Prevalence and Predictors of Burnout Among Medical Interns in 2 Major Cities of the Eastern Province of Saudi Arabia: A Cross-Sectional Study

Abstract

Background

Burnout is common among healthcare professionals. This study aimed to assess the prevalence of burnout and its predictors among medical interns in Saudi Arabia’s Eastern Province.

Material/Methods

This cross-sectional study included medical interns at hospitals in Dammam and Al Khobar. Data were collected between October 2024 and April 2025 using a self-administered online questionnaire that elicited information regarding sociodemographic characteristics, work-related stressors, work–life balance, and job satisfaction. Mental health symptoms were evaluated using the Patient Health Questionnaire-2 and the Generalized Anxiety Disorder-2. Burnout was measured using the Maslach Burnout Inventory-Human Services Survey, with burnout defined as high emotional exhaustion (EE), high depersonalization (DP), and low personal accomplishment (PA).

Results

A total of 117 medical interns participated. The overall prevalence of burnout was 7.7%; interestingly, low PA, high DP, and high EE were reported by 55.6%, 42.7%, and 12.8% of participants, respectively. Poor work–life balance, career-related stress, and low job satisfaction were significantly associated with burnout. Depression and anxiety symptoms were reported in 28.2% and 37.6% of participants, respectively, and were associated with higher EE and DP. Female interns had higher odds of EE, while living alone was associated with higher DP.

Conclusions

This study found that in medical interns there was a substantial disconnect between overall burnout prevalence, which was low, and subscale burden, which was high for PA and DP. Future longitudinal studies could determine the reasons for the low overall burnout prevalence, progression from subscale burden to burnout, and interventions targeting identified burnout predictors.

Introduction

Burnout is a psychological condition arising from unmanaged work-related stress and has 3 main dimensions: emotional exhaustion (EE), depersonalization (DP), and diminished personal accomplishment (PA) [1]. The World Health Organization recognizes burnout as an occupational phenomenon that adversely affects individual well-being, organizational productivity, and the quality of patient care [2]. It was first described by Freudenberger in 1974 and later formalized through the Maslach Burnout Inventory (MBI) [3]. Burnout has been extensively documented among physicians and is associated with detrimental effects on healthcare quality, patient safety, and provider well-being [4,5].

Healthcare professionals experience some of the highest rates of burnout globally, with a prevalence exceeding 50% in certain contexts [6]. The demanding nature of clinical practice, including extended working hours, night shifts, emotionally-exhausting work, and inadequate sleep, has been shown to be associated with burnout among healthcare professionals [7–9]. The COVID-19 pandemic further exacerbated these stressors, leading to unprecedented levels of fatigue, emotional strain, and psychological distress among healthcare workers [10,11].

Medical interns transitioning from academic training to clinical responsibilities are a particularly vulnerable group in the healthcare system. A steep learning curve, long working hours, heavy patient load, and limited professional support increase the risk of burnout [12]. A prospective study by Lin et al (2019) reported a significant deterioration in quality of life (QOL) among medical interns during internship. Notably, QOL was significantly associated with patient-related exhaustion (β = −0.502) and accepting new patients after 24 hours of continuous duty (β = −2.089) (P < .001) [13]. Burnout during this formative stage not only affects interns’ mental health, including anxiety, depression, and reduced professional efficacy [14,15] but also compromises patient care quality, safety, and increased likelihood of unethical behaviors [12,16,17]. A longitudinal study conducted in Australian tertiary hospitals revealed that medical interns experienced high levels of personal and work-related burnout throughout the year, with the highest levels occurring at 6 months. Patient-related burnout also increased significantly over time, highlighting its persistent and escalating nature during internship training [18].

Previous studies conducted in the Central and Western Regions of Saudi Arabia have reported significant levels of burnout among medical interns [17,19]. However, the study from the Central Region primarily relied on the Copenhagen Burnout Inventory to examine the relationship between burnout and unethical behavior, providing limited insight into the broader psychosocial and occupational dimensions of burnout. Notably, there is limited evidence regarding burnout among medical interns from the Eastern Province of Saudi Arabia, which is the third most populated region of the country. Therefore, to address this gap, this study investigated the prevalence of burnout among medical interns in the Eastern Province of Saudi Arabia and examined its key demographic, occupational, and psychosocial determinants. Using MBI alongside validated mental health screening tools, this study aimed to provide a comprehensive evaluation of social and work-related stressors. The findings may inform the development of targeted interventions that enhance interns’ well-being and support the sustainability of healthcare delivery.

Material and Methods

Study Design, Setting, and Participants

This cross-sectional survey included interns undergoing clinical training at hospitals in Dammam and Al Khobar, 2 major cities of the Eastern Province of Saudi Arabia, during the 2024–2025 academic year. Data were collected between October 13, 2024, to April 13, 2025.

According to the records of the hospitals included, a total of 227 interns were eligible for this study. The minimum sample size required for the study was calculated as 108 participants, using Epi Info software (version 7.0), with a 95% confidence level, a 5% margin of error, and an estimated burnout prevalence of 16% [19,20].

No exclusion criteria were initially applied, and all 227 interns were invited to complete the questionnaire. To participate in the study, participants were required to first provide informed consent. Completion of all questions was mandatory to submit the response.

Internship Context in Saudi Arabia

In Saudi Arabia, medical internship is a critical transitional phase during which interns rotate through core clinical departments, including internal medicine, surgery, pediatrics, emergency medicine, and family medicine, as well as additional specialty services in accordance with institutional training requirements. Their responsibilities, performed under supervision, include patient assessment, clinical documentation, procedural assistance, and active participation in ward rounds, outpatient clinics, and on-call duties. Long working hours, night shifts, and limited autonomy are often part of the internship. Medical interns also face additional pressures related to licensing examinations, residency applications, and career planning. Collectively, these demands create a high-risk environment for psychological distress and burnout, highlighting the relevance of the present investigation.

Data Collection

Data were collected over the 6-month study period using a self-administered, structured questionnaire developed using the QuestionPro platform. The questionnaire was administered in English, the primary language of medical education in Saudi Arabia. The survey was disseminated electronically through institutional email lists and WhatsApp groups associated with hospitals in Dammam and Al Khobar, where interns were undertaking clinical training. Multiple reminders were sent to enhance participation.

