Article Text

Factors influencing the information behaviour of doctors and nurses in South Africa’s Eastern Cape, Mpumalanga, Limpopo and Northern Cape provinces: a survey study protocol
  1. Nombulelo Chitha1,
  2. Sikhumbuzo A Mabunda2,3,4,
  3. Vivien Essel4,
  4. Itumeleng Funani4,
  5. Lizo Godlimpi5,
  6. Buyiswa Swartbooi4,
  7. Onke Mnyaka4,
  8. Jahman Thabede1,
  9. Ruth Tshabalala1,
  10. Wezile Chitha4
  1. 1Knowledge Management for Public Health Research unit, University of the Witwatersrand, Johannesburg, Gauteng, South Africa
  2. 2School of Population Health, University of New South Wales, Sydney, New South Wales, Australia
  3. 3George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
  4. 4Health System Enablement & Innovation unit, University of the Witwatersrand, Johannesburg, Gauteng, South Africa
  5. 5Department of Public Health, Walter Sisulu University, Mthatha, Eastern Cape, South Africa
  1. Correspondence to Dr Nombulelo Chitha; buli.chitha{at}


Introduction Information is a prerequisite for quality healthcare service. Health professionals play a key role in the health system as they jointly have the responsibility of looking after patients everyday. Failure to use evidence in medicine may lead to medical errors such as incorrect diagnosis and/or mismanagement. Health professionals with access to quality health information can improve health services. This study focuses on the information behaviour of doctors and nurses whose role involves direct patient care.

Methods and analysis This study will employ a quantitative approach using a cross-sectional survey design. Simple random sampling will be used to identify the provinces and hospitals. Stratified random sampling will be used to select doctors and nurses to whom a validated questionnaire will be administered. The study will use a structured self-administered questionnaire. Data collection will be carried out at Nelson Mandela Academic Hospital, Witbank Hospital, Pietersburg Hospital and Robert Mangaliso Hospital, respectively. Questionnaires are distributed to health professionals in one of two ways. First, by emailing an editable Microsoft word document (questionnaire) to the health professionals to complete and send back. Second, by sharing with the health professionals through WhatsApp or email, an online version of the questionnaire that has been created on Google Forms. Data collection process is scheduled to commence on 14 March 2022 and is expected to end on the 15 September 2022.

Ethics and dissemination Ethical approval was obtained from the University of the Witwatersrand Human Research Ethics Committee (reference: M211013) and Walter Sisulu University Human Research Ethics and Biosafety Committee (reference: 099/2021). Permission to access the health facilities was approved by the Provincial Health Research Committees of the Eastern Cape, Limpopo, Mpumalanga and Northern Cape. Finally, results will be shared with all key stakeholders, including hospital management, clinical staff, through public presentation and direct engagements with stakeholders.

  • Quality in health care

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Strengths and limitations of this study

  • This is the first study in South Africa to examine the information behaviour of health professionals in central and tertiary hospitals.

  • In this study, the cross-sectional survey design enabled an understanding of knowledge building dynamics and information behaviour towards clinical decision-making of doctors and nurses.

  • Due to time constraints among participants, this study is limited to doctors and nurses with direct patient care in four selected South African teaching hospitals.


Information Behaviour (IB) refers to the many ways in which people seek and use information in different contexts, including the workplace and everyday living.1 2 It is the totality of human behaviour in relation to sources and channels of information, which include both active and passive information seeking and information use.3 The concept of IB dates to 1948 when several papers on IB were presented at a Royal Society Scientific Information Conference.3 Since then, there has been great interest in understanding the IB of different professional groups. Due to this interest, researchers have produced numerous papers on IB of various professional groups and have developed models of IB to try and understand how information users interact with information.

