Abstract
Background
The work or practice environments of health professionals play a central role in their retention in the healthcare system and their ability to provide quality patient care. The aim of the study was to examine and compare the satisfaction of early-career health professionals in the WiSDOM (Wits longitudinal Study to Determine the Operation of the labour Market among its health professional graduates) study with their clinical practice environments (CPEs) in South Africa, and the factors influencing their satisfaction.
Methods
WiSDOM, a prospective longitudinal cohort study, consists of eight health professions: clinical associates, dentists, doctors, nurses, occupational therapists, oral hygienists, pharmacists, and physiotherapists. Every year we collect information on the cohort’s involvement in direct patient care, their perceived workload, availability of medicines and equipment for patients in their care, and their satisfaction with the CPE.
We used Stata®19 for analysis. We used panel linear regression to investigate factors associated with the cohort’s satisfaction with their CPEs from 2018 to 2024 and logistic regression to evaluate the association between CPE and intention to leave in 2024.
Results
In 2024, the mean age of the cohort was 30.9 (± 2.0), the majority were female (74.4%) and working in urban areas (92.7%). In 2024, 59.7% of the overall cohort reported a heavy workload compared to 69.2% in 2018. Over the follow-up period, reported problems with the availability of medicines or equipment were worse in the public sector and in rural areas, compared to the private sector and urban areas respectively.
The cohort’s satisfaction score with the CPE was 6.7 out of 10 in 2018 and 6.9 in 2024. The predictors of CPE were year of follow-up, health profession, employment sector, and geographic location. Nurses (β = −1.2; 95% CI −1.7, −0.7; P < .001), and pharmacists (β = −0.7; 95% CI −1.1, −0.4; P < .001) scored their CPE significantly lower than the other professional groups. Health professionals in the public sector (β = −1.1; 95% CI −1.3, −0.9; P < .001) and in rural areas (β = −0.6; 95% CI −0.9, −0.3; P < .001) were less satisfied with their CPE compared to those in the private sector and urban areas respectively. Dissatisfaction with the CPE was significantly associated with intention to leave the workplace and the profession.
Conclusion
The study findings underscore the need for positive CPEs for early-career health professionals in South Africa both as a health workforce and patient safety imperative.
Keywords: health workforce, early-career, workplace, practice environment, WiSDOM, South Africa
Introduction
The health workforce is essential for the achievement of high-quality universal health coverage [1]. However, there is a projected shortage of 14 million health workers by 2030, the majority in low- and middle-income countries (LMICs) in sub-Saharan Africa [1]. These shortages adversely affect health care access, the retention and well-being of health professionals, and population health outcomes [2]. Although complex reasons influence health worker well-being, the work or practice environments play a central role in their retention and ability to provide quality care [2].
The concept of positive practice environments in nursing gained prominence in the early 2000s. Subsequent research in diverse settings has consistently demonstrated that such environments are associated with improved nurse well-being, job satisfaction, retention, and quality of patient care [3, 4]. Although most studies focus on nurses, systematic reviews indicate similar benefits for other health professionals and improved patient outcomes [5, 6]. However, the evidence base is limited, with most studies conducted in North America or Europe, in hospital settings, and using cross-sectional designs [5].
The COVID-19 pandemic elevated the importance of positive practice environments for all health professionals. In response, the World Health Professions Alliance launched a campaign defining these as settings that support excellence, decent work, workforce retention, quality patient care, and health system strengthening [2]. The pandemic also exposed and exacerbated existing challenges in practice environments, resulting in negative consequences for care and an increased risk of healthcare worker infections [7, 8]. In contrast, positive practice environments played a vital role in mitigating both the risk of COVID-19 infection among HCWs and in reducing their psychological distress [9].
