1. Introduction
Human resources are considered one of the most valuable organizational assets, the most critical competitive advantage, and the scarcest resource in the knowledge-based economy. They are considered the greatest asset of any organization in terms of possessing the power of thought, creativity, and innovation, as any improvement and progress in technical and organizational structures are carried out by human resources (1). Healthcare workers have close and intimate contact with other people and have a critical responsibility for the health and life of humans (2). Dealing with sick people, incurable diseases, and death puts this profession in, leading to their high-stress jobs, fatigue, and burnout. Job burnout is one of the issues first introduced in the 1970s (3). Job burnout is a psychological syndrome of three dimensions: Emotional or affective exhaustion, depersonalization, and reduced personal accomplishment (4).
The central feature of burnout is emotional exhaustion, which is a general stress response and involves the depletion of emotional and affective resources in the individual. Depersonalization is a negative and callous response to the recipients of services and care and reflects a negative attitude of the individual towards the clients. This dimension of burnout is particularly in the human service professions. Reduced personal accomplishment is a decrease in the sense of competence and successful performance of duties and is a negative evaluation of oneself concerning work (5). Recently, the World Health Organization (WHO) recognized job burnout as an "occupational phenomenon" in the 11th revision of the International Classification of Diseases (ICD-11) and considered it a serious health issue (1). Job burnout has many consequences for families, social, personal, and organizational life, including absenteeism, repeated delays, various psychological complaints, conflicts, job changes, decreased quality of patient care, and interpersonal conflicts with colleagues (6-9).
According to reports, nurses and hospital staff are facing increasing psychological and physical pressures, including prolonged work hours, direct exposure to death, suffering, and injuries, physical activity, limited time for social interactions with friends and family, lack of social support networks, and increasing public expectations, which leads to more significant psychological and physical pressures (10). Given the importance of job burnout in healthcare workers and the complexity of its aspects, this study aims to investigate the extent of job burnout among healthcare workers in Iran.
2. Methods
2.1. Design
The review was conducted according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines.
2.2. Search Strategy
We conducted a systematic search using electronic databases, including PubMed, Scopus, Web of Science, PsycINFO, Magiran, SID, and IranDoc from inception until December 30, 2023, to identify studies investigating the prevalence of occupational burnout among healthcare workers in Iran. Additionally, a manual search of the reference lists of relevant review papers was performed to ensure all related publications were included. The search strategy was created using a combination of MeSH (medical subject headings) terms from the PubMed database as follows: {[Community Health Workers (Title/Abstract)] OR [Health Workers (Title/Abstract)] OR [Health Personnel (Title/Abstract)] AND [burnout (Title/Abstract)] AND [Iran (Title/Abstract)]}. This search yielded 45 potentially relevant papers from the mentioned electronic databases. After removing duplicates and excluding studies based on title and abstract review, several studies remained for full-text screening. Eighty-five studies were excluded due to unrelated topics, unsuitable design, and lack of access to the full text. The flowchart of the screening and study selection process is presented in Figure 1. For each electronic database, a search strategy was adopted using the POLIS model (Population, Outcome, Location, Index, and Study Design) for study selection (Table 1). This model is widely used for formulating empirical studies concerning evidence synthesis and ensures that the relevant aspects of the question are well-defined.
Figure 1.
Identification of studies through databases and registries based on PRISMA fLOW diagram (2020)
Table 1.The POLIS (Patients, Outcome, Location, Indicator and Study Design)
| POLIS Criteria | Patients | Outcome | Location | Indicator | Study Design |
|---|---|---|---|---|---|
| Description | Healthcare workers | Burn out | Iran | Prevalence of burnout | Observational study with cross-sectional design |
2.3. Inclusion and Exclusion Criteria
The inclusion criteria were studies that investigated the prevalence of burnout in healthcare workers in Iran (doctors, nurses, treatment assistants, health aides, faculty members of medical science universities, and students in related fields, dentists) and used the "Maslach Job Burnout Questionnaire" evaluation tool. No restrictions were applied regarding language, participant age, gender, or time period searched. Cross-sectional empirical studies were included in this review. Case studies (series of case reports or individual case reports) were excluded. Additionally, studies without full text and those conducted on other target groups were excluded.
2.4. Quality Appraisal
To conduct this section, two observers independently used the modified version of the quality assessment checklist for prevalence studies (adapted from Hoy et al.) for cross-sectional prevalence studies. This tool consists of 10 questions designed to assess the risk of bias. For this study, and considering the specific study conditions, the questions of this tool were modified, and the quality assessment of the papers was performed based on it. Disagreements at any review stage were resolved through discussion with a third independent reviewer. A data extraction and quality assessment form, which was previously designed in an Excel program, was provided to the two observers.