Doctors and nurses need to maintain their knowledge as well as improve their competencies through acquiring and using information from different sources timeously. It is noted that failure to use evidence in medicine can lead to medical errors such as incorrect diagnosis and failure to provide prophylactic treatment, etc. Such medical errors impact the equality of healthcare outcomes.4

Furthermore, information is a prerequisite for quality healthcare services.5–7 Therefore, it is important to understand the IB of doctors and nurses as it impacts the quality of the service they provide. This point is emphasised by IB research done in both high-income countries and low and middle-income countries (LMICs) as well as rural and urban settings.1–3 8–13 This study, therefore, focuses on the IB of doctors and nurses whose role regularly involves direct patient care. The doctors and nurses are key role players in the healthcare system and often work jointly on interprofessional cooperation for patient care.

There is significant research globally about the IB of various groups of health professionals such as doctors, nurses and pharmacists. However, in South Africa, there is little research concerning the IB of doctors and nurses. The demands of health services at different levels of health service delivery systems require that appropriate information be used by all health professionals.14 Research has also shown that there is a link between access to quality clinical information and quality health services.6–16 This signifies that doctors and nurses with access to quality health information can improve health services. As a critical catalyst in the provision of healthcare, the IB of doctors and nurses in South Africa must be understood from their perspective. This would assist with the improvement of information management systems and facilitate the provision of information that is relevant to their daily needs.

The delivery of healthcare services in South Africa is a constitutional requirement.17 However, the quadruple burden of diseases and lack of clinical information, especially for doctors and nurses in rural and semiurban areas, have negatively affected the delivery of healthcare.18 It is, therefore, important to find out what role clinical information plays in patient care or the lack of it thereof. Additionally, in line with the National Health Insurance (NHI) implementation, it is expected that by 2030, tertiary and central care should be providing quality care for all. Considering some of the challenges faced by tertiary and quaternary hospitals, understanding the IB of doctors and nurses at this point will provide insight as to what they need to play their part in ensuring that quality care for all is achieved by 2030.

In their study, Greyson and Johnson revealed that due to mobile technology, internet and unreliability of information, health research is increasingly focusing on how health information is dispersed online and searched for as well as how patients use social networks to seek, share and interpret health information.19 It was revealed, however, that library and information science (LIS) researchers have developed a wide range of models to explain how they work in order to understand how humans interact with information.19 However, the application of LIS theories in information-based interventions is uncommon in health behaviour research.19 According to Greyson and Johnson, individuals undergo a series of stages before they experience behavioural change. Their study used value-expectancy models that identified predictors of individual behaviours as well as other models, which examined the level at which individuals’ function as well as the level at which they function as a collective. Information is typically identified in the early phases of stage models of health behaviour change as a key facilitator of behaviour change. It has been suggested by the transtheoretical model (TTM) of Prochaska and Prochaska that someone’s awareness of the need to change behaviour is raised by outside forces in the precontemplation phase.

This information may be provided to an individual in many ways, even when they try so hard to avoid its availability. Now, an individual who considers changing during the contemplation phase thinks about the advantages and disadvantages, summarise the information and combine it with their beliefs and knowledge to make sense out of it. According to Greyson and Johnson, the role of information on health behaviour change is less consistent in value-expectancy models than in stages of change models.1–19

Second, the precaution adoption process model (PAPM) consists of seven stages that individuals go through, one of which is an exit stage.20 Using the stages of change principle of the TTM, PAPM focuses on protecting oneself from harm by addressing specific behaviours. According to this model, unawareness stage is categorised first, then unengaged, and finally decision-maker’s stage. Here, the individual has the option of not acting, or acting, which then leads to maintenance and acting stages. The TTM does not differentiate unengaged and unawareness stages, so it is obvious that the PAPM is highly relevant for providing, receiving and processing information.19 According to the PAPM, different strategies are suggested for communicating information depending on the stage of engagement between these two stages. An addition of intentional choice of not changing behaviour indicates that individuals are responsible for assessing information, and for engaging in protective practices, for instance, examining information without acting and avoiding.19