An emerging literature on the experiences of early-career health professionals and the clinical practice environment (CPE) highlights their vulnerability to adverse workplace outcomes, including sickness absenteeism, burnout, and intention to leave the profession. In the United States, studies among young doctors found that long working hours, reduced leisure or sleep, and balancing clinical, research, and educational responsibilities [10, 11] could lead to burnout and other negative health outcomes. A German study among early-career physicians highlighted the role of leadership, workplace, and safety culture in job satisfaction and retention, ultimately affecting healthcare quality [12]. In Australia, research among early-career nurses found a positive correlation between retention and the practice environment [13]. A qualitative systematic review found that early-career allied health professionals and doctors in rural areas reported positive practice environments when supported by structured training, hands-on learning, and quality supervision [14]. In Malaysia, a study found that supportive work environments and collegial relationships improved early-career pharmacists’ job satisfaction and fulfilment [15]. Similarly, a study across eight African countries found that work environments, supervision, and perceived fair remuneration influenced primary care health worker job satisfaction [16].
In South Africa, early-career doctors reported inadequate infrastructure, lack of essential medical equipment, and poor working conditions in rural settings, which influenced their retention [17]. Additionally, the COVID-19 pandemic foregrounded the challenging work environments of early-career health professionals, which were associated with higher infection rates [8].
Despite a substantial literature on health work settings and its association with workforce and patient outcomes, knowledge gaps remain on the satisfaction of different categories of early-career health professionals with their CPEs. These gaps are more pronounced in South Africa and in other sub-Saharan African countries.
The WiSDOM (Wits longitudinal Study to Determine the Operation of the labour Market among its health professional graduates) cohort study in South Africa was established in 2017 to investigate, inter alia, the career trajectories, satisfaction with different aspects of their jobs, working conditions, job locations, and future intentions of eight health professional categories that graduated from the University of the Witwatersrand in Johannesburg, South Africa [18]. The eight health professional categories comprise clinical associates, dentists, doctors, nurses, occupational therapists, oral hygienists, pharmacists, and physiotherapists [18]. An annual survey, which was in its eighth year in 2025, collects longitudinal data on these outcomes of interest, as well as changes in the cohort’s demographic and occupational characteristics.
Consequently, the primary aim of this study was to examine and compare the satisfaction of early-career health professionals in the WiSDOM cohort study with their CPEs since 2018 when they commenced formal employment. A secondary aim was to investigate the factors that influence CPE satisfaction. The rationale for the study is both its scholarly contribution and its policy relevance. The study contributes to and advances empirical knowledge on CPEs and on different groups of early-career health professionals in South Africa. The study contributes to the discourse on health workforce retention strategies in South Africa amid projections of chronic shortages in the lead-up to 2030, the target date for the achievement of the sustainable development goals. The study findings have relevance for other LMICs.
Materials and methods
The WiSDOM study design and data collection methods have been described in detail previously [18], but are outlined briefly here.
Study context
South Africa has a mixed public–private health system, with health a concurrent national and provincial responsibility [19]. The resource-constrained public sector provides care to over 80% of the population through a network of primary care facilities and hospitals but accounts for roughly half of total expenditure [20]. By contrast, the private sector, dominated by three large hospital groups, consumes a similar share of spending while serving 14% of the population [20]. Inequities in financing, workforce distribution, access, and care quality remain stark across sectors, provinces, and rural–urban areas [19]. Public facilities, especially in rural provinces, face persistent staff shortages, equipment gaps, and medicine stockouts [17, 21].
Study design
WiSDOM is a prospective, longitudinal health workforce cohort study that commenced in 2017, with three shared characteristics: final-year studies in 2017; education and training at the Faculty of Health Sciences of the same South African University; and health professional qualification [22].
Study population
At baseline in 2017, the universe of final-year students (n = 571) in each of the eight health professions was invited to participate in the study, hence there was no sampling [22]. We obtained a response rate of 89.5% at baseline [22]. Annual follow-up started in 2018, the first year of work after graduating, and will continue annually.
Data collection
We do annual electronic follow-up surveys that entail sending a unique survey link to the email address of the participating cohort members [18]. Every year, we obtain voluntary, informed consent from each participant, prior to completion of a self-administered questionnaire (SAQ) via REDCap (Research Electronic Data Capture), a secure, web-based software platform designed for online databases and surveys [23]. The annual survey occurs over a period of six weeks, with weekly reminders sent to the emails or mobile telephone numbers of cohort participants.
