Exploring mental health challenges and interventions for healthcare professionals in Africa; A scoping Review

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These pressures contribute to high rates of burnout, anxiety, depression, and trauma, which compromise personal wellbeing, patient outcomes, and workforce retention. Despite emerging interventions, including peer support, counseling, and digital platforms, their scope and effectiveness remain underexplored in African contexts. Methods We conducted a scoping review following the Joanna Briggs Institute (JBI) framework and reported according to PRISMA-ScR guidelines. A systematic search of SCOPUS, Web of Science, and PubMed identified studies published between 2000 and 2025. Eligible studies included peer-reviewed articles addressing mental health challenges or interventions among healthcare professionals in Africa. Data extraction captured study characteristics, cadres involved, mental health outcomes, interventions, and implementation barriers. Quantitative findings were summarized descriptively, while qualitative data were synthesized thematically. Results From 6,567 records, 119 studies met inclusion criteria, spanning 20 African countries. Most were cross-sectional (n = 105), with South Africa contributing the largest number (n = 19). Burnout was the most frequently reported challenge, with prevalence ranging from 20% in Ghana to 95% among South African medical interns. Anxiety rates peaked during the COVID-19 pandemic, reaching 90.5% in Egypt and 59.9% in Kenya. Depression prevalence ranged from 13.6% in Ethiopia to 94% of Egyptian healthcare workers. Nurses and midwives consistently reported higher burdens than physicians. Stress, PTSD, compassion fatigue, and workplace violence were recurrently reported particularly in conflict-affected or pandemic settings. Structural drivers included excessive workloads, poor remuneration, stigma, and inadequate protective equipment. Interventions such as psychosocial support groups, stress management workshops, and digital mental health platforms showed promise but lacked rigorous evaluation. Conclusions Healthcare professionals in Africa face substantial mental health challenges, exacerbated by systemic resource constraints and pandemic-related stressors. While innovative interventions exist, evidence on their effectiveness and sustainability remains limited. Strengthening culturally appropriate support systems and occupational health policies is essential to protect workforce wellbeing, enhance resilience, and improve health system performance across the continent. Clinical trial number: Not applicable Mental health Healthcare professionals Africa Anxiety Depression Burn out. Stress Figures Figure 1 Figure 2 Background Mental health challenges among healthcare professionals have emerged as a global public health concern, with rising rates of stress, burnout, anxiety, depression, and post-traumatic stress across health systems worldwide 1 . International studies show that a significant proportion of healthcare workers experience psychological distress due to demanding workloads, long working hours, emotionally intense clinical encounters, and the pressure to provide high-quality care in increasingly complex environments 2 , 3 . The COVID-19 pandemic further amplified this burden, exposing systemic vulnerabilities and underscoring the urgent need to protect the mental wellbeing of the healthcare workforce globally 4 . In Africa, these challenges are intensified by unique regional stressors. Healthcare professionals often work in under-resourced settings characterized by chronic staff shortages, high patient-to-provider ratios, recurrent infectious disease outbreaks, and limited medical supplies 5 . Consequently, stress and burnout are common, with many workers also experiencing anxiety, depression, compassion fatigue, and trauma from exposure to severe illness and mortality 6 . These psychological pressures not only affect personal wellbeing but also impact job performance, patient outcomes, and retention of skilled health workers 7 . Access to mental health resources remains limited across many African healthcare systems. Structural barriers such as inadequate mental health services, stigma surrounding mental illness, insufficient workplace support programs, and weak occupational health policies leave many healthcare workers without the help they need 4 , 8 . Systemic stressors including political instability, inconsistent remuneration, and reliance on overstretched public facilities further contribute to emotional exhaustion and erode resilience among healthcare professionals 9 , 10 . Evidence suggests that interventions such as peer-support programs, counseling services, stress management workshops, and organizational reforms can mitigate these challenges. In Africa, innovative approaches have emerged, including community-based psychosocial support in Uganda and digital mental health platforms piloted in South Africa 11 . Yet, the scope, effectiveness, and sustainability of such interventions remain underexplored, and global strategies often fail to account for local cultural norms, resource constraints, and the lived experiences of healthcare workers 6 . Given the critical role of healthcare professionals in advancing universal health coverage and responding to public health emergencies, addressing their mental health needs is both a moral imperative and a strategic priority 12 . By systematically mapping mental health challenges and interventions for healthcare professionals in Africa, this scoping review will generate context-specific insights to inform culturally appropriate policies, strengthen workforce resilience, and enhance health system performance across the continent. Methods Study Design This study was conducted as a scoping review to map the existing literature on mental health challenges and interventions for healthcare professionals in Africa. The review follows the methodological framework proposed by the Joanna Briggs Institute (JBI) for scoping reviews 13 . The reporting of this review adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist 14 . Study questions We used the PCC (population, concept and context). Q1 What are the current mental health challenges experienced by healthcare professionals in Africa? P: Healthcare professionals C: Mental health challenges (e.g., stress, burnout, depression, anxiety) C: Africa Q2 What mental health interventions have been implemented to support healthcare professionals in Africa? P: Healthcare professionals C: Mental health interventions/strategies C: Africa Q3 How effective are existing mental health strategies in improving psychological well-being among healthcare professionals in African settings? P: Healthcare professionals C: Effectiveness of mental health interventions C: Africa Q4 What barriers and facilitators affect the implementation of mental health strategies for healthcare professionals in Africa? P: Healthcare professionals C: Barriers and enablers to implementation C: Africa Study questions We used the PCC (population, concept and context). Q1 What are the current mental health challenges experienced by healthcare professionals in Africa? P: Healthcare professionals C: Mental health challenges (e.g., stress, burnout, depression, anxiety) C: Africa Q2 What mental health interventions have been implemented to support healthcare professionals in Africa? P: Healthcare professionals C: Mental health interventions/strategies C: Africa Q3 How effective are existing mental health strategies in improving psychological well-being among healthcare professionals in African settings? P: Healthcare professionals C: Effectiveness of mental health interventions C: Africa Q4 What barriers and facilitators affect the implementation of mental health strategies for healthcare professionals in Africa? P: Healthcare professionals C: Barriers and enablers to implementation C: Africa Information Sources A comprehensive search was conducted across the following electronic bibliographic databases including SCOPUS, Web of Science, PubMed and Citation tracking. Search Strategy A systematic search strategy was developed using medical subject headings (MeSH) and keywords related to the PCC framework. Boolean operators (AND, OR) will be utilized to combine search terms. The search string was adapted to the syntax of each specific database is provided in the supplementary file 1. Study Selection The selection process occurred in two stages: Title and Abstract Screening: Two independent reviewers screened titles and abstracts generated by the search against the inclusion criteria. Full-Text Review: Articles deemed potentially relevant underwent a full-text assessment by two independent reviewers. Any disagreements regarding eligibility at either stage were resolved through consultation with a third reviewer and discussion until consensus was reached. The study selection process was documented and presented using a PRISMA flow diagram to ensure transparency. Eligibility Criteria Inclusion Criteria Peer-reviewed journal articles of all study designs (quantitative, qualitative, and mixed-methods) Studies addressing mental health challenges affecting healthcare professionals in Africa including but not limited to stress, burnout, depression, anxiety, and PTSD. Studies addressing primary, secondary, or tertiary mental health interventions or strategies designed to support these healthcare professionals in Africa. Limited to articles published in the last 25 years. Only articles written in English or those with accessible English translations will be included. Exclusion Criteria Studies focusing on healthcare professionals working outside of Africa. Review articles, grey literature, editorials, commentaries, and conference abstracts lacking full data. Articles where full text is not available or data is insufficient for extraction. Data Extraction Data was extracted from the included articles by five independent reviewers using a standardized data extraction form developed for this study. The form captured the following variables: Author(s) and year of publication. Title of the study Country/Region of study Study design and sample size. Cadre of healthcare professionals involved. Specific mental health challenges identified. Type of interventions/strategies implemented (if any). Key findings regarding effectiveness, barriers, and facilitators. Data Synthesis and Analysis The analysis combined descriptive statistics with thematic synthesis to generate an integrated understanding of the burden, drivers, consequences of mental health challenges and interventions in place among healthcare professionals in Africa. Quantitative findings were summarized descriptively, with prevalence estimates compiled and compared across countries, professional cadres, and study designs. Tables were used to summarize the findings. A narrative synthesis was employed, which involved identifying recurring patterns, contextual drivers, and consequences of mental health challenges across settings as well as the interventions put in place. Qualitative findings were integrated thematically to enrich interpretation of quantitative prevalence data, particularly in relation to structural determinants such as workload, workplace violence, stigma, and pandemic-related stressors. Cross-cutting themes were highlighted to capture differences by cadre, gender, and country, as well as the co-occurrence of multiple mental health outcomes. Where available, studies reporting objective biomarkers of stress were synthesized alongside self-reported measures to provide a more comprehensive picture. For study characteristics, a map of Africa was designed using Rstudio Version 2025.05.1 + 513 to show the distribution of studies across the continent Results Study selection and characteristics A total of 6567 records were identified through database searches of which 119 studies met the inclusion criteria for this scoping review (PRISMA flow diagram, Fig. 1). The characteristics for the individual studies are shown in supplementary file 1. Selected studies were conducted in 20 countries and South Africa had the highest number of studies (n = 19). Two studies were multi-country; one was in Sudan and Tanzania while the other was in Uganda, Kenya and Tanzania. Figure 2 shows the distribution of these studies. The included studies were conducted in and published between 2003 and 2025. Study designs were heterogeneous, though the vast majority were cross-sectional studies (n = 105). Other study designs included mixed-methods studies, qualitative studies, quasi-experimental or pre-experimental studies, and longitudinal studies. Study populations varied and involved doctors/ physicians (n = 21), nurses (n = 27), midwives (n = 4), while most studies (n = 67) involved health care professions generally spanning across both clinical and non-clinical fields. Mental Health Challenges Identified 1. Burnout Prevalence and severity of burnout rates varied significantly by country, cadre, and setting. Some studies reported overall burnout prevalence while others reported scores in dimensions of burn out (i.e. emotional exhaustion, depersonalization, and personal accomplishment). Burnout was high among early-career professionals; for instance, a study of medical interns in a South African tertiary hospital reported a 95% prevalence of burnout. 15 Similarly, among resident physicians in Sudan found that 86.1% met the criteria for burnout in at least one dimension, with nearly 14% experiencing it across all three dimensions 16 . In Ethiopia, burnout rates among nurses and midwives ranged from 40% and 56% 9,17–20 , while a study covering Kenya, Tanzania, and Uganda classified nearly one-third of nurses as "burned out" with high levels of somatic complaints 21 . Conversely, some studies in Ghana reported low overall burnout rates among physicians. In one study the score was 2.2 on a 5-point scale 22 , while the other study that reported on dimensions of burnout found 5.5% depersonalization, 7.8% lack of personal achievement and 10.8% emotional exhaustion. Another study on nurses and midwives, found scores on burnout dimensions higher: 58% in emotional exhaustion, 55.5% poor personal accomplishment and 38.3% depersonalization) 23 . Excessive workloads and long working hours contributed to burnout; in Egypt, resident doctors working over 90 hours weekly during the COVID-19 pandemic showed significantly higher emotional exhaustion and depersonalization 24 . In Malawi, clinical officers attributed their occupational stress to "excessive workloads" aggravated by the COVID-19 pandemic 7 . The physical work environment also played a major role. Violence and safety concerns were also prominent; in Libya, burnout was exacerbated by the civil war context and fear of COVID-19, with over 57% of healthcare workers experiencing verbal abuse 25 . Similarly, midwives in Ethiopia identified workplace violence and exposure to blood/body fluids as significant predictors of burnout 9,10 . Nurses often bore a disproportionate burden. A comparative study in Nigeria found that nurses consistently scored higher on exhaustion and depersonalization than doctors and other health workers 26,27 . In the mental health sector, findings were mixed; while one South African study found low burnout among psychiatric nurses 28 , others in Tunisia and Nigeria reported high emotional exhaustion linked to poor funding and role conflict 29,30 . Among specialists, neurosurgery residents in Morocco reported a 77.3% burnout rate despite a favorable learning climate, largely driven by poor work-life balance 31 . In Tunisia, emergency medicine residents exhibited the highest rates of severe depression and exhaustion 32 , and 63% of oncology staff reported high emotional exhaustion 33 High burnout was strongly associated with depression 17,34 , anxiety, and poor quality of life 30,35 . In extreme cases, burnout was linked to suicidal thoughts and addictive behaviors among oncology staff in Tunisia 33 . It also compromised patient safety and quality of care. In Nigeria, burnout combined with the fear of contagion was associated with aggressive tendencies toward patients with HIV/AIDS 36 . In Ghana, team burnout was found to negatively impact psychological safety and civility within hospital units 37 , while another study identified burnout as a mediator for turnover intentions 38,39 . Table 1 shows the prevalence of burn out reported in the included studies. Table 1 Prevalence of burnout among health professionals reported in the included studies Authors and Year Profession and Country Prevalence of Burn out Y.A. M. Elhadi et. al (2022) 16 Resident Physicians (Sudan) 86.1% fulfilled criteria for burnout; 70.7% indicated high levels of emotional exhaustion. M. Elhadi (2020) 25 Hospital healthcare workers (Libya) 67.1% reported emotional exhaustion; 47.4% reported depersonalization. Fadle (2023) 24 Doctors (Egypt) 51.0% were high in emotional exhaustion; 83.0% were high in depersonalization. Ilham et al. (2022) 40 Nurses, Midwives, and Health Technicians (Morocco) Burnout affected > 75% (more than three quarters); 59.3% high emotional exhaustion. Efa et al. (2024) 17 Nurses (Ethiopia) Prevalence was 49.2%. Feleke et al. (2022) 18 Nurses (Ethiopia) 56.5% reported suffering from a high level of burnout. Ben Zid et al.(2018) 32 Medical residents (Tunisia) 17.14% had severe burnout. Mengistie et al. (2024) 9 Midwives (Ethiopia) Overall prevalence was 55.3% (Personal: 58.3%; Work-related: 60.3%). Morar & Marais (2022) 41 Psychiatric trainees (South Africa) Evidence of some degree of burnout in more than two-thirds (> 66%) of participants. Alfadul et al. (2023) 42 Doctors and Nurses (Sudan) 45.7% met criteria for high risk of burnout. Konlan et al. (2022) 39 Health workers (Ghana) Prevalence was 20.57%. Gelaw et al. (2023) 43 Health professionals (Ethiopia) 26.0% showed Burnout syndrome; 52.8% presented high emotional exhaustion. Kahsay et al. (2025) 19 Nurses (Ethiopia) Proportion of burnout was 41.10%. Bizuneh et al. (2025) 20 Nurses, Midwives, Physicians (Ethiopia) Overall prevalence was 54.7%. Guider et al. (2024) 44 Healthcare professionals (Morocco) 43.7% emotional exhaustion; 44.9% depersonalization; 58.2% diminished professional accomplishment. Halayem-Dhouib et al. (2010) 29 Nursing staff, residents (Tunisia) High levels of burnout were detected among nurses. Mashego et al. (2016) 45 Nurses (South Africa) 92% indicated moderate levels of burnout. Oudrhiri et al. (2015) 31 Neurosurgery residents (Morocco) 77.3% were in a burnout state. Daldoul et al. (2021) 33 Doctors and Nurses (Tunisia) Found in 21% of participants; 63% high emotional exhaustion. van der Doef et al. (2012) 21 Nurses (Kenya, Tanzania, Uganda) 32.1% labelled as burned out; 33.9% 'very highly' emotionally exhausted. Gadzama et al. (2023) 27 Healthcare professionals (Nigeria) 85% prevalence of burnout Tununu & Martin (2020) 28 Nurses (South Africa) High emotional exhaustion in 15.2%, high depersonalization in 4.5%, and 11.6% had low personal accomplishment (All of them did not meet the criteria for burnout). Ogboghodo & Edema (2020) 46 Resident doctors (Nigeria) Overall prevalence was 41.7%; 59.6% suffered emotional exhaustion. Opoku et al. (2023) 23 Nurses and Midwives (Ghana) Majority experienced low burnout (58% low emotional exhaustion). Malebo Kgatle (2024) 15 Medical interns (South Africa) 95% of the participants reported burnout. Udho & Kabunga (2022) 35 Nurses (Uganda) 49.1% had high levels of burnout; 36.2% reported average levels. Opoku & Apenteng (2014) 22 Physicians (Ghana) Overall, burnout was low; however, physicians exhibited Moderate levels of emotional exhaustion. Engelbrecht et al. (2008) 47 [45] Nurses (South Africa) High levels of burnout were identified. Alabi et al. (2021) 30 Mental Health Nurses (Nigeria) Prevalence of emotional exhaustion was 44.4%; depersonalization 31.7%. Payne et al. (2020) 48 Nursing staff (South Africa) Found relatively high personal (mean 49.2) and work-related burnout. Mamorobela et al. (2023) 49 Doctors (South Africa) 36% prevalence (lower-middle range). Abdo et al. (2016) 50 Physicians and nursing staff (Egypt) 24.9% had high burnout; 66.0% had moderate burnout. Afulani et al. (2021) 51 Maternity providers (Kenya) 19.6% high burnout; 65% low burnout. Biksegn et al. (2016) 52 [59] Healthcare workers (Ethiopia) Mean score of burnouts was 50.27 with standard deviation of ± 17.1528, 36.7% showed that burnout above the mean Hamid & Abdullah (2020) 53 Health Professionals (Tanzania and Sudan) Emotional exhaustion was higher in Sudan (44.4%) than Tanzania (33.3%), while high depersonalization was higher in Tanzania (40.3%) compared to Sudan (19.4%). For personal accomplishment (PA), Tanzanian participants showed a greater proportion with low PA scores (63.9%), whereas only 22.2% of Sudanese participants fell in this high-burnout PA range. Ayisi-Boateng et al. (2020) 54 Physicians (Ghana) 5.5% experienced depersonalization, 7.8% lack of personal achievement and 10.8% had emotional exhaustion. 