The Magnitude of Burnout Syndrome and Its Associated Factors among Health Extension Workers in South Gondar Zone,Northwest Ethiopia: A Cross-Sectional Study

Abstract

Introduction

Health Extension Workers (HEWs) in Ethiopia face heavy workloads, long hours, and limited resources, increasing their risk of Burnout Syndrome (BOS), a psychological condition characterized by emotional exhaustion, depersonalization (DP), and reduced personal accomplishment (PA). Despite their critical role in rural health systems, evidence on burnout prevalence and its determinants among HEWs in Northwest Ethiopia is limited.

Objective

To assess the magnitude of BOS and identify its associated factors among HEWs in the South Gondar Zone, Northwest Ethiopia, 2024.

Methods

A facility-based cross-sectional study was conducted from April 1, 2024, to April 30, 2024, among 406 HEWs selected using simple random sampling. Data were collected via face-to-face interviews using a structured, pretested questionnaire including the Maslach Burnout Inventory. Data were entered using EpiData version 4.6 and analyzed with SPSS version 25. Multivariable logistic regression analysis was performed to identify factors associated with burnout, and adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were reported.

Results

Burnout prevalence among HEWs was 22.17% (95% CI: 18.38–26.48%). Factors significantly associated with burnout included rural residence (AOR = 2.25; 95% CI: 1.09–4.64), fewer years of service at the current facility (AOR = 0.27; 95% CI: 0.12–0.61), job dissatisfaction (AOR = 2.67; 95% CI: 1.15–6.21), and inadequate availability of health post resources (AOR = 0.57; 95% CI: 0.37–0.88). Regarding burnout dimensions, 90.4% of participants reported low, 7.4% moderate, and 2.2% high levels of emotional exhaustion. Low levels of DP and PA were reported by 85.0% and 98.0% of HEWs, respectively.

Conclusion

A substantial proportion of HEWs in the South Gondar Zone experience burnout, which may negatively affect both their well-being and the quality of health services delivered. Targeted interventions addressing modifiable workplace and psychosocial factors are urgently needed to improve occupational health and ensure the sustainability of the primary healthcare workforce.

Keywords

burnout mental health occupational stress job satisfaction business concepts health systems research primary healthcare workforce

Introduction

Ethiopia's Health Extension Program (HEP) has greatly expanded access to healthcare, particularly in rural areas. Central to this initiative are Health Extension Workers (HEWs), who deliver essential services including maternal and child health care, disease prevention, and health education (Drown et al., 2023; Tesema et al., 2022). Despite notable achievements, the sustainability of HEP is challenged by workforce issues such as retention and performance. Health Extension Workers often face heavy workloads, long hours, and limited resources conditions that contribute to burnout (Medhanyie et al., 2012).

Burnout syndrome (BOS), defined by the World Health Organization (WHO) as a work-related condition marked by emotional exhaustion (EE), detachment, and reduced professional efficacy, arises from unmanaged workplace stress (Nair & Kumar, 2023; Subtypes & Bauernhofer, 2020). Globally, BOS is a major concern among healthcare workers, linked to diminished job performance, emotional depletion, and adverse health outcomes (Ramírez-Pérez & Osorio-Guzmán, 2023; Stichler, 2009; Weber & Jaekel-Reinhard, 2000). Stressful working conditions, inadequate support, and poor work–life balance further exacerbate burnout, leading to high EE and low personal accomplishment (PA; Iserson, 2018; Teksam et al., 2021).

Evidence shows high burnout rates among healthcare professionals. In Ethiopia, the pooled prevalence is estimated at 39.1%, rising to 39.8% among rural HEWs (Birhane et al., 2023; Mengist et al., 2021). Contributing factors include excessive workload, poor working environments, limited support, and lack of career advancement opportunities (Assefa et al., 2019; Banteyerga, 2011; Belay et al., 2021; Leao et al., 2022; Parwati et al., 2023; Vettor, 2002). These challenges compromise program sustainability and drive workforce attrition.

Given that HEWs are often the first and only point of contact for rural populations, their well-being directly affects the quality and continuity of healthcare services (Caglia et al., 2014). Understanding burnout in this group is therefore critical for designing evidence-based strategies that strengthen retention and performance. While burnout has been studied among other healthcare providers, data specific to HEWs—particularly in the South Gondar Zone, Northwest Ethiopia—remain limited (Bijari & Abassi, 2016; Xu et al., 2020).

This study aims to assess the prevalence of burnout and its associated factors among HEWs, generating evidence to guide targeted interventions that enhance their well-being and sustain healthcare service delivery (Aitmurzinova & Seitkabylov; Bridgeman et al., 2018; Jones, 1981). Findings will inform policymakers and healthcare administrators in developing strategies to mitigate burnout, thereby improving HEW performance and patient outcomes (Cohen et al., 2023; Shanafelt & Noseworthy, 2017; West et al., 2018).

Literature Review

Burnout is a psychological syndrome that arises from chronic workplace stress that has not been effectively managed. It is characterized by three core dimensions: EE, cynicism or depersonalization (DP), and reduced PA. The Maslach Burnout Inventory (MBI), developed in the early 1980s, is the most widely used psychometric tool for measuring these dimensions and has formed the basis of much empirical research on occupational burnout in health professions (Maslach & Jackson, 1981).

In 2019, the WHO officially recognized burnout as an occupational phenomenon (not a medical condition) in the International Classification of Diseases, 11th Revision, highlighting its importance for workforce well-being and occupational health policies. This recognition has intensified global attention on workplace-level interventions, prevention strategies, and monitoring systems (Sundram & Kumareswaran, 2024).

Globally, burnout prevalence varies widely across regions, professions, and healthcare settings. A meta-analysis of nurses reported an overall prevalence of approximately 30% worldwide, although rates have fluctuated over the past decade (Carod-Artal & Vázquez-Cabrera, 2012). Among medical and surgical residents, a 2019 meta-analysis reported a pooled prevalence of 51% (95% confidence interval [CI]: 45–57%), with marked variation by specialty and location (Low et al., 2019). At smaller institutional levels, prevalence may be lower; for instance, a study in Valledupar found a prevalence of 10.5% among health workers (Gómez-Urquiza et al., 2017). In sub-Saharan Africa, higher rates are reported: 20.6% of health workers in resource-constrained hospitals in Accra, Ghana, experienced burnout (Dehingia et al., 2022), while in Gabon, nearly half of medical practitioners reported burnout symptoms (Mackanga et al., 2020). A pilot study in Ghana further detailed burnout dimensions among physicians: 5.5% reported DP, 7.8% low PA, and 10.8% EE (Ayisi-Boateng et al., 2020).