In line with the study outcomes, we use a unique, customized SAQ that collects annual information on changes in demographics (e.g. marital status), geographic location (urban or rural), work status, employment sector (public or private), health facility, and satisfaction with different aspects of the job, and future intentions (e.g. intention to leave current workplace and/or profession).
In our study, the CPE refers to the overall setting and conditions (e.g. manageable workload, functioning equipment, medicine availability) in which healthcare professionals deliver patient care. Hence, every year, we establish whether the cohort members are involved in direct patient care and then ask about their perceived workload (five-point Likert scale from very light to very heavy), and the availability of medicines and equipment for patients in their care in the month preceding the survey (yes or no). They are also asked to rate their satisfaction with the CPE using a single question: ‘On a scale from 1 (Very Dissatisfied) to 10 (Very Satisfied), how satisfied are you with your clinical practice environment’.
Data analysis
The data were imported from REDCap into Stata® 19 for analysis. There were no missing data for the variables used in this analysis. For workload, we combined very light and light categories into one ‘light’ category, and the heavy and very heavy categories into one ‘heavy’ category, to compare with the ‘just right’ category. The 10-point CPE satisfaction score was analyzed numerically [24]. We computed the mean score for satisfaction with the CPE for each of the health professions, and for the entire cohort.
As this is a cohort study, we analyzed the longitudinal data on CPEs for the 7-year period from 2018 (the first follow-up after graduation) until 2024. We used random effects panel linear regression to investigate the factors associated with the cohort’s CPE satisfaction scores, without further clustering. We verified the suitability of the CPE score for linear regression by confirming residual normality and homoscedasticity. Changes over time were evaluated as a linear trend. Coefficients for the different professional groups were calculated as contrasts from the group mean rather than an arbitrary baseline group.
Finally, the association between satisfaction with the CPE and intention to leave was evaluated using multiple logistic regression. For this analysis, CPE score was dichotomized so that the dissatisfied cohort members (scoring 1–5 out of 10) could be compared with the satisfied (6–10 out of 10) to simplify interpretation, though the effects were consistent across alternative specifications.
Results
Between 2020 and 2023, the annual follow-up response rate in the WiSDOM cohort study remained at 71% of the original cohort but ranged from 56.0% for medical doctors to 100.0% for clinical associates and oral hygienists. In 2024, the overall response rate declined slightly to 68.1%.
Demographic and occupational characteristics
Table 1 shows the demographic and occupational characteristics of the WiSDOM cohort in 2024. The mean age of the cohort was 30.9 (± 2.0); the majority were female (74.4%) and working in urban areas (92.7%). In 2024, the proportion working in the public sector ranged from 0.0% of dentists to 79.9% of medical doctors.
Table 1.
Socio-demographic characteristics of WiSDOM cohort, 2024.
| CA | DT | MD | NS | OT | OH | PH | PT | Total | |
|---|---|---|---|---|---|---|---|---|---|
| (n = 38) | (n = 18) | (n = 155) | (n = 18) | (n = 24) | (n = 6) | (n = 53) | (n = 36) | (n = 348) | |
| Age (Mean ± SD) | 29.0 ± 1.3 | 31.6 ± 1.8 | 32.2 ± 1.9 | 30.3 ± 1.1 | 29.7 ± 0.8 | 28.7 ± 0.9 | 29.7 ± 1.5 | 30.2 ± 1.4 | 30.9 ± 2.0 |
| Age group (%) | |||||||||
| <30 years | 86.8% | 11.1% | 3.9% | 50.0% | 75.0% | 83.3% | 71.7% | 52.8% | 37.4% |
| ≥30 years | 13.2% | 88.9% | 96.1% | 50.0% | 25.0% | 16.7% | 28.3% | 47.2% | 62.6% |