2. Anxiety Anxiety was a pervasive mental health challenge, though the available evidence was heavily skewed toward the COVID-19 pandemic period with most studies conducted between 2020 and 2025. In this pandemic context, prevalence rates were exceptionally high; for instance, a study in Egypt reported that 90.5% of healthcare workers experienced some degree of anxiety, with 18.5% classified as severe 55 . Similarly in Kenya, 59.9% of staff in a teaching hospital screened positive for generalized anxiety disorder 56 and in Morocco, where 58.3% of workers reported anxiety symptoms 57 . However, rates varied significantly by setting; notably lower rates were observed in specific sub-groups, such as surgeons in Libya (15.2%) 58 and psychiatric nurses in Ghana (27%) 59 . Anxiety was directly driven by the unique stressors of the COVID-19 pandemic, specifically the fear of infection and systemic resource failures. In Ethiopia, the lack of personal protective equipment (PPE) was cited as a primary source of fear for 78.8% of staff, while 63.8% reported anxiety specifically regarding the risk of transmitting the virus to their families 60 . This "health anxiety" was further corroborated in Egypt, where it was found in 28% of workers and was inversely correlated with their quality of life 61 . In Botswana, anxiety was significantly predicted by the experience of stigma and the trauma of losing relatives to the disease 62 . Furthermore, frontline status was a critical determinant; healthcare workers stationed in isolation centers and treatment units in South Sudan and Ethiopia reported higher anxiety levels compared to their non-frontline counterparts 63,64 . In Nigeria, healthcare workers were anxious about getting and also infecting their relatives with COVID-19. 56 Evidence from the pre- COVID-19 pandemic era had reported anxiety. Two studies conducted in Uganda in 2014 identified a severe burden of "death anxiety" among midwives working in rural areas 65,66 . An overwhelming 94% of these midwives reported witnessing maternal deaths, and 93% exhibited moderate to high levels of death anxiety as a direct result 65 . Female healthcare professionals reported higher levels of anxiety than their male counterparts. This trend was statistically significant in studies from Ethiopia 60,67 , South Sudan 63 , and Morocco. Nurses and midwives appeared to be the most vulnerable group. In Ethiopia, nursing was independently associated with higher anxiety scores compared to other professions 60 . Other significant risk factors identified included working night shifts, working in emergency departments, and having conflicts with coworkers 67 . Anxiety also co-occurred with depression, burnout, and stress. In Cameroon, anxiety symptoms were strongly associated with depressive symptoms and the fear of death 68 . In Sudan, higher scores for depression and stress were significantly correlated with higher degrees of burnout 69 . The impact of coping strategies on anxiety outcomes was also significant. In South Africa, the use of avoidant coping mechanisms such as self-blame, denial, and substance use was found to be maladaptive, significantly increasing the risk of anxiety among mental health practitioners 70 . Table 2 shows prevalence of anxiety among health professionals in Africa. Table 2 Prevalence of Anxiety Among Healthcare Professionals in Africa Authors and Year Profession and Country Prevalence of Anxiety Misganaw et al. (2024) 67 Professional Nurses (Ethiopia) 33.9% overall prevalence. Mboua et al. (2021 71 Nurses and Physicians (Cameroon) 41.8% prevalence rate. Nguepy Keubo et al. (2021) 68 Health care professionals (Cameroon) 42.20% prevalence of anxiety symptoms. Wayessa et al (2023) 72 Healthcare Workers (Ethiopia) 25.5% prevalence of anxiety. M. Elhadi & Mshergh (2021) 58 Surgeons (Libya) 15.2% reached the cutoff score for anxiety symptoms. Aly et al. 2021) 55 Physicians, nurses (Egypt) 90.5% had different degrees of anxiety (40% mild, 32% moderate, 18.5% severe). Muliira & Bezuidenhout (2015) 65 Midwives (Uganda) 93% exhibited moderate to high levels of death anxiety (among those experiencing a maternal death). Muliira et al. (2015) 66 Midwives (Uganda) 74.6% reported experiencing moderate to high levels of death anxiety. Sayed et al. (2023) 73 House officers (Egypt) 32% of participants reported anxiety. Idrees & Bashir, 2023 63 Healthcare workers (South Sudan) 47% had borderline anxiety scores. Mulatu et al. (2021) 64 Doctors, nurses, etc. (Ethiopia) 11.7% and 5.7% had moderate and symptoms of anxiety respectively. Siamisang et al. (2022) 62 Healthcare professionals (Botswana) Detected in 28.2% of participants. Stals et al. (2024) 70 Mental healthcare practitioners (South Africa) 40.6% had high levels of anxiety. Opoku Agyemang et al. (2022) 59 Psychiatric Nurses (Ghana) 27% experienced mild to severe anxiety. Bouaddi et al. (2023) 57 Physicians and nurses (Morocco) 58.3% experienced mild to extremely severe anxiety. Bundi et al. (2024) 56 Health care providers (Kenya) 59.9% overall prevalence of generalized anxiety disorder symptoms. Abdelghani et al. (2021) 61 Healthcare workers (Egypt) 28% frequency of health anxiety to COVID-19. Chorwe-Sungani G. (2021) 74 Nurses (Malawi) COVID-19 related anxiety was 25.5% and nearly half of the respondents suffered from functional impairment. Kwobah et al. (2021) 75 Health care workers (Kenya) 36% of the participants scored positively for generalized anxiety during COVID-19 pandemic Ofori et al (2021) 76 Health care workers (Ghana) 27.8% had anxiety 3. Depression Prevalence rates surged during the COVID-19 pandemic. In Egypt, one study found that 94% of participants exhibited mild to severe depression 55 , while another reported that 63% of physicians suffered from severe or extremely severe depression 77 . In Morocco, 53.1% of healthcare workers reported symptoms ranging from mild to extremely severe 57 , and in Ghana, 52.1% of nurses screened positive for depression 78 [11]. Lower prevalence was observed in Botswana 62 (21%) and among psychiatric nurses in Ghana (19.6%) 59 . While the pandemic exacerbated these issues, evidence from the pre-pandemic era demonstrates that depression is an occupational problem for African healthcare workers. A 2015 study in Nigeria found that 14.9% of healthcare workers in tertiary hospitals met the criteria for depression, with symptoms significantly linked to sadness over poor working conditions 79 . Similarly, a 2018 study of medical residents in Tunisia revealed a 30.5% prevalence of depression, associating the disorder with the heavy burden of weekly working hours and night shifts 80 . The drivers of depression identified varied. In Ghana, a direct positive correlation was found between workplace bullying and depression, which in turn significantly increased nurses' intention to quit their jobs 78 . In Botswana, depression was strongly associated with the experience of stigma and smoking 62 . Furthermore, the COVID-19 pandemic introduced specific stressors; in Egypt, having a poor attitude toward personal protective equipment (PPE) and overall worry about the pandemic were significant predictors of depression 73 . Frontline status also played a critical role, with healthcare workers in COVID-19 treatment units in Ethiopia facing notably higher odds of depression compared to non-frontline staff 64 . Females were more susceptible. Female gender was significantly associated with higher depression scores in studies conducted in Morocco 81 , South Sudan 63 , Ethiopia 60 , Egypt 77 , Nigeria 79 , and Tunisia 80 . Age was another demographic factor with associations; while older age was associated with higher depression in Morocco 81 and Tunisia 80 , younger age was a risk factor for related comorbidities like eating disorders 81 . Depression also presented as part of a broader cluster of psychological and behavioral challenges. A study in Morocco found a significant rise in eating disorders during the pandemic, which were strongly associated with a diagnosis of depression, emotional eating, and obesity 81 . In South Africa, maladaptive coping mechanisms such as self-blame, behavioral disengagement, and substance use were found to significantly predict higher levels of depression among mental healthcare practitioners 70 . Furthermore, depression was linked to professional attrition; in Sudan, roughly one-third of mental health professionals felt disheartened and considered quitting, with depression scores negatively associated with age and experience 69 . Table 3 shows prevalence of depression among health care professionals in Africa in reported studies. Table 3 Prevalence of depression among health care professionals in Africa. Author & Year Profession & Country Prevalence of Depression Lahlou et al. (2022) 81 Medical doctors, nurses, students (Morocco) 29.3% had moderate to severe depression. Sayed et al. (2023) 73 House officers (Egypt) 22% of participants reported depression. Idrees & Bashir (2023) 63 Healthcare workers (South Sudan) 44% had borderline depression scores. Mulatu et al. (2021) 64 Doctors, nurses, and pharmacists (Ethiopia) 13.6% and 6.7% experienced moderate and severe symptoms of depression respectively. Siamisang et al. (2022) 62 Healthcare professionals (Botswana) Detected in 21.0% of participants. Stals et al. (2024) 70 Mental healthcare practitioners (South Africa) 28.3% had high levels of depression. Opoku Agyemang et al. (2022) 59 Psychiatric Nurses (Ghana) 19.6% experienced mild to severe depression. Bouaddi et al. (2023) 57 Physicians and nurses (Morocco) 53.1% reported symptoms of mild to extremely severe depression. Dapilah & Druye (2024) 78 Nurses (Ghana) 52.1% were depressed at various degrees. Khalaf et al. (2020) 77 Physicians (Egypt) The majority (63%) suffered from severe or extremely severe depression. Obi et al. (2015) 79 Healthcare workers (Nigeria) 14.9% met the study’s cut-off for depression. Aly et al. (2021) 55 Physicians, nurses, etc. (Egypt) 94% showed mild to severe depression. Marzouk et al. (2018) 80 Medical residents (Tunisia) 30.5% met the definite criteria for depression. Kwobah et al. (2021) 75 Health care workers (Kenya) 32.1% of the participants scored positively for depression. Ofori et al (2021) 76 Health care workers (Ghana) 21.1%, had depression, 4. Work-related Stress Stress was characterized by both acute pandemic-induced spikes and long term system stress. In the context of COVID-19, a study in Egypt reported that 98.5% of healthcare workers experienced moderate to severe stress 55 , while in Morocco, 67% reported high perceived stress 82 . Even in studies extending beyond the immediate pandemic peak or focusing on general occupational health, the burden remained high. In a 2025 study of nurses in Morocco, 87% reported moderate stress levels 83 , and in a rural county in Kenya, 85% of maternity providers reported moderate stress 51 . Similarly, a pre-pandemic study in Ethiopia found that 66.2% of nurses experienced work-related stress 84 . Structural drivers were consistent across time and geography. In South Africa, inadequate salary, covering for absent coworkers, and lack of control over work as primary stressors for doctors 85,86 . In Ethiopia, the shortage of nurses and the intensity of working in Intensive Care Units (ICUs) were identified as contributors 84 . The COVID-19 pandemic layered new stressors onto this fragile system; in Ghana, inadequate preparedness for the response was directly associated with higher stress and burnout, mediated partly by the fear of infection 87 . Qualitative evidence from Nigeria further emphasized that policy changes, extended use of PPE, and the lack of a secure working environment were major sources of distress 88,89 . Some studies linked work environments to stress. In Angola, "workaholism" was identified as a significant predictor of job stress, which in turn negatively impacted job satisfaction and psychological capital 90 . Demographic factors also played a role; female gender was associated with higher stress in Nigeria 91 and Morocco 83 , while in Egypt, younger married nurses were found to be more susceptible to Effort-Reward Imbalance 92 . Conversely, in Nigeria, emotional intelligence was identified as a protective factor, with independent relationships found between emotion appraisal and reduced work stress 93 . Notably, some included studies went beyond self-reported questionnaires to identify physiological biomarkers of stress, providing objective evidence of the physical toll on healthcare workers. In Egypt, a study found that healthcare workers had significantly elevated levels of Interleukin-6 (IL-6), a pro-inflammatory cytokine, which correlated with higher stress scores and night shift work 94 . Another Egyptian study found a significant correlation between psychosocial stress (Effort-Reward Imbalance) and oxidative stress, measured by Malondialdehyde (MDA) levels 92 . In Kenya, while cortisol levels did not show a statistically significant association in a small sample, researchers measured Heart Rate Variability (HRV) and found that "over-commitment" or motivation to work excessively was associated with increased stress 51 . Table 4 shows prevalence of stress among health care professionals in Africa reported in the selected studies. Table 4 Prevalence of work-related stress among health care professionals in Africa. Authors and Year Profession and Country Prevalence of Stress Oneib & Hasnaoui (2021) 82 Physicians and Nurses (Morocco) 67% reported high perceived stress. Zamurayeva et al. (2024) 88 Doctors, nurses, and lab technicians (Nigeria) Found high levels of occupational stress. Aly et al. (2021) 55 Physicians, nurses, technicians, etc. (Egypt) 98.5% showed moderate to severe stress (1.3% low stress). Afulani et al. (2021) 87 Nurses, midwives, and allied health workers (Ghana) 64.3% reported moderate stress; 4.3% reported high stress. Afulani et al. (2021) 51 Maternity providers (Kenya) 85% reported moderate stress; 11.5% reported high stress. Salem & Ebrahem et al. (2018) 92 Nursing staff (Egypt) 72.5% prevalence of Effort-Reward Imbalance (a proxy for stress). Thomas & Valli (2006) 86 Doctors (South Africa) Experienced higher levels of occupational stress compared to the general working population. Rahoui Chairi et al. (2025) 83 Nurses (Morocco) 87% experienced moderate levels of perceived stress. Baye et al. (2020) 84 Nurses (Ethiopia) Prevalence of work-related stress was 66.2%. Lawal & Idemudia (2017) 93 Nurses (Nigeria) Reported a moderate level of work stress. Ofori et al (2021) 76 Health care workers (Ghana) 8.2% had stress Psychological distress Psychological distress reached critical levels during the COVID-19 pandemic while maintained by structural occupational stressors in the pre-pandemic era. During the acute phases of the global health crisis, prevalence rates were alarmingly high; a study conducted in the early stages of the outbreak in Ethiopia reported that 78.3% of healthcare professionals suffered from psychological distress, driven largely by insomnia, lack of information, and social stigma 95 Similarly, in Egypt, 53.3% of primary healthcare workers exhibited high distress levels 96 , and approximately 50% of physicians reported severe distress, primarily fueled by the fear of transmitting the virus to their families 97 . In South Africa, 50.3% of nurses and 40.6% of medical practitioners were classified as psychologically distressed, with the lack of adequate leave and insurance coverage for COVID-19 cited as key systemic contributors 98 . Stigma in relationships with family, friends and neighbors during the pandemic also contributed to psychological distress. 99,100 However, evidence from pre-pandemic studies demonstrated that psychological distress is not merely a reaction to disease outbreak but a symptom of high-pressure work environments. In a 2014 study of residents in a Nigerian teaching hospital, 48.4% of respondents evinced psychological distress, which was significantly associated with the intensity of their workload 101 . Similarly, a 2019 study in Ethiopia found a 44.4% prevalence of distress, explicitly linking it to high job demands and low job control. Specific medical specializations appeared to carry unique burdens; for instance, a study of psychiatric nurses in Tunisia revealed that 74.5% had experienced aggression from patients and 45.5% had witnessed suicide attempts, leading 60% of them to wish for a transfer 102 . In Ethiopia, anesthesia professionals were identified as a high-risk group 103 , while in Egypt, nurses working in ICUs and internal medicine departments reported significantly higher rates of psychological ill health compared to other units 104 . Female gender and younger age as risk factors for distress. Female healthcare workers were found to have significantly higher odds of distress in studies from South Africa 98 , Ethiopia, and Egypt 97 . Regarding age, younger professionals (typically under 40) were more vulnerable in South Africa, Ethiopia 95 , and Egypt 104 , likely due to lower professional experience and resilience, although one Ethiopian study found the highest risk in the 35–44 age bracket 103 . Marital status also played a role, with unmarried personnel showing higher susceptibility to stress and anxiety 103 . Protective factors and coping mechanisms were also identified. In Morocco, a study on nurses emphasized that recognition from superiors was significantly correlated with better psychological health and job satisfaction 105 . In Nigeria, possessing a higher educational degree was found to lower the odds of distress 106 . Conversely, the lack of support systems exacerbated the issue; in Egypt, negative support from family and friends was a significant predictor of psychological ill health 104 , while religious coping was identified as the most effective strategy for physicians navigating the crisis 97 . Table 5 shows prevalence of psychological distress among health care professionals in Africa. Table 5 Prevalence of psychological distress among health care professionals in Africa Author and Year Profession and Country Prevalence of Psychological Distress Demilew et al. (2022) 103 Physicians, nurses, midwives, etc. (Ethiopia) 49.5% of the participants have psychological distress. Khiari et al. (2024) 102 Psychiatric Nurses (Tunisia) 61.8% anxiety, 36.4% stress, 34.5% depression (moderate to very severe levels). Abdu et al. (2023) 96 Primary health care workers (Egypt) 53.3% had high psychological distress. Ibigbami et al. (2022) 106 Health workers (Nigeria) 49.1% moderate and 5.8% severe psychological distress. Ramlagan et al. (2024) 98 Healthcare workers (South Africa) 50.3% (nurses), 40.6% (medical practitioners), and 47.4% (others) were classified as psychologically distressed. Yitayih et al. (2020) 95 Health care professionals (Ethiopia) Prevalence was 78.3%. Esan et al. (2006) 101 Residents (Nigeria) Evidence