Comparatively, value-expectancy models put less emphasis on information as a factor in changing health behaviour compared with stages of change models.19 The theory of reasoned action (TRA) suggests that changing behaviour depends on one’s own attitude and the subjective norms of others in the surrounding.21 TRA also claims that one is more likely to engage in a behaviour if they plan to do so. Theory of planned behaviour (TPB) (1991) is an extension of TRA that expands the notion of perceived behavioural control, which refers to an individual’s belief about the degree of control an individual has over his or her behaviours. There are few forms of explicit information practice in TRA and TPB value-expectancy theories. However, by communicating social norms and through intrinsic information, information plays a more indirect role in the development of social relations.

In healthcare, the health belief model (HBM)22 was initially developed by psychologists to explain why some people participate in screening programmes and others do not. It has been then applied to other areas of healthcare issues such as HIV sexual risk behaviours.19 Although HBM has changed over the past decades, its basic principle of the likelihood of individuals to adopt protective behaviours based on personal beliefs and perceptions about a health risk and the associated behaviour remains the same. The HBM differs from TRA and TPB models because it contains cues to action, which are believed to activate readiness and increase the chances of action, whether information is sought deliberately or just happened to be observed.19

Fisher and Fisher developed a newer value-expectancy model named information motivation behavioural (IMB) skills model for the identification and reduction of HIV risk behaviour.23 Despite the fact that knowledge and information models are not the same, the IMB model appears to use them interchangeably, even though one can receive a lot of information without necessarily becoming more knowledgeable.19

In addition to the above-mentioned models, there are several core models that do not fit whether on the stages of change or the value-expectancy models. Diffusion of innovation (DOI) by Rogers (1995) is the first core theory that was first proposed in 1950s, and it remains a core model to this day, it suggests that innovative ideas be disseminated through communication, allowing them to adapt to the changing environment over time. DOI put emphasis on information dissemination, since individuals find it hard to adopt new behaviour before they are informed about it.19–24

To understand the contributing factors of learning and behaviour, Bandura established the social cognitive theory.25 According to this theory, behavioural change is influenced by an individual’s characteristics, environmental factors and reciprocal determinism that standardise both one’s behaviour and environment. In this theory, knowledge is a requirement for behaviour change, although there are other factors, such as belief in one’s own ability to change, those are also necessary for behaviour change as they are in other models and theories.

There are still some unanswered questions regarding how people use information within their daily lives.19 They believe that understanding the role of information within processes and forecasting behavioural models will provide some clarity in their lives. They also mention that user’s behaviour, specifically self-identified needs, and preferences are the focus of information science. In controversy, communication is perceived crucial in health behaviour as it is often perceived more by others than by themselves. In the end, IB and practices are seldomly considered to have influence towards the public policy. As a result, Greyson and Johnson further argue that public health is predominantly a policymaking field.19

The aforementioned theories also expose that information is multifaceted and not just a commodity with intrinsic properties.19 Furthermore, IB and practices are contextual, and the acquisition of information does not translate to knowledge.19 It is important to understand information availability, provision, receipt and processing as this may help us better understand how to use information to support health behaviour change.19

Like any LMIC, South Africa is grappling with many challenges related to quality healthcare service (eg, adverse events and increased litigation, etc) despite quality improvement programmes in place. These conditions require health professionals who are proactive in seeking information, to have a supportive environment for information sources, to be innovative in the application of information, for the acquired information to translate to improved knowledge and for this information to be applied appropriately in the context to strive for improvement of public health broadly.19 This study, therefore, aims to investigate the factors that affect the IB of South African doctors and nurses in one central hospital and three tertiary hospitals: namely, Nelson Mandela Academic Hospital (NMAH) in the Eastern Cape Province, Witbank Hospital in Mpumalanga Province, Pietersburg Hospital in Limpopo Province and Robert Mangaliso Sobukwe Hospital (RMSH) in the Northern Cape Province. Understanding their IB in the rural South African context will help provide better insights into the information infrastructure needed to fulfil their information needs.