| Female (%) | 86.8% | 77.8% | 64.5% | 83.3% | 100.0% | 100.0% | 64.2% | 91.7% | 74.4% |
| Self-identified Race a (%) | |||||||||
| Black African | 97.3% | 22.2% | 47.7% | 77.8% | 8.7% | 66.7% | 71.2% | 14.7% | 51.3% |
| Coloured | 0.0% | 5.6% | 1.3% | 0.0% | 0.0% | 0.0% | 1.9% | 14.7% | 2.7% |
| Asian/Indian | 0.0% | 50.0% | 17.2% | 0.0% | 21.7% | 16.7% | 25.0% | 20.6% | 18.0% |
| White | 2.7% | 16.7% | 32.5% | 22.2% | 69.6% | 16.7% | 1.9% | 50.0% | 27.1% |
| Rural birth (%) | 13.2% | 0.0% | 12.9% | 16.7% | 4.2% | 16.7% | 30.2% | 5.6% | 13.8% |
| Geographical area of work | |||||||||
| Rural (Farm, village) | 17.9% | 6.2% | 8.1% | 7.1% | 0.0% | 0.0% | 6.4% | 3.0% | 7.3% |
| Urban (Town, City) | 82.1% | 93.8% | 91.9% | 92.9% | 100.0% | 100.0% | 93.6% | 97.0% | 92.7% |
| Employment sector | |||||||||
| Public sector | 39.3% | 0.0% | 79.9% | 35.7% | 25.0% | 0.0% | 29.8% | 18.2% | 51.1% |
| Private-for-profit | 57.1% | 100.0% | 16.1% | 28.6% | 66.7% | 100.0% | 68.1% | 78.8% | 43.8% |
| NGO/Not-for profit | 3.6% | 0.0% | 4.0% | 35.7% | 8.3% | 0.0% | 2.1% | 3.0% | 5.1% |
| Hospital setting (%) | 21.1% | 0.0% | 70.3% | 38.9% | 25.0% | 0.0% | 18.9% | 36.1% | 44.0% |
Abbreviations: CA, clinical associate; DT, dentist; MD, medical doctor; NS, nurse; OH, oral hygienist; OT, occupational therapist; PH, pharmacist; PT, physiotherapist.
Given South Africa’s apartheid legacy, ‘race’ continues to influence perspectives and socioeconomic outcomes, hence we left it to study participants to self-identify.
Reported workload
Figure 1 shows consistently high reported workloads from 2018 to 2024. In 2018, 69.2% of the cohort reported heavy workloads (ranging from 30.3% of clinical associates to 83.3% of nurses), and this remained high at 59.7% in 2024. Except for dentists and physiotherapists, most of the other six professions reported heavy workloads throughout the 7-year period.
Figure 1.
Reported workload by WiSDOM cohort members, 2018–2024.
Satisfaction with the CPE
The panels in Fig. 2 show the 2018–2024 trends in the mean scores of the CPE for the different professions.
Figure 2.
WiSDOM cohort’s satisfaction with the CPE, 2018–24.
In 2018, the satisfaction score with the CPE was 6.7 out of 10 for the entire cohort, and 6.9 in 2024. However, over the 7-year period, the mean scores for nurses have been lower than the overall cohort’s mean scores (5.9 in 2018 and 6.2 in 2024). The mean score for pharmacists dipped to a low of 5.6 in 2022.
Availability of medicines and equipment
Figure 3 compares the availability of medicines and equipment for patients under their care between the public and private health sectors and between urban and rural geographical areas. Medicines were unavailable more frequently in the public sector compared to the private sector, and this was worse in rural compared to urban areas, with similar patterns for equipment.
Figure 3.
Comparing the availability of medicines and equipment by sector and urban-rural areas.
Factors influencing satisfaction with the CPE
These patterns were formally tested in regression analysis. Table 2 shows that the predictors of satisfaction with the CPE were year of follow-up, health profession, employment sector, and geographic location. There was a significant annual decrease in satisfaction with the CPE over the 7-year period. Nurses (β = −1.2; 95% CI −1.7, −0.7; P < .001), and pharmacists (β = −0.7; 95% CI −1.1, −0.4; P < .001) scored their CPE significantly lower than the other professional groups. In contrast, doctors, dentists, and occupational therapists scored their CPEs higher than the average of all professional groups. Health professionals in the public sector (β = −1.1; 95% CI −1.3, −0.9; P < .001) and in rural areas (β = −0.6; 95% CI −0.9, −0.3; P < .001) were significantly less satisfied with their CPE than those in the private sector and urban areas respectively.