of distress in 48.4% of respondents. Kabito & Mekonnen (2020) 107 Healthcare professionals (Ethiopia) Symptoms in the past 4 weeks stood at 44.4%. Sehsah et al. (2021) 97 Physicians (Egypt) Approximately 50% exhibited severe psychological distress. Arafa et al. (2003) 104 Nurses (Egypt) 21.67% recorded moderate to severe psychological symptoms. Chipps et al. (2025) 108 Nurses (South Africa) High levels of psychological distress, during COVID-19 compared to current levels (27.2 vs 18.8; W = 8.9, p = < 0.001) Kambulandu et al. (2024) 109 Clinical Staff (Lesotho) 41.6% had moderate to severe psychological distress Vancampfort & Mugisha (2022) 110 Nurses (Uganda) 92.6% of participants had psychological distress (Kessler-6 score ≥ 13) Post-Traumatic Stress Disorder (PTSD) Among Healthcare Professionals PTSD was also reported by some studies during the COVID-19 pandemic. A nationwide study in Uganda found 44.4% of the nurses had elevated PTSD symptoms 110 . In Southern Ethiopia, a study assessing healthcare professionals found that over half (56.8%) screened positive for PTSD symptoms. The severity of these symptoms was, 36.7% of the workforce exhibiting severe levels of PTSD, while 7.8% and 12.9% showed moderate and mild symptoms, respectively 111 . The drivers of this trauma were identified as a combination of pandemic fears and systemic failures. In Central Uganda, predictive factors for PTSD among frontline nurses included a lack of social support, the intense fear of contracting COVID-19, and drastically increased workloads 112 . Also, the study noted that these pandemic stressors were exacerbated by a healthcare system that was "already under severe strain" prior to the outbreak, suggesting that the pandemic acted as a breaking point for a workforce already operating at capacity 112 . In Lesotho, 31.7% of clinical staff during the COVID-19 pandemic had severe PTSD. 109 Gender disparity was noted in the development of PTSD symptoms. A 2025 study in Morocco's Oriental region found that female healthcare workers, who constituted 68.3% of the sample, exhibited strong correlations between PTSD, anxiety, and perceived stress 113 [1]. The analysis revealed a pathway where gender exerted an indirect effect on PTSD; this relationship was mediated by anxiety and moderated by perceived stress, especially in high-pressure contexts 113 . Substance Use among healthcare professionals A few studies in Morocco, Kenya, and Nigeria reported on psychoactive substance (SPA) use. A large-scale Kenyan study reported that over half the sample, 51.7% of healthcare providers, had used substances at some point, 114 with another Nigerian study finding a lifetime prevalence of 66.0% 115 . Alcohol was the most substance of choice, cited by 93.7% of users in the Kenyan data followed by cannabis (28.9%), then tobacco (27.6%) 114 , whereas for the Nigerian study, Alcohol was most used (60.4%), followed by sedatives (12.7%), then tobacco (10.2%). Findings from a separate earlier Kenyan study indicated the following lifetime prevalence rates for substance use: alcohol (35.8%), tobacco (23.5%), cannabis and sedatives (9.3% each), cocaine (8.8%), amphetamine-like stimulants (6.4%), hallucinogens (5.4%), opioids (3.9%), and inhalants (3.4%). 116 Among resident physicians in Morocco, life time use of an SPA was 16.1%. 117 Substance use is rarely an isolated issue; the data overwhelmingly suggests it is a form of self-medication linked to severe distress. Occupational stress and stressful workload were explicitly identified as major factors influencing substance use in studies from both Kenya and Nigeria. 114,115 . Resident doctors in Morocco who used SPA were nearly twice as likely to have a history of psychiatric disorders (27% versus 14.7%) 117 . This same study also established a critical correlation between SPA use and severe outcomes, specifically noting that use was strongly associated with suicide attempts 117 . Vulnerability to substance use varies by professional rank and gender. Male gender was a highly significant predictor of SPA use in both the Moroccan 117 and Nigerian studies 115 . Work pressure was cited as a major influence on substance abuse. 118 Table 6 shows prevalence of substance use among health care professionals in Africa. Table 6 Prevalence of Substance use among health professionals in Africa Author and Year Profession and Country Prevalence of Substance Use and Key Findings Charlotte Mc Magh et al. (2023) 119 Doctors, Nurses, Clinical Associates, Dentists (South Africa) 20.9% of professionals reported risky alcohol use (AUDIT-C). Risky drinking was significantly higher in males ( 42.0% ) compared to females ( 15.4% ). Alcohol use was identified as a cause for concern, particularly in the male population. Aggrey G. Mokaya et al. (2016) 116 Nurses, Clinical Officers, Doctors, Support Staff (Kenya) Lifetime substance use was 35.8% for alcohol and 23.5% for tobacco. Use in the past 3 months was 19.6% for alcohol and 13.2% for tobacco. Other lifetime use included cannabis ( 9.3% ), sedatives ( 9.3% ), and cocaine ( 8.8% ). Tobacco was the only substance where a high-risk score ( 0.5% ) was recorded. Isinyemeze E. & Agbapuonwu N. E. (2024 ) 120 Healthcare professionals (Doctors, Nurses, Pharmacists, etc.) (Nigeria) 78.1% of respondents believed alcohol was the most commonly abused substance, followed by tobacco ( 67.5% ). High rates of usage were perceived for alcohol ( 80.2% rated as 'High') and tobacco ( 70.8% rated as 'High'). Reasons for abuse included easy access ( 62.5% ), excessive workload ( 56.9% ), and stress ( 51.7% ). Chidindu Prince Anagwu et al. (2024) 115 Doctors, Nurses, Lab Scientists (Nigeria) 66% of workers had used a substance at least once in their lifetime. Lifetime prevalence: Alcohol ( 60.4% ), Sedatives ( 12.7% ), Tobacco ( 10.2% ). Past 3 months use: Alcohol ( 50.8% ), Sedatives ( 5% ), Tobacco ( 4.1% ). 37.1% of participants were classified as moderate-risk alcohol users. Jasmit Shah et al. (2025) 114 Doctors, Nurses, Allied Health (Kenya) 51.7% of healthcare providers reported ever using a substance. Among those who used substances, 93.7% used alcohol, 28.9% used cannabis, and 27.6% used tobacco. Substance use was higher in doctors ( 37.5% alcohol, 58.4% cannabis) compared to nurses ( 29.7% alcohol, 12.1% cannabis). Echater et al. 2024 117 Resident Doctors (Morocco) Psychoactive substance use was reported by 16.1% of the group. Specific usage rates included tobacco (11.1%), alcohol (10%), and cannabis (6.1%), with reports of ecstasy and cocaine use (0.7%) Interventions for mental health challenges among healthcare professionals in Africa, effectiveness, and challenges in implementation Ten studies reported on interventions to address mental health challenges of health professionals. 1. Osman et al. (2021), South Africa. The study implemented a brief online mindfulness-based intervention (MBI) adapted for healthcare professionals (n = 47) during the COVID-19 pandemic. The program comprised four 1-hour group sessions delivered via Zoom, featuring exercises like the "raisin exercise," body scanning, yoga, and walking meditation. The intervention yielded statistically significant improvements. Post-intervention analysis showed a significant reduction in perceived stress levels (p < 0.05) and emotional exhaustion. Additionally, there was a significant increase in scores for mindful awareness and personal accomplishment. Qualitative analysis indicated a thematic shift from feelings of "powerlessness" to "acquired control." Implementation was hampered by a high dropout rate of 28%, with only 47 out of 65 registered participants completing the assessments. The primary barriers were erratic work schedules and pandemic-related exhaustion, which made attendance difficult despite the provision of make-up sessions. 121 2. Kelly et al. (2021), South Africa This was a self-directed e-learning intervention was deployed for 750 healthcare workers, consisting of five asynchronous online modules focused on stress management, mindfulness, and self-care planning. Among the 474 participants who completed the post-test, there were statistically significant increases in resilience, measured by the Connor-Davidson Resilience Scale (CD-RISC), and psychological well-being, measured by the WHO-5 Well-Being Index. Participants also reported significantly higher knowledge and confidence regarding mental health maintenance. The study faced substantial attrition, with only 63.2% (474/750) of the initial cohort completing the training. The reliance on convenience sampling was noted as a limitation that may have biased the results toward those already motivated to seek help. 122 3. Zingela et al. (2022), South Africa The researchers developed and piloted a Psychological Preparedness Training (PPT) program for 761 healthcare workers. The intervention involved group sessions (60–90 minutes) utilizing cognitive-behavioral principles to achieve goals of safety, calm, efficacy, and connectedness. The study reported statistically significant positive changes. Post-training data indicated a marked reduction in anxiety and an improvement in workers' perceptions of the outbreak. Participants reported a significantly increased ability to control their emotional reactions and support colleagues, shifting their mindset from helplessness to agency. The primary challenge was "worker weariness" and severe time constraints. The demanding clinical environment meant that despite the program's benefits, staff struggled to find the time and energy to attend sessions. 123 4. Waterman et al. (2018), Sierra Leone This study at 157 Ebola Treatment Centre workers, utilized a peer-delivered cognitive behavioral therapy (CBT) model. It progressed through three phases: screening/psychological first aid, psycho-educational workshops, and small group CBT sessions led by trained peers. The intervention was highly effective, with results showing significant reductions in clinical symptoms across the board. There were statistically significant decreases in scores for anxiety (GAD-7) and depression (PHQ-9) following the intervention phase. Implementation was complicated by Sierra Leone's limited mental health infrastructure. The study noted significant cultural barriers, including profound stigma around mental illness and a widespread reliance on traditional healers, which often conflicted with the clinical CBT approach. 124 5. Kacem et al. (2020), Tunisia This study introduced a music therapy intervention for 34 operating room staff in urology and maxillofacial departments. Participants were exposed to three 30-minute music sessions daily over a one-month period. The intervention resulted in a statistically significant decrease in occupational stress and burnout. Specifically, Perceived Stress Scale (PSS-10) scores dropped significantly (p = 0.006), and the emotional exhaustion subscale of the Maslach Burnout Inventory also showed a significant decrease (p = 0.004). The major limitation was the small sample size (n = 34) and the lack of a control group. The specificity of the operating room setting also raised questions about the feasibility of replicating this intervention in noisier or more chaotic hospital wards. 125 6. Maingi et al. (2022), Kenya In a study of 356 healthcare workers, the "intervention" was identified as the adoption of individual mitigation strategies in the absence of a formal institutional program. The study assessed adherence to Ministry of Health guidelines for mental well-being. The study found that 80.1% of workers utilized a healthy diet and 43.3% engaged in physical activity to mitigate mental health effects. Despite these individual efforts, the prevalence of mental health problems remained high at 44%, with 14.6% of workers reporting depression. The critical barrier was the lack of structural support. The study concluded that Ministry of Health measures were inadequate, effectively abandoning HCWs to manage their own mental health (self-care) without sufficient policy-level or organizational backing. 126 7. Abdelaziz et al. (2020), Egypt This quasi-experimental study involved 36 novice psychiatric nurses. They underwent a 7-week Assertiveness Training Program comprising two sessions per week (90–120 minutes each), utilizing lectures, role-play, and homework. The training was effective, yielding statistically significant improvements between pre- and post-test scores. Participants showed significant gains in assertiveness skills, psychological well-being, and work engagement. The study was limited by its small sample size (n = 36) and the absence of a control group, which limits the ability to generalize the findings or rule out external factors influencing the improvement. 127 8. Ledikwe et al. (2017), Botswana The study evaluated the National Workplace Wellness Program (WWP) across 27 health districts. The program was comprehensive on paper, including health screening, psychosocial care, and therapeutic recreation. Implementation fidelity varied significantly. While physical health screenings were frequently implemented, psychosocial support services were utilized much less. The study did not provide statistical outcomes on mental health improvement but rather focused on implementation success. Implementation was hindered by competing priorities, where patient care demands crowded out wellness activities. Additionally, there was a lack of technical expertise among staff to deliver occupational health services, and confidentiality concerns significantly reduced staff willingness to access the available support. 128 9. Moyo et al. (2023), Zimbabwe This qualitative study (n = 20) developed a psychosocial support model based on Donabedian’s framework (Structure, Process, Outcome). The model aimed to provide a structured reference guide for supporting healthcare workers during pandemics. The model was validated by a panel of experts who confirmed its relevance and necessity. It provided a clear theoretical pathway for institutions to move from ad-hoc support to structured care. The study highlighted that the model was born out of necessity due to severe systemic failures: a shortage of human and material resources, ineffective communication, and the complete absence of existing institutional support structures for staff well-being. 129 10. Abdelghaffar et al. (2021), Tunisia This case study described the rapid implementation of a Psychological Support Unit (PSU) at a hospital, which included a free telephone helpline and specific management activities for both patients and staff. While specific utilization statistics were not reported, the unit was qualitatively described as a critical resource that facilitated the management of staff anxiety and stress during the height of the pandemic. The success of the unit was challenged by logistical barriers, specifically movement restrictions during lockdown that made physical access difficult. Furthermore, a pervasive fear of contamination and the stigma associated with seeking psychological help discouraged some staff from utilizing the service. 130 Discussion and conclusion African healthcare workers (HCWs) bear an alarmingly high burden of mental health problems. Prevalence estimates from recent studies span wide ranges for example, rates of depression (2–76%), anxiety (5–96%), and PTSD (12–78%) have been reported across sub-Saharan samples. 131 Similarly, burnout and related stress are pervasive. A systematic review found that physicians and nurses in Africa often report very high burnout rates (e.g. up to 81% in one South African physician sample 132 , and studies of nursing staff have documented 30–50% or higher proportions with high emotional exhaustion or overall burnout 133 . Substance use is also emerging as a concern: for instance, a survey of Kenyan HCWs found that about half had ever used alcohol, tobacco or other drugs, and a substantial minority screened positive for risky use 114 . In sum, multiple studies document heavy burdens of burnout, depression, anxiety, work-related stress, psychological distress and related conditions among HCWs in Africa 131,133 . Prevalence rates of mental health challenges differ across countries and regions (often higher in South African and West African samples than in East or North Africa in the available literature) and by profession (nurses frequently report equal or higher burnout than physicians. Female HCWs and early-career staff tend to exhibit higher levels of distress in many studies. Similarly national reviews have noted that women and younger health workers generally have greater risk of depressive or anxiety symptoms 131 . This heterogeneity likely reflects contextual factors (health system resources, epidemics) and differing job roles (e.g. front-line nurses vs. support staff). Such variation indicates that interventions may need to be tailored by region and workforce cadre. Only a few intervention studies were identified in this study which were brief and mostly individual level. Similarly, one recent scoping review of African studies found just 11 programs targeting HCW mental health 134 , most focused on individual-level strategies: e-learning or psychoeducation modules, brief mindfulness or relaxation training, resilience-building workshops, cognitive-behavioral group sessions, even music therapy. These interventions often showed short-term promise. However, implementation was challenging: attrition was high (many HCWs dropped out due to shift schedules or fatigue), and deep-seated cultural and structural barriers like stigma around mental illness, understaffing, lack of managerial support thus limited uptake 135 . For our review, in some contexts (e.g. Sierra Leone, Kenya) stigma and sparse resources meant that health workers largely had to rely on self-care, with minimal systemic support, and reported persistent stress and depression despite guidelines. In sum, the evidence on interventions is preliminary and patchy: few randomized trials, mostly small samples, and persistent obstacles to implementation. Research gaps Major gaps were evident. Virtually no studies have used longitudinal or experimental designs to track long-term outcomes; follow-up was typically immediate or within a few weeks. Francophone and Lusophone countries are greatly under-studied, as noted by the predominance of South African and English-language reports. Almost no work has addressed system-level or policy interventions (for example, changes in work environment, regulatory or insurance policies) to reduce HCW stress. Implementation research is badly needed for example, studies of program fidelity, cost-effectiveness, and scalability in low resource settings. Likewise, integration of HCW mental health into national health policies is largely absent. In short, the literature lacks multi-level approaches and rigorous designs; it needs longitudinal follow-up and attention to health-system and policy contexts 131,136 . Policy and practice implications : These findings underscore urgent needs for action. National governments and health ministries should include HCW mental health in their policies and strategic plans. WHO’s guidelines on mental health at work advocate interventions at multiple levels (organizational, managerial and individual) 136 , and countries should adapt these to their context. For example, institutionalize workplace wellness programs such as peer-support groups, stress-management training and accessible counseling within hospitals and clinics. National strategies (as in a mental health action plan) should designate resources for HCW wellbeing and set standards for safe workloads. Moreover, support for vulnerable groups must be prioritized: early-career clinicians, female staff and nurses were repeatedly identified as high-risk groups in African studies. Tailored mentorship, flexible scheduling, and career development support for these groups could help mitigate burnout. In summary, a multi-pronged approach combining policy commitments with on-the-ground programs is needed to protect the continent’s health workforce and sustain quality care. Abbreviations WHO World Health Organization HCW Health Care Workers CBT Cognitive Behavioral Therapy PTSD Post Traumatic Stress Disorder PPE Personal protective Equipment PSU Psychological Support Unit WWP Workplace Wellness Programme Declarations Ethics approval and consent to participate Not applicable. Consent of publication Not applicable. Availability of data and materials The datasets used and/or analyzed during this study are available from the corresponding author. Competing interests The authors declare that they have no competing interests. Funding Not applicable Authors contributions KVN conceptualized the study and developed the review protocol. PMO conducted the database searches and citation tracking. DO and EM independently screened the titles and abstracts, while JLW and MM performed full text review. KVN, JK, MM, JO, MRN, SMN and SS extracted data using the standardized form, and PMO analyzed the findings. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8903391","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":607382774,"identity":"77be8157-f6b1-416a-8a87-1941811bcc70","order_by":0,"name":"Ketra Venesa 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Sciences","correspondingAuthor":false,"prefix":"","firstName":"Pascal","middleName":"Mathew","lastName":"Okorobe","suffix":""},{"id":607382776,"identity":"863c9b14-be52-4c19-9d53-588920f2e95e","order_by":2,"name":"Jamal-Diin Lubega Wamala","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jamal-Diin","middleName":"Lubega","lastName":"Wamala","suffix":""},{"id":607382777,"identity":"2ddced8c-1daa-4d45-b3a8-a0fe0171b607","order_by":3,"name":"Eddy Mpuuga","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Eddy","middleName":"","lastName":"Mpuuga","suffix":""},{"id":607382778,"identity":"0c9231ba-8942-4501-9d72-435663f094b4","order_by":4,"name":"Dan Otim","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Dan","middleName":"","lastName":"Otim","suffix":""},{"id":607382779,"identity":"e8642203-3523-42b2-b37d-eb97a411390c","order_by":5,"name":"Matthias Muruhuura","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Matthias","middleName":"","lastName":"Muruhuura","suffix":""},{"id":607382780,"identity":"058a34a7-98fb-402c-a584-e8d70bb6602c","order_by":6,"name":"Mable Regina Nagawa","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mable","middleName":"Regina","lastName":"Nagawa","suffix":""},{"id":607382781,"identity":"c0bd5f5b-89b0-49a2-915e-b98d85e8066a","order_by":7,"name":"Mustafah Mpiindi","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mustafah","middleName":"","lastName":"Mpiindi","suffix":""},{"id":607382782,"identity":"f0f8ad35-7047-41ee-ba97-62dbeb8d0d74","order_by":8,"name":"Jamirah Kayera","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jamirah","middleName":"","lastName":"Kayera","suffix":""},{"id":607382783,"identity":"b282ebc3-3b3c-4978-9df2-05c08588fa41","order_by":9,"name":"John Onama","email":"","orcid":"","institution":"Mbarara University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"","lastName":"Onama","suffix":""},{"id":607382784,"identity":"dea439ed-6238-4ad4-8dd2-f6baee974f9e","order_by":10,"name":"Sarah Marion Nakachwa","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"Marion","lastName":"Nakachwa","suffix":""},{"id":607382785,"identity":"86d95a71-aa24-4740-910c-47b5f20d1c53","order_by":11,"name":"Shilton SSerunkuma","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Shilton","middleName":"","lastName":"SSerunkuma","suffix":""},{"id":607382786,"identity":"0f6b276c-846e-4de3-b49e-e29cd24094ce","order_by":12,"name":"Mark Mugerwa","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mark","middleName":"","lastName":"Mugerwa","suffix":""}],"badges":[],"createdAt":"2026-02-17 17:38:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8903391/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8903391/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104998282,"identity":"51657825-5394-4898-af82-5f11deff69a2","added_by":"auto","created_at":"2026-03-19 16:26:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":37222,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePRISMA Flow Diagram\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8903391/v1/f3a4acc7509e16167198672c.png"},{"id":104998277,"identity":"b602a3a5-762b-4f88-9f35-9f004c16286e","added_by":"auto","created_at":"2026-03-19 16:26:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":28841,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eDistribution of studies by country.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8903391/v1/e6f3a0796bd5cc18c9dff42b.png"},{"id":104998435,"identity":"50f14ebc-61fd-4a50-b8d1-8782dd57894a","added_by":"auto","created_at":"2026-03-19 16:26:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1779893,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8903391/v1/f6f4e91e-439f-4d49-beb2-a3881c2683be.pdf"},{"id":104998259,"identity":"5fb4e971-1669-464c-b0db-29dc3fcbbabf","added_by":"auto","created_at":"2026-03-19 16:26:00","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":93607,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8903391/v1/f06d368ad2de1afc7c60e7e6.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring mental health challenges and interventions for healthcare professionals in Africa; A scoping Review","fulltext":[{"header":"Background","content":"\u003cp\u003eMental health challenges among healthcare professionals have emerged as a global public health concern, with rising rates of stress, burnout, anxiety, depression, and post-traumatic stress across health systems worldwide\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. International studies show that a significant proportion of healthcare workers experience psychological distress due to demanding workloads, long working hours, emotionally intense clinical encounters, and the pressure to provide high-quality care in increasingly complex environments\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. The COVID-19 pandemic further amplified this burden, exposing systemic vulnerabilities and underscoring the urgent need to protect the mental wellbeing of the healthcare workforce globally\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn Africa, these challenges are intensified by unique regional stressors. Healthcare professionals often work in under-resourced settings characterized by chronic staff shortages, high patient-to-provider ratios, recurrent infectious disease outbreaks, and limited medical supplies\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Consequently, stress and burnout are common, with many workers also experiencing anxiety, depression, compassion fatigue, and trauma from exposure to severe illness and mortality\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. These psychological pressures not only affect personal wellbeing but also impact job performance, patient outcomes, and retention of skilled health workers\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAccess to mental health resources remains limited across many African healthcare systems. Structural barriers such as inadequate mental health services, stigma surrounding mental illness, insufficient workplace support programs, and weak occupational health policies leave many healthcare workers without the help they need\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Systemic stressors including political instability, inconsistent remuneration, and reliance on overstretched public facilities further contribute to emotional exhaustion and erode resilience among healthcare professionals\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEvidence suggests that interventions such as peer-support programs, counseling services, stress management workshops, and organizational reforms can mitigate these challenges. In Africa, innovative approaches have emerged, including community-based psychosocial support in Uganda and digital mental health platforms piloted in South Africa\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Yet, the scope, effectiveness, and sustainability of such interventions remain underexplored, and global strategies often fail to account for local cultural norms, resource constraints, and the lived experiences of healthcare workers\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGiven the critical role of healthcare professionals in advancing universal health coverage and responding to public health emergencies, addressing their mental health needs is both a moral imperative and a strategic priority\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. By systematically mapping mental health challenges and interventions for healthcare professionals in Africa, this scoping review will generate context-specific insights to inform culturally appropriate policies, strengthen workforce resilience, and enhance health system performance across the continent.\u003c/p\u003e \n "},{"header":"Methods","content":"\u003ch3\u003eStudy Design\u003c/h3\u003e\u003cp\u003eThis study was conducted as a scoping review to map the existing literature on mental health challenges and interventions for healthcare professionals in Africa. The review follows the methodological framework proposed by the Joanna Briggs Institute (JBI) for scoping reviews\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. The reporting of this review adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy questions\u003c/h2\u003e \u003cp\u003eWe used the PCC (population, concept and context).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eQ1\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eWhat are the current mental health challenges experienced by healthcare professionals in Africa?\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eP: Healthcare professionals\u003c/p\u003e \u003cp\u003eC: Mental health challenges (e.g., stress, burnout, depression, anxiety)\u003c/p\u003e \u003cp\u003eC: Africa\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eQ2\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eWhat mental health interventions have been implemented to support healthcare professionals in Africa?\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eP: Healthcare professionals\u003c/p\u003e \u003cp\u003eC: Mental health interventions/strategies\u003c/p\u003e \u003cp\u003eC: Africa\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eQ3\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eHow effective are existing mental health strategies in improving psychological well-being among healthcare professionals in African settings?\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eP: Healthcare professionals\u003c/p\u003e \u003cp\u003eC: Effectiveness of mental health interventions\u003c/p\u003e \u003cp\u003eC: Africa\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eQ4\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eWhat barriers and facilitators affect the implementation of mental health strategies for healthcare professionals in Africa?\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eP: Healthcare professionals\u003c/p\u003e \u003cp\u003eC: Barriers and enablers to implementation\u003c/p\u003e \u003cp\u003eC: Africa\u003c/p\u003e \u003c/div\u003e\u003ch2\u003eStudy questions\u003c/h2\u003e\u003cp\u003eWe used the PCC (population, concept and context).\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eQ1\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eWhat are the current mental health challenges experienced by healthcare professionals in Africa?\u003c/p\u003e\u003cp\u003eP: Healthcare professionals\u003c/p\u003e\u003cp\u003eC: Mental health challenges (e.g., stress, burnout, depression, anxiety)\u003c/p\u003e\u003cp\u003eC: Africa\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eQ2\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eWhat mental health interventions have been implemented to support healthcare professionals in Africa?\u003c/p\u003e\u003cp\u003eP: Healthcare professionals\u003c/p\u003e\u003cp\u003eC: Mental health interventions/strategies\u003c/p\u003e\u003cp\u003eC: Africa\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eQ3\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eHow effective are existing mental health strategies in improving psychological well-being among healthcare professionals in African settings?\u003c/p\u003e\u003cp\u003eP: Healthcare professionals\u003c/p\u003e\u003cp\u003eC: Effectiveness of mental health interventions\u003c/p\u003e\u003cp\u003eC: Africa\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eQ4\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eWhat barriers and facilitators affect the implementation of mental health strategies for healthcare professionals in Africa?\u003c/p\u003e\u003cp\u003eP: Healthcare professionals\u003c/p\u003e\u003cp\u003eC: Barriers and enablers to implementation\u003c/p\u003e\u003cp\u003eC: Africa\u003c/p\u003e\u003ch3\u003eInformation Sources\u003c/h3\u003e\u003cp\u003eA comprehensive search was conducted across the following electronic bibliographic databases including SCOPUS, Web of Science, PubMed and Citation tracking.\u003c/p\u003e\u003ch3\u003eSearch Strategy\u003c/h3\u003e\u003cp\u003eA systematic search strategy was developed using medical subject headings (MeSH) and keywords related to the PCC framework. Boolean operators (AND, OR) will be utilized to combine search terms. The search string was adapted to the syntax of each specific database is provided in the supplementary file 1.\u003c/p\u003e\u003ch3\u003eStudy Selection\u003c/h3\u003e\u003cp\u003eThe selection process occurred in two stages:\u003c/p\u003e\u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTitle and Abstract Screening: Two independent reviewers screened titles and abstracts generated by the search against the inclusion criteria.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eFull-Text Review: Articles deemed potentially relevant underwent a full-text assessment by two independent reviewers.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e\u003cp\u003eAny disagreements regarding eligibility at either stage were resolved through consultation with a third reviewer and discussion until consensus was reached. The study selection process was documented and presented using a PRISMA flow diagram to ensure transparency.\u003c/p\u003e\u003ch3\u003eEligibility Criteria\u003c/h3\u003e\u003cp\u003e \u003cb\u003eInclusion Criteria\u003c/b\u003e \u003c/p\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePeer-reviewed journal articles of all study designs (quantitative, qualitative, and mixed-methods) Studies addressing mental health challenges affecting healthcare professionals in Africa including but not limited to stress, burnout, depression, anxiety, and PTSD.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eStudies addressing primary, secondary, or tertiary mental health interventions or strategies designed to support these healthcare professionals in Africa.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eLimited to articles published in the last 25 years. Only articles written in English or those with accessible English translations will be included.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003cp\u003e \u003cb\u003eExclusion Criteria\u003c/b\u003e \u003c/p\u003e\u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eStudies focusing on healthcare professionals working outside of Africa.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eReview articles, grey literature, editorials, commentaries, and conference abstracts lacking full data.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eArticles where full text is not available or data is insufficient for extraction.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e\u003ch2\u003eData Extraction\u003c/h2\u003e\u003cp\u003eData was extracted from the included articles by five independent reviewers using a standardized data extraction form developed for this study. The form captured the following variables:\u003c/p\u003e\u003cul\u003e \u003cli\u003e \u003cp\u003eAuthor(s) and year of publication.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTitle of the study\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCountry/Region of study\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStudy design and sample size.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCadre of healthcare professionals involved.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSpecific mental health challenges identified.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eType of interventions/strategies implemented (if any).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eKey findings regarding effectiveness, barriers, and facilitators.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e\u003ch3\u003eData Synthesis and Analysis\u003c/h3\u003e\u003cp\u003eThe analysis combined descriptive statistics with thematic synthesis to generate an integrated understanding of the burden, drivers, consequences of mental health challenges and interventions in place among healthcare professionals in Africa.\u003c/p\u003e\u003cp\u003eQuantitative findings were summarized descriptively, with prevalence estimates compiled and compared across countries, professional cadres, and study designs. Tables were used to summarize the findings.\u003c/p\u003e\u003cp\u003eA narrative synthesis was employed, which involved identifying recurring patterns, contextual drivers, and consequences of mental health challenges across settings as well as the interventions put in place. Qualitative findings were integrated thematically to enrich interpretation of quantitative prevalence data, particularly in relation to structural determinants such as workload, workplace violence, stigma, and pandemic-related stressors. Cross-cutting themes were highlighted to capture differences by cadre, gender, and country, as well as the co-occurrence of multiple mental health outcomes. Where available, studies reporting objective biomarkers of stress were synthesized alongside self-reported measures to provide a more comprehensive picture.\u003c/p\u003e\u003cp\u003eFor study characteristics, a map of Africa was designed using Rstudio Version 2025.05.1 + 513 to show the distribution of studies across the continent\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003eStudy selection and characteristics\u003c/h2\u003e\n \u003cp\u003eA total of 6567 records were identified through database searches of which 119 studies met the inclusion criteria for this scoping review (PRISMA flow diagram, Fig.\u0026nbsp;1). The characteristics for the individual studies are shown in supplementary file 1.\u003c/p\u003e\n \u003cp\u003eSelected studies were conducted in 20 countries and South Africa had the highest number of studies (n = 19). Two studies were multi-country; one was in Sudan and Tanzania while the other was in Uganda, Kenya and Tanzania. Figure\u0026nbsp;2 shows the distribution of these studies.\u003c/p\u003e\n \u003cp\u003eThe included studies were conducted in and published between 2003 and 2025. Study designs were heterogeneous, though the vast majority were cross-sectional studies (n = 105). Other study designs included mixed-methods studies, qualitative studies, quasi-experimental or pre-experimental studies, and longitudinal studies. Study populations varied and involved doctors/ physicians (n = 21), nurses (n = 27), midwives (n = 4), while most studies (n = 67) involved health care professions generally spanning across both clinical and non-clinical fields.\u003c/p\u003e\n \u003cp\u003eMental Health Challenges Identified\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003e1. Burnout\u003c/h2\u003e\n \u003cp\u003ePrevalence and severity of burnout rates varied significantly by country, cadre, and setting. Some studies reported overall burnout prevalence while others reported scores in dimensions of burn out (i.e. emotional exhaustion, depersonalization, and personal accomplishment). Burnout was high among early-career professionals; for instance, a study of medical interns in a South African tertiary hospital reported a 95% prevalence of burnout.