Burnout is influenced by both individual and work-related factors. Evidence from a 2019 cross-sectional study showed that younger age was associated with a lower risk of burnout (adjusted odds ratio [AOR] 0.4; 95% CI: 0.2–0.9), whereas long night shifts significantly increased the likelihood of burnout (AOR 3.36; 95% CI: 1.83–6.2). Protective factors included higher job satisfaction, which reduced burnout risk (AOR 1.3; 95% CI: 1.3–3.3), and higher educational attainment, which influenced vulnerability to burnout (Fentie et al., 2021).

In Ethiopia, evidence among HEWs indicates similar patterns. A cross-sectional study identified lower educational level (OR 0.5; 95% CI: 0.4–0.8) and shift work (OR 0.7; 95% CI: 0.5–0.9) as significant predictors of burnout, highlighting the interaction between individual characteristics and workplace conditions in shaping risk among frontline health workers (Birhane et al., 2023).

Purpose of the study: This study aims to assess the prevalence of BOS and identify factors associated with burnout among HEWs in the South Gondar Zone, Northwest Ethiopia.

Specific objectives:

To examine the magnitude of BOS among HEWs in South Gondar Zone, Northwest Ethiopia, 2024.

To identify factors contributing to burnout among HEWs in South Gondar Zone, Northwest Ethiopia, 2024.

Methods

Study Area, Design, and Period

This cross-sectional study was conducted from April 1, 2024, to April 30, 2024, in the South Gondar Zone, located in the Amhara Region of Northwest Ethiopia. According to the South Gondar Zonal Health Department, the zone has a total population of 2,619,680, comprising 1,307,220 males and 1,312,460 females. Debre Tabor, the zonal capital, is situated 97 km from Bahir Dar and 666 km northwest of Addis Ababa. The zone includes 15 districts served by a network of health facilities, comprising one comprehensive specialized hospital, nine primary hospitals, 96 health centers, and 406 health posts. A total of 2,283 healthcare providers work in these public facilities, of whom 978 are HEWs, who formed the target population for this study.

Inclusion and Exclusion Criteria

The study population included HEWs who actively worked at health posts in the South Gondar Zone during the data collection period. In Ethiopia, HEWs serve as female frontline public health workers recruited from the communities they serve. They typically complete at least a tenth-grade education and receive one year of formal training in preventive, promotive, and selected basic curative services. Each HEW delivers primary healthcare to an estimated 3,000–5,000 people and works full time for approximately 40 h per week, in addition to conducting outreach activities and participating in public health campaigns.

Inclusion criteria: Health Extension Workers with at least six months of continuous service at their current health post and who were present during data collection. Exclusion criteria: Health Extension Workers who were on annual, maternity, or sick leave, absent during the data collection period, or with less than six months of service at their current post.

Research Questions

What is the prevalence of BOS among HEWs in the South Gondar Zone, Northwest Ethiopia, 2024?

What factors are significantly associated with burnout among HEWs?

Sample Size Determination and Sampling Procedure

The sample size was calculated using a single population proportion formula, assuming a prevalence of 39.8% for BOS among HEWs, based on a previous study conducted in Ethiopia in 2019 (Birhane et al., 2023). With a 95% confidence level (Zα/2 = 1.96) and a 5% margin of error (d), the initial sample size was 369 participants. After accounting for a 10% nonresponse rate, we obtained the final sample size was 406.

Although additional calculations were performed for the second objective using two population proportions, with key variables such as work conditions and emotional support showing odds ratios of 11.89 and 11.88, respectively, these yielded smaller sample sizes (n = 223 per variable, including a 10% nonresponse adjustment). To ensure adequate power, the larger sample size calculated for the first objective (n = 406) was adopted as the final sample size for the study.

For sampling, a complete list of all HEWs in the South Gondar Zone was obtained from the Zonal Health Department and served as the sampling frame. Each HEW was assigned a unique identifier, and simple random sampling was conducted using a random number table to select the 406 participants.

Variables and Operational Definitions

Outcome variable: The primary outcome variable was BOS, measured as a dichotomous variable (yes/no) based on the MBI.

Independent variables: Independent variables were categorized into three domains to enhance conceptual clarity and analytical transparency:

Sociodemographic factors: Age, marital status, educational level, years of service, place of residence, and monthly income.

Work-related factors: Average weekly working hours, job satisfaction, organizational support, availability of health post resources, and work–life balance.

Psychosocial factors: Chronic work-related stress, EE, DP, PA, social support, and coping mechanisms.

Operational Definitions

Burnout syndrome: Burnout syndrome is a work-related psychological condition characterized by EE, DP, and reduced PA. It was assessed using the 22-item MBI–Human Services Survey (MBI-HSS), with items rated on a 7-point Likert scale ranging from 0 (never) to 6 (every day). In this study, a participant was classified as having burnout if they scored high on EE or DP and low on PA, consistent with previous studies (Adbaru et al., 2019; Ahmed et al., 2022; Gelaw et al., 2023; Quintanilla-Madero, 2020).

Emotional exhaustion: Reflects feelings of being emotionally overextended and depleted by work (low <16, moderate 17–26, high ≥27).

Depersonalization: Indicates an unfeeling and impersonal response toward service recipients (low <6, moderate 7–12, high ≥13).

Personal accomplishment: Reflects feelings of competence and successful achievement at work (low ≤31, moderate 32–38, high ≥39).

Job satisfaction: defined as the extent to which HEWs feel content and fulfilled with their job roles, responsibilities, and work environment (Prabadevi & Subramanian, 2023).

Social support: Refers to the perceived availability of emotional and practical assistance from colleagues, supervisors, family members, and the community (Saran et al., 2025).

Institutional Review Committee Approval and Ethical Considerations

Ethical approval for this study was obtained from the Institutional Review Committee of the hosting university. All study procedures were performed in accordance with the ethical standards of the responsible institutional review body and with the principles of the 1964 Helsinki Declaration and its subsequent amendments. Written informed consent was obtained from all participants prior to data collection.

Statistical Analysis

Data were collected using a structured, interviewer-administered questionnaire adapted from the MBI-HSS and other validated instruments (Kristensen et al., 2005; Maslach et al., 2001; Schaufeli et al., 2020). The questionnaire captured information on sociodemographic characteristics, work-related conditions, and psychosocial factors. It was initially developed in English, translated into Amharic, and then back-translated into English to ensure semantic consistency.

Data collection was conducted by four trained BSc nurses under the supervision of two public health professionals. All data collectors and supervisors received two days of intensive training on the study objectives, ethical considerations, interview techniques, and data quality assurance procedures. A pretest was carried out on 5% of the total sample in a neighboring district not included in the final study, and minor modifications were made to improve clarity and flow. Interviews were conducted primarily at health posts in private settings to ensure confidentiality, with alternative locations provided when necessary. Participation was voluntary, and written informed consent was obtained from all respondents. Supervisors performed daily checks to ensure completeness, accuracy, and adherence to data collection protocols.