Sociodemographic Data

The first section of the questionnaire collected sociodemographic data to characterize the study population. The variables included age, sex, marital status, nationality, and current living arrangement (ie, living alone or not living alone; not living alone was defined as living with family, spouse, roommates, or friends/shared accommodation).

Work-Related Factors

The second section assessed internship-related experiences and occupational stressors. Participants reported the number of months completed in their internship year. They were also asked to rate how frequently they experienced difficulty maintaining work–life balance, stress related to future career preparation (eg, the Saudi Medical Licensing Exam [SMLE], CV building, career development), and stress associated with routine internship responsibilities (eg, on-call duties, interacting with patients or senior staff, participating in rounds). In addition, job satisfaction was measured using a single-item question, wherein participants were asked to rate their satisfaction on a scale from 0 to 100. The section also captured information regarding the average number of working hours per week and the current acceptance status of a residency or fellowship training program.

Mental Health Screening

The third section included validated screening tools to assess symptoms of depression and anxiety. The Patient Health Questionnaire-2 (PHQ-2) was used to detect symptoms of depression, and the Generalized Anxiety Disorder-2 (GAD-2) scale was used to evaluate anxiety symptoms.

Burnout Assessment

The final section of the questionnaire assessed occupational burnout using the Maslach Burnout Inventory–Human Services Survey (MBI-HSS), a validated instrument widely used among healthcare professionals. A meta-analysis of Arab studies, including those from Saudi Arabia, reported Cronbach’s alpha coefficients of 0.83 for EE, 0.78 for DP, and 0.77 for reduced PA, indicating acceptable internal consistency across the subscales [21]. The MBI-HSS comprises 22 items that assess 3 core burnout subscales: EE, DP, and PA. The EE subscale, consisting of 9 items, measures feelings of emotional depletion resulting from work demands. The DP subscale, comprising 5 questions, assesses a detached and impersonal attitude toward patients or clients. The PA subscale, with 8 items, assesses one’s perceived competence and effectiveness in professional roles. Each item was rated on a 7-point Likert scale, with response options ranging from 0 (never) to 6 (every day). Burnout levels were classified according to standardized scoring criteria. EE was categorized as high (≥ 27), moderate (19–26), or low (0–18). DP was classified as high (≥ 10), moderate (6–9), or low (0–5). In contrast, PA was scored inversely, with low (≥ 40), moderate (34–39), and high (0–33) levels, where lower scores indicate higher burnout [1,19,22–26]. Overall burnout prevalence was determined using the tridimensional approach, which defines burnout as the presence of high EE, high DP, and low PA [26,27].

Statistical Analysis

Descriptive statistics were used to provide an overview of the dataset. Categorical variables were summarized as frequencies and percentages, while continuous variables were presented as mean ± standard deviation (SD) for normally distributed data and median with interquartile range (IQR) for non-normally distributed data. Normality was assessed using the Shapiro–Wilk test. Associations between categorical variables were examined using the chi-square test or Fisher’s exact test, as appropriate. Comparisons of continuous variables across groups were performed using the Kruskal–Wallis test for non-normally distributed data.

Binary logistic regression was used to assess factors associated with burnout subscales (EE, DP, and PA), categorized as low, moderate, and high, with the low category as the reference group. Both univariable and multivariable analyses were conducted. Variables with a P value < 0.20 in univariable analysis, along with clinically relevant variables, were included in the multivariable models. Results were presented as odds ratios (ORs) with 95% confidence intervals (CIs).

Job satisfaction was analyzed as a continuous variable, and its effect was expressed per 10-point increase in score to facilitate interpretation. As this was an exploratory observational study, formal adjustment for multiple comparisons was not performed. All analyses were performed using R version 4.3.2 (R Foundation for Statistical Computing, Vienna, Austria). Statistical significance was defined as P < 0.05.

Ethical Considerations

All participants were informed about the study, and written informed consent was obtained prior to participation. The ethical principles outlined in the Declaration of Helsinki, 2024, were followed during data collection, management, and storage, and measures were taken to safeguard participant anonymity. Ethical approval for this study was obtained from the Institutional Review Board (IRB) of Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia (Ref no.: IRB-2024-01-714).

Results

A total of 117 medical interns provided complete response to the questionnaire (response rate: 51.5%; median age: 24 years). The overall prevalence of burnout was 7.7%. Table 1 provides the overlap among burnout subscales. Most of the participants were male (52.1%), Saudis (93.2%), never married (89.7%), did not live alone (83.8%), and had completed ≤6 months of training (51.3%). In terms of stressors, 42.7% and 21.4% of the participants stated that they were “always” stressed about career preparation and internship duties, respectively, while 16.2% “always” had difficulties in maintaining work–life balance. The median number of weekly working hours was 40.0 (IQR: 30.0–43.0), and the median satisfaction score was 75.0 (IQR: 60.0–85.0). About one-fourth (26.5%) of interns reported being accepted into residency or fellowship programs. Based on the PHQ-2 and GAD-2 scores, 28.2% and 37.6% of participants had depression and anxiety, respectively (Table 2).

Table 1.

Distribution and overlap of burnout subscales (n = 117).

Emotional exhaustion (high)	Depersonalization (high)	Personal accomplishment (low)	Total
No	No	No	36 (30.8%)
No	No	Yes	29 (24.8%)
No	Yes	Yes	26 (22.2%)
No	Yes	No	11 (9.4%)
Yes	Yes	Yes	9 (7.7%)
Yes	Yes	No	4 (3.4%)
Yes	No	No	1 (0.9%)
Yes	No	Yes	1 (0.9%)

Overall burnout was defined as the simultaneous presence of high emotional exhaustion, high depersonalization, and low personal accomplishment. “Yes” indicates the presence of the respective criterion.

Table 2.

Description of sociodemographic and work-related characteristics of the study participants (n = 117).