\u003csup\u003e15\u003c/sup\u003e Similarly, among resident physicians in Sudan found that 86.1% met the criteria for burnout in at least one dimension, with nearly 14% experiencing it across all three dimensions\u003csup\u003e16\u003c/sup\u003e. In Ethiopia, burnout rates among nurses and midwives ranged from 40% and 56%\u003csup\u003e9,17–20\u003c/sup\u003e, while a study covering Kenya, Tanzania, and Uganda classified nearly one-third of nurses as \"burned out\" with high levels of somatic complaints\u003csup\u003e21\u003c/sup\u003e. Conversely, some studies in Ghana reported low overall burnout rates among physicians. In one study the score was 2.2 on a 5-point scale\u003csup\u003e22\u003c/sup\u003e, while the other study that reported on dimensions of burnout found 5.5% depersonalization, 7.8% lack of personal achievement and 10.8% emotional exhaustion. Another study on nurses and midwives, found scores on burnout dimensions higher: 58% in emotional exhaustion, 55.5% poor personal accomplishment and 38.3% depersonalization)\u003csup\u003e23\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eExcessive workloads and long working hours contributed to burnout; in Egypt, resident doctors working over 90 hours weekly during the COVID-19 pandemic showed significantly higher emotional exhaustion and depersonalization\u003csup\u003e24\u003c/sup\u003e. In Malawi, clinical officers attributed their occupational stress to \"excessive workloads\" aggravated by the COVID-19 pandemic\u003csup\u003e7\u003c/sup\u003e .\u003c/p\u003e\n \u003cp\u003eThe physical work environment also played a major role. Violence and safety concerns were also prominent; in Libya, burnout was exacerbated by the civil war context and fear of COVID-19, with over 57% of healthcare workers experiencing verbal abuse\u003csup\u003e25\u003c/sup\u003e. Similarly, midwives in Ethiopia identified workplace violence and exposure to blood/body fluids as significant predictors of burnout\u003csup\u003e9,10\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eNurses often bore a disproportionate burden. A comparative study in Nigeria found that nurses consistently scored higher on exhaustion and depersonalization than doctors and other health workers\u003csup\u003e26,27\u003c/sup\u003e. In the mental health sector, findings were mixed; while one South African study found low burnout among psychiatric nurses\u003csup\u003e28\u003c/sup\u003e, others in Tunisia and Nigeria reported high emotional exhaustion linked to poor funding and role conflict \u003csup\u003e29,30\u003c/sup\u003e. Among specialists, neurosurgery residents in Morocco reported a 77.3% burnout rate despite a favorable learning climate, largely driven by poor work-life balance\u003csup\u003e31\u003c/sup\u003e. In Tunisia, emergency medicine residents exhibited the highest rates of severe depression and exhaustion\u003csup\u003e32\u003c/sup\u003e, and 63% of oncology staff reported high emotional exhaustion\u003csup\u003e33\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eHigh burnout was strongly associated with depression \u003csup\u003e17,34\u003c/sup\u003e, anxiety, and poor quality of life\u003csup\u003e30,35\u003c/sup\u003e. In extreme cases, burnout was linked to suicidal thoughts and addictive behaviors among oncology staff in Tunisia \u003csup\u003e33\u003c/sup\u003e. It also compromised patient safety and quality of care. In Nigeria, burnout combined with the fear of contagion was associated with aggressive tendencies toward patients with HIV/AIDS\u003csup\u003e36\u003c/sup\u003e. In Ghana, team burnout was found to negatively impact psychological safety and civility within hospital units\u003csup\u003e37\u003c/sup\u003e, while another study identified burnout as a mediator for turnover intentions\u003csup\u003e38,39\u003c/sup\u003e. Table\u0026nbsp;1 shows the prevalence of burn out reported in the included studies.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePrevalence of burnout among health professionals reported in the included studies\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAuthors and Year\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProfession and Country\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePrevalence of Burn out\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eY.A. M. Elhadi et. al (2022)\u003csup\u003e16\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eResident Physicians (Sudan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.1% fulfilled criteria for burnout; 70.7% indicated high levels of emotional exhaustion.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM. Elhadi (2020)\u003csup\u003e25\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHospital healthcare workers (Libya)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.1% reported emotional exhaustion; 47.4% reported depersonalization.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFadle (2023) \u003csup\u003e24\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoctors (Egypt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51.0% were high in emotional exhaustion; 83.0% were high in depersonalization.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIlham et al. (2022) \u003csup\u003e40\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses, Midwives, and Health Technicians (Morocco)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBurnout affected \u0026gt; 75% (more than three quarters); 59.3% high emotional exhaustion.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEfa et al. (2024)\u003csup\u003e17\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence was 49.2%.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFeleke et al. (2022)\u003csup\u003e18\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.5% reported suffering from a high level of burnout.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBen Zid et al.(2018) \u003csup\u003e32\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedical residents (Tunisia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.14% had severe burnout.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMengistie et al. (2024) \u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMidwives (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverall prevalence was 55.3% (Personal: 58.3%; Work-related: 60.3%).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMorar \u0026amp; Marais (2022)\u003csup\u003e41\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychiatric trainees (South Africa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEvidence of some degree of burnout in more than two-thirds (\u0026gt; 66%) of participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlfadul et al. (2023)\u003csup\u003e42\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoctors and Nurses (Sudan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.7% met criteria for high risk of burnout.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKonlan et al. (2022)\u003csup\u003e39\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth workers (Ghana)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence was 20.57%.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGelaw et al. (2023)\u003csup\u003e43\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth professionals (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.0% showed Burnout syndrome; 52.8% presented high emotional exhaustion.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKahsay et al. (2025)\u003csup\u003e19\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProportion of burnout was 41.10%.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBizuneh et al. (2025)\u003csup\u003e20\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses, Midwives, Physicians (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverall prevalence was 54.7%.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGuider et al. (2024)\u003csup\u003e44\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealthcare professionals (Morocco)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.7% emotional exhaustion; 44.9% depersonalization; 58.2% diminished professional accomplishment.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHalayem-Dhouib et al. (2010)\u003csup\u003e29\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNursing staff, residents (Tunisia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh levels of burnout were detected among nurses.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMashego et al. (2016)\u003csup\u003e45\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (South Africa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92% indicated moderate levels of burnout.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOudrhiri et al. (2015)\u003csup\u003e31\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeurosurgery residents (Morocco)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77.3% were in a burnout state.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDaldoul et al. (2021)\u003csup\u003e33\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoctors and Nurses (Tunisia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFound in 21% of participants; 63% high emotional exhaustion.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003evan der Doef et al. (2012)\u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (Kenya, Tanzania, Uganda)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.1% labelled as burned out; 33.9% 'very highly' emotionally exhausted.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGadzama et al. (2023)\u003csup\u003e27\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealthcare professionals (Nigeria)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85% prevalence of burnout\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTununu \u0026amp; Martin (2020)\u003csup\u003e28\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (South Africa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh emotional exhaustion in 15.2%, high depersonalization in 4.5%, and 11.6% had low personal accomplishment (All of them did not meet the criteria for burnout).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOgboghodo \u0026amp; Edema (2020)\u003csup\u003e46\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eResident doctors (Nigeria)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverall prevalence was 41.7%; 59.6% suffered emotional exhaustion.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOpoku et al. (2023)\u003csup\u003e23\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses and Midwives (Ghana)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMajority experienced low burnout (58% low emotional exhaustion).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMalebo Kgatle (2024)\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedical interns (South Africa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% of the participants reported burnout.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUdho \u0026amp; Kabunga (2022)\u003csup\u003e35\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (Uganda)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.1% had high levels of burnout; 36.2% reported average levels.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOpoku \u0026amp; Apenteng (2014)\u003csup\u003e22\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysicians (Ghana)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverall, burnout was low; however, physicians exhibited Moderate levels of emotional exhaustion.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEngelbrecht et al. (2008)\u003csup\u003e47\u003c/sup\u003e [45]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (South Africa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh levels of burnout were identified.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlabi et al. (2021)\u003csup\u003e30\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMental Health Nurses (Nigeria)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence of emotional exhaustion was 44.4%; depersonalization 31.7%.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePayne et al. (2020)\u003csup\u003e48\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNursing staff (South Africa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFound relatively high personal (mean 49.2) and work-related burnout.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMamorobela et al. (2023)\u003csup\u003e49\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoctors (South Africa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36% prevalence (lower-middle range).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbdo et al. (2016)\u003csup\u003e50\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysicians and nursing staff (Egypt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.9% had high burnout; 66.0% had moderate burnout.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAfulani et al. (2021)\u003csup\u003e51\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternity providers (Kenya)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.6% high burnout; 65% low burnout.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiksegn et al. (2016)\u003csup\u003e52\u003c/sup\u003e [59]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealthcare workers (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean score of burnouts was 50.27 with standard deviation of ± 17.1528, 36.7% showed that burnout above the mean\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHamid \u0026amp; Abdullah (2020)\u003csup\u003e53\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth Professionals (Tanzania and Sudan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmotional exhaustion was higher in Sudan (44.4%) than Tanzania (33.3%), while high depersonalization was higher in Tanzania (40.3%) compared to Sudan (19.4%). For personal accomplishment (PA), Tanzanian participants showed a greater proportion with low PA scores (63.9%), whereas only 22.2% of Sudanese participants fell in this high-burnout PA range.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAyisi-Boateng et al. (2020)\u003csup\u003e54\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysicians (Ghana)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5% experienced depersonalization, 7.8% lack of personal achievement and 10.8% had emotional exhaustion.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003e2. Anxiety\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAnxiety was a pervasive mental health challenge, though the available evidence was heavily skewed toward the COVID-19 pandemic period with most studies conducted between 2020 and 2025. In this pandemic context, prevalence rates were exceptionally high; for instance, a study in Egypt reported that 90.5% of healthcare workers experienced some degree of anxiety, with 18.5% classified as severe\u003csup\u003e55\u003c/sup\u003e. Similarly in Kenya, 59.9% of staff in a teaching hospital screened positive for generalized anxiety disorder \u003csup\u003e56\u003c/sup\u003e and in Morocco, where 58.3% of workers reported anxiety symptoms\u003csup\u003e57\u003c/sup\u003e. However, rates varied significantly by setting; notably lower rates were observed in specific sub-groups, such as surgeons in Libya (15.2%)\u003csup\u003e58\u003c/sup\u003e and psychiatric nurses in Ghana (27%)\u003csup\u003e59\u003c/sup\u003e. Anxiety was directly driven by the unique stressors of the COVID-19 pandemic, specifically the fear of infection and systemic resource failures. In Ethiopia, the lack of personal protective equipment (PPE) was cited as a primary source of fear for 78.8% of staff, while 63.8% reported anxiety specifically regarding the risk of transmitting the virus to their families\u003csup\u003e60\u003c/sup\u003e. This \"health anxiety\" was further corroborated in Egypt, where it was found in 28% of workers and was inversely correlated with their quality of life\u003csup\u003e61\u003c/sup\u003e. In Botswana, anxiety was significantly predicted by the experience of stigma and the trauma of losing relatives to the disease\u003csup\u003e62\u003c/sup\u003e. Furthermore, frontline status was a critical determinant; healthcare workers stationed in isolation centers and treatment units in South Sudan and Ethiopia reported higher anxiety levels compared to their non-frontline counterparts\u003csup\u003e63,64\u003c/sup\u003e. In Nigeria, healthcare workers were anxious about getting and also infecting their relatives with COVID-19.\u003csup\u003e56\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eEvidence from the pre- COVID-19 pandemic era had reported anxiety. Two studies conducted in Uganda in 2014 identified a severe burden of \"death anxiety\" among midwives working in rural areas\u003csup\u003e65,66\u003c/sup\u003e. An overwhelming 94% of these midwives reported witnessing maternal deaths, and 93% exhibited moderate to high levels of death anxiety as a direct result\u003csup\u003e65\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eFemale healthcare professionals reported higher levels of anxiety than their male counterparts. This trend was statistically significant in studies from Ethiopia\u003csup\u003e60,67\u003c/sup\u003e, South Sudan\u003csup\u003e63\u003c/sup\u003e, and Morocco. Nurses and midwives appeared to be the most vulnerable group. In Ethiopia, nursing was independently associated with higher anxiety scores compared to other professions\u003csup\u003e60\u003c/sup\u003e. Other significant risk factors identified included working night shifts, working in emergency departments, and having conflicts with coworkers\u003csup\u003e67\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eAnxiety also co-occurred with depression, burnout, and stress. In Cameroon, anxiety symptoms were strongly associated with depressive symptoms and the fear of death\u003csup\u003e68\u003c/sup\u003e. In Sudan, higher scores for depression and stress were significantly correlated with higher degrees of burnout\u003csup\u003e69\u003c/sup\u003e. The impact of coping strategies on anxiety outcomes was also significant. In South Africa, the use of avoidant coping mechanisms such as self-blame, denial, and substance use was found to be maladaptive, significantly increasing the risk of anxiety among mental health practitioners \u003csup\u003e70\u003c/sup\u003e. Table\u0026nbsp;2 shows prevalence of anxiety among health professionals in Africa.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePrevalence of Anxiety Among Healthcare Professionals in Africa\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAuthors and Year\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProfession and Country\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePrevalence of Anxiety\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMisganaw et al. (2024)\u003csup\u003e67\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProfessional Nurses (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.9% overall prevalence.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMboua et al. (2021\u003csup\u003e71\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses and Physicians (Cameroon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.8% prevalence rate.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNguepy Keubo et al. (2021)\u003csup\u003e68\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth care professionals (Cameroon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.20% prevalence of anxiety symptoms.