Sage Journals: Discover world-class research

Abstract

Introduction

Burnout among nurses has emerged as a critical issue in healthcare and is gaining considerable attention due to its profound negative effects. The pervasive nature and significant effects that burnout might hold underscore the crucial need to assess this issue and its contributing factors among nurses. However, there is an evident gap in research precisely addressing this issue among nurses working in private hospitals in the Gulf Region.

Objective

This study aims to assess the prevalence and associated factors of burnout among nurses at private tertiary hospitals in Saudi Arabia and the United Arab Emirates.

Method

This is a cross-sectional study, and the data were collected by an electronic self-administered survey. This multicenter study involved a sample of 616 nurses and was performed in six different private tertiary care hospitals which belong to the largest private healthcare group in the Gulf Region. The Maslach Burnout Inventory—Human Services Survey was utilized to assess burnout levels.

Results

The study's results revealed that the overall burnout level was 67.2%. Notably, 82.8% of the participants were identified as having high Emotional Exhaustion (EE), 56.8% for high Depersonalization (DP), and 44.6% for low Personal Accomplishment (PA). The mean score for the EE dimension was 36.79 ± 10.34, the DP dimension was 13.91 ± 6.65, and the PA dimension had a mean score of 32.37 ± 7.73.

Conclusion

The conclusions revealed a significant prevalence of burnout among nurses working within the private sector in Saudi Arabia and the United Arab Emirates. This underscores the persistent problem of burnout among nurses, which necessitates targeted interventions.

Keywords

burnout nurse nursing prevalence associated factors private Saudi Arabia United Arab Emirates

Introduction

Burnout is a serious issue driven by unrelenting work-related stress. Burnout is a combination of psychological, emotional, and physical strain resulting from increased exposure to workplace stressors (Maslach et al., 1997). Nurse burnout is emerging as a critical healthcare issue and has received considerable attention due to its subtle negative impact on various aspects, including quality of life, nurse productivity, turnover rates, and medication administration errors (Jun et al., 2021; Kelly et al., 2021; Khatatbeh et al., 2022; Montgomery et al., 2021). The nature and possible negative effects of burnout have been recognized as critical when addressing this issue and the responses it has provided to nurses. Meanwhile, there may be a criticism, particularly relating to the issue of nurses working in private hospitals in Gulf countries.

Review of Literature

Burnout is considered to be among the most prevelant and frustrating characteristics associated with work in different jobs (Schaufeli et al., 2009). According to the 11th revision of the International Classification of Diseases (ICD-11), burnout is referred to as an occupational phenomenon that results from severe stress in the workplace that should not be overlooked (Harrison et al., 2021). Continued work stress, excessive workload, long working hours, and poor employee retention are all factors that can lead to burnout (Al-Omari et al., 2019; Cañadas-De La Fuente et al., 2015; Lin et al., 2021; Rotenstein et al., 2023).

Burnout manifests itself in three main dimensions, including Emotional Exhaustion (EE), Depersonalization (DP), as well as a strain on Personal Accomplishment (PA), all of which can particularly have a significant negative impact on nurses (Jun et al., 2021; Maslach, 2003). EE occurs when an individual experiences pain and emotional distress beyond work hours, and seems to be unable to attract the most emotional support or companionship. Meanwhile, the dimension of PA is a reduction in the participation of any personal aspect of work. With higher levels of burnout, individuals are more likely to experience a positive decrease in their self-efficacy behaviors and tasks, while at lower levels of personal self-efficacy, individuals are more likely to experience a decrease in self-efficacy behaviors and job performance. The physical, psychological, and interpersonal/social symptoms of burnout persist over time (Maslach & Jackson, 1981).

Generally, research shows that healthcare providers are at great risk of developing burnout due to the high level of stressors and being in a work environment that involves direct interactions with a high number of patients who have severe illnesses and deaths daily (Engelbrecht et al., 2008; Khamisa et al., 2013; Maslach, 2003). In reviewing previously published studies, the prevalence of burnout among nurses and other healthcare providers varies greatly and is influenced by the geographical region and the nature of work. While burnout prevalence was lowest in Central Asia and Europe, sub-Saharan regions of Africa reported the highest rates (Owuor et al., 2020; Woo et al., 2020). A high prevalence of burnout was reported among nurses (Frajerman et al., 2019; Khamisa et al., 2013; Rada & Johnson-Leong, 2004). Around 11.2% of nurses experience burnout worldwide (Woo et al., 2020). Around 37% of nurses in nursing homes and 33% of hospital nurses have experienced burnout (McHugh et al., 2011; Reith, 2018). A study reported that burnout levels were significantly associated with certain demographic factors, including nationality and the working unit. This suggests that these variables may play a key role in influencing burnout among nurses (Qedair et al., 2022). Another study also reported that demanding workloads and various aspects of the work environment, such as inadequate staffing ratios, poor communication between physicians and nurses, and a lack of organizational leadership, are commonly associated with burnout among nurses (Shah et al., 2024). Burnout has been well-documented among doctors, nurses, and frontline workers (Abdo et al., 2016), Egypt 2015 reported moderate burnout among 66% of the physicians and nurses in a tertiary care hospital, while (Youssef et al., 2022) Lebanon, reported moderate burnout among 90.7% of the study population. Puffer et al. (2017) demonstrated a burnout prevalence of 24.5% among U.S. physicians, while Wu et al. (2013) surveyed Chinese physicians of various specialities, demonstrating a burnout prevalence of 12.1%.