Variable	Characteristic	Total
Age (years)	Median (IQR)	24.0 (24.0–25.0)
Sex	Female	56 (47.9%)
	Male	61 (52.1%)
Marital status	Ever Married	12 (10.3%)
	Never Married	105 (89.7%)
Living Status	Alone	19 (16.2%)
	Not Alone	98 (83.8%)
Nationality	Saudi	109 (93.2%)
	Non-Saudi	8 (6.8%)
Duration of internship (months completed)	Less than or equal to 6 months	60 (51.3%)
	More than 6 months	57 (48.7%)
Work–life balance difficulty	Always	19 (16.2%)
	Often	33 (28.2%)
	Sometimes	43 (36.8%)
	Rarely	19 (16.2%)
	Never	3 (2.6%)
Stress related to future career preparation (eg, SMLE, CV building)	Always	50 (42.7%)
	Often	39 (33.3%)
	Sometimes	21 (17.9%)
	Rarely	7 (6.0%)
Stress related to internship responsibilities	Always	25 (21.4%)
	Often	34 (29.1%)
	Sometimes	35 (29.9%)
	Rarely	21 (17.9%)
	Never	2 (1.7%)
Average weekly working hours	Median (IQR)	40.0 (30.0–43.0)
Job satisfaction score (out of 100)	Median (IQR)	75.0 (60.0–85.0)
Acceptance into a residency/fellowship program	No	86 (73.5%)
	Yes	31 (26.5%)
Depression	Negative	84 (71.8%)
	Positive	33 (28.2%)
Anxiety	Negative	73 (62.4%)
	Positive	44 (37.6%)

Most participants had low EE (85, 72.6%), followed by moderate (17, 14.5%) and high (15, 12.8%) levels. Age (P = 0.030), sex (P = 0.017), living status (P = 0.035), difficulty maintaining work–life balance (P = 0.002), career-related stress (P = 0.041), internship-related stress (P = 0.015), and job satisfaction (P = 0.001) were significantly associated with EE levels. For example, 26.3% of those who reported always struggling with work–life balance and 24.0% of those who always stressed about internship responsibilities were in the high EE group (Table 3).

Table 3.

Association between sociodemographic, work-related, and psychological factors and burnout levels based on the emotional exhaustion subscale.

Variable	Characteristic	Low	Moderate	High	p
Age (years)	Median (IQR)	25.0 (24.0–25.0)	24.0 (24.0–24.0)	24.0 (24.0–25.0)	0.030
Sex	Female	35 (62.5%)	9 (16.1%)	12 (21.4%)	0.017
	Male	50 (82.0%)	8 (13.1%)	3 (4.9%)
Marital status	Ever married	10 (83.4%)	1 (8.3%)	1 (8.3%)	0.890
	Never married	75 (71.4%)	16 (15.2%)	14 (13.3%)
Status of living	Alone	11 (57.9%)	2 (10.5%)	6 (31.6%)	0.035
	Not alone	74 (75.5%)	15 (15.3%)	9 (9.2%)
Nationality	Saudi	78 (71.5%)	16 (14.7%)	15 (13.8%)	0.836
	Non-Saudi	7 (87.5%)	1 (12.5%)	0 (0.0%)
Duration of internship (months completed)	Less than or equal to 6 months	38 (63.3%)	12 (20.0%)	10 (16.7%)	0.076
	More than 6 months	47 (82.4%)	5 (8.8%)	5 (8.8%)
Work–life balance difficulty	Always	8 (42.1%)	6 (31.6%)	5 (26.3%)	0.002
	Often	19 (57.6%)	7 (21.2%)	7 (21.2%)
	Sometimes	3 (100.0%)	0 (0.0%)	0 (0.0%)
	Rarely	38 (88.4%)	2 (4.6%)	3 (7.0%)
	Never	17 (89.5%)	2 (10.5%)	0 (0.0%)
Stress related to future career preparation (eg, SMLE, CV building)	Always	28 (56.0%)	11 (22.0%)	11 (22.0%)	0.041
	Often	18 (85.7%)	1 (4.8%)	2 (9.5%)
	Sometimes	32 (82.1%)	5 (12.8%)	2 (5.1%)
	Rarely	7 (100.0%)	0 (0.0%)	0 (0.0%)
Stress related to internship responsibilities	Always	11 (44.0%)	8 (32.0%)	6 (24.0%)	0.015
	Often	24 (70.6%)	4 (11.8%)	6 (17.6%)
	Sometimes	28 (80.0%)	4 (11.4%)	3 (8.6%)
	Rarely	20 (95.2%)	1 (4.8%)	0 (0.0%)
	Never	2 (100.0%)	0 (0.0%)	0 (0.0%)
Average weekly working hours	Median (IQR)	40.0 (30.0–40.0)	36.0 (25.0–45.0)	40.0 (33.5–43.5)	0.828
Job satisfaction score (out of 100)	Median (IQR)	80.0 (67.0–90.0)	70.0 (50.0–75.0)	50.0 (45.0–78.0)	0.001
Acceptance into a residency/fellowship program	No	59 (68.6%)	15 (17.4%)	12 (14.0%)	0.254
	Yes	26 (83.9%)	2 (6.4%)	3 (9.7%)
Depression	Negative	73 (86.9%)	7 (8.3%)	4 (4.8%)	< 0.001
	Positive	12 (36.4%)	10 (30.3%)	11 (33.3%)
Anxiety	Negative	63 (86.3%)	8 (11.0%)	2 (2.7%)	< 0.001
	Positive	22 (50.0%)	9 (20.5%)	13 (29.5%)

Chi-square tests or Fisher’s exact tests were applied for categorical variables and the Kruskal–Wallis test for continuous variables.

Most participants had high DP (50, 42.7%), followed by low (40, 34.2%) and moderate (27, 23.1%). Age (P = 0.038), difficulty with work–life balance (P < 0.001), career-related stress (P < 0.001), internship-related stress (P < 0.001), and job satisfaction (P < 0.001) were significantly associated with DP levels. Notably, 68.4% of those who reported always having difficulty with work–life balance and 70.0% of those who were always stressed about career preparation were in the high DP category (Table 4).

Table 4.

Association between sociodemographic, work-related, and psychological factors and burnout levels based on the depersonalization subscale.

Variable	Characteristic	Low	Moderate	High	p
Age (years)	Median (IQR)	25.0 (24.0–26.0)	24.0 (24.0–24.5)	24.0 (24.0–25.0)	0.038
Sex	Female	18 (32.1%)	13 (23.2%)	25 (44.7%)	0.891
	Male	22 (36.1%)	14 (22.9%)	25 (41.0%)
Marital status	Ever married	5 (41.7%)	5 (41.7%)	2 (16.6%)	0.115
	Never married	35 (33.3%)	22 (20.9%)	48 (45.7%)
Status of living	Alone	5 (26.3%)	0 (0.0%)	14 (73.7%)	0.002
	Not alone	35 (35.7%)	27 (27.6%)	36 (36.7%)
Nationality	Saudi	4 (50.0%)	0 (0.0%)	4 (50.0%)	0.291
	Non-Saudi	36 (33.0%)	27 (24.8%)	46 (42.2%)
Duration of internship (months completed)	Less than or equal to 6 months	18 (30.0%)	14 (23.3%)	28 (46.7%)	0.575
	More than 6 months	22 (38.6%)	13 (22.8%)	22 (38.6%)
Work–life balance difficulty	Always	2 (10.5%)	4 (21.1%)	13 (68.4%)	< 0.001
	Often	4 (12.1%)	6 (18.2%)	23 (69.7%)
	Sometimes	21 (48.8%)	11 (25.6%)	11 (25.6%)
	Rarely	10 (52.6%)	6 (31.6%)	3 (15.8%)
	Never	3 (100.0%)	0 (0.0%)	0 (0.0%)
Stress related to future career preparation (eg, SMLE, CV building)	Always	7 (14.0%)	8 (16.0%)	35 (70.0%)	< 0.001
	Often	17 (43.6%)	13 (33.3%)	9 (23.1%)
	Sometimes	11 (52.4%)	5 (23.8%)	5 (23.8%)
	Rarely	5 (71.4%)	1 (14.3%)	1 (14.3%)
Stress related to internship responsibilities	Always	0 (0.0%)	1 (50.0%)	1 (50.0%)	< 0.001
	Often	8 (23.5%)	10 (29.4%)	16 (47.1%)
	Sometimes	14 (40.0%)	5 (14.3%)	16 (45.7%)
	Rarely	14 (66.7%)	6 (28.5%)	1 (4.8%)
	Never	4 (16.0%)	5 (20.0%)	16 (64.0%)
Average weekly working hours	Median (IQR)	40.0 (33.0–44.2)	35.0 (29.0–44.0)	40.0 (30.0–40.0)	0.796
Job satisfaction score (out of 100)	Median (IQR)	82.0 (73.5–92.8)	76.0 (60.5–86.5)	70.0 (49.2–80.0)	< 0.001
Acceptance into a residency/fellowship program	No	28 (32.5%)	20 (23.3%)	38 (44.2%)	0.831
	Yes	12 (38.7%)	7 (22.6%)	12 (38.7%)
Depression	Negative	36 (42.9%)	20 (23.8%)	28 (33.3%)	0.001
	Positive	4 (12.1%)	7 (21.2%)	22 (66.7%)
Anxiety	Negative	32 (43.8%)	18 (24.7%)	23 (31.5%)	0.004
	Positive	8 (18.2%)	9 (20.4%)	27 (61.4%)

Chi-square tests or Fisher’s exact tests were applied for categorical variables and the Kruskal–Wallis test for continuous variables.

Depression and anxiety were significantly associated with EE and DP. Among the participants who screened positive for depression, 33.3% had high EE and 66.7% had high DP (P < 0.001 and P < 0.001, respectively). Similarly, among those who screened positive for anxiety, 29.5% were classified as having high EE, and 61.4% had high DP (P < 0.001 and P = 0.004, respectively) (Tables 3, 4).

Based on the PA subscale, most participants had low PA (65, 55.6%), followed by moderate (32, 27.4%) and high (20, 17.1%). Significant associations were found between PA levels and several variables. Among the interns who had completed more than 6 months of training, 63.2% reported low PA (P = 0.018). Similarly, 63.2% of those who always struggled with work–life balance (P = 0.022) and 66.0% of those who always stressed about future career preparation (P = 0.049) were in the low PA group. A strong association was observed between job satisfaction and PA levels (P = 0.001) (Table 5).

Table 5.

Association between sociodemographic, work-related, and psychological factors and burnout levels based on the personal accomplishment subscale.

Variable	Characteristic	Low	Moderate	High	p
Age (years)	Median (IQR)	24.0 (24.0–25.0)	24.0 (24.0–25.0)	24.0 (24.0–25.0)	0.344
Sex	Female	10 (17.8%)	17 (30.4%)	29 (51.8%)	0.719
	Male	10 (16.4%)	15 (24.6%)	36 (59.0%)
Marital status	Ever married	1 (8.3%)	3 (25.0%)	8 (66.7%)	0.841
	Never married	19 (18.1%)	29 (27.6%)	57 (54.3%)
Status of living	Alone	5 (26.3%)	4 (21.1%)	10 (52.6%)	0.514
	Not alone	15 (15.3%)	28 (28.6%)	55 (56.1%)
Nationality	Saudi	0 (0.0%)	4 (50.0%)	4 (50.0%)	0.238
	Non-Saudi	20 (18.3%)	28 (25.7%)	61 (56.0%)
Duration of internship (months completed)	Less than or equal to 6 months	16 (26.7%)	15 (25.0%)	29 (48.3%)	0.018
	More than 6 months	4 (7.0%)	17 (29.8%)	36 (63.2%)
Work–life balance difficulty	Always	5 (26.3%)	2 (10.5%)	12 (63.2%)	0.022
	Often	3 (9.1%)	7 (21.2%)	23 (69.7%)
	Sometimes	5 (11.6%)	17 (39.6%)	21 (48.8%)
	Rarely	7 (36.8%)	6 (31.6%)	6 (31.6%)
	Never	0 (0.0%)	0 (0.0%)	3 (100.0%)
Stress related to future career preparation (eg, SMLE, CV building)	Always	8 (16.0%)	9 (18.0%)	33 (66.0%)	0.049
	Often	5 (12.8%)	13 (33.3%)	21 (53.9%)
	Sometimes	3 (14.3%)	8 (38.1%)	10 (47.6%)
	Rarely	4 (57.1%)	2 (28.6%)	1 (14.3%)
Stress related to internship responsibilities	Always	4 (16.0%)	7 (28.0%)	14 (56.0%)	0.072
	Often	2 (5.9%)	7 (20.6%)	25 (73.5%)
	Sometimes	7 (20.0%)	10 (28.6%)	18 (51.4%)
	Rarely	7 (33.3%)	6 (28.6%)	8 (38.1%)
	Never	0 (0.0.0%)	2 (100.0%)	0 (0.0%)
Average weekly working hours	Median (IQR)	36.0 (32.0–48.0)	40.0 (30.0–46.2)	40.0 (30.0–40.0)	0.398
Job satisfaction score (out of 100)	Median (IQR)	80.0 (73.8–90.0)	80.0 (70.0–92.0)	72.0 (50.0–80.0)	0.001
Acceptance into a residency/fellowship program	No	17 (19.8%)	21 (24.4%)	48 (55.8%)	0.316
	Yes	3 (9.7%)	11 (35.5%)	17 (54.8%)
Depression	Negative	14 (16.7%)	26 (30.9%)	44 (52.4%)	0.424
	Positive	6 (18.2%)	6 (18.2%)	21 (63.6%)
Anxiety	Negative	12 (16.5%)	22 (30.1%)	39 (53.4%)	0.680
	Positive	8 (18.2%)	10 (22.7%)	26 (59.1%)

For the personal accomplishment subscale, higher levels indicate lower personal accomplishment (ie, higher burnout). Chi-square tests or Fisher’s exact tests were applied for categorical variables and the Kruskal–Wallis test for continuous variables.

According to univariate analysis, several factors were significantly associated with reduced odds of high EE. Older participants had a 64% reduction in the odds of EE (OR = 0.36, 95% CI: 0.14–0.77, P = 0.017). Interns who were not living alone had 78% lower odds of high EE than those living alone did (OR = 0.22, 95% CI: 0.07–0.77, P = 0.015). According to the multivariate model, male participants had significantly lower odds of high EE than female participants (aOR = 0.17, 95% CI: 0.03–0.68, P = 0.021), with an 83% reduction in odds. Furthermore, each 10-point increase in job satisfaction was associated with lower odds of high EE (aOR = 0.66, 95% CI: 0.48–0.90, P = 0.005) (Table 6).

Table 6.

Binary logistic regression analysis of factors associated with burnout levels based on the emotional exhaustion subscale.

Variable	Category	Low	Moderate	Univariable OR (95% CI)	Multivariable OR (95% CI)
Age (years)	Mean (SD)	24.7 (1.1)	24.1 (0.4)	0.36 (0.14–0.77), p = 0.017	0.46 (0.16–1.04), p = 0.111
Sex	Female	35 (79.5)	9 (20.5)	-	-
	Male	50 (86.2)	8 (13.8)	0.62 (0.21–1.78), p = 0.374	0.52 (0.15–1.73), p = 0.291
Marital status	Ever married	10 (90.9)	1 (9.1)	-	-
	Never married	75 (82.4)	16 (17.6)	2.13 (0.37–40.54), p = 0.485	1.44 (0.20–29.47), p = 0.751
Status of living	Alone	11 (84.6)	2 (15.4)	-	-
	Not Alone	74 (83.1)	15 (16.9)	1.11 (0.26–7.68), p = 0.894	1.97 (0.34–19.32), p = 0.498
Duration of internship (months completed)	Less than or equal to 6 months	38 (76.0)	12 (24.0)	-	-
	More than 6 months	47 (90.4)	5 (9.6)	0.34 (0.10–0.99), p = 0.059	0.67 (0.16–2.59), p = 0.566
Average weekly working hours	Mean (SD)	37.0 (12.3)	38.1 (22.2)	1.00 (0.97–1.04), p = 0.787	1.02 (0.98–1.06), p = 0.255
Job satisfaction score (out of 100)	Mean (SD)	75.7 (18.4)	61.9 (20.1)	0.74 (0.54–0.90), p = 0.011	0.74 (0.54–1.00), p = 0.057
Variable	Category	Low	High	Univariable OR (95% CI)	Multivariable OR (95% CI)
Age (years)	Mean (SD)	24.7 (1.1)	25.0 (2.0)	1.16 (0.76–1.67), p = 0.439	1.09 (0.61–1.91), p = 0.784
Sex	Female	35 (74.5)	12 (25.5)	-	-
	Male	50 (94.3)	3 (5.7)	0.18 (0.04–0.60), p = 0.011	0.17 (0.03–0.68), p = 0.021
Marital status	Ever married	10 (90.9)	1 (9.1)	-	-
	Never married	75 (84.3)	14 (15.7)	1.87 (0.32–35.62), p = 0.566	1.95 (0.20–65.11), p = 0.631
Status of living	Alone	11 (64.7)	6 (35.3)	-	-
	Not Alone	74 (89.2)	9 (10.8)	0.22 (0.07–0.77), p = 0.015	0.22 (0.05–1.02), p = 0.049
Duration of internship (months completed)	Less than or equal to 6 months	38 (79.2)	10 (20.8)	-	-
	More than 6 months	47 (90.4)	5 (9.6)	0.40 (0.12–1.24), p = 0.124	1.20 (0.25–5.99), p = 0.817
Average weekly working hours	Mean (SD)	37.0 (12.3)	37.9 (15.0)	1.01 (0.96–1.05), p = 0.814	1.00 (0.95–1.06), p = 0.910
Job satisfaction score (out of 100)	Mean (SD)	75.7 (18.4)	54.1 (27.5)	0.66 (0.48–0.82), p = 0.001	0.66 (0.48–0.90), p = 0.005

Outcome: Burnout level (low, moderate, high), based on the emotional exhaustion subscale (reference category: low). Job satisfaction ORs are reported per 10-point increase in score.

In the multivariate analysis, each 10-point increase in job satisfaction was associated with lower odds of high DP (aOR = 0.54, 95% CI: 0.39–0.74, P < 0.001) and low PA (aOR = 0.54, 95% CI: 0.31–0.74, P = 0.003) (Tables 7, 8). Additionally, interns who had completed > 6 months of training were significantly more likely to report low PA, with odds more than 10 times higher than those with ≤6 months (aOR = 10.64, 95% CI: 2.62–−55.16, P = 0.002) (Table 8).

Table 7.

Binary logistic regression analysis of factors associated with burnout levels based on the depersonalization subscale.

Variable	Category	Low	Moderate	Univariable OR (95% CI)	Multivariable OR (95% CI)
Age (years)	Mean (SD)	24.9 (1.2)	24.4 (1.3)	0.66 (0.38–1.05), p = 0.113	0.73 (0.37–1.19), p = 0.266
Sex	Female	18 (58.1)	13 (41.9)	-	-
	Male	22 (61.1)	14 (38.9)	0.88 (0.33–2.36), p = 0.800	0.82 (0.28–2.40), p = 0.722
Marital status	Ever married	5 (50.0)	5 (50.0)	-	-
	Never married	35 (61.4)	22 (38.6)	0.63 (0.16–2.50), p = 0.500	0.80 (0.18–3.61), p = 0.762
Status of living	Alone	5 (100.0)		-	-
	Not Alone	35 (56.5)	27 (43.5)	NE*	NE*
Duration of internship (months completed)	Less than or equal to 6 months	18 (56.2)	14 (43.8)	-	-
	More than 6 months	22 (62.9)	13 (37.1)	0.76 (0.28–2.02), p = 0.582	1.10 (0.34–3.82), p = 0.878
Average weekly working hours	Mean (SD)	38.2 (14.5)	35.9 (9.8)	0.99 (0.95–1.02), p = 0.451	0.99 (0.94–1.04), p = 0.654
Job satisfaction score (out of 100)	Mean (SD)	80.6 (15.6)	72.4 (20.1)	0.74 (0.54–1.00), p = 0.077	0.74 (0.54–1.10), p = 0.120
Variable	Category	Low	High	Univariable OR (95% CI)	Multivariable OR (95% CI)
Age (years)	Mean (SD)	24.9 (1.2)	24.6 (1.2)	0.85 (0.58–1.20), p = 0.361	0.74 (0.44–1.21), p = 0.244
Sex	Female	18 (41.9)	25 (58.1)	-	-
	Male	22 (46.8)	25 (53.2)	0.82 (0.35–1.88), p = 0.637	0.87 (0.32–2.31), p = 0.776
Marital status	Ever married	5 (71.4)	2 (28.6)	-	-
	Never married	35 (42.2)	48 (57.8)	3.43 (0.70–24.92), p = 0.155	3.85 (0.61–37.73), p = 0.182
Status of living	Alone	5 (26.3)	14 (73.7)	-	-
	Not Alone	35 (49.3)	36 (50.7)	0.37 (0.11–1.07), p = 0.080	0.42 (0.11–1.50), p = 0.196
Duration of internship (months completed)	Less than or equal to 6 months	18 (39.1)	28 (60.9)	-	-
	More than 6 months	22 (50.0)	22 (50.0)	0.64 (0.28–1.48), p = 0.301	1.78 (0.59–5.88), p = 0.320
Average weekly working hours	Mean (SD)	38.2 (14.5)	37.3 (16.3)	1.00 (0.97–1.02), p = 0.771	1.00 (0.97–1.04), p = 0.857
Job satisfaction score (out of 100)	Mean (SD)	80.6 (15.6)	62.4 (22.9)	0.60 (0.43–0.74), p < 0.001	0.54 (0.39–0.74), p < 0.001

Outcome: Burnout level (low, moderate, high), based on the depersonalization subscale (reference category: low).

^*NE, not estimable due to sparse data or separation; estimates are unstable and not reported.

Job satisfaction ORs are reported per 10-point increase in score.

Table 8.

Binary logistic regression analysis of factors associated with burnout levels based on the personal accomplishment subscale.

Variable	Category	Low	Moderate	Univariable OR (95% CI)	Multivariable OR (95% CI)
Age (years)	Mean (SD)	24.4 (1.0)	25.0 (1.7)	1.52 (0.96–2.93), p = 0.132	1.41 (0.92–2.60), p = 0.161
Sex	Female	10 (37.0)	17 (63.0)	-	-
	Male	10 (40.0)	15 (60.0)	0.88 (0.29–2.72), p = 0.826	0.56 (0.14–2.09), p = 0.402
Marital status	Ever married	1 (25.0)	3 (75.0)	-	-
	Never married	19 (39.6)	29 (60.4)	0.51 (0.02–4.31), p = 0.571	1.19 (0.05–14.93), p = 0.899
Status of living	Alone	5 (55.6)	4 (44.4)	-	-
	Not Alone	15 (34.9)	28 (65.1)	2.33 (0.54–10.71), p = 0.254	2.87 (0.51–18.18), p = 0.235
Duration of internship (months completed)	Less than or equal to 6 months	16 (51.6)	15 (48.4)	-	-
	More than 6 months	4 (19.0)	17 (81.0)	4.53 (1.32–18.62), p = 0.022	4.70 (1.11–23.48), p = 0.042
Average weekly working hours	Mean (SD)	38.5 (11.8)	41.0 (18.1)	1.01 (0.98–1.05), p = 0.575	1.00 (0.96–1.04), p = 0.947
Job satisfaction score (out of 100)	Mean (SD)	76.7 (19.6)	79.5 (18.7)	1.10 (0.82–1.48), p = 0.602	0.90 (0.60–1.34), p = 0.662
Variable	Category	Low	High	Univariable OR (95% CI)	Multivariable OR (95% CI)
Age (years)	Mean (SD)	24.4 (1.0)	24.6 (1.0)	1.28 (0.76–2.36), p = 0.389	1.46 (0.66–3.36), p = 0.354
Sex	Female	10 (25.6)	29 (74.4)	-	-
	Male	10 (21.7)	36 (78.3)	1.24 (0.45–3.42), p = 0.673	1.07 (0.31–3.58), p = 0.915
Marital status	Ever married	1 (11.1)	8 (88.9)	-	-
	Never married	19 (25.0)	57 (75.0)	0.38 (0.02–2.24), p = 0.370	0.53 (0.02–6.34), p = 0.654
Status of living	Alone	5 (33.3)	10 (66.7)	-	-
	Not Alone	15 (21.4)	55 (78.6)	1.83 (0.51–6.04), p = 0.329	2.25 (0.52–9.83), p = 0.272
Duration of internship (months completed)	Less than or equal to 6 months	16 (35.6)	29 (64.4)	-	-
	More than 6 months	4 (10.0)	36 (90.0)	4.97 (1.62–18.81), p = 0.009	10.64 (2.62–55.16), p = 0.002
Average weekly working hours	Mean (SD)	38.5 (11.8)	35.1 (12.6)	0.98 (0.94–1.02), p = 0.284	0.96 (0.91–1.01), p = 0.144
Job satisfaction score (out of 100)	Mean (SD)	76.7 (19.6)	64.9 (21.5)	0.74 (0.54–1.00), p = 0.038	0.54 (0.31–0.74), p = 0.003

Outcome: Burnout level (low, moderate, high), based on the personal accomplishment subscale (reference category: low). Job satisfaction ORs are reported per 10-point increase in score.

Discussion

Overall Prevalence

In the present study, the overall prevalence of burnout among medical interns was 7.7%. This rate is lower than those reported in local and regional studies on medical interns that similarly used the tridimensional approach: 15% in Oman [20] and 16.7% in Jeddah, Saudi Arabia [19]. However, the prevalence rate found in the present study is substantially lower than in studies that also included medical interns and used the MBI, but either used a liberal definition of burnout (ie, high EE and/or high DP) (57.5% in Brazil) [28] or did not specify the definition of burnout (60% among COVID-19–positive interns in India [29] and 90% in Morocco [30]). Collectively, this indicates that the operational definition of burnout when using the MBI-HSS substantially influences the reported prevalence rates, thereby indicating the need for standardization of the definition of burnout to improve comparability in research and for assisting policymakers. Similarly, in studies across Europe that assessed burnout among physicians or medical staff using the tridimensional approach, prevalence was found to range from 2.5% to 19.4% [26,31–35]. Therefore, differences in the reported burnout rates are likely due to differences in population and setting as well as in healthcare systems and workload intensity, in addition to factors such as institutional and cultural support, highlighting the important role of local context in shaping burnout risk.

A notable finding of the current study is the dissociation between overall burnout prevalence and subscale burden, with a substantial proportion of interns reporting low PA (55.6%) and high DP (42.7%) despite the overall burnout rate being only 7.7%. This may indicate that burnout among medical interns manifests across individual dimensions at different stages (ie, fragmented burnout), or that a large proportion of participants were in a pre-burnout stage. This dissociation also suggests that domain-specific burnout should be independently considered; for example, although EE was not that high, the high DP and low PA may indicate early or distinct manifestations of burnout.

Demographic and Social Determinants of EE Among Medical Interns

Older age, male sex, and not living alone were found to be significantly associated with a lower risk of EE. These findings are consistent with prior research suggesting that personal experiences, sex-related stressors, and the presence of social support systems are factors associated with lower burnout levels [36–38].

The association between older age and reduced EE (OR = 0.36, 95% CI: 0.14–0.77, P = 0.017) aligns with prior research reporting higher burnout rates in younger healthcare professionals. Limited clinical experience, underdeveloped coping mechanisms, and challenges in transitioning from academic settings to demanding clinical environments have been reported as factors contributing to this association [39]. Studies among medical residents have also reported inverse correlations between age and burnout dimensions, such as DP, reinforcing the notion that greater professional experience is associated with higher emotional regulation and resilience [40]. Moreover, younger physicians, particularly those in training or in the early stages of their careers, may face an increased risk of burnout due to extended working hours, greater responsibilities, and limited control over clinical decisions [41]. Interventions such as structured training, time management, stress management, and the involvement of junior doctors in decision-making processes have been proposed to increase their sense of agency and mitigate stress-related outcomes [41]. A possible explanation for higher resilience among older interns is accumulation of adaptive strategies, greater self-efficacy in clinical practice, and a more established professional identity. Conversely, other studies have suggested that age alone is not a consistent predictor of burnout. A systematic review of postgraduate medical trainees reported that most studies found no significant association between age and burnout prevalence [42]. These discrepancies highlight the multifaceted nature of burnout, suggesting that while age and experience can influence burnout risk, they operate within a broader context shaped by both individual vulnerabilities and systemic pressures.

The current study found that male interns had an 83% lower likelihood of experiencing EE than female interns (aOR = 0.17, 95% CI: 0.03–0.68; P = 0.021). Similarly, a study from the United States found that female medical students had higher burnout prevalence (78%) than males (72%); however, it should be noted that the study only used a 2-item MBI [43]. Similar findings have been reported among physicians in the United States, and this disparity in EE was attributed to factors such as higher workloads, increased emotional labor, and greater demands for patient-centered communication among female than male physicians [44]. Several studies have also shown that female doctors are more likely to experience difficulties in balancing professional responsibilities with personal and family roles [45–47], highlighting it as a potential contributor to burnout, particularly EE. In fact, a Norwegian study has reported that female physicians had higher EE scores than males, and the strongest predictors of burnout were workload and conflicts between work and home life [48].

In addition to age and sex, social support is another potentially important factor associated with burnout. Medical interns who did not live alone had lower odds of high EE compared with those living alone (OR = 0.22, 95% CI: 0.07–0.77, P = 0.015). Although the study did not account for confounding factors, a possible explanation for the current findings is that presence of family members, spouse, or roommates may serve as a buffer against work-related stressors, offering both emotional and practical support. Similarly, a study of respiratory therapists in Saudi Arabia revealed that single individuals had significantly greater odds of severe burnout than married individuals, further highlighting the role of social support in mitigating EE [49]. Similarly, research has shown that healthcare workers who perceive strong family support are significantly less likely to experience burnout, highlighting the potential protective effect of a robust social network [50]. Moreover, research conducted in Japan during the COVID-19 pandemic showed that increased social support was significantly associated with reduced odds of EE among healthcare professionals, supporting the role of social connections in mitigating burnout [51]. Emotional support from cohabitants may foster a sense of belonging, whereas practical support, such as assistance with household responsibilities, may enable medical interns to recover more effectively from the demands of their clinical duties.

These findings highlight the multifaceted nature of burnout among medical interns and emphasize the importance of demographic and social determinants in mitigating EE. Older interns may have benefited from accumulated professional resilience, whereas male interns may be less exposed to sex-related stressors that are associated with burnout. Additionally, social support structures, particularly for those living with family or partners, may provide essential emotional and logistical support, which in turn may reduce the burden of EE. Addressing these factors through institutional interventions—such as targeted mentoring for younger interns, sex-sensitive policies to support female professionals, and initiatives that promote social connectedness—may help reduce burnout and improve the well-being of medical interns.

The Role of Job Satisfaction in Mitigating Burnout Among Medical Interns

The present study found that a significant association between job satisfaction and lower levels across all 3 burnout domains. Specifically, each 10-point increase in job satisfaction was associated with a 34% reduction in the adjusted odds of EE (aOR = 0.66, 95% CI: 0.48–0.90, P = 0.005), a 46% reduction in the adjusted odds of DP (aOR = 0.54, 95% CI: 0.39–0.74, P < 0.001), and a 46% reduction in the adjusted odds of low PA (aOR = 0.54, 95% CI: 0.31–0.74, P = 0.003). These findings are consistent with the existing literature. For instance, a study from Oman found that job dissatisfaction was a significant predictor of both EE and DP among medical interns [20]. Likewise, research in Tunisia reported that dissatisfaction with salary, task allocation, and limited resources was associated with reduced resilience and a heightened risk of burnout [52]. Across diverse healthcare professions, higher job satisfaction has been consistently associated with lower levels of EE, DP, and overall burnout. Similar findings were reported across various healthcare professions, including mental health professionals, radiographers, hospital staff, nurses, and emergency health workers. In these settings, satisfaction with compensation, supportive work environments, and role clarity has been linked to reduced burnout, whereas occupational stress and its psychological and physical consequences are associated with poorer outcomes [36,38,53,54]. Collectively, the published evidence highlights the important role of job satisfaction in mitigating burnout. Implementing strategies that align professional and organizational values, enhance team dynamics, and manage workload demands may help foster a more supportive work environment [55]. Furthermore, resilience can be strengthened through effective leadership practices and meaningful recognition [52].

Impact of Internship Duration on PA among Medical Interns

Medical interns who had completed > 6 months of internship had significantly greater odds of reduced PA than those who had completed ≤6 months of internship (OR = 4.97, 95% CI: 1.62–18.81; P = 0.009), suggesting an association that needs to be investigated further in future studies. However, the very wide confidence interval in the multivariate analysis (aOR = 10.64, 95% CI: 2.62–55.16) suggests considerable uncertainty around the effect estimate; therefore, the finding should be interpreted with caution. Nonetheless, the findings of the current study align with the literature on increased burnout among residents as they advance in training. A longitudinal study of family medicine residents found that indicators of burnout, including EE and DP, increased from the start of residency through the beginning of the second year and remained elevated through graduation. Notably, emotional intelligence, a protective factor against burnout, declined during this period and was lower at graduation than at the start of residency [56].

The increased risk of low PA among interns beyond six months may be attributed to multiple factors. The initial enthusiasm for starting clinical practice may wane over time, leading to decreased motivation and satisfaction. Additionally, the cumulative stress of prolonged working hours, high workload, and the emotional toll of patient care can contribute to feelings of ineffectiveness. A systematic review and meta-analysis reported that residents are subject to sleep deprivation, high workload, and unsatisfactory salaries, which may increase their vulnerability to burnout, which interferes with their ability to manage diagnostic dilemmas and make complex treatment decisions [57].

To mitigate this risk, medical institutions should consider implementing supportive measures targeting interns during their training. Interventions such as wellness training, mentorship programs, workload management, and resilience training have been shown to be potentially effective in reducing burnout among residents. A scoping review of burnout interventions among medical residents indicated that longitudinal wellness programs and similar strategies can reduce burnout rates, but the robustness and generalizability of these findings are limited by the methodological constraints of the reviewed studies [58].

Conclusions

This observational cross-sectional study found that among medical interns from 2 major cities of the Eastern Province of Saudi Arabia, the overall prevalence of burnout was 7.7%. However, there was a substantial disconnect between this overall burnout prevalence, which was low, and subscale burden, which was high for PA and DP. Between subscales, low PA was most prevalent, followed by DP and EE. Older age, male sex, and not living alone were associated with lower EE risk. Further, higher job satisfaction was significantly associated with lower levels of EE and DP and higher levels of PA. Medical interns with > 6 months of training had greater odds of low PA. These findings suggest that internship programs could integrate strategies for enhancing social support and job satisfaction as well as for monitoring interns with > 6 months of training for early detection of risk of low PA. Future longitudinal studies could determine the reasons for the low overall burnout prevalence, progression from subscale burden to burnout, and interventions targeting identified burnout predictors.

Strengths and Limitations

This study has several methodological strengths. It contributes to the limited literature examining the prevalence of burnout and its associated factors among medical interns in the Eastern Province of Saudi Arabia, addressing a notable gap in the regional literature. The use of validated instruments, namely the MBI-HSS, PHQ-2, and GAD-2, supports the reliability and validity of the findings. The inclusion of a wide range of demographic, occupational, and psychosocial variables allowed for a comprehensive assessment of factors contributing to burnout. Recruiting participants from multiple training hospitals in Dammam and Al Khobar improved the contextual relevance and may enhance the generalizability of the findings within the region.

Several limitations should also be noted. The cross-sectional design precludes causal inferences regarding burnout and its associated factors. Reliance on self-reported data may have introduced response and social desirability bias. In addition, the use of convenience sampling through online distribution (email and WhatsApp) may have introduced selection bias, as individuals who are more engaged, more distressed, or more motivated to participate may have been overrepresented. This may have influenced the estimated prevalence of burnout and should be considered when interpreting the findings. Although the sample size was adequate for the primary analyses, it was moderate, which may have limited the ability to detect more subtle associations. As there were only 15 events in the high EE category, the events-per-variable was considerably lower than recommended levels. This may have resulted in overfitting the multivariable logistic regression model; therefore, the multivariable findings should be considered exploratory, and the adjusted estimates should be interpreted with caution. The findings may not be fully generalizable to interns in other regions of Saudi Arabia or in different healthcare systems. Potential confounders such as personality traits and coping mechanisms were not assessed, which may have influenced the observed associations. Additionally, multiple statistical comparisons were conducted without formal adjustment for multiplicity, which may have increased the risk of type I error and false-positive findings; therefore, statistically significant associations should also be interpreted with appropriate caution.

Data Availability Statement

The raw data supporting the conclusions of this article can be made available by the author on request. The raw data supporting the findings of this article will be made available by the author on request.