Methods and analysis

Study design, setting and participants

In the context of this study, a doctor refers to a person who has undergone medical training. Other doctors undergo extra training in one type of medical field and are called specialists or subspecialists. Conversely, nurses in the context of this study refer to professional nurses or registered nurses, enrolled nurses and enrolled nursing assistants. Doctors and nurses constantly take care of patients; therefore, they should be searching for information to incorporate the best available evidence into their decisions.8

Understanding the IB (which includes understanding of their needs, information source barriers encountered while seeking information) of doctors and nurses in the context of rural South Africa is essential in order to appreciate how they use information to manage patients and deal with challenges facing the health system. The study will employ a quantitative cross-sectional survey to get better insights into the IB of doctors and nurses in the selected South African hospitals. Data collection commenced on the 14 March 2022 and anticipated to end on 15 September 2022.

The study population is doctors and nurses in selected South African hospitals. The sample comprises of doctors and nurses working in one rural central hospital and three tertiary hospitals, namely NMAH, RMSH, Pietersburg Hospital and Witbank Hospital. Please see table 1 for research methods summary.26

Table 1

Research methods summary (adapted from Leckie et al, Modelling the information seeking of professionals)26

Sampling and sample size calculation

Simple random sampling and stratified random sampling were used to design the study. First, simple random sampling was used for the identification of the provinces and hospitals. Stratified random sampling was undertaken to select doctors and nurses to whom a questionnaire will be administered. The total sample size for the four hospitals was calculated using the equation, Embedded Image for a one-sided 95% CI and a 5% significance level (z=1.96). Since the proportion (p) of IB (the categorised distribution of IB patterns in a given category, for example, information sources, reasons for seeking information, etc) among health professionals is not known, this (p) was set at 50% and the desired precision, (d) was set at 3.5%. This, thus, yields a total minimum sample size of 784 health professionals. To factor in data entry errors, a further 10% (79) was added to yield the desired sample size of 863 participants for the four sites. Based on the actual number of doctors and nurses in each hospital, individual hospital sample sizes were proportionally weighted at 35% (NMAH), 25% (Pietersburg Hospital) and 20% each for Witbank Hospital and RMSH, based on the number of doctors and nurses in the four hospitals. As such, 303 of the participants will be drawn from NMAH, 216 from Pietersburg hospital and 172 each from Witbank hospital and RMSH (table 2). A random sampling of health professionals from each of the health facilities and stratified by profession was then undertaken.

Table 2

Strata specific samples for study sites

Based on the staff category, four sets of clinicians; namely, medical doctors and three groups of nurses, will be requested from the hospitals, and each will be allocated a unique number based on their appearance on the list. Three categories of nurses are drawn because of the differences in training between the three streams (enrolled nursing assistants=3 months, enrolled nurses=2 years and professional nurses=3 or 4 years) and registration with the Council, whereas all medical doctors have a similar foundational qualification and Council registration regardless of future career path. Nurses and medical doctors will be randomly drawn with the assistance of STATA statistical software (v.17.0) to get the total sample size.

Data collection instrument

A self-administered validated questionnaire (online supplemental appendix A) will be used to collect data. The questionnaire was adapted from a validated instrument that was previously used to ascertain the IB of nurses and doctors of one rural South African district,27 IB of medical doctors and professional nurses in selected hospitals of OR Tambo Health District, Eastern Cape Province, South Africa (Doctoral Thesis). The questionnaire will be distributed to the nurses and doctors in one of two ways. First, by emailing an editable Microsoft word document (questionnaire) to the doctors and nurses to complete and send back the completed questionnaire to the researchers. Second, by sharing an online version of the questionnaire that has been created on Google Forms through WhatsApp (should they provide their personal contact number and be amenable to this option) or email with the doctors and nurses. To achieve the above strategies, the researchers will be assisted by the Chief Executive officer, nursing manager, operational nurses and the doctors’ heads of departments or units. By completing and submitting the online survey means consenting to participate in this study (online supplemental appendix B). A study number will be allocated to each participant.