2.5. Study Selection and Data Extraction
Strictly following the inclusion and exclusion criteria, two reviewers retrieved and independently reviewed full-text papers after screening the titles and abstracts of all papers. The two reviewers independently evaluated every article for inclusion in this systematic review and meta-analysis. Any disagreements regarding article inclusion were resolved through discussion with a third reviewer to reach a consensus. Two independent reviewers performed data extraction. For data extraction, variables included the first author's name, publication year, research location, study design, sample size, mean age, target population, work experience, type of instrument used, the average score of occupational burnout, outcomes, and quality assessment score.
2.6. Occupational Burnout Assessment Tool
The MBI (Maslach burnout inventory) was developed in 1996 for use in healthcare workers. This tool assesses three dimensions of occupational burnout: Emotional exhaustion, depersonalization, and personal accomplishment. The scale consists of 22 items with Likert Scale responses, and the total scores can classify the respondent into different levels of occupational burnout (no burnout, mild burnout, moderate burnout, and severe burnout).
2.7. Synthesis
Using meta-analysis techniques with the "metaprop" command in STATA version 12, the data from studies that addressed the prevalence of occupational burnout in healthcare personnel in Iran were synthesized, and the results were reported with a 95% confidence interval. The I-squared test was used to identify heterogeneity among studies: I2 < 25% indicates no heterogeneity, I2 = 25 - 50% indicates moderate heterogeneity, and I2 > 50% indicates significant heterogeneity. The Begg test was used to assess publication bias. A P-value less than 0.05 was considered statistically significant.
3. Results
3.1. Characteristics of the Included Studies
The characteristics of the 63 articles systematically reviewed are reported in Table 2. Due to the large volume, Table 2 is not included in the article file but is attached separately.
Table 2.The Characteristics of the Iranian Included Studies
| Author, City, Year (Ref) | Title of the Study | Type of Study | Sample Size | Instruments | Main Results |
|---|---|---|---|---|---|
| Sheykhi, MA, Zabol, 2020 (7) | The effect of group logotherapy on burnout of nurses in special wards | Quasi-experimental | 40 | Demographic, Maslach burnout inventory, and semantic therapy | There was a significant relationship between meaning therapy and its effect on the frequency and severity of job burnout. Also, it means that therapy was effective in three areas of job burnout: Emotional exhaustion, depersonalization, and job conflict. These were effective, but they did not affect the dysfunction area. |
| Aghili, M, Gorgan, 2022 (8) | Evaluation of burnout rate of nurses in different intensive care units, obstetrics and gynecology wards, and neonatal wards in public hospitals | Cross-sectional | 162 | Maslach burnout inventory | The level of burnout among nurses in the obstetrics and gynecology unit was reported to be significantly lower than that of nurses in intensive care units. |
| Torabi Parizi, M, Kerman, 2015 (9) | The frequency of job burnout among dentists of Kerman City | Cross-sectional | 145 | Maslach burnout inventory | There was a significant relationship between marital status and employment with the depersonalization component. |
| Zare, S, Shiraz,2021 (10) | Beyond the outbreak of COVID-19: Factors affecting burnout in nurses in Iran | Cross-sectional | 208 | Britain Health and Safety Executive (HSE) Stress Indicator and Maslach burnout inventory | The workload was recognized as the most crucial factor in job burnout. |
| Etesam, F, Tehran, 2021 (11) | Comparative study of occupational burnout and job stress of frontline and non-frontline healthcare workers in hospital wards during the COVID-19 pandemic | Case-control | 324 | Demographic questionnaire, Maslach burnout inventory, Parker`s Job Stress Scale | There was a significant relationship between different levels of job burnout with job stress and its two dimensions (time and pressure). |
| Jalili, M, Tehran, 2021 (12) | Burnout among healthcare professionals during COVID-19 pandemic: A cross-sectional study | Cross-sectional | 645 | Demographic and occupational characteristics questionnaire and Maslach burnout inventory | Factors such as age, gender, job class, and workplace had a significant relationship with job burnout. |
| Kamali, M, Shiraz, 2020 (13) | Burnout among nurses during the coronavirus disease 2019 outbreak in Shiraz | Cross-sectional | 261 | Maslach burnout inventory | The total number of shifts during the pandemic had a significant positive correlation with emotional exhaustion. |
| Khorshidian, N, Shiraz, 2016 (14) | The relationship between mental disorders and burnout in health practitioners | Cross-sectional | 300 | Maslach burnout inventory, symptoms checklist for mental disorders | There was a positive and significant relationship between job burnout and all symptoms of mental disorders. |