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWayessa et al (2023)\u003csup\u003e72\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealthcare Workers (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.5% prevalence of anxiety.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM. Elhadi \u0026amp; Mshergh (2021)\u003csup\u003e58\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSurgeons (Libya)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.2% reached the cutoff score for anxiety symptoms.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAly et al. 2021)\u003csup\u003e55\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysicians, nurses (Egypt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90.5% had different degrees of anxiety (40% mild, 32% moderate, 18.5% severe).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMuliira \u0026amp; Bezuidenhout (2015)\u003csup\u003e65\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMidwives (Uganda)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93% exhibited moderate to high levels of death anxiety (among those experiencing a maternal death).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMuliira et al. (2015)\u003csup\u003e66\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMidwives (Uganda)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74.6% reported experiencing moderate to high levels of death anxiety.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSayed et al. (2023)\u003csup\u003e73\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHouse officers (Egypt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32% of participants reported anxiety.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIdrees \u0026amp; Bashir, 2023 \u003csup\u003e63\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealthcare workers (South Sudan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47% had borderline anxiety scores.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMulatu et al. (2021)\u003csup\u003e64\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoctors, nurses, etc. (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.7% and 5.7% had moderate and symptoms of anxiety respectively.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSiamisang et al. (2022)\u003csup\u003e62\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealthcare professionals (Botswana)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDetected in 28.2% of participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStals et al. (2024)\u003csup\u003e70\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMental healthcare practitioners (South Africa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.6% had high levels of anxiety.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOpoku Agyemang et al. (2022)\u003csup\u003e59\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychiatric Nurses (Ghana)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27% experienced mild to severe anxiety.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBouaddi et al. (2023)\u003csup\u003e57\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysicians and nurses (Morocco)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.3% experienced mild to extremely severe anxiety.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBundi et al. (2024)\u003csup\u003e56\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth care providers (Kenya)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59.9% overall prevalence of generalized anxiety disorder symptoms.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbdelghani et al. (2021)\u003csup\u003e61\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealthcare workers (Egypt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28% frequency of health anxiety to COVID-19.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChorwe-Sungani G. (2021)\u003csup\u003e74\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (Malawi)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCOVID-19 related anxiety was 25.5% and nearly half of the respondents suffered from functional impairment.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKwobah et al. (2021)\u003csup\u003e75\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth care workers (Kenya)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36% of the participants scored positively for generalized anxiety during COVID-19 pandemic\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOfori et al (2021)\u003csup\u003e76\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth care workers (Ghana)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.8% had anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003e3. Depression\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ePrevalence rates surged during the COVID-19 pandemic. In Egypt, one study found that 94% of participants exhibited mild to severe depression\u003csup\u003e55\u003c/sup\u003e, while another reported that 63% of physicians suffered from severe or extremely severe depression\u003csup\u003e77\u003c/sup\u003e. In Morocco, 53.1% of healthcare workers reported symptoms ranging from mild to extremely severe\u003csup\u003e57\u003c/sup\u003e, and in Ghana, 52.1% of nurses screened positive for depression\u003csup\u003e78\u003c/sup\u003e [11]. Lower prevalence was observed in Botswana\u003csup\u003e62\u003c/sup\u003e (21%) and among psychiatric nurses in Ghana (19.6%)\u003csup\u003e59\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eWhile the pandemic exacerbated these issues, evidence from the pre-pandemic era demonstrates that depression is an occupational problem for African healthcare workers. A 2015 study in Nigeria found that 14.9% of healthcare workers in tertiary hospitals met the criteria for depression, with symptoms significantly linked to sadness over poor working conditions\u003csup\u003e79\u003c/sup\u003e. Similarly, a 2018 study of medical residents in Tunisia revealed a 30.5% prevalence of depression, associating the disorder with the heavy burden of weekly working hours and night shifts\u003csup\u003e80\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eThe drivers of depression identified varied. In Ghana, a direct positive correlation was found between workplace bullying and depression, which in turn significantly increased nurses' intention to quit their jobs\u003csup\u003e78\u003c/sup\u003e. In Botswana, depression was strongly associated with the experience of stigma and smoking\u003csup\u003e62\u003c/sup\u003e. Furthermore, the COVID-19 pandemic introduced specific stressors; in Egypt, having a poor attitude toward personal protective equipment (PPE) and overall worry about the pandemic were significant predictors of depression\u003csup\u003e73\u003c/sup\u003e. Frontline status also played a critical role, with healthcare workers in COVID-19 treatment units in Ethiopia facing notably higher odds of depression compared to non-frontline staff\u003csup\u003e64\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eFemales were more susceptible. Female gender was significantly associated with higher depression scores in studies conducted in Morocco\u003csup\u003e81\u003c/sup\u003e, South Sudan\u003csup\u003e63\u003c/sup\u003e, Ethiopia\u003csup\u003e60\u003c/sup\u003e, Egypt\u003csup\u003e77\u003c/sup\u003e, Nigeria\u003csup\u003e79\u003c/sup\u003e, and Tunisia\u003csup\u003e80\u003c/sup\u003e. Age was another demographic factor with associations; while older age was associated with higher depression in Morocco\u003csup\u003e81\u003c/sup\u003e and Tunisia\u003csup\u003e80\u003c/sup\u003e, younger age was a risk factor for related comorbidities like eating disorders\u003csup\u003e81\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eDepression also presented as part of a broader cluster of psychological and behavioral challenges. A study in Morocco found a significant rise in eating disorders during the pandemic, which were strongly associated with a diagnosis of depression, emotional eating, and obesity\u003csup\u003e81\u003c/sup\u003e. In South Africa, maladaptive coping mechanisms such as self-blame, behavioral disengagement, and substance use were found to significantly predict higher levels of depression among mental healthcare practitioners\u003csup\u003e70\u003c/sup\u003e. Furthermore, depression was linked to professional attrition; in Sudan, roughly one-third of mental health professionals felt disheartened and considered quitting, with depression scores negatively associated with age and experience\u003csup\u003e69\u003c/sup\u003e. Table\u0026nbsp;3 shows prevalence of depression among health care professionals in Africa in reported studies.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePrevalence of depression among health care professionals in Africa.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAuthor \u0026amp; Year\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProfession \u0026amp; Country\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePrevalence of Depression\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLahlou et al. (2022)\u003csup\u003e81\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedical doctors, nurses, students (Morocco)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.3% had moderate to severe depression.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSayed et al. (2023)\u003csup\u003e73\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHouse officers (Egypt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22% of participants reported depression.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIdrees \u0026amp; Bashir (2023)\u003csup\u003e63\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealthcare workers (South Sudan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44% had borderline depression scores.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMulatu et al. (2021)\u003csup\u003e64\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoctors, nurses, and pharmacists (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.6% and 6.7% experienced moderate and severe symptoms of depression respectively.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSiamisang et al. (2022)\u003csup\u003e62\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealthcare professionals (Botswana)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDetected in 21.0% of participants.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStals et al. (2024)\u003csup\u003e70\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMental healthcare practitioners (South Africa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.3% had high levels of depression.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOpoku Agyemang et al. (2022)\u003csup\u003e59\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychiatric Nurses (Ghana)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.6% experienced mild to severe depression.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBouaddi et al. (2023)\u003csup\u003e57\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysicians and nurses (Morocco)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.1% reported symptoms of mild to extremely severe depression.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDapilah \u0026amp; Druye (2024)\u003csup\u003e78\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (Ghana)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.1% were depressed at various degrees.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKhalaf et al. (2020)\u003csup\u003e77\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysicians (Egypt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe majority (63%) suffered from severe or extremely severe depression.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObi et al. (2015)\u003csup\u003e79\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealthcare workers (Nigeria)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.9% met the study’s cut-off for depression.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAly et al. (2021)\u003csup\u003e55\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysicians, nurses, etc. (Egypt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94% showed mild to severe depression.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarzouk et al. (2018)\u003csup\u003e80\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedical residents (Tunisia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.5% met the definite criteria for depression.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKwobah et al. (2021)\u003csup\u003e75\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth care workers (Kenya)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.1% of the participants scored positively for depression.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOfori et al (2021)\u003csup\u003e76\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth care workers (Ghana)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.1%, had depression,\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003e4. Work-related Stress\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eStress was characterized by both acute pandemic-induced spikes and long term system stress. In the context of COVID-19, a study in Egypt reported that 98.5% of healthcare workers experienced moderate to severe stress\u003csup\u003e55\u003c/sup\u003e, while in Morocco, 67% reported high perceived stress\u003csup\u003e82\u003c/sup\u003e. Even in studies extending beyond the immediate pandemic peak or focusing on general occupational health, the burden remained high. In a 2025 study of nurses in Morocco, 87% reported moderate stress levels\u003csup\u003e83\u003c/sup\u003e, and in a rural county in Kenya, 85% of maternity providers reported moderate stress\u003csup\u003e51\u003c/sup\u003e. Similarly, a pre-pandemic study in Ethiopia found that 66.2% of nurses experienced work-related stress\u003csup\u003e84\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eStructural drivers were consistent across time and geography. In South Africa, inadequate salary, covering for absent coworkers, and lack of control over work as primary stressors for doctors\u003csup\u003e85,86\u003c/sup\u003e. In Ethiopia, the shortage of nurses and the intensity of working in Intensive Care Units (ICUs) were identified as contributors\u003csup\u003e84\u003c/sup\u003e. The COVID-19 pandemic layered new stressors onto this fragile system; in Ghana, inadequate preparedness for the response was directly associated with higher stress and burnout, mediated partly by the fear of infection\u003csup\u003e87\u003c/sup\u003e. Qualitative evidence from Nigeria further emphasized that policy changes, extended use of PPE, and the lack of a secure working environment were major sources of distress\u003csup\u003e88,89\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eSome studies linked work environments to stress. In Angola, \"workaholism\" was identified as a significant predictor of job stress, which in turn negatively impacted job satisfaction and psychological capital\u003csup\u003e90\u003c/sup\u003e. Demographic factors also played a role; female gender was associated with higher stress in Nigeria\u003csup\u003e91\u003c/sup\u003e and Morocco\u003csup\u003e83\u003c/sup\u003e, while in Egypt, younger married nurses were found to be more susceptible to Effort-Reward Imbalance\u003csup\u003e92\u003c/sup\u003e. Conversely, in Nigeria, emotional intelligence was identified as a protective factor, with independent relationships found between emotion appraisal and reduced work stress\u003csup\u003e93\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eNotably, some included studies went beyond self-reported questionnaires to identify physiological biomarkers of stress, providing objective evidence of the physical toll on healthcare workers. In Egypt, a study found that healthcare workers had significantly elevated levels of Interleukin-6 (IL-6), a pro-inflammatory cytokine, which correlated with higher stress scores and night shift work\u003csup\u003e94\u003c/sup\u003e. Another Egyptian study found a significant correlation between psychosocial stress (Effort-Reward Imbalance) and oxidative stress, measured by Malondialdehyde (MDA) levels\u003csup\u003e92\u003c/sup\u003e. In Kenya, while cortisol levels did not show a statistically significant association in a small sample, researchers measured Heart Rate Variability (HRV) and found that \"over-commitment\" or motivation to work excessively was associated with increased stress\u003csup\u003e51\u003c/sup\u003e. Table\u0026nbsp;4 shows prevalence of stress among health care professionals in Africa reported in the selected studies.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePrevalence of work-related stress among health care professionals in Africa.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAuthors and Year\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProfession and Country\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePrevalence of Stress\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOneib \u0026amp; Hasnaoui (2021)\u003csup\u003e82\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysicians and Nurses (Morocco)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67% reported high perceived stress.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZamurayeva et al. (2024)\u003csup\u003e88\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoctors, nurses, and lab technicians (Nigeria)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFound high levels of occupational stress.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAly et al. (2021)\u003csup\u003e55\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysicians, nurses, technicians, etc. (Egypt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98.5% showed moderate to severe stress (1.3% low stress).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAfulani et al. (2021)\u003csup\u003e87\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses, midwives, and allied health workers (Ghana)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64.3% reported moderate stress; 4.3% reported high stress.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAfulani et al. (2021)\u003csup\u003e51\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternity providers (Kenya)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85% reported moderate stress; 11.5% reported high stress.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSalem \u0026amp; Ebrahem et al. (2018)\u003csup\u003e92\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNursing staff (Egypt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72.5% prevalence of Effort-Reward Imbalance (a proxy for stress).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThomas \u0026amp; Valli (2006)\u003csup\u003e86\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoctors (South Africa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExperienced higher levels of occupational stress compared to the general working population.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRahoui Chairi et al. (2025)\u003csup\u003e83\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (Morocco)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87% experienced moderate levels of perceived stress.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBaye et al. (2020)\u003csup\u003e84\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence of work-related stress was 66.2%.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLawal \u0026amp; Idemudia (2017)\u003csup\u003e93\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (Nigeria)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReported a moderate level of work stress.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOfori et al (2021)\u003csup\u003e76\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth care workers (Ghana)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.2% had stress\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003ePsychological distress\u003c/h2\u003e\n \u003cp\u003ePsychological distress reached critical levels during the COVID-19 pandemic while maintained by structural occupational stressors in the pre-pandemic era. During the acute phases of the global health crisis, prevalence rates were alarmingly high; a study conducted in the early stages of the outbreak in Ethiopia reported that 78.3% of healthcare professionals suffered from psychological distress, driven largely by insomnia, lack of information, and social stigma\u003csup\u003e95\u003c/sup\u003e Similarly, in Egypt, 53.3% of primary healthcare workers exhibited high distress levels\u003csup\u003e96\u003c/sup\u003e, and approximately 50% of physicians reported severe distress, primarily fueled by the fear of transmitting the virus to their families\u003csup\u003e97\u003c/sup\u003e. In South Africa, 50.3% of nurses and 40.6% of medical practitioners were classified as psychologically distressed, with the lack of adequate leave and insurance coverage for COVID-19 cited as key systemic contributors\u003csup\u003e98\u003c/sup\u003e. Stigma in relationships with family, friends and neighbors during the pandemic also contributed to psychological distress.\u003csup\u003e99,100\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eHowever, evidence from pre-pandemic studies demonstrated that psychological distress is not merely a reaction to disease outbreak but a symptom of high-pressure work environments. In a 2014 study of residents in a Nigerian teaching hospital, 48.4% of respondents evinced psychological distress, which was significantly associated with the intensity of their workload\u003csup\u003e101\u003c/sup\u003e. Similarly, a 2019 study in Ethiopia found a 44.4% prevalence of distress, explicitly linking it to high job demands and low job control. Specific medical specializations appeared to carry unique burdens; for instance, a study of psychiatric nurses in Tunisia revealed that 74.5% had experienced aggression from patients and 45.5% had witnessed suicide attempts, leading 60% of them to wish for a transfer\u003csup\u003e102\u003c/sup\u003e. In Ethiopia, anesthesia professionals were identified as a high-risk group\u003csup\u003e103\u003c/sup\u003e, while in Egypt, nurses working in ICUs and internal medicine departments reported significantly higher rates of psychological ill health compared to other units\u003csup\u003e104\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eFemale gender and younger age as risk factors for distress. Female healthcare workers were found to have significantly higher odds of distress in studies from South Africa\u003csup\u003e98\u003c/sup\u003e, Ethiopia, and Egypt\u003csup\u003e97\u003c/sup\u003e. Regarding age, younger professionals (typically under 40) were more vulnerable in South Africa, Ethiopia\u003csup\u003e95\u003c/sup\u003e, and Egypt\u003csup\u003e104\u003c/sup\u003e, likely due to lower professional experience and resilience, although one Ethiopian study found the highest risk in the 35–44 age bracket\u003csup\u003e103\u003c/sup\u003e. Marital status also played a role, with unmarried personnel showing higher susceptibility to stress and anxiety\u003csup\u003e103\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eProtective factors and coping mechanisms were also identified. In Morocco, a study on nurses emphasized that recognition from superiors was significantly correlated with better psychological health and job satisfaction\u003csup\u003e105\u003c/sup\u003e. In Nigeria, possessing a higher educational degree was found to lower the odds of distress\u003csup\u003e106\u003c/sup\u003e. Conversely, the lack of support systems exacerbated the issue; in Egypt, negative support from family and friends was a significant predictor of psychological ill health\u003csup\u003e104\u003c/sup\u003e, while religious coping was identified as the most effective strategy for physicians navigating the crisis\u003csup\u003e97\u003c/sup\u003e. Table\u0026nbsp;5 shows prevalence of psychological distress among health care professionals in Africa.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePrevalence of psychological distress among health care professionals in Africa\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAuthor and Year\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProfession and Country\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePrevalence of Psychological Distress\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDemilew et al. (2022)\u003csup\u003e103\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysicians, nurses, midwives, etc. (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.5% of the participants have psychological distress.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKhiari et al. (2024)\u003csup\u003e102\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychiatric Nurses (Tunisia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61.8% anxiety, 36.4% stress, 34.5% depression (moderate to very severe levels).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbdu et al. (2023) \u003csup\u003e96\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary health care workers (Egypt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.3% had high psychological distress.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIbigbami et al. (2022)\u003csup\u003e106\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth workers (Nigeria)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.1% moderate and 5.8% severe psychological distress.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRamlagan et al. (2024)\u003csup\u003e98\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealthcare workers (South Africa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.3% (nurses), 40.6% (medical practitioners), and 47.4% (others) were classified as psychologically distressed.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYitayih et al. (2020)\u003csup\u003e95\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealth care professionals (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrevalence was 78.3%.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEsan et al. (2006) \u003csup\u003e101\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eResidents (Nigeria)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEvidence of distress in 48.4% of respondents.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKabito \u0026amp; Mekonnen (2020) \u003csup\u003e107\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealthcare professionals (Ethiopia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSymptoms in the past 4 weeks stood at 44.4%.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSehsah et al. (2021) \u003csup\u003e97\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysicians (Egypt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eApproximately 50% exhibited severe psychological distress.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArafa et al. (2003) \u003csup\u003e104\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (Egypt)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.67% recorded moderate to severe psychological symptoms.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChipps et al. (2025)\u003csup\u003e108\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (South Africa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh levels of psychological distress, during COVID-19 compared to current levels (27.2 vs 18.8; W = 8.9, p = \u0026lt; 0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKambulandu et al. (2024)\u003csup\u003e109\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClinical Staff (Lesotho)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.6% had moderate to severe psychological distress\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVancampfort \u0026amp; Mugisha (2022)\u003csup\u003e110\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses (Uganda)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92.6% of participants had psychological distress (Kessler-6 score ≥ 13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003ePost-Traumatic Stress Disorder (PTSD) Among Healthcare Professionals\u003c/h2\u003e\n \u003cp\u003ePTSD was also reported by some studies during the COVID-19 pandemic. A nationwide study in Uganda found 44.4% of the nurses had elevated PTSD symptoms\u003csup\u003e110\u003c/sup\u003e. In Southern Ethiopia, a study assessing healthcare professionals found that over half (56.8%) screened positive for PTSD symptoms. The severity of these symptoms was, 36.7% of the workforce exhibiting severe levels of PTSD, while 7.8% and 12.9% showed moderate and mild symptoms, respectively\u003csup\u003e111\u003c/sup\u003e. The drivers of this trauma were identified as a combination of pandemic fears and systemic failures. In Central Uganda, predictive factors for PTSD among frontline nurses included a lack of social support, the intense fear of contracting COVID-19, and drastically increased workloads\u003csup\u003e112\u003c/sup\u003e. Also, the study noted that these pandemic stressors were exacerbated by a healthcare system that was \"already under severe strain\" prior to the outbreak, suggesting that the pandemic acted as a breaking point for a workforce already operating at capacity\u003csup\u003e112\u003c/sup\u003e. In Lesotho, 31.7% of clinical staff during the COVID-19 pandemic had severe PTSD.\u003csup\u003e109\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eGender disparity was noted in the development of PTSD symptoms. A 2025 study in Morocco's Oriental region found that female healthcare workers, who constituted 68.3% of the sample, exhibited strong correlations between PTSD, anxiety, and perceived stress\u003csup\u003e113\u003c/sup\u003e [1]. The analysis revealed a pathway where gender exerted an indirect effect on PTSD; this relationship was mediated by anxiety and moderated by perceived stress, especially in high-pressure contexts\u003csup\u003e113\u003c/sup\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\"\u003e\n \u003ch2\u003eSubstance Use among healthcare professionals\u003c/h2\u003e\n \u003cp\u003eA few studies in Morocco, Kenya, and Nigeria reported on psychoactive substance (SPA) use. A large-scale Kenyan study reported that over half the sample, 51.7% of healthcare providers, had used substances at some point,\u003csup\u003e114\u003c/sup\u003e with another Nigerian study finding a lifetime prevalence of 66.0%\u003csup\u003e115\u003c/sup\u003e. Alcohol was the most substance of choice, cited by 93.7% of users in the Kenyan data followed by cannabis (28.9%), then tobacco (27.6%)\u003csup\u003e114\u003c/sup\u003e, whereas for the Nigerian study, Alcohol was most used (60.4%), followed by sedatives (12.7%), then tobacco (10.2%). Findings from a separate earlier Kenyan study indicated the following lifetime prevalence rates for substance use: alcohol (35.8%), tobacco (23.5%), cannabis and sedatives (9.3% each), cocaine (8.8%), amphetamine-like stimulants (6.4%), hallucinogens (5.4%), opioids (3.9%), and inhalants (3.4%).\u003csup\u003e116\u003c/sup\u003e Among resident physicians in Morocco, life time use of an SPA was 16.1%. \u003csup\u003e117\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eSubstance use is rarely an isolated issue; the data overwhelmingly suggests it is a form of self-medication linked to severe distress. Occupational stress and stressful workload were explicitly identified as major factors influencing substance use in studies from both Kenya and Nigeria.\u003csup\u003e114,115\u003c/sup\u003e. Resident doctors in Morocco who used SPA were nearly twice as likely to have a history of psychiatric disorders (27% versus 14.7%)\u003csup\u003e117\u003c/sup\u003e. This same study also established a critical correlation between SPA use and severe outcomes, specifically noting that use was strongly associated with suicide attempts\u003csup\u003e117\u003c/sup\u003e. Vulnerability to substance use varies by professional rank and gender. Male gender was a highly significant predictor of SPA use in both the Moroccan\u003csup\u003e117\u003c/sup\u003e and Nigerian studies\u003csup\u003e115\u003c/sup\u003e. Work pressure was cited as a major influence on substance abuse.\u003csup\u003e118\u003c/sup\u003e Table\u0026nbsp;6 shows prevalence of substance use among health care professionals in Africa.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv\u003eTable 6\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePrevalence of Substance use among health professionals in Africa\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAuthor and Year\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProfession and Country\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePrevalence of Substance Use and Key Findings\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCharlotte Mc Magh et al. (2023)\u003csup\u003e119\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoctors, Nurses, Clinical Associates, Dentists (South Africa)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e20.9%\u003c/strong\u003e of professionals reported risky alcohol use (AUDIT-C). Risky drinking was significantly higher in males (\u003cstrong\u003e42.0%\u003c/strong\u003e) compared to females (\u003cstrong\u003e15.4%\u003c/strong\u003e). Alcohol use was identified as a cause for concern, particularly in the male population.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAggrey G. Mokaya et al. (2016) \u003csup\u003e116\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNurses, Clinical Officers, Doctors, Support Staff (Kenya)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLifetime substance use was \u003cstrong\u003e35.8%\u003c/strong\u003e for alcohol and \u003cstrong\u003e23.5%\u003c/strong\u003e for tobacco. Use in the past 3 months was \u003cstrong\u003e19.6%\u003c/strong\u003e for alcohol and \u003cstrong\u003e13.2%\u003c/strong\u003e for tobacco. Other lifetime use included cannabis (\u003cstrong\u003e9.3%\u003c/strong\u003e), sedatives (\u003cstrong\u003e9.3%\u003c/strong\u003e), and cocaine (\u003cstrong\u003e8.8%\u003c/strong\u003e). Tobacco was the only substance where a high-risk score (\u003cstrong\u003e0.5%\u003c/strong\u003e) was recorded.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIsinyemeze E. \u0026amp; Agbapuonwu N. E. (2024\u003cstrong\u003e)\u003c/strong\u003e\u003csup\u003e120\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealthcare professionals (Doctors, Nurses, Pharmacists, etc.) (Nigeria)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e78.1%\u003c/strong\u003e of respondents believed alcohol was the most commonly abused substance, followed by tobacco (\u003cstrong\u003e67.5%\u003c/strong\u003e). High rates of usage were perceived for alcohol (\u003cstrong\u003e80.2%\u003c/strong\u003e rated as 'High') and tobacco (\u003cstrong\u003e70.8%\u003c/strong\u003e rated as 'High'). Reasons for abuse included easy access (\u003cstrong\u003e62.5%\u003c/strong\u003e), excessive workload (\u003cstrong\u003e56.9%\u003c/strong\u003e), and stress (\u003cstrong\u003e51.7%\u003c/strong\u003e).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChidindu Prince Anagwu et al. (2024)\u003csup\u003e115\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoctors, Nurses, Lab Scientists (Nigeria)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e66%\u003c/strong\u003e of workers had used a substance at least once in their lifetime. Lifetime prevalence: Alcohol (\u003cstrong\u003e60.4%\u003c/strong\u003e), Sedatives (\u003cstrong\u003e12.7%\u003c/strong\u003e), Tobacco (\u003cstrong\u003e10.2%\u003c/strong\u003e). Past 3 months use: Alcohol (\u003cstrong\u003e50.8%\u003c/strong\u003e), Sedatives (\u003cstrong\u003e5%\u003c/strong\u003e), Tobacco (\u003cstrong\u003e4.1%\u003c/strong\u003e). \u003cstrong\u003e37.1%\u003c/strong\u003e of participants were classified as moderate-risk alcohol users.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJasmit Shah et al. (2025)\u003csup\u003e114\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoctors, Nurses, Allied Health (Kenya)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e51.7%\u003c/strong\u003e of healthcare providers reported ever using a substance. Among those who used substances, \u003cstrong\u003e93.7%\u003c/strong\u003e used alcohol, \u003cstrong\u003e28.9%\u003c/strong\u003e used cannabis, and \u003cstrong\u003e27.6%\u003c/strong\u003e used tobacco. Substance use was higher in doctors (\u003cstrong\u003e37.5%\u003c/strong\u003e alcohol, \u003cstrong\u003e58.4%\u003c/strong\u003e cannabis) compared to nurses (\u003cstrong\u003e29.7%\u003c/strong\u003e alcohol, \u003cstrong\u003e12.1%\u003c/strong\u003e cannabis).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEchater et al. 2024 \u003csup\u003e117\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eResident Doctors (Morocco)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychoactive substance use was reported by 16.1% of the group. Specific usage rates included tobacco (11.1%), alcohol (10%), and cannabis (6.1%), with reports of ecstasy and cocaine use (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\"\u003e\n \u003ch2\u003eInterventions for mental health challenges among healthcare professionals in Africa, effectiveness, and challenges in implementation\u003c/h2\u003e\n \u003cp\u003eTen studies reported on interventions to address mental health challenges of health professionals.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e1. Osman et al. (2021), South Africa.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe study implemented a brief online mindfulness-based intervention (MBI) adapted for healthcare professionals (n = 47) during the COVID-19 pandemic. The program comprised four 1-hour group sessions delivered via Zoom, featuring exercises like the \"raisin exercise,\" body scanning, yoga, and walking meditation. The intervention yielded statistically significant improvements. Post-intervention analysis showed a significant reduction in perceived stress levels (p \u0026lt; 0.05) and emotional exhaustion. Additionally, there was a significant increase in scores for mindful awareness and personal accomplishment. Qualitative analysis indicated a thematic shift from feelings of \"powerlessness\" to \"acquired control.\" Implementation was hampered by a high dropout rate of 28%, with only 47 out of 65 registered participants completing the assessments. The primary barriers were erratic work schedules and pandemic-related exhaustion, which made attendance difficult despite the provision of make-up sessions.\u003csup\u003e121\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e2. Kelly et al. (2021), South Africa\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThis was a self-directed e-learning intervention was deployed for 750 healthcare workers, consisting of five asynchronous online modules focused on stress management, mindfulness, and self-care planning. Among the 474 participants who completed the post-test, there were statistically significant increases in resilience, measured by the Connor-Davidson Resilience Scale (CD-RISC), and psychological well-being, measured by the WHO-5 Well-Being Index. Participants also reported significantly higher knowledge and confidence regarding mental health maintenance. The study faced substantial attrition, with only 63.2% (474/750) of the initial cohort completing the training. The reliance on convenience sampling was noted as a limitation that may have biased the results toward those already motivated to seek help.\u003csup\u003e122\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e3. Zingela et al. (2022), South Africa\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe researchers developed and piloted a Psychological Preparedness Training (PPT) program for 761 healthcare workers. The intervention involved group sessions (60–90 minutes) utilizing cognitive-behavioral principles to achieve goals of safety, calm, efficacy, and connectedness. The study reported statistically significant positive changes. Post-training data indicated a marked reduction in anxiety and an improvement in workers' perceptions of the outbreak. Participants reported a significantly increased ability to control their emotional reactions and support colleagues, shifting their mindset from helplessness to agency. The primary challenge was \"worker weariness\" and severe time constraints. The demanding clinical environment meant that despite the program's benefits, staff struggled to find the time and energy to attend sessions.\u003csup\u003e123\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e4. Waterman et al. (2018), Sierra Leone\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThis study at 157 Ebola Treatment Centre workers, utilized a peer-delivered cognitive behavioral therapy (CBT) model. It progressed through three phases: screening/psychological first aid, psycho-educational workshops, and small group CBT sessions led by trained peers. The intervention was highly effective, with results showing significant reductions in clinical symptoms across the board. There were statistically significant decreases in scores for anxiety (GAD-7) and depression (PHQ-9) following the intervention phase. Implementation was complicated by Sierra Leone's limited mental health infrastructure. The study noted significant cultural barriers, including profound stigma around mental illness and a widespread reliance on traditional healers, which often conflicted with the clinical CBT approach.\u003csup\u003e124\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e5. Kacem et al. (2020), Tunisia\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThis study introduced a music therapy intervention for 34 operating room staff in urology and maxillofacial departments. Participants were exposed to three 30-minute music sessions daily over a one-month period. The intervention resulted in a statistically significant decrease in occupational stress and burnout. Specifically, Perceived Stress Scale (PSS-10) scores dropped significantly (p = 0.006), and the emotional exhaustion subscale of the Maslach Burnout Inventory also showed a significant decrease (p = 0.004). The major limitation was the small sample size (n = 34) and the lack of a control group. The specificity of the operating room setting also raised questions about the feasibility of replicating this intervention in noisier or more chaotic hospital wards.\u003csup\u003e125\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e6. Maingi et al. (2022), Kenya\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eIn a study of 356 healthcare workers, the \"intervention\" was identified as the adoption of individual mitigation strategies in the absence of a formal institutional program. The study assessed adherence to Ministry of Health guidelines for mental well-being. The study found that 80.1% of workers utilized a healthy diet and 43.3% engaged in physical activity to mitigate mental health effects. Despite these individual efforts, the prevalence of mental health problems remained high at 44%, with 14.6% of workers reporting depression. The critical barrier was the lack of structural support. The study concluded that Ministry of Health measures were inadequate, effectively abandoning HCWs to manage their own mental health (self-care) without sufficient policy-level or organizational backing.\u003csup\u003e126\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e7. Abdelaziz et al. (2020), Egypt\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThis quasi-experimental study involved 36 novice psychiatric nurses. They underwent a 7-week Assertiveness Training Program comprising two sessions per week (90–120 minutes each), utilizing lectures, role-play, and homework. The training was effective, yielding statistically significant improvements between pre- and post-test scores. Participants showed significant gains in assertiveness skills, psychological well-being, and work engagement. The study was limited by its small sample size (n = 36) and the absence of a control group, which limits the ability to generalize the findings or rule out external factors influencing the improvement.\u003csup\u003e127\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e8. Ledikwe et al. (2017), Botswana\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe study evaluated the National Workplace Wellness Program (WWP) across 27 health districts. The program was comprehensive on paper, including health screening, psychosocial care, and therapeutic recreation. Implementation fidelity varied significantly. While physical health screenings were frequently implemented, psychosocial support services were utilized much less. The study did not provide statistical outcomes on mental health improvement but rather focused on implementation success. Implementation was hindered by competing priorities, where patient care demands crowded out wellness activities. Additionally, there was a lack of technical expertise among staff to deliver occupational health services, and confidentiality concerns significantly reduced staff willingness to access the available support.\u003csup\u003e128\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e9. Moyo et al. (2023), Zimbabwe\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThis qualitative study (n = 20) developed a psychosocial support model based on Donabedian’s framework (Structure, Process, Outcome). The model aimed to provide a structured reference guide for supporting healthcare workers during pandemics. The model was validated by a panel of experts who confirmed its relevance and necessity. It provided a clear theoretical pathway for institutions to move from ad-hoc support to structured care. The study highlighted that the model was born out of necessity due to severe systemic failures: a shortage of human and material resources, ineffective communication, and the complete absence of existing institutional support structures for staff well-being.\u003csup\u003e129\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e10. Abdelghaffar et al. (2021), Tunisia\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThis case study described the rapid implementation of a Psychological Support Unit (PSU) at a hospital, which included a free telephone helpline and specific management activities for both patients and staff. While specific utilization statistics were not reported, the unit was qualitatively described as a critical resource that facilitated the management of staff anxiety and stress during the height of the pandemic. The success of the unit was challenged by logistical barriers, specifically movement restrictions during lockdown that made physical access difficult. Furthermore, a pervasive fear of contamination and the stigma associated with seeking psychological help discouraged some staff from utilizing the service.\u003csup\u003e130\u003c/sup\u003e\u003c/p\u003e\n\u003c/div\u003e\n"},{"header":"Discussion and conclusion","content":"\u003cp\u003eAfrican healthcare workers (HCWs) bear an alarmingly high burden of mental health problems. Prevalence estimates from recent studies span wide ranges for example, rates of depression (2–76%), anxiety (5–96%), and PTSD (12–78%) have been reported across sub-Saharan samples.\u003csup\u003e131\u003c/sup\u003e Similarly, burnout and related stress are pervasive. A systematic review found that physicians and nurses in Africa often report very high burnout rates (e.g. up to 81% in one South African physician sample\u003csup\u003e132\u003c/sup\u003e, and studies of nursing staff have documented 30–50% or higher proportions with high emotional exhaustion or overall burnout\u003csup\u003e133\u003c/sup\u003e. Substance use is also emerging as a concern: for instance, a survey of Kenyan HCWs found that about half had ever used alcohol, tobacco or other drugs, and a substantial minority screened positive for risky use\u003csup\u003e114\u003c/sup\u003e. In sum, multiple studies document heavy burdens of burnout, depression, anxiety, work-related stress, psychological distress and related conditions among HCWs in Africa\u003csup\u003e131,133\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003ePrevalence rates of mental health challenges differ across countries and regions (often higher in South African and West African samples than in East or North Africa in the available literature) and by profession (nurses frequently report equal or higher burnout than physicians. Female HCWs and early-career staff tend to exhibit higher levels of distress in many studies. Similarly national reviews have noted that women and younger health workers generally have greater risk of depressive or anxiety symptoms\u003csup\u003e131\u003c/sup\u003e. This heterogeneity likely reflects contextual factors (health system resources, epidemics) and differing job roles (e.g. front-line nurses vs. support staff). Such variation indicates that interventions may need to be tailored by region and workforce cadre.\u003c/p\u003e\u003cp\u003eOnly a few intervention studies were identified in this study which were brief and mostly individual level. Similarly, one recent scoping review of African studies found just 11 programs targeting HCW mental health\u003csup\u003e134\u003c/sup\u003e, most focused on individual-level strategies: e-learning or psychoeducation modules, brief mindfulness or relaxation training, resilience-building workshops, cognitive-behavioral group sessions, even music therapy. These interventions often showed short-term promise. However, implementation was challenging: attrition was high (many HCWs dropped out due to shift schedules or fatigue), and deep-seated cultural and structural barriers like stigma around mental illness, understaffing, lack of managerial support thus limited uptake\u003csup\u003e135\u003c/sup\u003e. For our review, in some contexts (e.g. Sierra Leone, Kenya) stigma and sparse resources meant that health workers largely had to rely on self-care, with minimal systemic support, and reported persistent stress and depression despite guidelines. In sum, the evidence on interventions is preliminary and patchy: few randomized trials, mostly small samples, and persistent obstacles to implementation.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResearch gaps\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eMajor gaps were evident. Virtually no studies have used longitudinal or experimental designs to track long-term outcomes; follow-up was typically immediate or within a few weeks. Francophone and Lusophone countries are greatly under-studied, as noted by the predominance of South African and English-language reports. Almost no work has addressed system-level or policy interventions (for example, changes in work environment, regulatory or insurance policies) to reduce HCW stress. Implementation research is badly needed for example, studies of program fidelity, cost-effectiveness, and scalability in low resource settings. Likewise, integration of HCW mental health into national health policies is largely absent. In short, the literature lacks multi-level approaches and rigorous designs; it needs longitudinal follow-up and attention to health-system and policy contexts\u003csup\u003e131,136\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003ePolicy and practice implications\u003c/strong\u003e: These findings underscore urgent needs for action. National governments and health ministries should include HCW mental health in their policies and strategic plans. WHO’s guidelines on mental health at work advocate interventions at multiple levels (organizational, managerial and individual)\u003csup\u003e136\u003c/sup\u003e, and countries should adapt these to their context. For example, institutionalize workplace wellness programs such as peer-support groups, stress-management training and accessible counseling within hospitals and clinics. National strategies (as in a mental health action plan) should designate resources for HCW wellbeing and set standards for safe workloads. Moreover, support for vulnerable groups must be prioritized: early-career clinicians, female staff and nurses were repeatedly identified as high-risk groups in African studies. Tailored mentorship, flexible scheduling, and career development support for these groups could help mitigate burnout. In summary, a multi-pronged approach combining policy commitments with on-the-ground programs is needed to protect the continent’s health workforce and sustain quality care.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHCW\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealth Care Workers\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCBT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCognitive Behavioral Therapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePTSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePost Traumatic Stress Disorder\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePPE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePersonal protective Equipment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePsychological Support Unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWWP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorkplace Wellness Programme\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent of publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during this study are available from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKVN conceptualized the study and developed the review protocol. PMO conducted the database searches and citation tracking. DO and EM independently screened the titles and abstracts, while JLW and MM performed full text review. KVN, JK, MM, JO, MRN, SMN and SS extracted data using the standardized form, and PMO analyzed the findings. PMO drafted the results section while KVN, MM and SS contributed to writing the background and methods. JK and JLW prepared the discussion and conclusions. All authors critically reviewed the manuscript, provided input and approved the final version for submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely appreciate Dr. Mwesiga Kiiza Emmanuel for his thorough review of the manuscript prior to submission. His constructive feedback and guidance strengthened the quality of this work.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSaragih ID, Tonapa SI, Saragih IS, Advani S, Batubara SO, Suarilah I, et al. Global prevalence of mental health problems among healthcare workers during the Covid-19 pandemic: A systematic review and meta-analysis. Int J Nurs Stud. 2021;121:104002\u0026ndash;104002.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShanafelt TD, Boone S, Tan L, Dyrbye LN, Sotile W, Satele D, et al. Burnout and satisfaction with work-life balance among US physicians relative to the general US population. Arch Intern Med. 2012;172(18):1377\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaslach C, Leiter MP. Understanding the burnout experience: recent research and its implications for psychiatry. 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[cited 2025 Nov 28]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789240053052\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/9789240053052\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mental health, Healthcare professionals, Africa, Anxiety, Depression, Burn out., Stress","lastPublishedDoi":"10.21203/rs.3.rs-8903391/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8903391/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMental health challenges among healthcare professionals have become a global public health concern, with Africa facing unique stressors such as under-resourced health systems, high patient-to-provider ratios, recurrent infectious disease outbreaks, and workplace violence. These pressures contribute to high rates of burnout, anxiety, depression, and trauma, which compromise personal wellbeing, patient outcomes, and workforce retention. Despite emerging interventions, including peer support, counseling, and digital platforms, their scope and effectiveness remain underexplored in African contexts.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003e We conducted a scoping review following the Joanna Briggs Institute (JBI) framework and reported according to PRISMA-ScR guidelines. A systematic search of SCOPUS, Web of Science, and PubMed identified studies published between 2000 and 2025. Eligible studies included peer-reviewed articles addressing mental health challenges or interventions among healthcare professionals in Africa. Data extraction captured study characteristics, cadres involved, mental health outcomes, interventions, and implementation barriers. Quantitative findings were summarized descriptively, while qualitative data were synthesized thematically.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFrom 6,567 records, 119 studies met inclusion criteria, spanning 20 African countries. Most were cross-sectional (n\u0026thinsp;=\u0026thinsp;105), with South Africa contributing the largest number (n\u0026thinsp;=\u0026thinsp;19). Burnout was the most frequently reported challenge, with prevalence ranging from 20% in Ghana to 95% among South African medical interns. Anxiety rates peaked during the COVID-19 pandemic, reaching 90.5% in Egypt and 59.9% in Kenya. Depression prevalence ranged from 13.6% in Ethiopia to 94% of Egyptian healthcare workers. Nurses and midwives consistently reported higher burdens than physicians. Stress, PTSD, compassion fatigue, and workplace violence were recurrently reported particularly in conflict-affected or pandemic settings. Structural drivers included excessive workloads, poor remuneration, stigma, and inadequate protective equipment. Interventions such as psychosocial support groups, stress management workshops, and digital mental health platforms showed promise but lacked rigorous evaluation.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eHealthcare professionals in Africa face substantial mental health challenges, exacerbated by systemic resource constraints and pandemic-related stressors. While innovative interventions exist, evidence on their effectiveness and sustainability remains limited. Strengthening culturally appropriate support systems and occupational health policies is essential to protect workforce wellbeing, enhance resilience, and improve health system performance across the continent.\u003c/p\u003e\u003cp\u003e\u003cb\u003eClinical trial number:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNot applicable\u003c/p\u003e","manuscriptTitle":"Exploring mental health challenges and interventions for healthcare professionals in Africa; A scoping Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-19 16:23:56","doi":"10.21203/rs.3.rs-8903391/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-14T21:39:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"211267574592974195630397880178994100198","date":"2026-03-26T18:04:18+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-17T06:58:47+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-23T07:21:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-21T13:45:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-21T13:42:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2026-02-17T17:29:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"334a79c7-22cd-495d-a699-717483b5ecc0","owner":[],"postedDate":"March 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-19T16:23:56+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-19 16:23:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8903391","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8903391","identity":"rs-8903391","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}