Table 2.
Random effects panel linear regression: factors influencing satisfaction with CPE.
| Variable | Coefficient | CI | P value |
|---|---|---|---|
| Year | −0.07 | −0.11, −0.03 | .001 |
| Public sector | −1.09 | −1.33, −0.85 | <.001 |
| Rural area | −0.57 | −0.85, −0.30 | <.001 |
| Outside SA | 0.72 | 0.26, 1.18 | .002 |
| Professional group | |||
| NS vs mean | −1.20 | −1.71, −0.69 | <.001 |
| PH vs mean | −0.73 | −1.09, −0.37 | <.001 |
| OH vs mean | −0.18 | −1.10, 0.74 | .701 |
| CA vs mean | −0.09 | −0.48, 0.30 | .651 |
| PT vs mean | 0.30 | −0.07, 0.67 | .114 |
| MD vs mean | 0.38 | 0.09, 0.66 | .009 |
| DT vs mean | 0.66 | 0.12, 1.20 | .016 |
| OT vs mean | 0.86 | 0.42, 1.30 | <.001 |
| n | 2123 | ||
| Individuals | 397 | ||
| Chi-squared | 196.9 | ||
| P value | <0.001 | ||
| R 2 | 0.167 | ||
| ICC | 0.252 |
Model also adjusted for gender and age as potential confounders.
Abbreviations: CA, clinical associate; DT, dentist; MD, medical doctor; NS, nurse; OH, oral hygienist; OT, occupational therapist; PH, pharmacist; PT, physiotherapist.
Impact of dissatisfaction with the CPE
Satisfaction with the CPE was significantly associated with workplace and professional retention. In 2024, early-career health professionals who reported dissatisfaction with the CPE were 3.6 (95% CI: 1.8, 7.2; P < .001) times more likely to indicate that they planned to leave their healthcare facility than those who reported satisfaction with the CPE, after adjusting for age, gender, professional group, area, sector and South African location. Similarly, those dissatisfied with the CPE were 5.4 (95% CI: 1.6, 17.5; P = .006) times more likely to state that they planned to leave the profession compared to those who were satisfied with their CPE, after adjusting for confounders.
Discussion
Statement of principal findings
The WiSDOM study provides novel insights into early-career health professionals’ satisfaction with their CPEs in South Africa over seven years and highlights systemic challenges. Satisfaction varied by health profession, employment sector, geographic location, and time. Nurses and pharmacists scored their CPEs lower compared to the other six professions. Medicine shortages and lack of or malfunctioning equipment were worse in the public health sector and in rural areas. These CPE shortcomings were associated with an increased intention to leave the profession and workplace, with potential negative consequences for workforce stability and health system performance.
Interpretation within the context of the wider literature
Most previous studies have reported on a single category of health professionals [12, 13, 15, 25]. Our WiSDOM study examined eight health professional categories simultaneously. Despite some variation, self-reported workload remained consistently high across professions from 2018–2024, with over two-thirds reporting heavy workloads upon workplace entry in 2018. Other South African studies among early-career registered nurses [26] and occupational therapists [27] reported heavy workloads, long work hours, and inadequate organizational support. A 2022 qualitative systematic review of early-career health professionals in rural settings reported high workloads, stress, limited support, and burnout, contributing to decisions to leave rural practice [14]. Our study period includes the COVID-19 pandemic, but we did not find significant changes in reported workloads. In contrast, evidence from a 2022 scoping review attributes increased healthcare provider workloads during pandemics to more complex care, added tasks, documentation demands, and new skill requirements [28].
The WiSDOM cohort’s consistent reporting of medicine unavailability, especially in public and rural settings, is supported by evidence of chronic stockouts from another South African study [21] and a scoping review that included several African countries [29].
Similarly, the cohort’s reports of lack of or malfunctioning equipment for patients under their care, worse in rural and public facilities, were also documented in other LMICs [30].
The study findings highlight how different groups of health professionals experience their CPEs, shaped by occupation, sector, and geographic location. The variation suggests that contextual and structural inequities, rather than individual factors, play a significant role in shaping workplace experiences. These disparities are concerning given evidence from a systematic review demonstrating that supportive and well-functioning CPEs are associated with higher quality of care and improved patient outcomes [5].
Implications for policy, practice, and research
The persistently high self-reported workloads of the WiSDOM cohort over the 7-year period are concerning. Workload pressures could be mitigated by flexible scheduling, task-sharing and team-based care models, and employee wellness programmes targeting early-career health professionals.
Medicine stockouts disrupt continuity of care, put additional pressure on health professionals who often have to deal with angry or disgruntled patients. Similarly, equipment deficits hinder diagnostic accuracy and treatment effectiveness, compromising patient outcomes. These constraints were more pronounced in the public sector and rural areas, consistent with the observed differences in reported CPEs. The public–private and rural inequities point to the need for a national equity-focused policy that prioritizes implementation in rural and underserved areas, ring-fenced budgets for essential medicines and equipment, and improved supply chain systems.
Early career health professionals are the future health workforce. Retention strategies should prioritize their well-being and professional development, including supportive management, supervision, and mentorship. Ultimately, creating supportive CPEs is essential for sustaining the health workforce and ensuring high-quality, equitable patient care, regardless of geographical location.
Further research should examine the empirical relationship between self-reported CPE and objective measures of patient safety, service quality, and patient outcomes, as well as the differences across the eight health professions and practice settings.
Strengths and limitations
The WiSDOM cohort study provides empirical evidence on the factors that influence the satisfaction of early-career health professionals with their CPEs. The cohort study design is a major strength, enabling the analysis of longitudinal data on reported workload, perceptions of the CPEs, and availability of medicines and equipment. The longitudinal design also allows the assessment of whether improved workplace conditions reduce health professional attrition over time. The novelty of the study is the simultaneous focus on eight health professional groups and the longitudinal follow-up, uncommon in both high-income and LMICs.
The reliance on self-reported measures introduces possible social desirability bias and subjective interpretation of the CPE. The lower participation rate among medical doctors may limit the representativeness of this group. However, the highest doctor attrition occurred in 2018, the first year of follow-up, hence the same group of doctors has participated consistently from 2018 to 2024. Importantly, these limitations are mitigated by the cohort design, which strengthens the robustness of the analysis and enhances confidence in the observed patterns over time.
Conclusions
Our study found high reported workloads by early-career health professionals over the 7-year period, and persistent challenges in medicine and equipment availability—especially in the public sector and rural settings in South Africa. Although the cohort’s satisfaction with the CPE remained relatively stable, significant disparities by profession, sector, and location point to systemic inequities. Our findings show that unsatisfactory CPEs are associated with intention to leave the profession and the workplace. These negative outcomes could lead to compromised patient care, making investment in equitable, supportive work environments essential for sustaining the health workforce.
Acknowledgements
The paper draws on a presentation done at the 2024 ISQua Conference in Istanbul, Türkiye. The WiSDOM study would not have been possible without the support and encouragement of many people. We owe a debt of gratitude to the cohort members, from whom we continue to learn a great deal. We thank the various stakeholders in the Wits Faculty of Health Sciences, and the Wits communications and marketing division for helping us to make WiSDOM a reality.
Contributor Information
Laetitia C Rispel, Centre for Health Policy & South African Research Chairs Initiative (SARChI), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Prudence Ditlopo, Centre for Health Policy, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Duane Blaauw, Centre for Health Policy, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Author contributions
Laetitia Rispel (Conceptualization, Data curation, Funding acquisition, Methodology, Project administration, Supervision, Visualization, Writing—editing), Prudence Ditlopo (Conceptualization, Data curation, Methodology), and Duane Blaauw (Conceptualization, Data curation, Formal analysis, Methodology, Visualization, Writing—editing)
Conflicts of interest
Laetitia Rispel is an ISQua member and an inaugural member of the International Academy of Quality and Safety (IAQS). Otherwise, the authors declare no conflict of interest, financial or otherwise.
Funding
The South African Research Chairs Initiative (SARChI) of the South African National Research Foundation funded this study (Grant #SARCI150322115715). Laetitia Rispel is the Chair holder. The views expressed in this study are those of the authors. The funding source was not involved in the design of the study, in the data collection or analysis, in the interpretation of the results, or in the writing of the manuscript.
Data Availability
We cannot share data publicly because this is an active cohort study of health professional graduates. The Human Research Ethics Committee (Medical) of the University of the Witwatersrand has imposed restrictions because of the confidential and sensitive nature of the data.
Ethical approval and other permissions
In 2017, we obtained ethics approval for the study from the University of the Witwatersrand Human Research Ethics Committee (Medical #M170 550), and we renewed the ethics approval in 2022 (#M220 672). All study procedures followed are in accordance with the Singapore Declaration on Research Integrity of 2010, available at: www.singaporestatement.org. We also obtained study permission from all the relevant university authorities. The details are contained in previous publications (Rispel et al. 2021; Rispel et al. 2019).
References
- 1. Boniol M, Kunjumen T, Nair TS et al. The global health workforce stock and distribution in 2020 and 2030: a threat to equity and ‘universal’ health coverage? BMJ Glob Health 2022;7:e009316. 10.1136/bmjgh-2022-009316 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. World Health Professions Alliance. Stand up for Positive Practice Environments. Geneva: World Health Professions Alliance, 2023.
- 3. Aiken LH, Sermeus W, Van den Heede K et al. Patient safety, satisfaction, and quality of hospital care: cross sectional surveys of nurses and patients in 12 countries in Europe and the United States. BMJ 2012;344:e1717. 10.1136/bmj.e1717 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Munyewende P, Rispel LC, Chirwa T. Positive practice environments influence job satisfaction of primary health care clinic nursing managers in two South African provinces. Hum Resour Health 2014;12:27. 10.1186/1478-4491-12-27 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Braithwaite J, Herkes J, Ludlow K et al. Association between organisational and workplace cultures, and patient outcomes: systematic review. BMJ Open 2017;7:e017708. 10.1136/bmjopen-2017-017708 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Al-Ghraiybah T, Sim J, Lago L. The relationship between the nursing practice environment and five nursing-sensitive patient outcomes in acute care hospitals: a systematic review. Nurs Open 2021;8:2262–71. 10.1002/nop2.828 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Risko N, Werner K, Offorjebe OA et al. Cost-effectiveness and return on investment of protecting health workers in low-and middle-income countries during the COVID-19 pandemic. PLoS One 2020;15:e0240503. 10.1371/journal.pone.0240503 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Rispel L, Ditlopo P, White JA et al. Vaccination status, personal and workplace experiences of early career health professionals in the WiSDOM cohort study during the COVID-19 pandemic in South Africa. BMJ Open 2024;14:e089998. 10.1136/bmjopen-2024-089998 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Zungu M, Voyi K, Mlangeni N et al. Organizational factors associated with health worker protection during the COVID-19 pandemic in four provinces of South Africa. BMC Health Serv Res 2021;21:1080. 10.1186/s12913-021-07077-w [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Cranley NM, Cunningham CJL, Panda M. Understanding time use, stress and recovery practices among early career physicians: an exploratory study. Psychol Health Med 2016;21:362–7. 10.1080/13548506.2015.1061675 [DOI] [PubMed] [Google Scholar]
- 11. Kulkarni K, Muia J, Boulaftali Y et al. Early career professionals: a challenging road. Res Pract Thromb Haemost 2018;2:11–3. 10.1002/rth2.12070 [DOI] [Google Scholar]
- 12. Etti N, Weigl M, Gambashidze N. Psychological safety, job satisfaction, and the intention to leave among German early-career physicians. Int J Qual Health Care 2025;37:mzaf002. 10.1093/intqhc/mzaf002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Mills J, Woods C, Harrison H et al. Retention of early career registered nurses: the influence of self-concept, practice environment and resilience in the first five years post-graduation. J Res Nurs 2017;22:372–85. 10.1177/1744987117709515 [DOI] [Google Scholar]