Statistical analysis

The data will first be captured and organised into a Microsoft Excel spreadsheet to inspect it for completeness and consistency, to inspect for any missing data and to code all data into numerical form. The data will then be imported into STATA V.17 (StataCorp LLC, College Station, Texas) for analyses. Age and duration of practice, numerical variables will be explored for normality using the Shapiro-Wilk test. If normally distributed numerical variables will be summarised using the mean, SD and range, and if not normally distributed, numerical variables will be summarised using the median and IQR. Categorical variable will be summarised using frequency tables, percentages and graphs. The comparison of the ages and duration of practice of nurses and doctors will be undertaken using the t test and/or the Wilcoxon rank sum test depending on the normality of the distribution of the concerned numerical variable. Comparison of ages and duration of experience of nurses or doctors by health facility will be undertaken using the one-way analysis of variance test if normally distributed or the Kruskal-Wallis test if not normally distributed. The χ2 test will be used to compare factors associated with two or more categorical variables. However, if the expected frequencies are <5, then the Fisher’s exact test will be used. Post hoc categorisation of open-ended responses will be undertaken. A significant level of 0.05 or less will be considered statistically significant.

Patient and public involvement

Not applicable.

Ethics and dissemination

Ethical approval was obtained from the University of the Witwatersrand Human Research Ethics Committee (reference: M211013) and Walter Sisulu University Human Research Ethics and Biosafety Committee (reference: 099/2021). Access approval was obtained from the Eastern Cape (reference: EC_202110_012), Limpopo (reference: LP_202110_007), Northern Cape (reference: NC_202110_001) and Mpumalanga (reference: MP_202110_011) Provincial Health Research Committees, respectively. The study will be conducted in accordance with the International Conference on Harmonisation (ICH) guidelines for good clinical practice in the conduct of research in human participants in South Africa and abide by the four ethical principles of autonomy, beneficence, non-maleficence and justice. Written informed consent will be obtained from participants.

Participation in the study will be free and voluntary. Any participant can withdraw from the study at any stage without giving any reason for the decision to do so, and this withdrawal will have no consequences whatsoever (online supplemental appendix B).

There are no risks involved in participation. There is no direct benefit to the participant, but the results of the study will benefit the health system of South Africa. All participant records will be identified using a unique study number. All records will be stored securely in locked filing cabinets with access limited to staff only. All listings which link participant identification numbers to other identifying information will be stored in a separate locked file that has limited access. All electronic information will also be securely stored on a network system with password-restricted access, which is limited to the principal investigator and other designated staff.

Findings will be disseminated widely to all relevant stakeholders, including participants. The results of this study will serve as a blueprint for developing policies related to information provision for health professionals in public hospitals in the South African context. The results will immediately provide information about the IB of doctors and nurses in tertiary hospitals for the implementation of the NHI in South Africa. Results will be presented at annual partner meetings, national and international conferences. Results will also be published in open-access peer-reviewed journals to facilitate broad access to findings.

Ethics statements

Patient consent for publication


The authors would like to thank the officials of the participating hospitals and provinces for their support and assistance.


Supplementary materials

  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.


  • Twitter @SikhumbuzoAMab1

  • Contributors NC devised the research, engaged stakeholders, completed the first draft of the manuscript and jointly approved the final draft. BS and JT facilitated ethics and research access approvals, edited and commented on versions of the manuscript, and incorporated and addressed feedback from the co-authors. SAM provided methodological strategy, a step-by-step plan of action, guided the thought processes of the research team, edited the manuscript, and approved the final version. VE edited versions of the manuscript and approved the final draft. WC is the content expert, edited and commented on versions of the manuscript. IF organised funding, LG, OM and RT edited versions of the manuscript.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.