Upon reviewing the literature, it is evident that burnout can negatively impact well-being, job satisfaction, and mental health and is strongly associated with staff turnover, low morale, absenteeism, and other issues, all of which can have serious repercussions on the quality of patient care and safety (Al-Omari et al., 2019; Dall’Ora et al., 2020; Edú-Valsania et al., 2022; Lee et al., 2023; Salama et al., 2022). Given the profound negative influence that burnout can have on healthcare delivery and the limitedness of studies focusing specifically on nurses in private hospitals within Saudi Arabia and the United Arab Emirates, this study aims to assess the prevalence and associated factors of burnout among nurses at private tertiary hospitals in Saudi Arabia and the United Arab Emirates.

Method

Design

This study utilized an exploratory, descriptive, cross-sectional design. The data were gathered by an electronic self-administered survey that was distributed between January and March 2019, before the COVID-19 pandemic. Noting that the results reflect burnout levels in nurses before the onset of the pandemic, which may have had subsequent effects on burnout rates and healthcare work environments. This multicenter study was conducted in six private tertiary care hospitals belonging to the largest private healthcare group in Saudi Arabia and the United Arab Emirates. The data presented in this paper was gathered as part of a broader research project that aimed to explore the factors of burnout among private healthcare providers in Saudi Arabia (Al-Omari et al., 2019). While the original project included all healthcare providers, this article specifically focuses on nurses, narrowing the scope to provide a more detailed analysis of their burnout experiences. By concentrating on nurses, this study aims to identify key trends and associated factors that may otherwise be obscured in broader analyses involving multiple healthcare professionals.

Research Question

What is the prevalence of burnout among healthcare professionals in private hospitals in Saudi Arabia and the United Arab Emirates?

What are the key factors associated with burnout among healthcare professionals working in private hospitals in Saudi Arabia and the United Arab Emirates?

Sample

The study consisted of nurses working in the six selected private tertiary care hospitals across the Gulf region of KSA and the UAE, regardless of their nationality. This study focuses exclusively on the subset of nurses from the original project. From a total of 1,150 email invitations distributed, 900 responses were received. After removing incomplete, missing, and ineligible responses, 616 were included in the final analysis, allowing for a more in-depth analysis of factors specifically affecting nurses within the broader healthcare provider population. This study used a convenience sampling approach, and a power analysis was conducted prior to data collection to ensure that a sample of 616 would provide 80% power at a 95% CI to measure moderate effect sizes.

Data Collection and Instruments

An anonymous self-administered electronic survey was distributed via nurses’ email. An online survey was chosen because it expanded the capability of reaching the needed number of participants instantly. One-time access for each user was set in the survey settings to ensure that participants could submit the survey only once, thereby preventing replication. To ensure that the required sample size for the study was reached, follow-up emails were systematically distributed at 3-day intervals. This approach aimed to enhance participant engagement and maximize response rates by providing repeated reminders, thereby increasing the likelihood of participation, including among individuals who may not check their emails regularly.

This electronic survey consisted of two parts: sociodemographics and the Maslach Burnout Inventory—Human Services Survey (MBI-HSS). The sociodemographics had five items, including which hospital they work at, their gender (male/female), marital status (single/married/divorced) citizenship (citizen/noncitizen), and total years of experience (1–5 years/6–10 years/11 years and above), whilst the MBI had a total of 22 items. The MBI-HSS was utilized to assess burnout levels based on three dimensions, encompassing EE, DP, and PA. According to the literature, MBI-HSS has been extensively examined in numerous studies, and its reliability and validity have been proven (Lin et al., 2022; Maslach & Leiter, 2016). The Cronbach's alpha value calculated in this study was .871, which further supports the reliability of the measurement. The Cronbach's alpha coefficients for the subscales were EE at .85, DP at .716, and PA at .795. High scores in EE and DP, along with low scores in PA, indicate a higher risk of burnout. Based on the third edition of the MBI-HSS, the established cutoff points for identifying high levels are a score of 27 or higher for high EE, a score of 13 or higher for high DP, and a score of 31 or lower for high PA. Burnout was identified based on the criteria that include either “high EE and high DP” or “high EE and low PA” (Lim et al., 2019).

Ethical Approval and Informed Consent to Participate

Ethical approval was granted by the Institutional Review Board of the selected institution (Approval No. RC 18.11.21). Participation was completely voluntary, and the study survey included a consent statement indicating an agreement to take part in the study. Confidentiality was maintained throughout the study. Participants were assured that the gathered information would be used for research purposes only.

Statistical Analysis

Data were first entered into an Excel spreadsheet. Afterwards, the data were imported into Statistical Package for the Social Sciences (SPSS) version 29.0.1 for the analysis process. Missing values were handled using missing value analysis. To analyze the gathered data, both descriptive and inferential statistics were carried out. Mean and standard deviations were calculated as part of the descriptive statistics. To predict the statistical significance between the variables, independent samples t-test, analysis of variance (ANOVA), and correlational analysis were performed as appropriate. The study tested specific hypotheses related to differences in burnout dimensions across demographic variables. The variables tested included gender, marital status, citizenship, and years of experience. Specifically, independent samples t-tests were used to compare mean differences in the burnout dimensions based on gender and citizenship variables, while ANOVA was applied to assess differences across multiple categorical groups, including marital status and years of experience. Statistically significant results were determined based on a confidence interval of 95% and a p-value of ≤ .05. These thresholds were applied to assess the significance of the observed differences in burnout dimensions between the different demographic groups. Confidence intervals were used to estimate the range in which the true population parameter is likely to fall, ensuring the robustness and reliability of the findings.

Results

A total of 616 nurses were included in the current study to assess the prevalence and predictors of burnout among nurses at private tertiary hospitals in Saudi Arabia and the United Emirates. The demographics of the current study showed that the majority of participants were female, and more than half were single. Approximately half of the participants had between 1 and 5 years of experience. As illustrated in Table 1, among the participants, 518 (84.1%) were female, 312 (52.3%) were single, and 279 (45.3%) were married, 584 (94.8%) were foreign nurses. 284 (46.1%) had 0–5 years of experience, and 267 (43.3%) had 6–10 years of experience.

Table 1.

Nurses’ Sociodemographics (n = 616).

Characteristics	Subgroups	Frequency (%)
Centers	Hospital A	109 (17.7%)
	Hospital B	129 (20.9%)
	Hospital C	60 (9.7%)
	Hospital D	51 (8.3%)
	Hospital E	130 (21.1%)
	Hospital F	137 (22.2%)
Gender	Male	98 (15.9%)
Gender	Female	518 (84.1%)
Marital status	Single	312 (52.3%)
	Married	279 (45.3%)
	Divorced	15 (2.4%)
Citizenship	Citizen	32 (5.1%)
Citizenship	Foreign	584 (94.8%)
Years of experience	0–5 years	284 (46.1%)
	6–10 years	267 (43.3%)
	> 10 years	65 (10.6%)

Table 2 presents descriptive statistics for burnout dimensions. The mean score for the EE dimension was 36.79 ± 10.34, the DP dimension had a mean score of 13.91 ± 6.65, and the PA dimension had a mean score of 32.37 ± 7.73.

Table 2.

Descriptive Statistics for Burnout Dimensions.

Dimensions	Mean (SD)	Minimum	Maximum	Range
Emotional exhaustion	36.79 (±10.34)	7	54	47
Depersonalization	13.91 (±6.65)	0	30	30
Personal accomplishment	32.37 (±7.73)	0	48	48

Table 3 presents the prevalence of burnout and its dimensions among nurses. The analysis indicated that 82.8% of the participants were identified as high for EE, 44.6% high for DP, and 56.8% for low PA. The overall burnout level was 67.2%.

Table 3.

Prevalence of Burnout and its Dimensions Among Nurses.

Overall Burnout Level, n (%)	High Emotional Exhaustion	High Depersonalization	Low Personal Accomplishment
414 (67.2%)	510 (82.8%)	350 (56.8%)	227 (44.6%)

The relationship between the dimensions using inferential statistics, and their correlation was calculated and examined by heatmap correlation and computed by Pearson's Correlation r. EE and DP have the strongest correlation (r = .62), suggesting that as EE increases, DP also tends to increase. PA is positively correlated with both EE and DP (r = .29 and .30, respectively), but these correlations are weaker compared to the correlation between EE and DP (Figure 1).

Figure 1.

Heatmap of Burnout Levels/dimensions. EE: Emotional Exhaustion, PA: Personal Accomplishment, DP: Depersonalization R = −1 to +1.

Table 4 presents the associations between participants’ sociodemographic characteristics and burnout dimensions. The study revealed significant differences in EE based on citizenship and years of experience, while gender and marital status did not show statistically significant differences. Foreign nurses exhibited higher EE levels (36.99 ± 10.24) compared to citizens (33.06 ± 11.68, p-value = .036), suggesting that noncitizen nurses may experience greater work-related stress, possibly due to challenges related to workplace integration and job security. Similarly, nurses with less experience (0–5 years) had significantly higher EE levels (37.48 ± 9.29) compared to those with over 10 years of experience (33.66 ± 10.80, p-value = .027), indicating that early-career nurses may be more susceptible to burnout due to increased job demands and limited coping strategies. However, there were no significant differences in EE between male (37.15 ± 10.39) and female nurses (36.73 ± 10.34, p-value = .717) or across marital status categories (p = .153). Differences in EE, PA and DP levels were found across different hospitals. PA and DP did not show significant variations across any of the remaining sociodemographic variables.

Table 4.

Participants’ Sociodemographics and Burnout Dimensions Mean Comparisons (n = 616).

Variables	Burnout Dimensions
	EE		PA		DP
	M (SD)	p-Value	M (SD)	p-Value	M (SD)	p-Value
Centers		<.001**		.003		<.001**
Hospital A	27.09 (±9.55)		5.34 (±2.93)		32.36 (±9.0)
Hospital B	33.93 (±8.97)		9.55 (±1.82)		30.87 (±6.89)
Hospital C	38.91 (±11.44)		16.05 (±7.08)		34.5 (±8.79)
Hospital D	43.43 (±7.44)		19.69 (±3.78)		35.38 (±7.94)
Hospital E	40.62 (±8.57)		17.87 (±4.42)		32.0 (±6.74)
Hospital F	40.18 (±7.84)		17.97 (±4.62)		32.09 (±7.32)
Gender
Male	37.15 (±10.39)	.717	31.71 (±8.62)	.404	14.77 (±6.96)	.161
Female	36.73 (±10.34)		32.49 (±7.45)		13.74 (±6.57)
Marital status
Single	36.18 (±10.00)	.153	33.04 (±11.25)	.073	13.45 (±10.00)	.151
Married	37.63 (±10.34)		31.67 (±10.00)		14.33 (±6.078)
Divorced	34.00 (±11.53)		31.00 (±21.00)		15.73 (±13.90)
Citizenship
Citizen	33.06 (±11.68)	.036**	31.18 (±9.22)	.374	14.46 (±7.04)	.626
Foreign	36.99 (±10.24)		32.43 (±7.64)		13.87 (±6.63)
Experience
0–5 years	37.48 (±09.29)	.027**	32.07 (±7.32)	.487	14.28 (±6.11)	.161
6–10 years	36.82 (±10.91)		32.45 (±7.87)		13.85 (±6.94)
> 10 years	33.66 (±10.80)		33.66 (±9.83)		12.54 (±7.51)

Note. EE = emotional exhaustion; PA = personal accomplishment; DP = depersonalization.

**p-value ≤ .05.

Generalized Linear Model Between Burnout and Demographic Factors

A multivariate generalized linear model (GLM) is a type of regression model that is applied to measure the strength of the relationship between burnout levels (multivariate) and other associated factors. Table 5 presents the GLM for predicting different dimensions of burnout based on demographic variables. In this case, the dependent variables considered were EE, PA, and DP while the independent variables consisted of gender, marital status years of experience, centers, and nationality. The multivariate GLM analysis used to model and predict burnout dimensions based on demographic factors showed that for centers, there were highly significant effects across all burnout dimensions: EE (F = 21.638, p-value < .001), PA (F = 6.624, p-value < .001), and DP (F = 1082.762, p-value < .001). These results suggest that burnout levels differ significantly across centers. As for gender, no significant effects were found with EE (F = 0.056, p-value = .813), PA (F = 0.025, p-value = .875), or DP (F = 0.209, p-value = .648), indicating that gender does not play a significant role in burnout.

Table 5.
Multivariate GLM of Modeling and Predicting Different Burnout Dimensions With Demographics.

Independent Variables Dependent Variables SS MS F-Statistic p-Value

Centers Emotional exhaustion 22.650 4.530 21.638 <.001*

Personal accomplishment 19.769 3.954 6.624 <.001*

Depersonalization 290.080 58.016 1082.762 <.001*

Gender Emotional exhaustion 0.012 0.012 0.056 .813

Personal accomplishment 0.015 0.015 0.025 .875

Depersonalization 0.011 0.011 0.209 .648

Nationality Emotional exhaustion 1.041 1.041 4.973 .026

Personal accomplishment 1.283 1.283 2.149 .143

Depersonalization 0.315 0.315 5.877 .016

Years of Experience Emotional exhaustion 1.095 0.547 2.615 .074

Personal accomplishment 0.679 0.339 0.569 .567

Depersonalization 0.078 0.039 0.725 .485

Marital status Emotional exhaustion 0.090 0.045 0.215 .807

Personal accomplishment 3.414 1.707 2.860 .058

Depersonalization 0.486 0.243 4.535 .011

GLM = generalized linear model.

Nationality had a significant effect on EE (F = 4.973, p = .026) and DP (F = 5.877, p = .016), but not on PA (F = 2.149, p = .143), suggesting that foreign nurses may experience higher emotional exhaustion and depersonalization compared to citizens. Years of experience did not show significant effects for EE (F = 2.615, p = .074), PA (F = 0.569, p = .567), or DP (F = 0.725, p = .485). Lastly, marital status was not significantly related to EE (F = 0.215, p = .807), but had a marginally significant effect on PA (F = 2.860, p = .058) and a significant effect on DP (F = 4.535, p = .011), suggesting that marital status may influence depersonalization (Table 3).

Discussion

The study revealed that the overall burnout level was 67.2%. Notably, 82.8% of participants were identified as high for EE, 56.8% for high DP, and 44.6% for low PA. These findings collectively indicate a significant prevalence of burnout among nurses working in the private sector among nurses from six different centers. Further analysis of burnout levels on sociodemographic variables revealed perceived differences. The foreign nurses recorded higher levels of EE (36.99 ± 10.24) than their mother counterparts (33.06 ± 11.68, p-value = .036), suggesting that nonmother nurses may experience greater work-related stress, possibly because my returns mimic the hams of workplace adaptation or lack of job security. Similarly, experience level played a role in burnout, with nurses with maybe 0–5 years of experience showing higher EE (37.48 ± 9.29) compared to those with higher individual experience (33.66 ± 10.80). Al-Omari's (2019) study, which is more extensive in scope, agrees with recent studies in highlighting that nurses experienced a higher rate of burnout compared to other health care professionals. The same study recognized nursing as a profession in particular with high levels of EE and burnout. The high rate of burnout observed in this study has been consistent with previous reports from other Gulf Region countries (Abdelrazek & Higazy, 2023; Chemali et al., 2019; Elbarazi et al., 2017). Similarly, recent studies have reported high rates of job compliance among nurses in Iran, a neighboring Gulf country (Khammar et al., 2018; Sohrabi et al., 2022). The case of those who have been dismissed can be explained in terms of lack of time and excessive workload. A review of 91 research papers theorized that high workload, lack of work and long shift times were associated with higher levels of compliance among nurses (Dall'Ora et al., 2020). The excessive workload and inadequate training resulting from deficiencies in nursing skills can contribute to higher levels of DP, namely more awareness of psychological and physical health problems of nurses.

Similarly, recent studies reported a high prevalence of job burnout among nurses in Iran, a neighboring country to the Gulf (Khammar et al., 2018; Sohrabi et al., 2022). Such findings might be explained by the staff shortages and work overload. A review of 91 research papers theorized that high workload, staffing shortage and long shift hours are linked to higher levels of burnout among nurses (Dall’Ora et al., 2020). Work overload and insufficient training resulting from nursing staff shortages may contribute to higher DP levels, making nurses more prone to psychological and physical health problems.

This study found that study members exhibited higher levels of EE compared to DP and PA. Possible reasons for this include staff shortages and workload. A systematic review and meta-analysis suggested that nurses, particularly in primary care who care for chronically ill patients, often develop empathy and close relationships with their patients (Monsalve-Reyes et al., 2018). This relationship may enhance the quality of care, thereby reducing DP and promoting a greater sense of personal achievement (Bicker et al., 2015). The study results are in agreement with the literature reporting on burnout when using the MBI-HSS tool. Nurses often reported that EE was due to the complex nature of the care they provide (Poku et al., 2020). In addition, one study found that reducing overload and increasing safety can prevent burnout (Gómez Sánchez et al., 2009). Nurses who experienced EE were more likely to exhibit higher levels of DP, because emotional strain increased feelings of detachment and loyalty. The complexity of this interplay increased the psychological and physical demands of the nurses and could be reflected in the mutual reinforcement traces of EE and DP. One study in the literature has investigated the relationship between demographic characteristics and dimensions of burnout (Al-Turki et al., 2010; Cañadas-de La Fuente et al., 2014; Chen et al., 2022; Choi et al., 2018; Galvez-Arevalo et al., 2023; Ramirez-Elvira et al., 2021). In this study, there was a positive association between health levels and EE, with foreign nurses showing higher levels of EE compared to their peers. In this study, samples from private institutions were the most common among foreign institutions, accounting for 94% of the sample. Because foreign nurses showed higher levels of EE, the study identified the potential for increased burnout as a pressing issue within the private sector. This observation is highly supported in the literature, as non-Saudi nurses experienced better EE compared to their Saudi counterparts (Al-Turki et al., 2010). Recently, a study found that Saudi nurses are more likely to be emotionally aware than their foreign counterparts, highlighting other issues (Qedair et al., 2022). In this study, high EE scores were affected by the years of experience. This aligns with a previous research article, in which it was reported that poor professional experience is one of the main factors associated with burnout (Ramírez-Elvira et al., 2021). A higher PA score in nurses with more advanced work experience could be associated with their own more positive attitudes toward their abilities, having the same years of experience (Faria & Maia, 2007; Hussein, 2018). The results of our study found no positive effects of marriage and marital age on measures of burnout. Similarly, many studies have observed that burnout does not affect marriage and marital survival. In contrast, recent studies have reported differences in the traces of the effects of marriage and marital age, except for one study by Choi et al. (2018) reported that marriage is associated with higher EE due to balancing family and work responsibilities. Additionally one study (Cañadas-De La Fuente et al., 2015) found that being male and being single or divorced was associated with higher levels of burnout among nurses. In a study by Al-Omari et al. (2019) when EE was examined particularly among nurses, no significant differences were found between male and female nurses, although there was a significant difference in EE levels among the whole sample of the healthcare. The specific pattern being observed is that men in other healthcare professions were more likely to have lower levels of EE, while women in other professions are more likely to have higher levels of EE.

Strengths and Limitations

The main strength of the study is including nurses from multiple private-sector institutions in Saudi Arabia and the United Arab Emirates. The study captures a broader and more representative snapshot of burnout prevalence. The main limitation of the study is the use of convenience sampling methodology may introduce selection bias to some extent and can therefore limit the generalizability of findings. Participants of the study may not represent the broader population, potentially affecting the external validity of the results. Additionally, self-reported data could be subject to response bias. Additionally, while this design is sufficient for assessing the prevalence of burnout, it provides limited insight into the intention to leave the profession due to burnout. Future research could address this limitation by employing a longitudinal or qualitative study to explore this aspect in more depth.

Implications for Practice

The findings of this study have significant implications for healthcare management and policy in private hospitals across Saudi Arabia and the United Arab Emirates. By identifying the prevalence and associated factors of burnout among healthcare professionals, this research highlights the urgent need for targeted interventions to support staff well-being and sustain workforce productivity. Implementing organizational policies that promote work–life balance, recognition, and professional development may help mitigate burnout risks.

Conclusions

The findings revealed a significant prevalence of burnout among nurses working within the private sector in Saudi Arabia and the United Arab Emirates. The results of this study underscore the pervasive problem of burnout among nurses, highlighting the need for targeted interventions. Given that the risk of burnout was higher among foreign nurses and those with less experience, targeted interventions specifically for those groups should be developed to tackle this issue. Interventions should focus on providing support, cultural competence training, and stress reduction programs. Additionally, newer nurses with less experience should receive mentorship and professional development to build resilience. Further research is needed to explore the long-term subsequent effects of burnout on quality indicators within clinical practice. Future studies should also investigate the effectiveness of specific interventions in reducing burnout, improving job satisfaction, and enhancing patient care outcomes, while also examining the role of organizational support and leadership in mitigating burnout among healthcare workers.

Supplemental Material

sj-doc-1-son-10.1177_23779608251350578 - Supplemental material for Prevalence and Associated Factors of Burnout Among Nurses at Private Tertiary Hospitals in the Gulf Region: A Cross-Sectional Multicenter Study

Supplemental material, sj-doc-1-son-10.1177_23779608251350578 for Prevalence and Associated Factors of Burnout Among Nurses at Private Tertiary Hospitals in the Gulf Region: A Cross-Sectional Multicenter Study by Abbas Al Mutair, Kawthar Alsaleh, Awatif Alrasheeday, Noura Almadani, Hanan Alyami, Muhammad Daniyal and Sana Almahmoud in SAGE Open Nursing

Supplemental Material

sj-docx-2-son-10.1177_23779608251350578 - Supplemental material for Prevalence and Associated Factors of Burnout Among Nurses at Private Tertiary Hospitals in the Gulf Region: A Cross-Sectional Multicenter Study

Supplemental material, sj-docx-2-son-10.1177_23779608251350578 for Prevalence and Associated Factors of Burnout Among Nurses at Private Tertiary Hospitals in the Gulf Region: A Cross-Sectional Multicenter Study by Abbas Al Mutair, Kawthar Alsaleh, Awatif Alrasheeday, Noura Almadani, Hanan Alyami, Muhammad Daniyal and Sana Almahmoud in SAGE Open Nursing

Independent Variables	Dependent Variables	SS	MS	F-Statistic	p-Value
Centers	Emotional exhaustion	22.650	4.530	21.638	<.001***
Personal accomplishment	19.769	3.954	6.624	<.001***
Depersonalization	290.080	58.016	1082.762	<.001***
Gender	Emotional exhaustion	0.012	0.012	0.056	.813
Personal accomplishment	0.015	0.015	0.025	.875
Depersonalization	0.011	0.011	0.209	.648
Nationality	Emotional exhaustion	1.041	1.041	4.973	.026**
Personal accomplishment	1.283	1.283	2.149	.143
Depersonalization	0.315	0.315	5.877	.016**
Years of Experience	Emotional exhaustion	1.095	0.547	2.615	.074
Personal accomplishment	0.679	0.339	0.569	.567
Depersonalization	0.078	0.039	0.725	.485
Marital status	Emotional exhaustion	0.090	0.045	0.215	.807
Personal accomplishment	3.414	1.707	2.860	.058
Depersonalization	0.486	0.243	4.535	.011**

Footnotes

ORCID iDs

Abbas Al Mutair

Kawthar Alsaleh

Awatif Alrasheeday

Noura Almadani

Hanan Alyami

Muhammad Daniyal

Sana Almahmoud

Author Contributions

Conceptualization: A.A.M. and A.A.; methodology: S.A. and A.A.M.; formal analysis: A.A.M., H.A., M.D., and K.A.; data curation: S.A. and K.A.; writing—original draft preparation: S.A., A.A., H.A., M.D., and N.A.; writing—review and editing: K.A. and S.A.; supervision: A.S. and A.A.M.; All authors have read and agreed to the published version of the manuscript.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Princess Nourah Bint Abdulrahman University Researchers Supporting Project number (PNURSP2025R386), Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.

Declaration of Conflicting Interests

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

Supplemental Material

Supplemental material for this article is available online.

References

Abdelrazek

E. M.

Higazy

O. A.

(2023). Burnout among nurses in Jazan General Hospital, Saudi Arabia: Its prevalence and associated factors. African Journal of Reproductive Health, 27(4), 43–53. https://doi.org/10.29063/ajrh2023/v27i4.5

Abdo

S. A.

El-Sallamy

R. M.

El-Sherbiny

A. A.

Kabbash

I. A.

(2016). Burnout among physicians and nursing staff working in the emergency hospital of Tanta University, Egypt. Eastern Mediterranean Health Journal, 21(12), 906–915. https://doi.org/10.26719/2015.21.12.906

Al-Omari

Al Mutair

Shamsan

Al Mutairi

(2019). Predicting burnout factors among healthcare providers at private hospitals in Saudi Arabia and United Arab Emirates: A cross-sectional study. Applied Sciences, 10(1), Article 157. https://doi.org/10.3390/app10010157

Al-Turki

Al-Dardas

Al-Gazal

Al-Maghrabi

Al-Enizi

Ghareeb

(2010). Burnout syndrome among multinational nurses working in Saudi Arabia. Annals of African Medicine, 9(4), Article 226. https://doi.org/10.4103/1596-3519.70960

Bikker

A. P.

Fitzpatrick

Murphy

Mercer

S. W.

(2015). Measuring empathic, person-centred communication in primary care nurses: Validity and reliability of the consultation and relational empathy (CARE) measure. BMC Family Practice, 16(1), Article 149. https://doi.org/10.1186/s12875-015-0374-y

Cañadas-de La Fuente

G. A.

San Luis

Manuel Lozano

Vargas

García

De La Fuente

E. I.

(2014). Evidencia de validez factorial del maslach burnout inventory y estudio de los niveles de burnout en profesionales sanitarios. Revista Latinoamericana de Psicología, 46(1), 44–52. https://doi.org/10.1016/S0120-0534(14)70005-6

Cañadas-De La Fuente

G. A.

Vargas

San Luis

García

Cañadas

G. R.

De La Fuente

E. I.

(2015). Risk factors and prevalence of burnout syndrome in the nursing profession. International Journal of Nursing Studies, 52(1), 240–249. https://doi.org/10.1016/j.ijnurstu.2014.07.001

Chemali

Ezzeddine

F. L.

Gelaye

Dossett

M. L.

Salameh

Bizri

Dubale

Fricchione

(2019). Burnout among healthcare providers in the complex environment of the Middle East: A systematic review. BMC Public Health, 19(1), Article 1337. https://doi.org/10.1186/s12889-019-7713-1

Chen

Y.-H.

Lou

S.-Z.

Yang

Tang

H.-M.

Lee

C.-H.

Jong

G.-P.

(2022). Effect of marriage on burnout among healthcare workers during the COVID-19 pandemic. International Journal of Environmental Research and Public Health, 19(23), Article 15811. https://doi.org/10.3390/ijerph192315811

10.

Choi

B.-S.

Kim

J. S.

Lee

D.-W.

Paik

J.-W.

Lee

B. C.

Lee

J. W.

Lee

H.-S.

Lee

H.-Y.

(2018). Factors associated with emotional exhaustion in South Korean nurses: A cross-sectional study. Psychiatry Investigation, 15(7), 670–676. https://doi.org/10.30773/pi.2017.12.31

11.

Dall’Ora

Ball

Reinius

Griffiths

(2020). Burnout in nursing: A theoretical review. Human Resources for Health, 18(1), Article 41. https://doi.org/10.1186/s12960-020-00469-9

12.

Edú-Valsania

Laguía

Moriano

J. A.

(2022). Burnout: A review of theory and measurement. International Journal of Environmental Research and Public Health, 19(3), Article 1780. https://doi.org/10.3390/ijerph19031780

13.

Elbarazi

Loney

Yousef

Elias

(2017). Prevalence of and factors associated with burnout among health care professionals in Arab countries: A systematic review. BMC Health Services Research, 17(1), Article 491. https://doi.org/10.1186/s12913-017-2319-8

14.

Engelbrecht

M. C.

Bester

C. l.

Van Den Berg

Van Rensburg

H. c. j.

(2008). A study of predictors and levels of burnout: The case of professional nurses in primary health care facilities in the free state 1. South African Journal of Economics, 76(s1), S15–S27. https://doi.org/10.1111/j.1813-6982.2008.00164.x

15.

Faria

D. A. P.

Maia

E. M. C.

(2007). Nursing professionals’ anxiety and feelings in terminal situations in oncology. Revista Latino-Americana de Enfermagem, 15(6), 1131–1137. https://doi.org/10.1590/S0104-11692007000600012

16.

Frajerman

Morvan

Krebs

M.-O.

Gorwood

Chaumette

(2019). Burnout in medical students before residency: A systematic review and meta-analysis. European Psychiatry, 55, 36–42. https://doi.org/10.1016/j.eurpsy.2018.08.006

17.

Gálvez-Arévalo

R. A.

Fernandez-Guzman

Kirschbaum-Chrem

J. P.

Racchumí-Vela

A. E.

Cutimbo-Mendivil

Dávila-Espinoza

Ugas-Charcape

C. F.

(2023). Prevalencia del síndrome de burnout en el personal de un hospital de tercer nivel de salud especializado en pediatría. Investigación e Innovación Clínica y Quirúrgica Pediátrica, 1(2), 11–19. https://doi.org/10.59594/iicqp.2023.v1n2.58

18.

Gómez Sánchez

M. C.

Álamo Santos

M. C.

Amador Bohórquez

Ceacero Molina

Mayor Pascual

Muñoz González

Izquierdo Atienza

(2009). Estudio de seguimiento del desgaste profesional en relación con factores organizativos en el personal de enfermería de medicina interna. Medicina y Seguridad Del Trabajo, 55(215), 52–62. https://doi.org/10.4321/S0465-546X2009000200005

19.

Harrison

J. E.

Weber

Jakob

Chute

C. G.

(2021). ICD-11: An international classification of diseases for the twenty-first century. BMC Medical Informatics and Decision Making, 21(S6), Article 206. https://doi.org/10.1186/s12911-021-01534-6

20.

Hussein

(2018). Work engagement, burnout and personal accomplishments among social workers: A comparison between those working in children and adults’ services in England. Administration and Policy in Mental Health and Mental Health Services Research, 45(6), 911–923. https://doi.org/10.1007/s10488-018-0872-z

21.

Jun

Ojemeni

M. M.

Kalamani

Tong

Crecelius

M. L.

(2021). Relationship between nurse burnout, patient and organizational outcomes: Systematic review. International Journal of Nursing Studies, 119, Article 103933. https://doi.org/10.1016/j.ijnurstu.2021.103933

22.

Kelly

L. A.

Gee

P. M.

Butler

R. J.

(2021). Impact of nurse burnout on organizational and position turnover. Nursing Outlook, 69(1), 96–102. https://doi.org/10.1016/j.outlook.2020.06.008

23.

Khamisa

Peltzer

Oldenburg

(2013). Burnout in relation to specific contributing factors and health outcomes among nurses: A systematic review. International Journal of Environmental Research and Public Health, 10(6), 2214–2240. https://doi.org/10.3390/ijerph10062214

24.

Khammar

Dalvand

Hashemian

A. H.

Poursadeghiyan

Yarmohammadi

Babakhani

Yarmohammadi

(2018). Data for the prevalence of nurses׳ burnout in Iran (a meta-analysis dataset). Data in Brief, 20, 1779–1786. https://doi.org/10.1016/j.dib.2018.09.022

25.

Khatatbeh

Pakai

Al-Dwaikat

Onchonga

Amer

Prémusz

Oláh

(2022). Nurses’ burnout and quality of life: A systematic review and critical analysis of measures used. Nursing Open, 9(3), 1564–1574. https://doi.org/10.1002/nop2.936

26.

Lee

T.-H. T.

Fuller

J. A.

Freedman

Bannon

Wilkins

J. T.

Moskowitz

J. T.

Hirschhorn

L. R.

Wallia

Evans

C. T.

(2023). The association of burnout with work absenteeism and the frequency of thoughts in leaving their job in a cohort of healthcare workers during the COVID-19 pandemic. Frontiers in Health Services, 3, Article 1272285. https://doi.org/10.3389/frhs.2023.1272285

27.

Lim

W. Y.

Ong

Hao

Abdullah

H. R.

Koh

D. L.

Mok

U. S. M.

(2019). The abbreviated maslach burnout inventory can overestimate burnout: A study of anesthesiology residents. Journal of Clinical Medicine, 9(1), Article 61. https://doi.org/10.3390/jcm9010061

28.

Lin

C.-Y.

Alimoradi

Griffiths

M. D.

Pakpour

A. H.

(2022). Psychometric properties of the Maslach Burnout Inventory for medical personnel (MBI-HSS-MP). Heliyon, 8(2), e08868. https://doi.org/10.1016/j.heliyon.2022.e08868

29.

Lin

R.-T.

Lin

Y.-T.

Hsia

Y.-F.

Kuo

C.-C.

(2021). Long working hours and burnout in health care workers: Non-linear dose-response relationship and the effect mediated by sleeping hours—A cross-sectional study. Journal of Occupational Health, 63(1), Article e12228. https://doi.org/10.1002/1348-9585.12228

30.

Maslach

(2003). Burnout: The cost of caring. Malor Books.

31.

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

32.

Maslach

Jackson

S. E.

Leiter

M. P.

(1997). Maslach Burnout Inventory. In Zalaquett

C. P.

Wood

R. J.

(Eds.), Evaluating stress: A book of resources (3rd ed., pp. 191–218). Scarecrow Education.

33.

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

34.

McHugh

M. D.

Kutney-Lee

Cimiotti

J. P.

Sloane

D. M.

Aiken

L. H.

(2011). Nurses’ widespread job dissatisfaction, burnout, and frustration with health benefits signal problems for patient care. Health Affairs, 30(2), 202–210. https://doi.org/10.1377/hlthaff.2010.0100

35.

Monsalve-Reyes

C. S.

San Luis-Costas

Gómez-Urquiza

J. L.

Albendín-García

Aguayo

Cañadas-De la Fuente

G. A.

(2018). Burnout syndrome and its prevalence in primary care nursing: A systematic review and meta-analysis. BMC Family Practice, 19(1), Article 59. https://doi.org/10.1186/s12875-018-0748-z

36.

Montgomery

A. P.

Azuero

Baernholdt

Loan

L. A.

Miltner

R. S.

Raju

Patrician

P. A.

(2021). Nurse burnout predicts self-reported medication administration errors in acute care hospitals. Journal for Healthcare Quality, 43(1), 13–23. https://doi.org/10.1097/JHQ.0000000000000274

37.

Owuor

R. A.

Mutungi

Anyango

Mwita

C. C.

(2020). Prevalence of burnout among nurses in sub-Saharan Africa: A systematic review. JBI Evidence Synthesis, 18(6), 1189–1207. https://doi.org/10.11124/JBISRIR-D-19-00170

38.

Poku

C. A.

Donkor

Naab

(2020). Determinants of emotional exhaustion among nursing workforce in urban Ghana: A cross-sectional study. BMC Nursing, 19(1), Article 116. https://doi.org/10.1186/s12912-020-00512-z

39.

Puffer

J. C.

Knight

H. C.

O'Neill

T. R.

Rassolian

Bazemore

A. W.

Peterson

L. E.

Baxley

E. G.

(2017). Prevalence of burnout in board certified family physicians. The Journal of the American Board of Family Medicine, 30(2), 125–126. https://doi.org/10.3122/jabfm.2017.02.160295

40.

Qedair

J. T.

Balubaid

Almadani

Ezzi

Qumosani

Zahid

Alfayea

(2022). Prevalence and factors associated with burnout among nurses in Jeddah: A single-institution cross-sectional study. BMC Nursing, 21(1), Article 1. https://doi.org/10.1186/s12912-022-01070-2

41.

Rada

R. E.

Johnson-Leong

(2004). Stress, burnout, anxiety and depression among dentists. The Journal of the American Dental Association, 135(6), 788–794. https://doi.org/10.14219/jada.archive.2004.0279

42.

Ramírez-Elvira

Romero-Béjar

J. L.

Suleiman-Martos

Gómez-Urquiza

J. L.

Monsalve-Reyes

Cañadas-De La Fuente

G. A.

Albendín-García

(2021). Prevalence, risk factors and burnout levels in intensive care unit nurses: A systematic review and meta-analysis. International Journal of Environmental Research and Public Health, 18(21), Article 11432. https://doi.org/10.3390/ijerph182111432

43.

Reith

T. P.

(2018). Burnout in United States healthcare professionals: A narrative review. Cureus, 10(12), e3681. https://doi.org/10.7759/cureus.3681

44.

Rotenstein

L. S.

Brown

Sinsky

Linzer

(2023). The association of work overload with burnout and intent to leave the job across the healthcare workforce during COVID-19. Journal of General Internal Medicine, 38(8), 1920–1927. https://doi.org/10.1007/s11606-023-08153-z

45.

Salama

Abdou

A. H.

Mohamed

S. A. K.

Shehata

H. S.

(2022). Impact of work stress and job burnout on turnover intentions among hotel employees. International Journal of Environmental Research and Public Health, 19(15), 9724. https://doi.org/10.3390/ijerph19159724

46.

Schaufeli

W. B.

Leiter

M. P.

Maslach

(2009). Burnout: 35 years of research and practice. Career Development International, 14(3), 204–220. https://doi.org/10.1108/13620430910966406

47.

Shah

A. H.

Catalano

Bhatia

Gupta

Daruwalla

Osrin

Nadkarni

(2024). Coping strategies and help-seeking behaviors among survivors of intimate partner violence: A qualitative study of spouses of men with heavy drinking in India. Health & Social Care in the Community, 2024, 1–15. https://doi.org/10.1155/2024/6839787

48.

Sohrabi

Yarmohammadi

Pouya

A. B.

Arefi

M. F.

Hassanipour

Poursadeqiyan

(2022). Prevalence of job burnout in Iranian nurses: A systematic review and meta-analysis. Work, 73(3), 937–943. https://doi.org/10.3233/WOR-210283

49.

Woo

Tang

Tam

(2020). Global prevalence of burnout symptoms among nurses: A systematic review and meta-analysis. Journal of Psychiatric Research, 123, 9–20. https://doi.org/10.1016/j.jpsychires.2019.12.015

50.

Wu Hui

W. H.

Liu Li

L. L.

Wang Yang

W. Y.

Gao Fei

G. F.

Zhao Xue

Z. X.

Wang Lie

W. L.

(2013). Factors associated with burnout among Chinese hospital doctors: A cross-sectional study.

51.

Youssef

Abou-Abbas

Kawtharani

Hassan

(2022). Prevalence and correlates of burnout among physicians in a developing country facing multi-layered crises: A cross-sectional study. Scientific Reports, 12(1), Article 12615. https://doi.org/10.1038/s41598-022-16095-5

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.08 MB

0.03 MB