- 14. Dymmott A, George S, Campbell N et al. Experiences of working as early career allied health professionals and doctors in rural and remote environments: a qualitative systematic review. BMC Health Ser Res 2022;22:951. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Chee PY, Tan LV, Lee CCW et al. The stress, satisfaction and fulfilment of early career pharmacists–a qualitative analysis of a survey on their professional and personal lives. Int J Pharm Pract 2023;31:250–6. 10.1093/ijpp/riad004 [DOI] [PubMed] [Google Scholar]
- 16. Muhula S, Opanga Y, Kassim S et al. Predictors of health-workforce job satisfaction in primary care settings: Insights from a cross-sectional multi-country study in eight African countries. Int J Environ Res Public Health 2025;22:1108. 10.3390/ijerph22071108 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Kotzee T, Couper ID. What interventions do South African qualified doctors think will retain them in rural hospitals of the Limpopo province of South Africa? RRH 2006;6:1–17. 10.22605/RRH581 [DOI] [PubMed] [Google Scholar]
- 18. Rispel LC, Ditlopo P, White J et al. Methodological considerations in establishing and maintaining longitudinal health workforce studies: lessons learned from the WiSDOM cohort in South Africa. Glob Health Action 2021;14:1996688. 10.1080/16549716.2021.1996688 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. The Presidency SA. Towards a 30 Year Review of South Africa’s Democracy: 1994-2024-Synthesis Report. Pretoria: Government Printing Works, 2024. [Google Scholar]
- 20. Statistics South Africa. Household Expenditure on Health in South Africa: Findings from the Income and Expenditure Survey, 2022/23. Pretoria: Statistics South Africa, 2026. [Google Scholar]
- 21. Modisakeng C, Matlala M, Godman B et al. Medicine shortages and challenges with the procurement process among public sector hospitals in South Africa: findings and implications. BMC Health Serv Res 2020;20:234. 10.1186/s12913-020-05080-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Rispel LC, Ditlopo P, White JA et al. Socio-economic characteristics and career intentions of the WiSDOM health professional cohort in South Africa. PLoS One 2019;14:e0223739. 10.1371/journal.pone.0223739 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Harris PA, Taylor R, Thielke R et al. Research electronic data capture (REDCap ) - a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42:377–81. 10.1016/j.jbi.2008.08.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Norman G. Likert scales, levels of measurement and the “laws” of statistics. Adv Health Sci Educ Theory Pract 2010;15:625–32. 10.1007/s10459-010-9222-y [DOI] [PubMed] [Google Scholar]
- 25. McKillop A, Doughty L, Atherfold C et al. Reaching their potential: perceived impact of a collaborative academic–clinical partnership programme for early career nurses in New Zealand. Nurse Educ Today 2016;36:145–51. 10.1016/j.nedt.2015.09.005 [DOI] [PubMed] [Google Scholar]
- 26. Scheepers N, Coetzee SK, Fourie E. Early-career registered nurses’ work experience and nurse outcomes in South African hospitals: a cross-sectional survey. BMC Nurs 2025;24:523. 10.1186/s12912-025-03188-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. de Witt P, Bruce M, Botha M et al. Early career South African occupational therapists’ perceptions of person–environment fit in work–life areas that influence work stress. Occup Ther Int 2024;2024:3189429. 10.1155/2024/3189429 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Doleman G, De Leo A, Bloxsome D. The impact of pandemics on healthcare providers’ workloads: a scoping review. J Adv Nurs 2023;79:4434–54. 10.1111/jan.15690 [DOI] [PubMed] [Google Scholar]
- 29. Yenet A, Nibret G, Tegegne BA. Challenges to the availability and affordability of essential medicines in African countries: a scoping review. Clinicoecon Outcomes Res 2023;15:443–58. 10.2147/CEOR.S413546 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Gupta N, Coates MM, Bekele A et al. Availability of equipment and medications for non-communicable diseases and injuries at public first-referral level hospitals: a cross-sectional analysis of service provision assessments in eight low-income countries. BMJ Open 2020;10:e038842. 10.1136/bmjopen-2020-038842 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
We cannot share data publicly because this is an active cohort study of health professional graduates. The Human Research Ethics Committee (Medical) of the University of the Witwatersrand has imposed restrictions because of the confidential and sensitive nature of the data.