| Bazmi, E, Tehran, 2019 (15) | Job burnout and related factors among health sector employees | Cross-sectional | 1807 | Maslach burnout inventory | Factors such as being single, having more than twenty years of work experience, and working shifts were associated with job burnout. |
| Shokrpour, N, Fasa, 2021 (16) | The relationship between empowerment and job burnout in auxiliary health workers in 2019 | Descriptive-analytical | 120 | Maslach burnout inventory, psychological empowerment instrument | There was a negative relationship between psychological empowerment and job burnout. |
| Ershad Sarabi, R, Kerman, 2020 (17) | Study of burnout syndrome, job satisfaction, and related factors among health care workers in rural areas of Southeastern Iran | Cross-sectional | 225 | Maslach burnout inventory, Smith e job satisfaction questionnaires | Emotional exhaustion had a negative and significant relationship with job satisfaction |
| Zarei, E, Western region of Iran, 2019 (18) | Prevalence of burnout among primary health care staff and its predictors: A study in Iran | Cross-sectional | 539 | Maslach burnout inventory | Single-status healthcare workers with less work experience, over 35, and being physicians were at higher risk of job burnout. |
| Kalani, S, Isfahan, 2017 (19) | Prevalence of burnout syndrome among the residents in Isfahan University of Medical Sciences, Isfahan, Iran | Cross-sectional | 104 | Demographic, Maslach burnout inventory | The prevalence of burnout in married assistants was significantly higher than that of single assistants. Job burnout was higher in women than men, but this difference was not statistically significant. |
| Roghanizad, N, Tehran, 2013 (20) | Prevalence of burnout Syndrome and its three dimensions in Dental Faculty Members of Azad Dental University in 2008 | Descriptive-analytical | 99 | Demographic, Maslach burnout inventory | Variables such as the duration of employment in dentistry, the number of working hours per week, and the field of specialization did not significantly correlate with job burnout. |
| Monsef Kasmaei, V, Iran, 2022 (21) | Comparative study of occupational burnout between professors and residents of Emergency Medicine in Educational-Remedial Centers of Medical Sciences Universities | Descriptive-analytical | 176 | Demographic, Maslach burnout inventory | In the group of emergency medical assistants, there was a significant relationship between gender, having children, and the number of monthly patient visits. |
| Kakemam, E, Tabriz, 2021 (22) | Burnout and its relationship to self‐reported quality of patient care and adverse events during COVID‐19: A cross‐sectional online survey among nurses | Cross-sectional | 1004 | Demographic, Maslach burnout inventory | The most important symptoms of job burnout were high emotional burnout and lack of personal success. |
| Amiri, M, Shahroud, 2019 (23) | Study of the relationship between self-efficacy, general health, and Burnout among Iranian health workers | Cross-sectional | 249 | Sherer Self-Efficacy Scale Questionnaire, General Health Questionnaire, Maslach burnout inventory | There was a statistically significant relationship between gender and general health status, in which men had a higher level of public health. Job burnout was higher in married individuals. |
| Homayoun Valiani, L, Tehran, 2017 (24) | Investigating the relation between basic psychological needs satisfaction and job burnout among basic and clinical sciences faculty members of Iran University of Medical Sciences | Survey | 100 | Maslach burnout inventory, Desi and Ryan basic psychological needs satisfaction questionnaire | Among the dimensions of job burnout, the highest mean was related to personal adequacy, emotional exhaustion, and personality. |
| Bijari, B, Birjand, 2016 (25) | Prevalence of burnout syndrome and associated factors among rural health workers (Behvarzes) in South Khorasan | Cross-sectional | 423 | Demographic, Maslach burnout inventory, General Health Questionnaire-22 | This study's average general health score was three, from 0 to 12. About 34.5% of the participants experienced moderate to severe burnout. |
| Eslamipour, F, Isfahan, 2017 (26) | Occupational burnout among dentists In Isfahan | Cross-sectional | 300 | Maslach burnout inventory | Women, women with more age and work experience, and married people had less job burnout. |
| Ziaei, M, Kermanshah, 2014 (27) | Prevalence and risk factors of occupational burnout among nurses of a hospital in Kermanshah in 2013 | Cross-sectional | 189 | Demographic, Maslach burnout inventory | With increasing age and work experience, personal adequacy increased. Also, there was a significant relationship between employment status and education level with emotional exhaustion and employment status, and work shift with depersonalization. |
