mixture of geometric distributions over gap lengths; however, due to the input and output context, the precise length of inserted or deleted sequences will also depend on the sequence content of those indels.

# Abbreviations

DART, DNA, Amino Acid and RNA Tests; FPR, false positive rate; HMM, hidden Markov model; ncRNA, non-coding RNA; ROC, receiver operating characteristic; UTR, untranslated region.

# Authors' contributions

AV wrote GSIMULATOR. RB wrote the SIMGENOME phylo-grammar, ran the gene-prediction benchmarks and prepared the ROC curve figures. IH wrote SIMGRAM (and related programs), the SIMGENOME Perl script, and the manuscript. All authors read and approved the final manuscript.

### Acknowledgements

This work was funded by NIH/NHGRI grant GM076705. RKB was partially supported by an NSF Graduate Research Fellowship.