Completed questionnaires were coded and entered into EpiData version 6.7, then exported to SPSS version 25 for analysis. Data were checked for completeness, consistency, and outliers before analysis. Descriptive statistics including frequencies, percentages, means, and standard deviations were used to summarize participant characteristics and key variables.

Bivariable logistic regression analysis was initially performed to assess associations between each independent variable and BOS. Variables with a p-value <.25 in the bivariable analysis were included in the multivariable logistic regression model to control for potential confounding factors. Model fitness was evaluated using appropriate diagnostic tests. In the final model, variables with a p-value <.05 at the 95% confidence level were considered statistically significant. The strength of associations was reported as AORs with corresponding 95% confidence intervals (CIs). Findings were presented using narrative descriptions, tables, and figures to ensure clarity and consistency.

Result

Sociodemographic Characteristics of Study Participants

A total of 406 HEWs participated in the study, yielding a 100% response rate. The largest proportions of respondents were from Estie 67 (16.50%), Fogera 60 (14.78%), and Farta 48 (11.82%) woredas. Nearly half of the participants were aged 25–34 years 198 (48.77%), with a mean age of 31.13 ± 5.20 years. Most respondents were married 357 (87.94%) and resided in rural areas 366 (90.15%).

Regarding professional characteristics, the majority had completed Level IV training 365 (89.90%). More than two-thirds had over 10 years of work experience 277 (68.23%), while 265 (65.29%) had served at their current health post for less than five years (Table 1).

Table 1.

Sociodemographic Characteristics of Study Participants in South Gondar Zone, Northwest Ethiopia, 2024.

Variables	Category	Frequency (N = 406)	Percentage (%)
Woreda	Estie	67	16.50
	Fogera	60	14.78
	Farta	48	11.82
	Andabet	40	9.85
	Ebinat	36	8.87
	Simada	35	8.62
	Sedi muja	34	8.37
	Guna	30	7.39
	Libokemkem	23	5.67
	Others	33	8.13
Age	<25	68	16.75
	25–34	198	48.77
	>35	140	34.48
Marital status	Married	357	87.93
	Single	39	9.61
	Separated	6	1.48
	Divorced	3	0.74
	Widowed	1	0.25
Residence	Urban	40	9.15
Residence	Rural	366	90.15
Educational level	Level IV	364	89.66
	Level III	40	9.85
	Degree	2	0.49
Years of service as HEW	<5	53	13.05
	5–10	76	18.73
	>10	277	68.23
Service years in current facility	<5	265	65.29
	5–10	109	26.85
	>10	32	7.88
Living arrangement	With family	333	82.02
	Alone	58	14.29
	With colleagues	15	3.69
Distance from home to health post	<4 km	288	70.9
	5–10 km	112	27.6
	>10	6	1.5
Monthly income (ETB)	≤5,338	217	53.4
Monthly income (ETB)	>5,338	189	46.6

Other = Addis zemen, Meketawuha, Woreta, Dera, Tachgaynet, and laygaynet.

Work-Related Factors of HEWs

Among the 406 participants, 348 (85.71%) reported working more than 40 h per week, and 397 (97.78%) had no secondary employment. A total of 251 (61.82%) described their work environment as comfortable or moderately comfortable, while 259 (63.79%) reported having supportive supervisors. Adequate resources were available for 233 (57.39%) participants; however, 209 (51.48%) reported dissatisfaction with their workload.

Regarding health and well-being, 170 (41.87%) rated their health status as poor, and 214 (52.71%) perceived their quality of life as poor. Job dissatisfaction was reported by 168 (41.38%) participants, while 53 (13.05%) planned to leave their job within one year (Table 2).

Table 2.

Work-Related Factors of HEWs in South Gondar Zone, Northwest Ethiopia, 2024.

Variables	Category	Frequency (N = 406)	Percentage (%)
Weekly working hours	≥40 h	348	85.71
Weekly working hours	< 40 h	58	14.29
Secondary employment	No	397	97.78
Secondary employment	Yes	9	2.22
Work environment	Comfortable/Moderately comfortable	251	61.82
Work environment	Uncomfortable/Highly uncomfortable/Neutral	155	38.18
Supervisory support	Supportive/Strongly supportive	259	63.79
Supervisory support	Not supportive/Neutral/Strongly not supportive	147	36.21
Access to resources at workplace	Sufficient	233	57.39
Access to resources at workplace	Insufficient/Uncertain	173	42.61
Satisfaction with workload	Satisfied/Very satisfied	197	48.52
Satisfaction with workload	Dissatisfied/Very dissatisfied/Neutral	209	51.48
Participation in decision-making	Yes	320	78.82
Participation in decision-making	No	86	21.18
Supportive work environment	Supportive/Strongly supportive	148	36.45
Supportive work environment	Not supportive/Strongly not supportive	258	63.55
Availability of equipment in health post	Yes	208	51.23
Availability of equipment in health post	No	198	48.77
Current health status	Good/Fair	236	58.13
Current health status	Poor	170	41.87
Perceived quality of life	Good/Fair	192	47.29
Perceived quality of life	Poor	214	52.71
Satisfaction with work	Good/Fair	238	58.62
Satisfaction with work	Poor	168	41.38
Plan to leave within 1 year	No	353	86.95
Plan to leave within 1 year	Yes	53	13.05
Work-related health problems	Headache	214	52.71
	Backache	106	26.11
	Insomnia	57	14.04
	Depression	35	8.62
	Hypertension	9	2.22
	Other*	151	37.19
Medication/activities used for work-related health issues	Analgesic	205	50.49
	Physical activity	62	15.27
	Anxiolytics/sleeping pills	11	2.71
	Other**	177	43.6

Other* = Normal and other** = did not take any measures.

Emotional Exhaustion-Related Factors of HEWs

Among the respondents, 185 (45.60%) reported never experiencing EE, while 118 (29.10%) experienced EE once a month or less. Regarding physical exhaustion, 291 (71.70%) indicated that they never felt physically exhausted, whereas 63 (15.50%) reported experiencing physical exhaustion at least once a month. In relation to fatigue when facing another workday, 301 (74.10%) stated that they never felt tired.

With respect to DP, 296 (72.90%) reported never feeling indifferent toward service recipients, while 35 (8.60%) experienced this feeling once a month or less, and 31 (7.60%) reported experiencing it a few times per month (Table 3)

Table 3.

Emotional Exhaustion-Related Factors of HEWs in South Gondar Zone, Northwest Ethiopia, 2024.