| Dashti, S, Hamedan, 2014 (28) | Survey of factors associated with burnout among health care staff in Hamadan County in the year 2012 | Descriptive-analytical | 278 | Demographic, Maslach burnout inventory | There was a significant relationship between university major with emotional exhaustion score, age and university major with depersonalization, and level of education and university major with personal sufficiency. |
| Saeidi, S, Yazd, 2013 (29) | The effect of job burnout on social support and self-esteem of personnel health of Yazd city | Cross-sectional | 130 | Maslach's burnout inventory, Eyseng's self-esteem, and Cassidy's social support | There was a significant relationship between the dimensions of job burnout and the variables of work experience, marital status, gender, place of service, type of job, and personnel work experience. |
| Habibi, E, Isfahan, 2015 (30) | A survey of the relationship between shift work and job burnout in nurse staff of Alzahra Hospital application Maslach's burnout questionnaire | Descriptive-analytical | 77 | Demographic, Maslach burnout inventory | There was a significant relationship between shift work and burnout of nurses. |
| Torgheh, M, Ghazvin, 2015 (31) | Effect of humor on burnout and resiliency of nurses | Descriptive | 60 | Maslach burnout inventory | There was a statistically significant relationship between the mean burnout score and the frequency of burnout with the humor score. |
| Marofi, M, Isfahan, 2016 (32) | The relationship between burnout and quality of work life in pediatric and neonatal intensive care unit nurses | Descriptive-correlational | 76 | Maslach burnout inventory, Connor's quality of life | There was an inverse statistical relationship in the intensity range between emotional exhaustion and the average score of quality of work life. |
| Sadra Abarghouei, M, Yazd, 2016 (33) | Surveying the relationship of total ergonomics with burnout (with case study) | Descriptive-correlational | 216 | Maslach burnout inventory, organizational support, organizational justice, and physical conditions of the work environment | There was a significant relationship between job burnout and its components with variables such as organizational support, organizational justice, and the physical conditions of the work environment. |
| Amini, F, Tehran, 2013 (34) | The relationship between resiliency and burnout in nurses | Descriptive-correlational | 304 | Maslach burnout inventory, Connor and Davidson resilience questionnaire, and demographic | As the level of resilience increased, the burnout of nurses decreased. |
| Soleimani, R, Rasht, 2015 (35) | Comparison of Mental Health and Burn Out in Medical Staff of Rasht Shafa and Heshmat Hospitals | Descriptive-correlational | 183 | Demographic, Maslach burnout inventory, General Health Questionnaire | The mean emotional exhaustion and depersonalization among Heshmat Hospital nurses was average, more than that of the nurses of Shefa Hospital. Also, the nurses of both hospitals had good mental health. In Heshmat nurses, physical symptoms, anxiety, and depression were reported more than in Shafa nurses. |
| MosaviaN, Z, Ahvaz, 2017 (36) | The relationship between shift work and occupational burnout among nurses in a teaching hospital in Ahvaz. | Descriptive-correlational | 180 | Demographic, Maslach burnout inventory | A significant relationship was reported between the type of nurse employment ward, shift work, and depersonalization component. |
| Assadi, T, Shahroud, 2019 (37) | Occupational burnout and its related factors among Iranian nurses: A cross-sectional study in Shahroud, Northeast of Iran | Cross-sectional | 250 | Demographic, Maslach burnout inventory, job satisfaction | There was a significant relationship between the gender variable and emotional exhaustion component and the marriage variable with individual dysfunction |
| Moghaddasi, J, Shahrekord, 2013 (38) | Burnout among nurses working in medical and educational centers in Shahrekord, Iran | Descriptive | 340 | Demographic, Maslach burnout inventory, job information | The burnout rate among nurses in Shahrekord was significant due to the disproportionate relationship between the number of nurses, income, and workload. |
| Molavynejad, Sh, Ahvaz, 2019 (39) | Relationship between personality traits and burnout in oncology nurses | Cross-sectional | 106 | Maslach burnout inventory, Personality questionnaire (NEO) | There was a significant relationship between all dimensions of job burnout with personality traits and anxiety and depression. |
| Yektatalab, S, Jahrom, 2019 (40) | Relationship between occupational burnout and demographic variables among nurses in Jahrom, Iran | Descriptive-correlational | 250 | Demographic, Maslach burnout inventory | There was a significant relationship between educational level, age, and individual success. Similarly, there was a significant relationship between the three components of job burnout with the income level and a significant relationship between personality disorder and gender. |
| Darban, F, Sistan and Baluchestan, 2016 (41) | Effect of communication skills training on the burnout of nurses: A cross-sectional study | Cross-sectional | 60 | Maslach burnout inventory, Communication skills training workshop two days for 8 hours a week | With the intervention, job burnout decreased. |
| Soroush, F, Isfahan, 2016 (42) | The relationship between nurse clinical competence and burnout in neonatal intensive care units | Cross-sectional | 86 | Demographic, Maslach burnout inventory, Patricia clinical competency | There is a significant negative relationship between burnout and clinical competency. |
| Noori, F, Yazd, 2022 (43) | Determination of professional job burnout and temperament (Mizaj) from the viewpoint of Traditional Persian Medicine and work-related variables among Iranian dentists: a cross-sectional study | Cross-sectional | 120 | Maslach burnout inventory | There was a positive significant relationship between emotional exhaustion and work avoidance. |
| Taleghani, F, Isfahan, 2017 (44) | Empathy, burnout, demographic variables and their relationships in oncology nurses | Descriptive | 67 | Demographic, Maslach burnout inventory, Jefferson Scale of Empathy | There was a significant negative relationship between job burnout and empathy. |
| Karimi, L, Tehran, 2022 (45) | Association between dimensions of professional burnout and turnover intention among nurses working in hospitals during Coronavirus disease (COVID-19) pandemic in Iran based on structural model | Cross-sectional | 170 | Maslach burnout inventory, Turnover intention questionnaire | A significant relationship between the work position and interest in being in the organization with the turnover intention was reported |
| Amiri, M, Shahroud, Sabzevar, Neishabur, Bojnoord, 2016 (46) | Burnout and it is influencing factors among primary healthcare care providers in the northeast of Iran | Cross-sectional | 548 | Maslach burnout inventory | There was a significant relationship between job interest and job burnout |
| Abarghouei, M, Yazd, 2016 (47) | A study of job stress and burnout and related factors in the hospital personnel of Iran | Cross-sectional | 306 | Demographic, Maslach burnout inventory, HSS-35 | There was a significant positive relationship between personal success and job history, emotional exhaustion, and age and a negative relationship between the two variables of age and job history and depersonalization. Also, married health workers reported more burnout. |
| Zakeri, M, South regions of Iran, 2021 (48) | Burnout, anxiety, stress, and depression among Iranian nurses: Before and during the first wave of the COVID-19 pandemic | Cross-sectional | 508 | Demographic, Maslach burnout inventory, DASS-21 | There was a significant relationship between variables such as types of hospital wards and shifts with nurses' burnout. |
| Ghoraishian, M, Tehran & Yazd, 2021 (49) | The frequency of burnout among Iranian orthopedic surgeons and residents | Cross-sectional | 180 | Demographic, Maslach burnout inventory | There was a significant relationship between variables such as lower educational level, low age, little time spent on leisure and sports activities, and working in the public sector with job burnout. |
| Janighorban, M, Isfahan, 2020 (50) | The Correlation between Psychological Empowerment and Job Burnout in Midwives Working in the Labor Ward of Hospitals | Cross-sectional | 282 | Maslach burnout inventory, Psychological Empowerment Questionnaire (PEQ) | No significant relationship was found between job burnout and psychological empowerment with demographic variables. |
| Rivaz, M, Shiraz, 2020 (51) | Assessment of the relationship between nurses’ perception of ethical climate and job burnout in intensive care units | Cross-sectional | 212 | Maslach burnout inventory, Olson’s Hospital Ethical Climate Survey (HECS) | There was an inverse relationship between the severity and frequency of burnout and moral climate. A significant association was reported between variables such as age with moral climate and gender, and work shift with job burnout. |
| Maghbouli, N, Tehran, 2021 (52) | Burnout and clinical learning environment among residents in Tehran | Cross-sectional | 221 | Maslach burnout inventory, PHEEM | Job burnout components were significantly predicted by perceived social support. |
| Shirali, Gh, Tehran 2022 (53) | The effect of COVID-19 pandemic on mental workload and occupational burnout in medical staff: a case-control study | Case-control | 412 | NASA-TLX and Maslach Burnout Inventory questionnaires were used to assess mental workload and burnout, respectively | The present study's findings revealed that the prevalence of COVID-19 could increase the values of mental workload parameters and burnout of healthcare personnel in medical settings. |
| Masoor Roudsary, D, Tehran, 2022 (54) | Relationship between job burnout and organizational climate in nurses working in teaching hospitals affiliated to Iran University of Medical Sciences | Cross-sectional | 200 | Demographic form, the Maslach burnout inventory, and Halpin and Croft’s organizational climate description questionnaire were used | With the increase in organizational climate, emotional exhaustion increases, resulting in more job burnout. Emotional exhaustion domain of job burnout had a statistically significant correlation with all dimensions of organizational climate except for group spirit and disengagement |
| Hasani, Z, Abadan Ahwaz, Mahshahr and Tehran, 2018 (55) | Job burnout and mental health of non-medical staff of general, specialty and sub-specialty hospitals affiliated to the Iranian oil industry | Descriptive-analytical | 251 | Demographic checklist, Goldberg General Health Questionnaire, and Maslach Burnout Questionnaire. | There is a meaningful and reverse relationship between burnout and mental health, mental health and emotional exhaustion, and depersonalization and personal adequacy in non-medical staff in general. |
| Honarvar, Z, Mashhad, 2022 (56) | The effect of emotional intelligence on distresstolerance and burnout in forensic staff | Quasi-experimental | 30 | Metacognition and behavior and monte aha positive metacognition questionnaires, Simmons and Kaher (2005) distress tolerance questionnaire and Mezlach burnout were used to collect data. | Metacognitive training can be effective on the dimensions of happiness, stress tolerance, and burnout. |
| Talebi Ghadicolaei, H, Mazandaran, 2022 (57) | Relationship between moral intelligence and occupational burnout in Mazandaran pre-hospital emergency staff during COVID-19 pandemic | Cross-sectional | 250 | Data were collected using a demographic characteristics checklist, the Moral Intelligence Scale (Lennick & Kiel), and the Maslach Burnout Inventory (MBI). | Improvements in moral intelligence scores decreased the burnout score. |
| Sadeghzade, Gh, Tehran, Isfahan, and Sanandaj, 2021 (58) | Assessment of mental workload and job burnout of medical employees during the COVID-19 pandemic in Iran | Descriptive-analytic research | 510 | The mental workload and the job burnout of staff have been evaluated using NASA-TLX software and the job burnout Maslach, respectively. | The mental workload and job burnout in medical employees during the COVID-19 pandemic are high, and warning and the mental workload in employees associated with patients suffering from COVID-19 are higher than other employees. |
| Seyedi, p, Hospitals in Khorramabad city, 2021(59) | Investigating the relationship of emotional intelligence with job satisfaction and burnout in nurses | Descriptive-analytic research | 467 | The instruments used in this study were Demographic Information, Bradbury and Graves' Emotional Intelligence Questionnaire, Maslach burnout inventory (MBI), and Visoki and Chrome's Job Satisfaction Questionnaire | The findings showed that there was no significant relationship between emotional intelligence and job satisfaction, but there was a significant relationship between emotional intelligence and burnout. |
| Nasrolah Beigi1, F, Tehran, 2021 (60) | The relationship between human resources management functions and job burnout from the perspective of managers and staff in deputy of health at Iran University of Medical Sciences | Cross-sectional | 242 | Two questionnaires on burnout and human resources management functions. | Job burnout can be significantly reduced with the improvement of human resources management functions. |
| Sharjabad, F, Bushehr and Borazjan, Iran, 2021 (61) | Job burnout and its related factors among the workers of comprehensive healthcare centers in Bushehr and Borazjan, Iran, in 2019 | Cross-sectional | 203 | Data were collected using the Maslach burnout inventory and HSE Management Standards Questionnaires in 2019. | There was a strong negative correlation between job burnout and management standards (r = -0.69, P < 0.001). The two components, including the organizational role and job relationship, predicted job burnout and explained 63% of the changes in job burnout. |
| Mohammadnahal, L, Tehran 2020, (62) | THE effect of caring for COVID-19 patients on nurses' productivity and burnout | Descriptive-analytical cross-sectional | 120 | Data was collected using the Maslach Burnout Questionnaire and Hersey and Goldsmith Human Resources Productivity Questionnaire, and they were analyzed using descriptive statistics. | Caring for COVID-19 patients reduces productivity and increases the burnout of nurses. |
| EYNi, S, Bandar Abbas, 2021(63) | Comparison of perceived stress, work-family conflict and job burnout in nurses and teachers in Bandar Abbas | Descriptive and causal-comparative | 70 nurses and 70 teachers were selected by simple random sampling | Cohen et al.'s (1983) Perceived Stress Questionnaire, Carlson et al.'s Family Conflict Questionnaire (2000), and Maslash Burnout Questionnaire (1981) were used to collect data. | Job burnout among nurses was higher than among teachers due to a lack of job security and a bright future. |
| Rastjoo, S, Yazd, 2021 (64) | Predicting job burnout of female nurses based on effort-reward imbalance and characteristics of positive psychology | Descriptive; correlation type | 132 | Three questionnaires (Muslesh & Jackson`s job burnout, Seligman`s positive psychological characteristics scale, and effort-reward imbalance of Seigersit) were completed by nurses. | Job burnout of nurses is moderate. the results of multiple regression analysis showed that 40% of variances of job burnout were predicted by the meaning of life, the effort-reward imbalance, and the engagement life. |
| Hemmat Panah, A, Tehran, 2021 (65) | The relationship between leadership styles with occupational stress, organizational deviant behaviors, and job burnout in a military health, rescue, and treatment center | Descriptive-analytical study | 165 | The instruments used were the Bass Leadership Style Questionnaire, the Kahn Stress questionnaire, Bennett's Deviant Behaviors Questionnaire, and the Maslach Burnout Questionnaire. | Transformational, transactional, and laissez-faire leadership styles are important predictors of job stress, organizational deviant behaviors, and burnout. |
| Rahmani, R, Zahedan, 2020 (66) | Relationship between COVID-19-caused anxiety and Job Burnout among hospital staff: A cross-sectional study in the Southeast of Iran | Descriptive cross-sectional | 353 | Containing demographic and occupational information, the Corona Disease Anxiety Scale, and the Maslach Burnout Inventory | There was a significant relationship between corona-caused anxiety and job burnout. |
| Farrokhi, P, 2022 (67) | Job stress and its management methods among pre-hospital emergency staff in Iran: A systematic review | Systematic review | Published English and Persian studies without time limitation were searched and reviewed electronically in Persian and English databases from PubMed, Web of Science, Scopus, SID, Magiran, and Google Scholar using related keywords. | After removing duplicate and unrelated articles, the quality of the articles was evaluated by the authors based on the Strobe checklist. Finally, the narrative synthesis method was used to combine the data. | Pre-hospital emergency workers face stressful situations on average in Iran. |
| HonarvarZ , Neishabour, 2022 (56) | The effect of emotional intelligence on distress tolerance and burnout in forensic staff | Quasi-experimental study | 30 | Metacognition and behavior and Monte Aha positive metacognition questionnaires, Simmons and Kaher (2005) distress tolerance questionnaire and Mezlach burnout were used to collect data. | Findings indicate that metacognitive intervention has been associated with increased distress tolerance and meta-emotional dimensions and reduced burnout. |
| Hezaveh Z, Tehran, 2021 (68) | The effect of resilience training program on the job burnout of nurses: A quasi-experimental study | This quasi-experimental | 96 | Data were collected using the demographic form and Maslach and Jackson Burnout Inventory | The resilience training program reduces the burnout of nurses and, given that nursing is one of the professions that makes people prone to burnout |
| Roohi, Gh, Gorgan, 2008 (69) | How to manage nursing and its relationship with job burnout in nurses of Golestan University of Medical Sciences Hospitals | Descriptive-analytical | 277 | Tasks of planning, organizing, controlling and monitoring, directing and leading, motivating, employee participation, encouraging and punishing. and the tool for measuring job burnout is the Maslach Standard Questionnaire (MBI), including the dimensions of emotional exhaustion, depersonalization, and It was an individual failure. | The relatively favorable management style of nursing managers promises to provide better quality services. The existence of a relationship between the way of management and job burnout of nurses requires managers to pay more attention to personnel and use scientific methods of management. |
3.2. Quality Assessment
Approximately 62.2% of the studies had a low risk of bias, and 33.3% had a moderate risk. Two articles were found to have a high risk of bias. A common weakness in most studies was the lack of explicit mention of the participants' exposure level and the sampling method (online or in-person) during the study (Table 3).
Table 3.Evaluation of the Quality of Included Studies to Check the Risk of Bias
| Author, City, Year (Ref) | Was an Acceptable Case Definition Used in the Study? | Was the Study Instrument That Measured the Parameter of Interest (e.g., Prevalence of Burn Out) Shown to Have Reliability and Validity (if Necessary)? | Was the Same Mode of Data Collection Used for All Subjects? | Was the Length of the Shortest Prevalence Period for the Parameter Of Interest Appropriate? | Score |
|---|---|---|---|---|---|
| Sheykhi, M. A, Zabol, 2020 (7) | Yes | Yes | Not clear | Not clear | Moderate risk of bias |
| Aghili, M, Gorgan, 2022 (8) | Yes | Yes | Not clear | Not clear | Moderate risk of bias |
| Torabi Parizi, M, Kerman, 2015 (9) | Yes | Yes | Not clear | Yes | Low risk of bias |
| Zare, S, Shiraz,2021 (10) | Yes | Yes | No | Not clear | Moderate risk of bias |
| Etesam, F, Tehran, 2021 (11) | Yes | Yes | Not clear | Not clear | Moderate risk of bias |
| Jalili, M, Tehran, 2021 (12) | Yes | Yes | No | No | Moderate risk of bias |
| Kamali, M, Shiraz, 2020 (13) | Yes | Yes | Not clear | No | Moderate risk of bias |
| Khorshidian, N, Shiraz, 2016 (14) | Yes | Yes | Not clear | Yes | Low risk of bias |
| Bazmi, E, Tehran, 2019 (15) | Yes | Yes | Not clear | Not clear | Moderate risk of bias |
| Shokrpour, N, Fasa, 2021 (16) | Yes | Yes | Not clear | Yes | Low risk of bias |
| Ershad Sarabi, R, Kerman, 2020 (17) | Yes | Yes | Yes | Not clear | Low risk of bias |
| Zarei, E, Western region of Iran, 2019 (18) | Yes | Yes | Yes | Not clear | Low risk of bias |
| Kalani, S, Isfahan, 2017 (19) | Yes | Yes | Not clear | Yes | Low risk of bias |
| Roghanizad, N, Tehran, 2013 (20) | Yes | Yes | No | Yes | Low risk of bias |
| Monsef Kasmaei, V, Iran, 2022 (21) | Yes | Yes | Yes | Not clear | Low risk of bias |
| Kakemam, E, Tabriz, 2021 (22) | No | Yes | Not clear | Not clear | High risk of bias |
| Amiri, M, Shahroud, 2019 (23) | Yes | Yes | Not clear | Yes | Low risk of bias |
| Homayoun Valiani, F, Tehran, 2017 (24) | Yes | Yes | Yes | Not clear | Low risk of bias |
| Bijari, B, Birjand, 2016 (25) | Yes | Yes | Yes | Not clear | Low risk of bias |
| Eslamipour, F, Isfahan, 2017 (26) | Yes | Yes | Not clear | Not clear | Moderate risk of bias |
| Ziaei, M, Kermanshah, 2014 (27) | Yes | Yes | Yes | No | Low risk of bias |
| Dashti, S, Hamedan, 2014 (28) | Yes | Yes | Not clear | Yes | Low risk of bias |
| Saeidi, M, Yazd, 2013 (29) | Yes | Yes | Not clear | Not clear | Moderate risk of bias |
| Habibi, E, Isfahan, 2015 (30) | Yes | Yes | Yes | Yes | Low risk of bias |
| Torgheh, M, Ghazvin, 2015 (31) | Yes | Yes | Yes | Yes | Low risk of bias |
| Marofi, M, Isfahan, 2016 (32) | Yes | Yes | Yes | No | Low risk of bias |
| Abarghouei, M, Yazd, 2016 (33) | Yes | No | Not clear | Not clear | High risk of bias |
| Amini, F, Tehran, 2013 (34) | Yes | Yes | Not clear | Not clear | Moderate risk of bias |
| Soleimani, R, Rasht, 2015 (35) | Yes | Yes | Yes | Not clear | Low risk of bias |
| Mosavianasl, Z, Ahvaz, 2017 (36) | Yes | Yes | Yes | Yes | Low risk of bias |
| Assadi, T, Shahroud, 2019 (37) | Yes | Yes | Yes | Yes | Low risk of bias |
| Moghaddasi, J, Shahrekord, 2013 (38) | Yes | Yes | No | No | Moderate risk of bias |
| Molavynejad, Sh, Ahvaz, 2019 (39) | Yes | Yes | Yes | No | Low risk of bias |
| Yektatalab, S, Jahrom, 2019 (40) | Yes | Yes | Not clear | No | Moderate risk of bias |
| Darban, F, Sistan and Baluchestan, 2016 (41) | Yes | Yes | Not clear | Not clear | Moderate risk of bias |
| Soroush, F, Isfahan, 2016 (42) | Yes | Yes | Not clear | Yes | Low risk of bias |
| Noori, F, Yazd, 2022 (43) | Yes | Yes | Not clear | Yes | Low risk of bias |
| Taleghani, F, Isfahan, 2017 (44) | Yes | Yes | Yes | Yes | Low risk of bias |
| Karimi, L, Tehran, 2022 (45) | Yes | Yes | No | No | Moderate risk of bias |
| Amiri, M, Shahroud, Sabzevar, Neishabur, Bojnoord, 2016 (46) | Yes | Yes | Yes | Yes | Low risk of bias |
| Abarghouei, M, Yazd, 2016 (47) | Yes | Yes | Yes | Yes | Low risk of bias |
| Zakeri, M, South regions of Iran, 2021 (48) | Yes | Yes | Not clear | Not clear | Moderate risk of bias |
| Ghoraishian, M, Tehran & Yazd, 2021 (49) | Yes | Yes | Yes | Yes | Low risk of bias |
| Janighorban, M, Isfahan, 2020 (50) | Yes | Yes | Yes | Not clear | Low risk of bias |
| Rivaz, M, Shiraz, 2020 (51) | Yes | Yes | Yes | Not clear | Low risk of bias |
| Maghbouli, N, Tehran, 2021 (52) | Yes | Yes | Not clear | Not clear | High risk of bias |
| Shirali, Gh, Tehran 2022 (53) | Yes | Yes | Yes | Not clear | Moderate risk of bias |
| Masoor Roudsary, D, Tehran, 2022 (54) | Yes | Yes | Not clear | Not clear | High risk of bias |
| Hasani1, Z, Abadan Ahwaz, Mahshahr and Tehran, 2018 (55) | Yes | No | Yes | No | High risk of bias |
| Honarvar, Z, Mashhad, .2022 (56) | Yes | Yes | Yes | Yes | Low risk of bias |
| Talebi Ghadicolaei, H, Mazandaran, 2022 (57) | Yes | Yes | Yes | Yes | Low risk of bias |
| Sadeghzade, Tehran, Isfahan, and Sanandaj, 2021 (58) | Yes | Yes | Yes | No | Moderate risk of bias |
| Seyedi, P, hospitals in Khorramabad city, 2021 (59) | Yes | Yes | Yes | No | Moderate risk of bias |
| Nasrolah Beigi1, F, Tehran, 2021 (60) | Yes | Yes | Yes | No | Moderate risk of bias |
| Najafi Sharjabad, F, Bushehr and Borazjan, 2021 (61) | Yes | Yes | Not clear | No | High risk of bias |
| Mohammadnahal, L, 2020, Tehran (62) | Yes | Yes | Yes | No | Moderate risk of bias |
| EYNi, S, 2021, Bandar Abbas (63) | Yes | Yes | No | No | High risk of bias |
| Rastjoo S, Yazd, 2021 (64) | Yes | Yes | