Abstract
Background
During the Sudan war, healthcare workers have encountered extraordinary challenges, including physical assaults and the immense strain of delivering care with critically limited resources. These conditions are likely to intensify burnout among healthcare professionals. This study aimed to determine the prevalence of burnout among Sudanese healthcare workers and investigate the coping mechanisms they employ during the ongoing conflict.
Methods
A cross-sectional study was conducted among Sudanese healthcare workers using the standardized Maslach Burnout Inventory – Human Services Survey (MBI-HSS). Multivariable linear regression analysis was conducted to identify independent predictors of burnout domains. A significance level of p < 0.05 was considered for all statistical tests.
Results
High emotional exhaustion was reported by 13.7% of participants, while 56.5% experienced high depersonalization, and only 4.4% reported low levels of personal accomplishment. The leading coping mechanism was talking with friends and family, adopted by 28.8% of participants, while 15.5% turned to spiritual or religious practices.
Conclusion
Sudanese healthcare workers demonstrate high levels of burnout, particularly in the depersonalization domain, with talking to friends and family being the most commonly used coping mechanism. Future research is needed to explore the unique stressors faced by healthcare workers in conflict-affected settings like ours.
Keywords: Burnout, MBI-HSS, Healthcare workers, Coping mechanisms, Sudan, War
Background
On April 15th, 2023, violent clashes erupted between the Sudanese Armed Forces (SAF) and the paramilitary Rapid Support Forces (RSF), plunging Sudan into a devastating conflict. This war has resulted in the displacement of over 12.5 million people, including internally displaced persons (IDPs), asylum seekers, and refugees [1]. The health infrastructure has been severely crippled, with the World Health Organization (WHO) reporting that 70% of public and private healthcare facilities in war-affected states were forced to close by the end of 2023 [2]. The violence has also directly targeted medical personnel, with more than 200 documented violations against healthcare workers, including the killing of 38 staff members. Incidents of kidnapping, assault, and intimidation have created an atmosphere of fear, leading to a critical shortage of healthcare workers as many have fled or refused to work due to safety concerns [3].
Living under wartime conditions, characterized by constant risk, uncertainty, and extreme suffering, exacerbates the loss of personal and professional resources. Such conditions are known to accelerate burnout processes in occupational settings and have long-term detrimental effects on mental health [4]. Burnout, a syndrome resulting from unmanaged chronic workplace stress, is characterized by three key dimensions: feelings of energy depletion or exhaustion, increased mental distance from one’s job (often manifested as negativism or cynicism), and reduced professional efficacy [5]. Among healthcare workers, burnout not only undermines individual well-being but also compromises the functioning of the entire healthcare system. It is associated with an increased risk of medical errors, reduced patient safety, and lower patient satisfaction, as well as higher rates of complaints from patients and their families [6].
Even prior to the current conflict, studies had already highlighted significant levels of burnout among Sudanese healthcare professionals. One study among resident physicians reported that 70.7% experienced high emotional exhaustion, while 44.2% showed high levels of depersonalization [7]. Likewise, during the COVID-19 pandemic, 45.7% of healthcare workers were found to be experiencing burnout [8]. These findings underscore the pre-existing vulnerabilities and psychological strain within Sudan’s healthcare workforce. Since the outbreak of the war, healthcare workers in Sudan have faced unprecedented challenges, including physical attacks, accusations of partisanship, and the overwhelming burden of providing care with severely limited resources in the few remaining functional hospitals [9]. These conditions are likely to exacerbate burnout and further deteriorate the mental health of healthcare workers, creating a vicious cycle that undermines both their well-being and the quality of care they can provide.
Studies from conflict-affected low- and middle-income countries have reported high levels of burnout among healthcare workers. For instance, a study among Palestinian health professionals during ongoing political violence found a burnout prevalence of 72.9%, with 44.2% experiencing emotional exhaustion and 9.8% reporting depersonalization [10]. However, no studies to date have assessed burnout among healthcare workers in Sudan during the current war. Therefore, this study aims to assess the prevalence of burnout among Sudanese healthcare workers and explore the coping mechanisms they employ to navigate these extraordinary circumstances.
Methods
Study design
This cross-sectional study was conducted in November 2024. It included healthcare workers from various healthcare facilities in the safest states of Sudan. The findings and methodology of this study were meticulously reported in the manuscript in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines.
Study population
The study included healthcare professionals, defined as individuals directly involved in patient care and healthcare delivery, such as physicians, nurses, technicians, pharmacists, and allied health staff, aged 18 years or older. Eligible participants had been employed at their current facility for at least one month to ensure they had adequate exposure to the work environment and stressors necessary for a meaningful assessment of burnout. Participation required written informed consent and completion of the study questionnaire. Exclusions included incomplete or inconsistent responses, those on long-term leave during data collection, and individuals previously diagnosed with mental health conditions such as anxiety or depression, as well as those receiving medications or therapy for any mental health issues.
Sampling
We estimated the sample size using the Cochrane formula, given the unavailability of official population records of healthcare workers in Sudan. Assuming a population proportion of 50%, a margin of error of 5%, and a confidence interval of 95%, the minimum sample size required was calculated to be 385 participants. Ultimately, 563 healthcare workers participated in the study.
Convenience sampling was employed due to the challenges in accessing official healthcare workers records. Data collection was conducted through a combination of face-to-face interviews and an online survey administered via Google Forms. Trained medical students carried out the interviews in a confidential setting to promote honest and accurate responses while safeguarding participants’ privacy. They received prior instruction to ensure ethical conduct, accuracy, and consistency throughout the process. The online survey was shared among healthcare workers using widely used social media platforms in Sudan, such as WhatsApp, Telegram, and Facebook. Participation was entirely voluntary, anonymous, and without any form of compensation.
Study instrument
The study employed a comprehensive tool comprising two sections, 13 questions in the socio-demographic section, covering age, sex, marital status, residence, displacement status, job roles, years of experience, exposure to conflict, living situation, access to basic necessities, access to mental health support, type of healthcare facility, and coping mechanisms. The second section of the questionnaire utilized the Maslach Burnout Inventory– Human Services Survey (MBI-HSS), which is the most widely accepted and commonly used tool for assessing burnout. It has been previously used in published research conducted in Sudan [7]. The MBI-HSS consists of 22 items divided into three domains: emotional exhaustion (6 items), depersonalization (8 items), and personal accomplishment (8 items) [11]. Each item was scored on a 7-point frequency scale (0 = Never to 6 = Every day). Emotional exhaustion scores were categorized as low (≤ 16), moderate [17–26], and high (≥ 27). Depersonalization scores were classified as low (≤ 6), moderate [7–12], and high (≥ 13). Personal accomplishment scores were categorized inversely, with low (≥ 39), moderate [32–38], and high (≤ 31) indicating higher levels of burnout. This study relied on the primary definition of burnout, as cited by previous studies [12, 13], which considers individuals with either high emotional exhaustion (≥ 27) or high depersonalization (≥ 13) as experiencing burnout. The MBI-HSS was administered in English, as it is the primary language used in Sudanese hospitals and among healthcare professionals [14].
Statistical analysis
Data were analyzed using IBM SPSS Statistics, version 27. Descriptive statistics—means, standard deviations, frequencies, and percentages—were used to summarize demographic characteristics, burnout scores, and coping strategies. Multivariable linear regression analysis was conducted to identify independent predictors of burnout domains. All demographic and contextual variables identified a priori from existing literature (e.g., age, sex, job role, exposure to conflict, access to necessities) were simultaneously entered into the model. No variable selection procedures (e.g., stepwise regression) were applied. Significance was defined at p < 0.05 for all tests.
Result
Demographic factors
The study sample consisted of 563 participants, with a mean age of 27.9 years (SD = 6.3). The majority of the participants were female (61.1%), and most were single (77.8%). In terms of work experience, 43.5% had less than 1 year of experience and 4.1% had more than 15 years of experience. Regarding exposure to conflict situations, 19.5% reported no exposure, while 3.2% had extreme exposure. The majority of participants (70%) were living with family during the conflict with 16.2% lived alone. Access to basic necessities varied, with 23.1% having fully sufficient resources and 5.9% having extremely insufficient resources. 28.4% had access to psychological services, while 71.6% did not. In terms of healthcare facilities, most participants were affiliated with public hospitals (72.8%) while 21.2% worked in private hospitals. Finally, job roles varied, with physicians making up 64.3% of the participants, followed by technicians (10.5%) and pharmacists (10.1%) (Table 1).
Table 1.
Socio-demographic characteristics
| Variable | Overall (N = 563) | Variable | Overall (N = 563) |
|---|---|---|---|
| Age | Years of Work Experience | ||
| Mean (SD) | 27.9 (6.3) | Less than 1 year | 245 (43.5%) |
| Sex | 1–5 years | 218 (38.7%) | |
| Female | 344 (61.1%) | 6–10 years | 58 (10.3%) |
| Male | 219 (38.9%) | 11–15 years | 19 (3.4%) |
| Marital Status | More than 15 years | 23 (4.1%) | |
| Single | 438 (77.8%) | Exposure to Conflict Situations | |
| Married | 116 (20.6%) | None | 110 (19.5%) |
| Divorced | 6 (1.1%) | Minimal | 148 (26.3%) |
| Widowed | 3 (0.5%) | Moderate | 193 (34.3%) |
| Residence | High | 94 (16.7%) | |
| Blue Nile State | 3 (0.5%) | Extreme | 18 (3.2%) |
| Darfour Region | 1 (0.2%) | Living Situation during Conflict | |
| East Kordofan | 1 (0.2%) | Alone | 91 (16.2%) |
| Gadarif | 143 (25.4%) | In shared accommodation with colleagues | 78 (13.9%) |
| Gezira | 25 (4.4%) | With family | 394 (70.0%) |
| Kassala | 49 (8.7%) | Access to Basic Necessities (Medical, Food, Supplies) | |
| Khartoum | 36 (6.4%) | Fully sufficient | 130 (23.1%) |
| North Kordofan | 5 (0.9%) | Mostly sufficient | 199 (35.3%) |
| Northern State | 71 (12.6%) | Insufficient but manageable | 201 (35.7%) |
| Red Sea State | 58 (10.3%) | Extremely insufficient | 33 (5.9%) |
| River Nile State | 82 (14.6%) | Access to Mental Health Support | |
| Sennar State | 21 (3.7%) | Yes (Psychologist, counselor, etc.) | 160 (28.4%) |
| South Kordofan | 1 (0.2%) | No | 403 (71.6%) |
| White Nile State | 67 (11.9%) | Type of Healthcare Facility | |
| Internally displaced persons (IDPs) | Public Hospital | 409 (72.8%) | |
| Yes | 362 (64.3%) | Private Hospital | 119 (21.2%) |
| No | 201 (35.7%) | Community Pharmacy | 11 (2.0%) |
| Job Role | Private Pharmacy | 6 (1.1%) | |
| Physician | 362 (64.3%) | Non-governmental organization (NGO)/Relief Organization | 19 (3.4%) |
| Technician | 59 (10.5%) | ||
| Pharmacist | 57 (10.1%) | ||
| Nurse | 37 (6.6%) | ||
| Medical laboratory | 23 (4.1%) | ||
| Administrative staff | 14 (2.5%) | ||
| Dentist | 11 (2.0%) |
Burnout
The burnout domains revealed varied experiences across healthcare workers. Emotional exhaustion was reported by 68.0% of participants as low, 18.3% as moderate, and 13.7% as high. Depersonalization had a higher percentage, with 56.5% of participants experiencing high depersonalization. Personal accomplishment was high for 90.9% of participants (Table 2).
Table 2.
Burnout domains (MBI-HSS)
| Burnout Domain | Mean (SD) | Range | Low | Moderate | High |
|---|---|---|---|---|---|
| Emotional Exhaustion | 12.5 (10.4) | 0.0–36.0 | 383 (68.0%) | 103 (18.3%) | 77 (13.7%) |
| Depersonalization | 15.2 (11.5) | 0.0–48.0 | 157 (27.9%) | 88 (15.6%) | 318 (56.5%) |
| Personal Accomplishment | 11.7 (11.2) | 0.0–48.0 | 25 (4.4%) | 26 (4.6%) | 512 (90.9%) |
Regression analysis revealed several significant predictors across the three burnout dimensions. For emotional exhaustion, individuals with 1–5 years of work experience reported significantly higher scores compared to those with less than 1 year (β = 2.28, p = 0.026). Living in shared accommodation with colleagues during the conflict (β = 4.76, p = 0.003) and having insufficient but manageable access to basic necessities (β = 4.42, p < 0.001) were also associated with higher emotional exhaustion. Additionally, participants with extreme exposure to conflict had significantly elevated emotional exhaustion scores (β = 5.32, p = 0.043). Higher depersonalization scores were observed among participants with 1–5 years of work experience compared to those with less than 1 year (β = 2.35, p = 0.042), as well as among those with extreme conflict exposure (β = 8.26, p = 0.005) and insufficient but manageable access to basic necessities (β = 2.78, p = 0.043). Conversely, lower depersonalization scores were reported by those who had no access to mental health support (β = − 2.16, p = 0.048). For personal accomplishment, fewer predictors reached significance; however, participants reporting insufficient but manageable basic necessities had higher scores (β = 3.91, p = 0.004), and those with mostly sufficient access also showed slightly elevated scores (β = 2.62, p = 0.047). Other sociodemographic variables such as age, sex, marital status, and job role did not significantly predict burnout outcomes across the three domains (Table 3).
Table 3.
Adjusted associations between demographic/contextual factors and MBI subscale scores (Multivariable linear regression)
| Predictor | Emotional Exhaustion (β [95% CI], p) |
Depersonalization (β [95% CI], p) |
Personal Accomplishment (β [95% CI], p) |
|---|---|---|---|
| IDPs (Ref: No) | |||
| Yes | 1.41 [−0.40, 3.23], 0.127 | –0.93 [–2.97, 1.11], 0.369 | –0.82 [–2.83, 1.18], 0.421 |
| Age | 0.07 [–0.15, 0.28], 0.532 | –0.05 [–0.29, 0.20], 0.711 | –0.03 [–0.27, 0.20], 0.780 |
| Sex (Ref: Female) | |||
| Male | –0.83 [–2.63, 0.97], 0.367 | 1.09 [–0.93, 3.12], 0.290 | –0.91 [–2.90, 1.09], 0.374 |
| Marital Status (Ref: Single) | |||
| Married | –0.21 [–2.64, 2.23], 0.869 | –1.17 [–3.91, 1.57], 0.402 | 0.19 [–2.51, 2.89], 0.889 |
| Divorced | 6.35 [–2.00, 14.69], 0.136 | 5.43 [–3.95, 14.81], 0.256 | 2.89 [–6.35, 12.14], 0.539 |
| Widowed | –2.15 [–14.34, 10.04], 0.729 | –6.54 [–20.24, 7.17], 0.349 | –5.46 [–18.96, 8.05], 0.428 |
| Job Role (Ref: Physician) | |||
| Technician | –3.40 [–6.21, − 0.60], 0.017 | –0.76 [–3.91, 2.39], 0.637 | –1.84 [–4.94, 1.27], 0.246 |
| Pharmacist | 2.31 [–0.64, 5.26], 0.124 | 2.99 [–0.33, 6.30], 0.077 | 1.90 [–1.36, 5.17], 0.253 |
| Nurse | –0.99 [–4.56, 2.58], 0.586 | 3.68 [–0.33, 7.69], 0.072 | 1.65 [–2.30, 5.60], 0.413 |
| Lab Staff | –3.40 [–7.73, 0.93], 0.124 | 2.15 [–2.71, 7.02], 0.385 | –1.62 [–6.41, 3.18], 0.508 |
| Admin Staff | –0.96 [–6.40, 4.47], 0.727 | 5.64 [–0.47, 11.74], 0.070 | 4.15 [–1.87, 10.17], 0.176 |
| Dentist | 0.66 [–5.43, 6.75], 0.832 | –2.54 [–9.39, 4.30], 0.466 | 0.63 [–6.11, 7.38], 0.854 |
| Work Experience (Ref: <1 year) | |||
| 1–5 years | 2.28 [0.27, 4.29], 0.026 | 2.35 [0.09, 4.61], 0.042 | 0.41 [–1.82, 2.63], 0.719 |
| 6–10 years | –0.06 [–3.46, 3.33], 0.971 | 1.22 [–2.60, 5.03], 0.532 | 0.98 [–2.78, 4.74], 0.609 |
| 11–15 years | 0.82 [–4.75, 6.39], 0.772 | –2.22 [–8.48, 4.04], 0.486 | –3.21 [–9.38, 2.96], 0.308 |
| > 15 years | –2.21 [–8.00, 3.57], 0.453 | –0.41 [–6.92, 6.09], 0.901 | 0.27 [–6.14, 6.69], 0.933 |
| Conflict Exposure (Ref: None) | |||
| Minimal | 1.43 [–1.11, 3.98], 0.269 | 1.40 [–1.46, 4.26], 0.338 | 0.72 [–2.10, 3.54], 0.615 |
| Moderate | 1.50 [–0.99, 3.99], 0.236 | 1.78 [–1.02, 4.57], 0.213 | 1.79 [–0.97, 4.54], 0.203 |
| High | 2.13 [–0.86, 5.11], 0.162 | 2.04 [–1.32, 5.39], 0.233 | 2.68 [–0.62, 5.99], 0.111 |
| Extreme | 5.32 [0.16, 10.49], 0.043 | 8.26 [2.46, 14.06], 0.005 | 4.67 [–1.05, 10.39], 0.109 |
| Living Situation (Ref: Alone) | |||
| Shared accommodation with colleagues | 4.76 [1.68, 7.85], 0.003 | 3.51 [0.04, 6.97], 0.047 | 3.06 [–0.35, 6.48], 0.079 |
| With family | 0.69 [–1.69, 3.06], 0.569 | 1.96 [–0.71, 4.63], 0.150 | 2.39 [–0.24, 5.02], 0.075 |
| Access to Basic Necessities (Ref: Fully sufficient) | |||
| Mostly sufficient | 3.12 [0.79, 5.46], 0.009 | 1.82 [–0.80, 4.44], 0.173 | 2.62 [0.03, 5.20], 0.047 |
| Insufficient (manageable) | 4.42 [2.03, 6.82], < 0.001 | 2.78 [0.09, 5.48], 0.043 | 3.91 [1.25, 6.56], 0.004 |
| Extremely insufficient | 2.70 [–1.22, 6.63], 0.176 | 3.77 [–0.64, 8.18], 0.093 | 3.70 [–0.64, 8.05], 0.095 |
| Mental Health Support (Ref: Yes) | |||
| No | 0.46 [–1.44, 2.37], 0.633 | –2.16 [–4.30, − 0.02], 0.048 | –0.35 [–2.46, 1.76], 0.746 |
Note: Bold values indicate statistically significant results (p < 0.05)
Coping mechanisms
The coping mechanisms employed by participants in response to stress and challenges are diverse, as illustrated in Fig. 1. The most commonly used coping strategy is talking to friends or family, reported by 28.8% of participants. Other prominent methods include spiritual or religious practices (15.5%), which help individuals navigate difficult situations, and reduced medical effectiveness (14.8%), highlighting a coping method linked to compromised health care delivery. Professional mental health support is used by 12.3% of participants, while physical activity or exercise is another coping mechanism, favored by 12.0%.
Fig. 1.
Coping mechanisms among participants
Discussion
Burnout among healthcare workers can impair clinical decision-making, hinder effective communication with patients and colleagues, and reduce their capacity to manage work-related stress [15]. This study aimed to assess the prevalence of burnout among Sudanese healthcare workers and explore the coping strategies they use amid the ongoing conflict.
The ongoing Sudanese military conflict has severely impacted healthcare services due to infrastructure destruction and a critical shortage of health workers [16]. The WHO has verified 88 attacks on healthcare resulting in 55 deaths and 104 injuries [17]. Incidents of killing, kidnapping, and assault have worsened the shortage of healthcare staff [3]. This is further exacerbated by shortage of medications and equipment [18, 19] and outbreaks of diseases like cholera and dengue [20, 21]. These factors likely contribute to the high levels of burnout among healthcare workers in Sudan. It has been suggested that there is an interaction between burnout and secondary traumatic stress in the Middle East [22].
Depersonalization was the most affected in our study, followed by emotional exhaustion and, finally, personal accomplishment, with only 4.4% reporting low levels of personal accomplishment. This aligns with findings from other countries [23, 24]. Notably, the proportion of participants experiencing depersonalization in our study was higher than that reported among healthcare workers in Gaza during their war [25]. These findings suggest that physicians in conflict-affected settings have a strong sense of self accomplishment, however factors like the workload, staff shortage, and working environment cause emotional exhaustion and depersonalization leading to high levels of burnout. Depersonalization and emotional exhaustion are considered the core components of burnout, whereas reduced personal accomplishment may act as either a precursor or an outcome of the syndrome [26]. The particularly high levels of depersonalization observed may indicate a psychological coping mechanism, whereby healthcare workers detach emotionally from their patients as a way to shield themselves from chronic stress [26]. In settings like Sudan, where prolonged trauma exposure and critical resource limitations are common, this emotional distancing can serve as a necessary—though potentially harmful—adaptation to survive in a highly strained and unsupportive healthcare environment.
Nearly two-thirds of the participants in this study were internally displaced. Sudan has the largest displacement crisis, more than 11 million internally displaced people [27]. There was no significant association between displacement status and burnout domains in this study. Less than one-fifth of participants had more than five years of experience, which may reflect the characteristics of healthcare practitioners remaining in Sudan during the war. Senior physicians are more likely to find jobs abroad to support their families, while younger physicians, who lack training, are more likely to stay. This pattern may also reflect differences in social media use and availability, as younger physicians are more likely to complete online questionnaires. These plausible explanations require further investigations to obtain robust evidence. Burnout levels varied by years of experience, with early-career professionals (1–5 years) showing significantly higher emotional exhaustion and depersonalization. This finding is consistent with previous studies that have reported greater burnout among those with fewer years of experience [28, 29].
Nurses were more likely to report depersonalization compared to physicians; however, this difference was not statistically significant. A study conducted among healthcare workers during the COVID-19 pandemic found that Sudanese physicians were more likely to report burnout compared to nurses. A plausible explanation for this finding is the heavier workload and frontline role of physicians during COVID-19. This contrasts with findings from other studies that report higher levels of burnout among nurses [30, 31]. Some studies, however, report no significant difference between the two groups [32]. Technicians were significantly less likely to experience emotional exhaustion compared to physicians, a difference that may also be attributed to workload.
Less than a quarter of participants reported having fully sufficient access to basic necessities. This is consistent with the general situation in war-torn Sudan, where one in every three people is at risk of food insecurity [33]. Insufficient but manageable access to basic necessities was significantly associated with high levels of emotional exhaustion and depersonalization. A probable explanation is that the affected access domain is financial, which can be managed by working longer hours in multiple hospitals. This year, food prices have increased by more than 120% [34].
More than two-thirds of participants reported a lack of access to psychological support. The expertise of mental health and psychological support groups is fragmented, and there is no shared platform to coordinate priority actions or strengthen responses to mental health needs [35].
Participants with extreme conflict exposure showed significantly higher levels of emotional exhaustion and depersonalization. Similarly, a study conducted among academic staff in Ukraine found that prolonged stress related to the ongoing war led to notable increases in depersonalization [36]. Despite the severe impact of the war, many conflict-related variables in our study were not significantly associated with burnout in our adjusted models. One possible explanation is that the conflict affected nearly all healthcare workers in some way, creating a uniformly high baseline of stress and reducing detectable differences across exposure levels. Additionally, the effects of the war may have manifested more through indirect stressors, such as economic hardship, longer working hours, and lack of basic resources, which were better captured by other variables like access to necessities and living arrangements.
The most commonly reported coping mechanisms were talking to friends and families as well as spiritual or religious practices. Previous studies have found that social relationships may help in managing the effects of burnout [37, 38]. Additionally, religious practices are regarded as protective and beneficial in managing burnout [39, 40]. A previous study conducted among displaced individuals in shelters in Port Sudan highlighted the significant role of religious and spiritual practices—such as prayer, reading the Quran, and trusting in God—in coping with distress. The study also emphasized the importance of social and emotional support, noting that individuals often leaned on family ties and built supportive social relationships to manage their circumstances [41]. These coping strategies may reflect the strong communal and religious values embedded in Sudanese culture, where individuals often rely on close-knit family networks and faith during times of crisis. In the context of limited access to formal mental health services during the conflict, these culturally rooted mechanisms may serve as essential substitutes, helping individuals manage stress and emotional exhaustion.
This study offers valuable insights into burnout among healthcare providers in a conflict-affected country. A notable strength is the inclusion of participants from various professional roles within the healthcare system. However, the interpretation of the findings should consider several limitations. The cross-sectional design restricts the ability to draw causal inferences. Moreover, the use of a non-probability sampling technique may limit the generalizability of the results. Participants’ responses may have been influenced by recall bias and the tendency to provide socially desirable answers. Additionally, the disproportionate distribution of participants across healthcare roles—with physicians comprising approximately two-thirds of the sample—may affect the representativeness and limit the generalizability of the findings to the broader population of healthcare workers.
Conclusion
Healthcare workers in Sudan exhibit a high level of burnout mainly in the depersonalization domain. However, the most commonly used coping mechanisms include talking to friends and family, as well as engaging in spiritual or religious practices. There is a need for context-specific research into the unique stressors faced by healthcare workers in conflict-affected settings like ours. In addition, healthcare workers should receive targeted training on evidence-based strategies to manage and prevent burnout.
Acknowledgements
Not applicable.
Abbreviations
- MBI-HSS
Maslach Burnout Inventory– Human Services Survey
- SAF
Sudanese Armed Forces
- RSF
Rapid Support Forces
- IDPs
Internally displaced persons
- WHO
World Health Organization
- STROBE
Strengthening the Reporting of Observational Studies in Epidemiology
- NGO
Non-governmental organization
Authors’ contributions
“All authors participated in the conceptualization and design of the study. MBMA, LEEM, MEMA, and MOOA were responsible for data collection. SMMA conducted the data analysis and drafted the manuscript. All authors contributed to the manuscript writing process. ABMA reviewed and revised the manuscript. All authors read and approved the final draft of the manuscript.”
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Data availability
“The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.”
Declarations
Ethics approval and consent to participate
Ethical approval was obtained from Gadarif University’s Medical Research Ethics Committee (Ref. No.: GU/FM/REC/Q3.10.24.4). The study adhered to the ethical principles outlined in the Declaration of Helsinki, ensuring respect for participants’ rights and dignity. Written informed consent was obtained from all participants after a detailed explanation of the study’s purpose, with participants given the freedom to withdraw from the study at any time.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.UNHCR. Sudan Crisis Explained. UNHCR. 2024. Available from: https://www.unrefugees.org/news/sudan-crisis-explained/.
- 2.Elamin A, Abdullah S, Abda ElAbbadi A, Abdellah, Hakim A, Naiema Wagiallah et al. Sudan: from a forgotten war to an abandoned healthcare system. BMJ Global Health. 2024;9(10):e016406–6. Available from: https://gh.bmj.com/content/9/10/e016406. Cited 2024 Nov 4. [DOI] [PMC free article] [PubMed]
- 3.Badri R, Dawood I. The implications of the Sudan war on healthcare workers and facilities: a health system tragedy. Conflict Health. 2024. 10.1186/s13031-024-00581-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Hakhmigari MK, Diamant I. Occupational burnout during war: the role of stress, disruptions in routine, sleep, work-family conflict, and organizational support as a moderator. PLoS One. 2025;20(1):e0316917-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.World Health Organization. Burn-out an. Occupational Phenomenon: International Classification of Diseases. World Health Organization. 2019. Available from: https://www.who.int/news/item/28-05-2019-burn-out-an-occupational-phenomenon-international-classification-of-diseases.
- 6.Izdebski Z, Kozakiewicz A, Białorudzki M, Dec-Pietrowska J, Mazur J. Occupational Burnout in Healthcare Workers, Stress and Other Symptoms of Work Overload during the COVID-19 Pandemic in Poland. Int J Environ Res Public Health. 2023;20(3):2428 Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9916221/. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Elhadi YAM, Ahmed A, Salih EB, Abdelhamed OS, Ahmed MHH, El Dabbah NA. A cross-sectional survey of burnout in a sample of resident physicians in Sudan. Kirgiz MS, editor. Plos One. 2022;17(3):e0265098. [DOI] [PMC free article] [PubMed]
- 8.Esraa SA, Alfadul, Idrees M, Alrawa SS, Osman RO, Hassan H, Alsamany T, Albasheir et al. Burnout and its associated factors among healthcare workers in COVID-19 isolation centres in Khartoum, Sudan: A cross-sectional study. Plos One. 2023;18(7):e0288638–8. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10361487/. Cited 2023 Oct 4. [DOI] [PMC free article] [PubMed]
- 9.Dalouk K, Haar RJ. Protecting health in conflict in Sudan: a call for health worker solidarity. BMJ. 2023;381:p1453. Available from: https://www.google.com/url?q=https://www.bmj.com/content/381/bmj.p1453%26;sa=D%26;source=docs%26;ust=1707794362193077%26;usg=AOvVaw2FWD7q1Wa1LoM0tVbIr0G. Cited 2024 Feb 13. [DOI] [PubMed]
- 10.Ahmead M, El Sharif N, Alwawi A, Hemeid A, Ziqan M. The prevalence of burnout and coping strategies among Palestinian health professionals: a cross sectional study. Frontiers in Public Health. 2024;12. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC11688348/. [DOI] [PMC free article] [PubMed]
- 11.Erwan F, Iqbal M, Hasanuddin I, Zuhri S, Maydini CM. Burnout syndrome analysis among hospital nurses using Maslach Burnout Inventory - Human Service Survey (MBI-HSS): a case study. IOP Conference Series: Materials Science and Engineering. 2020;931: 012025. [Google Scholar]
- 12.Rotenstein LS, Torre M, Ramos MA, Rosales RC, Guille C, Sen S, et al. Prevalence of Burnout Among Physicians. JAMA. 2018;320(11):1131 Available from: https://jamanetwork.com/journals/jama/fullarticle/2702871. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Li-Sauerwine S, Rebillot K, Melamed M, Addo N, Lin M. A 2-Question summative score correlates with the Maslach burnout inventory. WestJEM 213 May Issue. 2020;21(3):610–7. [DOI] [PMC free article] [PubMed]
- 14.Ali Dinar G. E. English as a Medium of Instruction in Arab-Speaking Hospitals: Opportunities and Challenges. Egyptian J Hospital Med. 2025;99(1):2319–25. Available from: https://ejhm.journals.ekb.eg/article_432811.html?utm_source=chatgpt.com. Cited 2025 Jul 2.
- 15.Batanda I. Prevalence of burnout among healthcare professionals: a survey at fort portal regional referral hospital. npj Mental Health Res. 2024;3(1):1–10. Available from: https://www.nature.com/articles/s44184-024-00061-2#:~:text=Burnout%20among%20healthcare%20professionals%20can. [DOI] [PMC free article] [PubMed]
- 16.Dafallah A, Osman, Ibrahim M, Rania E, Elsheikh, Blanchet K. Destruction, disruption and disaster: sudan’s health system amidst armed conflict. Confl Health. 2023;17(1):43. [DOI] [PMC free article] [PubMed]
- 17.WHO condemns the increasing attacks on health care amid Sudan’s war. World Health Organization - Regional Office for the Eastern Mediterranean. 2024. Available from: https://www.emro.who.int/sdn/sudan-news/who-condemns-the-increasing-attacks-on-health-care-amid-sudans-war.html.
- 18.Sudan Restrictions and lack of medicines deprive people in Khartoum state of lifesaving care| MSF. Médecins Sans Frontières (MSF) International. 2023. Available from: https://www.msf.org/sudan-restrictions-and-lack-medicines-deprive-people-khartoum-state-lifesaving-care. Cited 2025 Mar 1.
- 19.Soaring medical needs mark 500 days of war in Sudan| MSF. Médecins Sans Frontières (MSF) International. 2024. Available from: https://www.msf.org/soaring-medical-needs-mark-500-days-war-sudan.
- 20.UNICEF. Over Three Million Children at Heighted Risk of Cholera and other Deadly Diseases in Sudan. Unicef.org. 2024. Available from: https://www.unicef.org/sudan/press-releases/over-three-million-children-heighted-risk-cholera-and-other-deadly-diseases-sudan.
- 21.First famine, now cholera and dengue fever surge hits war-torn Sudan, UN News. 2024. Available from: https://news.un.org/en/story/2024/11/1156461.
- 22.Chemali Z, Ezzeddine FL, Gelaye B, Dossett ML, Salameh J, Bizri M, et al. Burnout among healthcare providers in the complex environment of the Middle East: a systematic review. BMC Public Health. 2019. 10.1186/s12889-019-7713-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Magalhães E, Oliveira ÁCM, de Govêia S, Ladeira CS, Queiroz LCA, Vieira DM. Prevalence of burnout syndrome among anesthesiologists in the federal district. Brazilian J Anesthesiology. 2015;65(2):104–10. [DOI] [PubMed] [Google Scholar]
- 24.Ugwu FO, Ugwu C, Njemanze VC, Nwosu I. Family cohesion and family size moderating burnout and recovery connection. Occup Med. 2018;69(1):28–34. [DOI] [PubMed] [Google Scholar]
- 25.Aldabbour B, Dardas LA, Hamed L, Alagha H, Alsaiqali R, El-shanti N, et al. Emotional exhaustion, depersonalization, and personal accomplishment: exploring burnout in Gaza’s healthcare workforce during the war. Middle East Curr Psychiatry. 2025. 10.1186/s43045-025-00519-9. [Google Scholar]
- 26.Edú-Valsania S, Laguía A, Moriano JA, Burnout. A review of theory and measurement. International Journal of Environmental Research and Public Health. 2022;19(3):1–27. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC8834764/. [DOI] [PMC free article] [PubMed]
- 27.Displacement in Sudan Crosses 11 Million as Devastating Crisis Reaches New Heights: IOM Chief. International Organization for Migration. 2021. Available from: https://www.iom.int/news/displacement-sudan-crosses-11-million-devastating-crisis-reaches-new-heights-iom-chief.
- 28.Youssef D, Youssef J, Abou-Abbas L, Kawtharani M, Hassan H. Prevalence and correlates of burnout among physicians in a developing country facing multi-layered crises: a cross-sectional study. Sci Rep. 2022;12(1): 12615. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Patel R, Bachu R, Adikey A, Malik M, Shah M. Factors Related to Physician Burnout and Its Consequences: A Review. Behav Sci. 2018;8(11). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6262585/. [DOI] [PMC free article] [PubMed]
- 30.Giselle Dayana Valdes-Elizondo, Álvarez-Maldonado P, Maria Angélica Ocampo-Ocampo, Hernández-Ríos G, Réding-Bernal A, Hernández-Solís A. Burnout symptoms among physicians and nurses before, during and after COVID-19 care. Revista Latino-americana De Enfermagem. 2023;31:e4046. [DOI] [PMC free article] [PubMed]
- 31.Dubale BW, Friedman LE, Chemali Z, Denninger JW, Mehta DH, Alem A, et al. Systematic review of burnout among healthcare providers in sub-Saharan Africa. BMC Public Health. 2019. 10.1186/s12889-019-7566-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Papazian L, Hraiech S, Loundou A, Herridge MS, Boyer L. High-level burnout in physicians and nurses working in adult ICUs: a systematic review and meta-analysis. Intensive Care Med. 2023;400. 10.1007/s00134-023-07025-8. [DOI] [PMC free article] [PubMed]
- 33.Sudan, Summary of the Humanitarian Needs and Response Plan and the Regional Refugee Response Plan (February. 2024)| OCHA. www.unocha.org.2024. Available from: https://www.unocha.org/publications/report/sudan/sudan-summary-humanitarian-needs-and-response-plan-and-regional-refugee-response-plan-february-2024.
- 34.Sudan war. Nearly 26 million going hungry due to rising food prices, access challenges| UN News. news.un.org. 2024. Available from: https://news.un.org/en/story/2024/07/1152426.
- 35.Mental Health and Psychosocial Support (MHPSS) Technical Working Group in Sudan Terms of Reference (TOR.) - Sudan. ReliefWeb. 2024. Available from: https://reliefweb.int/report/sudan/mental-health-and-psychosocial-support-mhpss-technical-working-group-sudan-terms-reference-tor. Cited 2025 Mar 1.
- 36.Tsybuliak N, Yana Suchikova, Shevchenko L, Popova A, Serhii, Kovachev. Olha Hurenko. Burnout dynamic among Ukrainian academic staff during the war. Scientific Reports. 2023;13(1). Available from: https://www.nature.com/articles/s41598-023-45229-6?utm_source=chatgpt.comCited 2025 Feb 22. [DOI] [PMC free article] [PubMed]
- 37.Doolittle BR. Association of burnout with emotional coping strategies, friendship, and institutional support among internal medicine physicians. J Clin Psychol Med Settings. 2020;15(2):361–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Rogers E, Polonijo AN, Carpiano RM. Getting by with a little help from friends and colleagues: Testing how residents’ social support networks affect loneliness and burnout. Canadian Family Physician. 2016;62(11):e677. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9844583/. [PMC free article] [PubMed]
- 39.De Diego-Cordero R, Iglesias-Romo M, Badanta B, Lucchetti G, Vega-Escaño J. Burnout and spirituality among nurses: A scoping review. Explore. 2021;18(5):612–20. [DOI] [PubMed]
- 40.Doolittle BR, Windish DM, Seelig CB. Burnout, coping, and spirituality among internal medicine resident physicians. J Graduate Med Educ. 2013;5(2):257–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Alfahal MS, Bashar Alasha, Essam A, Tsabeh Abdelrahem Higazy, Khalid EM, Saif D et al. Conflict and displacement in Sudan: Health challenges, socio-economic strain, trauma, and coping mechanisms among internally displaced persons in Port Sudan shelters. Medicine. 2025;104(16):e42232–2. Available from: https://journals.lww.com/md-journal/fulltext/2025/04180/conflict_and_displacement_in_sudan__health.8.aspx?context=latestarticles#. [DOI] [PMC free article] [PubMed]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
“The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.”