Variables	Category	Frequency (N = 406)	Percentage (%)
I feel emotionally drained from my work.	Never	185	45.57
	A few times a year or less	85	20.94
	Once a month or less	118	29.06
	A few times a month	8	1.97
	Once a week	4	0.99
	A few times a week	4	0.99
	Every day	2	0.49
I seem physically exhausted and wiped out.	Never	291	71.67
	A few times a year or less	25	6.16
	Once a month or less	63	15.52
	A few times a month	18	4.43
	Once a week	5	1.23
	A few times a week	3	0.74
	Every day	1	0.25
I feel fatigued when I get up in the morning and have to face another day.	Never	301	74.14
	A few times a year or less	15	3.69
	Once a month or less	52	12.81
	A few times a month	24	5.91
	Once a week	5	1.23
	A few times a week	8	1.97
	Every day	1	0.25
I feel of incompetence when dealing with work task.	Never	313	77.09
	A few times a year or less	11	2.71
	Once a month or less	40	9.85
	A few times a month	25	6.16
	Once a week	11	2.71
	A few times a week	4	0.99
	Every day	2	0.49
I feel overwhelmed with my work demands.	Never	271	66.75
	A few times a year or less	22	5.42
	Once a month or less	83	20.44
	A few times a month	19	4.68
	Once a week	6	1.48
	A few times a week	3	0.74
	Every day	2	0.49
I worry that this job is hardening me emotionally.	Never	186	45.82
	A few times a year or less	81	19.95
	Once a month or less	127	31.28
	A few times a month	3	0.74
	Once a week	5	1.23
	A few times a week	3	0.74
	Every day	1	0.25
I feel like I'm at the end of my rope.	Never	296	72.91
	A few times a year or less	9	2.22
	Once a month or less	13	3.20
	A few times a month	28	6.90
	Once a week	30	7.39
	A few times a week	24	5.91
	Every day	6	1.48
I feel recipients blame me for some of their problem.	Never	264	65.02
	A few times a year or less	14	3.45
	Once a month or less	103	25.37
	A few times a month	2	0.49
	Once a week	5	1.23
	A few times a week	17	4.19
	Every day	1	0.25

Depersonalization-Related Items among HEWs

Among the respondents, 320 (78.80%) reported that they never felt they treated beneficiaries as impersonal objects, while 27 (6.70%) experienced this once a month or less and 27 (6.70%) reported experiencing it a few times a month. In addition, 313 (77.10%) stated that they never lacked access to a social–professional support group, whereas 41 (10.10%) reported a lack of such access once a month or less (Table 4).

Table 4.

Depersonalization-Related Items among HEWs in South Gondar Zone, Northwest Ethiopia, 2024.

Variables	Category	Frequency (N = 406)	Percentage (%)
I feel I treat some recipients as if they were impersonal objects.	Never	320	78.82
	A few times a year or less	18	4.43
	Once a month or less	27	6.65
	A few times a month	27	6.65
	Once a week	8	1.97
	A few times a week	4	0.99
	Every day	2	0.49
I lack access to a social-professional support group.	Never	313	77.09
	A few times a year or less	16	3.94
	Once a month or less	41	10.10
	A few times a month	14	3.45
	Once a week	12	2.96
	A few times a week	7	1.72
	Every day	3	0.74
Working with people all day is really a strain for me.	Never	301	74.14
	A few times a year or less	49	12.07
	Once a month or less	28	6.90
	A few times a month	9	2.22
	Once a week	10	2.46
	A few times a week	8	1.97
	Every day	1	0.25
Working with people directly puts too much stress on me.	Never	319	78.57
	A few times a year or less	39	9.61
	Once a month or less	26	6.40
	A few times a month	13	3.20
	Once a week	5	1.23
	A few times a week	3	0.74
	Every day	1	0.25
I don't really care what happens to some recipients.	Never	296	72.91
	A few times a year or less	25	6.16
	Once a month or less	35	8.63
	A few times a month	31	7.64
	Once a week	8	1.97
	A few times a week	9	2.22
	Every day	2	0.49

Personal Accomplished-Related Factors among HEW

Regarding common work-related experiences, 266 (65.54%) of the respondents reported that they never felt frustrated by their work, while 73 (17.99%) experienced frustration occasionally. A majority, 290 (71.43%), reported that they rarely felt very energetic. In terms of patient interactions, 268 (66.01%) indicated that they never dealt effectively with patients’ problems, whereas 62 (15.27%) managed such problems occasionally. Furthermore, 165 (40.64%) reported that they were able to create a relaxed atmosphere with patients, while 81 (19.95%) did so occasionally (Table 5).

Table 5.

Personal Accomplished-Related Factors among HEWs in South Gondar Zone, Northwest Ethiopia, 2024.

Variables	Category	Frequency (N = 406)	Percentage (%)
I feel frustrated because of the work.	Never	266	65.52
	A few times a year or less	33	8.13
	Once a month or less	51	12.56
	A few times a month	22	5.42
	Once a week	9	2.22
	A few times a week	10	2.46
	Every day	15	3.70
I feel very energetic.	Never	290	71.43
	A few times a year or less	24	5.91
	Once a month or less	42	10.34
	A few times a month	24	5.91
	Once a week	5	1.23
	A few times a week	11	2.71
	Every day	10	2.46
I deal very effectively with the problems of my recipients.	Never	268	66.01
	A few times a year or less	32	7.88
	Once a month or less	62	15.27
	A few times a month	24	5.91
	Once a week	8	1.97
	A few times a week	6	1.48
	Every day	6	1.48
I can easily create a relaxed atmosphere with my recipients.	Never	165	40.64
	A few times a year or less	74	18.23
	Once a month or less	81	19.95
	A few times a month	43	10.59
	Once a week	20	4.93
	A few times a week	15	3.70
	Every day	8	1.97
I feel exhilarated after working closely with my recipients.	Never	284	69.95
	A few times a year or less	36	8.87
	Once a month or less	45	11.08
	A few times a month	31	7.64
	Once a week	5	1.23
	A few times a week	4	<1
	Every day	1	<1
I have accomplished many worthwhile things in this job.	Never	280	68.97
	A few times a year or less	34	8.38
	Once a month or less	65	16.01
	A few times a month	16	3.94
	Once a week	8	1.97
	A few times a week	2	<1
	Every day	1	<1
I feel I'm positively influencing other people's lives through my work.	Never	288	70.93
	A few times a year or less	35	8.62
	Once a month or less	41	10.10
	A few times a month	22	5.42
	Once a week	11	2.71
	A few times a week	7	1.72
	Every day	2	0.49
In my work, I deal with emotional problems very calmly.	Never	280	68.97
	A few times a year or less	22	5.42
	Once a month or less	69	17.00
	A few times a month	21	5.17
	Once a week	7	1.72
	A few times a week	5	1.23
	Every day	2	<1
I feel I'm working too hard on my job.	Never	293	72.17
	A few times a year or less	32	7.88
	A few times a month	72	17.74
	Once a week	4	<1
	A few times a week	5	1.23
The main stressors encountered in work	High workload	338	83.25
	Inadequate resources	57	14.04
	Interpersonal conflicts	25	6.16
	Emotional demands	11	2.71
	Role ambiguity	4	<1
	Organizational challenges	3	<1
Coping with work-related stress and burnout	Seeking social and emotional support	311	76.6
	Engaging in physical activity	88	21.67
	Having realistic expectations	12	2.96
	Practicing self-compassion	12	2.96
	Participating in organizational activities	11	2.71
	Finding passion in your work	11	2.71
	Reflecting on positive patient interactions	7	1.72
	Practicing mindfulness or meditation	5	1.23
	Setting boundaries	1	<1

Most study participants reported low levels of EE, with the majority falling in the low category, while only a small proportion experienced moderate or high EE. Similarly, DP was predominantly low among HEWs, with few participants classified as having moderate or high DP. In contrast, low PA was highly prevalent, affecting nearly all participants. The frequency and percentage distribution of EE, DP, and PA across low, moderate, and high categories are presented in Figure 1.

Figure 1.

Emotion, depersonalization, and personal accomplished items among health extension workers in South Gondar Zone, Northwest Ethiopia, 2024. This figure illustrates the distribution of participants by the three core dimensions of burnout syndrome: Emotional exhaustion (EE) (low, moderate, high), depersonalization (low, moderate, high), and personal accomplishment (PA) (low, moderate, high), as measured using the Maslach Burnout Inventory.

As shown in Figure 2, out of the 406 HEWs included in the study, 90 (22.17%) were identified as having BOS, with a 95% CI ranging from 18.38% to 26.48%.

Figure 2.

Prevalence of burnout syndrome among health extension workers in South Gondar Zone, Northwest Ethiopia, 2024. The pie chart illustrates the proportion of health extension workers experiencing burnout syndrome. The blue segment represents respondents who reported burnout syndrome (22.17%), while the orange segment represents those who did not report burnout syndrome (77.83%).

Factors Associated with BOS among HEWs

In the multivariable logistic regression analysis, only job satisfaction and years of service at the current health facility were significantly associated with burnout among HEWs (p < .05).

Health Extension Workers who reported being fairly satisfied with their work had 2.82 times higher odds of experiencing burnout compared with those who reported poor satisfaction (AOR = 2.82; 95% CI: 1.50–5.30; p = .001). Those who reported good satisfaction also had higher odds of burnout compared with poorly satisfied HEWs (AOR = 2.35; 95% CI: 1.17–4.74; p = .017).

Regarding years of service at the current health facility, HEWs who had worked 5–10 years had 2.14 times higher odds of burnout compared with those who had worked less than 5 years (AOR = 2.14; 95% CI: 1.51–3.02; p < .001). Similarly, HEWs with more than 10 years of service had 2.07 times higher odds of burnout compared with those with less than 5 years of service (AOR = 2.07; 95% CI: 1.45–2.95; p < .001) (Table 6).

Table 6.

Bivariable and Multivariable Logistic Regression Analyses of BOS among HEWs in South Gondar Zone, Northwest Ethiopia, 2024.

Variables	Burnout		Bivariable Logistic Regression		Multivariable Logistic Regression
Variables	Yes	No	COR (95%CI)	p Value	AOR (95% CI)	p Value
Supportive supervision
Strongly supportive	2	1	1	.090	1
Supportive	58	199	8.21(0.72, 93.84)	.090	8.47(0.54, 132.31)	.128
Neutral	2	1	1.2(0.72, 1.99)	.486	1.23(0.71, 2.12)	.461
Not supportive	28	115	8.21(0.72, 93.84)	.090	5.69(0.43, 75.96)	.189
Involvement in the decision-making process
Yes	64	256	1		1
No	26	60	0.58(0.34, 0.99)	.044	0.62(0.34(1.13)	.117
Availability of enough resources at the workplace
Yes	40	168	1		1
No	50	148	0.71(0.44, 1.13)	.145	0.87(0.50, 1.50)	.606
Perception of current health status
Poor	51	119	1		1
Fair	21	76	2.88 (1.59, 5.23)	.079	2.48 (0.77, 8.00)	.128
Good	18	121	1.86 (.93, 3.71)	.000	1.71(0.56, 5.26)	.347
Perception of quality of life
Poor	57	157	1		1
Fair	17	61	2.22 (1.21, 4.09)	.010	0.38 (0.10, 1.48)	.163
Good	16	98	1.71(0.80, 3.63)	.164	0.40 (0.10, 1.61)	.195
Satisfaction of work
Poor	49	116	1		1
Fair	25	83	3.09 (1.66, 5.74)	.024	2.82 (1.5, 5.3)	.001*
Good	16	133	2.20 (1.11, 4.38)	.000	2.35 (1.17, 4.74)	.017
Work experience
<5 years	5	48	1		1
5–10 years	19	57	1.42 (0.99, 2.05)	.060	1.08 (0.71, 1.64)	.732
>10 years	66	211	0	.00	0	.063
Years of service at the current workplace
<5 years	38	227	1		1
5–10 years	42	67	2.14 (1.51, 3.02)	.000	2.14 (1.51, 3.02)	.000*
>10 years	10	22	1.81(1.21, 2.32)	.000	2.07(1.45, 2.95)	.000*

*Significant.

Discussion

This study found that the overall prevalence of BOS among HEWs in the South Gondar Zone was 22.17% (95% CI: 18.38–26.48). This rate is higher than the 12.6% reported among urban HEWs, but lower than the 39.8% observed among rural HEWs in another Ethiopian study (Birhane et al., 2023). Such differences may reflect contextual variations in workload, support systems, and resource availability between urban and rural settings.

Compared with other healthcare professionals, the prevalence reported here is lower than the 34% among nurses in Southwest Ethiopia (Belay et al., 2021), the 54.1% among health professionals in Dire Dawa (Ahmed et al., 2022), and the 31.6% among HEWs in Addis Ababa (Fentie et al., 2021). Burnout among nurses in the Amhara region was reported at 50.4% (Adbaru et al., 2019), while a nationwide meta-analysis estimated a pooled prevalence of 39% among Ethiopian nurses (Hailay et al., 2020). These variations highlight the influence of workload, organizational support, career advancement opportunities, and local health system structures. For instance, HEWs in some regions may face heavier patient loads, inadequate supplies, or greater administrative burdens—all known contributors to burnout (Olivares Faúndez, 2017).

In this study, job satisfaction and years of service at the current facility were significantly associated with BOS. HEWs with longer tenure were more likely to experience burnout, consistent with international evidence suggesting that prolonged exposure to stressors, limited recovery, and restricted career progression increase exhaustion and DP (Maresca et al., 2022; Maslach & Leiter, 2016). Similar findings have been reported among community health workers in China, where longer service correlated with higher burnout due to chronic demand and stagnation in professional growth (Xie et al., 2011). Conversely, studies in high-income countries suggest that greater professional experience may buffer against burnout, as seasoned workers often develop coping strategies and resilience (Schaufeli, 2018). This contrast underscores the importance of contextual workplace factors such as workload distribution, organizational culture, and support mechanisms in shaping burnout risk.

The relatively high prevalence of BOS is concerning because burnout has been linked to decreased job satisfaction, higher turnover intention, reduced productivity, and poorer quality of care, which ultimately undermine primary healthcare delivery (Ahmed et al., 2022). For HEWs who play a critical role in Ethiopia's primary health system addressing burnout is essential to sustain workforce performance and community health outcomes.

The relatively high prevalence of BOS among HEWs is concerning given its implications for job satisfaction, workforce retention, productivity, and quality of care. Burnout threatens the sustainability of Ethiopia's primary healthcare system, where HEWs serve as the first and often only point of contact for rural populations. Addressing burnout is therefore critical to safeguard workforce performance and ensure continuity of essential health services.

Strengths and Limitations

This study has several strengths. First, the use of the MBI, a validated and widely adopted tool, enhances the comparability of our findings with other studies on burnout. Second, the large sample size and high response rate improve the precision of the estimates and the generalizability of the results to HEWs in the South Gondar Zone. Third, random sampling and the use of well-trained data collectors minimized potential selection and interviewer biases. Finally, the study provides novel evidence on burnout among HEWs, a critical but understudied workforce in rural Ethiopia, contributing valuable insights for policy and practice in this context.

Despite these strengths, there are some limitations. The use of face-to-face, interviewer-administered data collection for the MBI may have introduced social desirability bias. Since the MBI is traditionally self-administered, participants may have been reluctant to disclose sensitive professional emotions, such as DP or EE, directly to an interviewer. This could have contributed to the very low observed proportion of high EE and DP scores. Additionally, the cross-sectional design limits causal interpretation, as the temporal direction of associations cannot be established; for example, while job dissatisfaction was associated with burnout, it is equally plausible that burnout itself contributes to dissatisfaction. The absence of qualitative data restricts deeper contextual interpretation, such as understanding why burnout levels were higher among rural HEWs, which may relate to social isolation, resource limitations, or workload differences. Finally, very limited variability in the PA dimension constrained statistical modeling, making multivariable analysis for this dimension unreliable; thus, interpretations related to PA should be approached with caution.

Implications for Practice

The findings of this study highlight several actionable areas for policy and programmatic intervention aimed at reducing burnout among HEWs. Enhancing supportive supervision and organizational support through regular, constructive engagement and managerial guidance can help reduce job stress and improve worker satisfaction. Policies that promote fair workload distribution, recognition systems, career development opportunities, and appropriate incentives can further improve job satisfaction and reduce burnout risk. Integrating stress management and resilience programs, including training on coping strategies, mental health awareness, and resilience building, can equip HEWs to better manage the chronic demands of their work. Addressing risks associated with long tenure at a single facility through rotation policies, mentorship programs, and clear career advancement pathways may help mitigate cumulative stress. Ensuring adequate resources and supportive work environments, such as the availability of essential supplies, safe working conditions, and infrastructural support, can reduce frustration and strain. Finally, institutionalizing mental health support by providing routine mental health screening and access to counseling services can facilitate early identification and timely intervention for burnout. Together, these strategies can strengthen workforce wellbeing and enhance the effectiveness of community health services.

Conclusion

This study revealed a 22.17% prevalence of BOS among HEWs in the South Gondar Zone, with job satisfaction and longer years of service at the same facility identified as significant associated factors. These findings underscore the urgent need for targeted institutional interventions, supportive workforce policies, and professional development strategies to reduce burnout and sustain the well-being of HEWs. Addressing burnout in this essential workforce is crucial for maintaining the quality and continuity of primary healthcare services in Ethiopia.

Supplemental Material

sj-docx-1-son-10.1177_23779608261433768 - Supplemental material for The Magnitude of Burnout Syndrome and Its Associated Factors among Health Extension Workers in South Gondar Zone, Northwest Ethiopia: A Cross-Sectional Study

Supplemental material, sj-docx-1-son-10.1177_23779608261433768 for The Magnitude of Burnout Syndrome and Its Associated Factors among Health Extension Workers in South Gondar Zone, Northwest Ethiopia: A Cross-Sectional Study by Eshetie Molla Alemu, Endalkachew Mesfin Gebeyehu and Asresu Lake in SAGE Open Nursing

Supplemental Material

sj-docx-2-son-10.1177_23779608261433768 - Supplemental material for The Magnitude of Burnout Syndrome and Its Associated Factors among Health Extension Workers in South Gondar Zone, Northwest Ethiopia: A Cross-Sectional Study

Supplemental material, sj-docx-2-son-10.1177_23779608261433768 for The Magnitude of Burnout Syndrome and Its Associated Factors among Health Extension Workers in South Gondar Zone, Northwest Ethiopia: A Cross-Sectional Study by Eshetie Molla Alemu, Endalkachew Mesfin Gebeyehu and Asresu Lake in SAGE Open Nursing

Footnotes

Acknowledgments

The authors would like to thank the South Gondar Zonal Health Department for their cooperation and support. The authors are also grateful to the health extension workers who participated in this study for their time and valuable information.

ORCID iD

Endalkachew Mesfin Gebeyehu

Author Contributions

Eshetie Molla Alemu conceived and designed the study, coordinated data collection, and contributed to data analysis and interpretation. Asresu Lake assisted in study design, data analysis, and drafting of the manuscript. Endalkachew Mesfin Gebeyehu supervised the overall research process, guided data analysis and interpretation, critically reviewed and revised the manuscript for intellectual content, and approved the final version for submission. All authors read and approved the final manuscript.

Consent for Publication

Not applicable. This study did not involve identifiable patient data or images requiring consent for publication.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The datasets generated and/or analyzed during the current study are not publicly available due to participant confidentiality but are available from the corresponding author upon reasonable request.

Supplemental Material

Supplemental material for this article is available online.

References

Adbaru

Assen

Demelew

Teshome

(2019). Magnitude of burnout and its associated factors among nurses working in public hospitals of Amhara regional state, Ethiopia. MOJ Womens Health, 8(2), 133–141. https://doi.org/10.15406/mojwh.2019.08.00225

Ahmed

Hawulte

Yuya

Birhanu

Oljira

(2022). Prevalence of burnout and associated factors among health professionals working in public health facilities of Dire Dawa city administration, Eastern Ethiopia. Frontiers in Public Health, 10, 836654. https://doi.org/10.3389/fpubh.2022.836654

Aitmurzinova

Seitkabylov

Burnout Syndrome among Medical Professionals: Literature Review.

Assefa

Gelaw

Y. A.

Hill

P. S.

Taye

B. W.

Van Damme

(2019). Community health extension program of Ethiopia, 2003–2018: Successes and challenges toward universal coverage for primary healthcare services. Globalization and Health, 15(1), 24. https://doi.org/10.1186/s12992-019-0470-1

Ayisi-Boateng

N. K.

Bankah

E. M.

Ofori-Amankwah

G. K.

Egblewogbe

D. A.

Ati

Aninng

D. O.

Appiah-Brempong

Spangenberg

(2020). A cross-sectional self-assessment of burnout amongst a sample of doctors in Ghana. African Journal of Primary Health Care and Family Medicine, 12(1), 1–6. https://doi.org/10.4102/phcfm.v12i1.2336

Banteyerga

(2011). Ethiopia's health extension program: Improving health through community involvement. MEDICC Review, 13, 46–49. https://doi.org/10.37757/MR2011V13.N3.11

Belay

Guangul

M. M.

Asmare

W. N.

Bogale

S. K.

Manaye

(2021). Prevalence and associated factors of burnout syndrome among nurses in public hospitals, Southwest Ethiopia. Ethiopian Journal of Health Sciences, 31(3), 543. https://doi.org/10.4314/EJHS.V31I3.11

Bijari

Abassi

(2016). Prevalence of burnout syndrome and associated factors among rural health workers (Behvarzes) in South Khorasan. Iranian Red Crescent Medical Journal, 18(10), e25390. https://doi.org/10.5812/ircmj.25390

Birhane

Medhin

Demissie

Tassew

Gebru

Tadesse

Jebena

M. G.

Teklu

A. M.

Deyessa

(2023). Depression and burnout among health extension workers in Ethiopia: A cross-sectional study. Ethiopian Journal of Health Sciences, 33(2), 63.

10.

Bridgeman

P. J.

Bridgeman

M. B.

Barone

(2018). Burnout syndrome among healthcare professionals. American Journal of Health-System Pharmacy: AJHP, 75(3), 147–152. https://doi.org/10.2146/ajhp170460

11.

Caglia

Kearns

Langer

(2014). Health extension workers in Ethiopia: Delivering community-based antenatal and postnatal care. Maternal Health Task Force.

12.

Carod-Artal

F. J.

Vázquez-Cabrera

(2012). Burnout syndrome in an international setting. In Burnout for experts: Prevention in the context of living and working (pp. 15–35). Springer.

13.

Cohen

Pignata

Bezak

Tie

Childs

(2023). Workplace interventions to improve well-being and reduce burnout for nurses, physicians and allied healthcare professionals: A systematic review. BMJ Open, 13(6), e071203. https://doi.org/10.1136/bmjopen-2022-071203

14.

Dehingia

Dey

A. K.

McDougal

McAuley

Singh

Raj

(2022). Help seeking behavior by women experiencing intimate partner violence in India: A machine learning approach to identifying risk factors. PLoS One, 17(2), e0262538. https://doi.org/10.1371/journal.pone.0262538

15.

Drown

Amberbir

Teklu

Zelalem

Tariku

Tadesse

Gebeyehu

Semu

Ntawukuriryayo

J. T.

VanderZanden

Binagwaho

Hirschhorn

. (2023). Reducing the equity gap in under-5 mortality through an innovative community health program in Ethiopia: An implementation research study. medRxiv. https://doi.org/10.1101/2023.05.30.23290706

16.

Fentie

E. T.

Daba Wami

Guyasa Kabito

(2021). Prevalence of burnout syndrome and associated factors among health care workers at public hospitals in Addis Ababa, Ethiopia: Results from a cross-sectional study. International Journal of Mental Health, 50(4), 368–380. https://doi.org/10.1080/00207411.2021.1946904

17.

Gelaw

Y. M.

Hanoch

Adini

(2023). Burnout and resilience at work among health professionals serving in tertiary hospitals, in Ethiopia. Frontiers in Public Health, 11, 1118450. https://doi.org/10.3389/fpubh.2023.1118450

18.

Gómez-Urquiza

J. L.

De la Fuente-Solana

E. I.

Albendín-García

Vargas-Pecino

Ortega-Campos

E. M.

Canadas-De la Fuente

G. A.

(2017). Prevalence of burnout syndrome in emergency nurses: A meta-analysis. Critical Care Nurse, 37(5), e1–e9. https://doi.org/10.4037/ccn2017508

19.

Hailay

Aberhe

Mebrahtom

Zereabruk

Gebreayezgi

Haile

(2020). Burnout among Nurses Working in Ethiopia. Behavioural Neurology. https://doi.org/10.1155/2020/8814557

20.

Iserson

K. V

. (2018). Burnout syndrome: Global medicine volunteering as a possible treatment strategy. The Journal of Emergency Medicine, 54(4), 516–521. https://www.jem-journal.com/article/S0736-4679(18)30005-2/abstract https://doi.org/10.1016/j.jemermed.2017.12.062

21.

Jones

J. W.

(1981). The burnout syndrome: Current research, theory, interventions. London House Press.

22.

Kristensen

T. S.

Borritz

Villadsen

Christensen

K. B.

(2005). The Copenhagen burnout inventory: A new tool for the assessment of burnout. Work & Stress, 19(3), 192–207. https://doi.org/10.1080/02678370500297720

23.

Leao

G. P.

Papes

Nunes

S. K.

Pereira

E. M

. (2022). Burnout syndrome prevalence amongst physicians: a systematic review / Prevalência de síndrome de Burnout entre médicos: uma revisão sistemática. https://doi.org/10.34117/BJDV8N5-126

24.

Low

Z. X.

Yeo

K. A.

Sharma

V. K.

Leung

G. K.

McIntyre

R. S.

Guerrero

Sin Fai Lam

C. C.

Tran

B. X.

Nguyen

L. H.

(2019). Prevalence of burnout in medical and surgical residents: A meta-analysis. International Journal of Environmental Research and Public Health, 16(9), 1479. https://doi.org/10.3390/ijerph16091479

25.

Mackanga

J.-R.

Mouendou Mouloungui

E. G.

Iba-Ba

Pottier

Moussavou Kombila

J.-B.

Boguikouma

J.-B.

(2020). Burnout level and associated factors in a sub-Saharan African medical setting: Prospective cross-sectional survey. BMC Medical Education, 20(1), 295. https://doi.org/10.1186/s12909-020-02194-2

26.

Maresca

Corallo

Catanese

Formica

Lo Buono

(2022). Coping strategies of healthcare professionals with burnout syndrome: A systematic review. Medicina, 58(2), 327. https://doi.org/10.3390/medicina58020327

27.

Maslach

Jackson

S. E.

(1981). The measurement of experienced burnout. Journal of Organizational Behavior, 2(2), 99–113. https://doi.org/10.1002/job.4030020205

28.

Maslach

Leiter

M. P.

(2016). Understanding the burnout experience: Recent research and its implications for psychiatry. World Psychiatry, 15(2), 103–111. https://doi.org/10.1002/wps.20311

29.

Maslach

Schaufeli

W. B.

Leiter

M. P.

(2001). Job burnout. Annual Review of Psychology, 52(2001), 397–422. https://doi.org/10.1146/annurev.psych.52.1.397

30.

Medhanyie

Spigt

Kifle

Schaay

Sanders

Blanco

GeertJan

Berhane

(2012). The role of health extension workers in improving utilization of maternal health services in rural areas in Ethiopia: A cross sectional study. BMC Health Services Research, 12, 352. https://doi.org/10.1186/1472-6963-12-352

31.

Mengist

Amha

Ayenew

Gedfew

Akalu

T. Y.

Assemie

M. A.

Alene

Desta

(2021). Occupational stress and burnout among health care workers in Ethiopia: A systematic review and meta-analysis. Archives of Rehabilitation Research and Clinical Translation, 3(2), 100125. https://doi.org/10.1016/J.ARRCT.2021.100125

32.

Nair

Kumar

(2023). An Overview of Burnout Syndrome in Physiotherapists.

33.

Olivares Faúndez

(2017). Christina Maslach, comprendiendo el burnout. Ciencia y Trabajo, 59–62. https://doi.org/10.4067/S0718-24492017000100059

34.

Parwati

P. A.

Swarjana

I. K.

Sastamidhyani

N. P. A. J.

Adiana

I. N.

(2023). Factors associated with burnout syndrome: a cross-sectional study among nurse anesthetists in Indonesia. Journal of Public Health and Development. https://doi.org/10.55131/JPHD/2023/210202

35.

Prabadevi

Subramanian

K. P

. (2023). ‘Work contentment’—an enabler for career development—A study with special reference to the hospital industry. International Journal of Professional Business Review, 8(5), 28. https://doi.org/10.26668/businessreview/2023.v8i5.1738

36.

Quintanilla-Madero

M. B.

(2020). Burnout: A silent organizational problem. In Strategy, power and CSR: Practices and challenges in organizational management (pp. 69–83). Emerald Publishing Limited.

37.

Ramírez-Pérez

J. I.

Osorio-Guzmán

. (2023). Burnout syndrome due to workload in the care for cancer patients. Revista Medica del Instituto Mexicano del Seguro Social, 61(3), 327–334. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10437221/pdf/04435117-61-3-327.pdf

38.

Saran

Brenna

C. T.

Brar

Lee

Thomas

Huszti

Sharma

Ladha

K. S.

Ladha

(2025). Academic output of anesthesiology departments in Canada from 2014 to 2023: A bibliometric analysis study. Cureus, 17(4).

39.

Schaufeli

W. B.

(2018). Professional burnout: Recent developments in theory and research.

40.

Schaufeli

W. B.

Desart

De Witte

(2020). Burnout assessment tool (BAT)—development, validity, and reliability. International Journal of Environmental Research and Public Health, 17(24), 9495. https://doi.org/10.3390/ijerph17249495

41.

Shanafelt

T. D.

Noseworthy

J. H

. (2017). Executive leadership and physician well-being: nine organizational strategies to promote engagement and reduce burnout. Mayo Clinic Proceedings.

42.

Stichler

J. F.

(2009). Healthy, healthful, and healing environments: A nursing imperative. Critical Care Nursing Quarterly, 32(3), 176–188. https://doi.org/10.1097/CNQ.0b013e3181ab9149

43.

Subtypes

Bauernhofer

(2020). Burnout Subtypes Symptoms, risk factors, and treatment.

44.

Sundram

B. M.

Kumareswaran

(2024). Developing a conceptual framework for burnout intervention program in the workplace. Universa Medicina, 43(1), 88–101. https://doi.org/10.18051/UnivMed.2024.v43.88-101

45.

Teksam

Agın

Erkek

Arslankoylu

A. E.

Akca

Esen

Derinoz

Yener

Kılınc

M. A.

Yılmaz

(2021). The burden of burnout syndrome in pediatric intensive care unit and pediatric emergency department: A multicenter evaluation. Pediatric Emergency Care, 37(12), e955–e961. https://doi.org/10.1097/PEC.0000000000001839

46.

Tesema

Peiris

Abimbola

Ajisegiri

W. S.

Narasimhan

Mulugeta

Joshi

(2022). Community health extension workers’ training and supervision in Ethiopia: Exploring impact and implementation challenges for non-communicable disease service delivery. PLOS Global Public Health. https://doi.org/10.1371/JOURNAL.PGPH.0001160

47.

Vettor

S. M.

(2002). Predicting work stress burnout in rural and urban emergency medical technicians through the use of early recollections. Andrews University.

48.

Weber

Jaekel-Reinhard

(2000). Burnout syndrome: a disease of modern societies? Occupational Medicine, 50(7). https://doi.org/10.1093/occmed/50.7.512

49.

West

C. P.

Dyrbye

L. N.

Shanafelt

T. D.

(2018). Physician burnout: Contributors, consequences and solutions. Journal of Internal Medicine, 283(6), 516–529. https://doi.org/10.1111/joim.12752

50.

Xie

Wang

Chen

(2011). Nurse burnout and its association with occupational stress in a cross-sectional study in Shanghai. Journal of Advanced Nursing, 67(7), 1537–1546. https://doi.org/10.1111/j.1365-2648.2010.05576.x

51.

Pan

Zhang

. (2020). Job burnout among primary healthcare workers in rural China: A multilevel analysis. International Journal of Environmental Research and Public Health, 17(3), 727. https://mdpi-res.com/d_attachment/ijerph/ijerph-17-00727/article_deploy/ijerph-17-00727-v2.pdf?version=1579938089 https://doi.org/10.3390/ijerph17030727

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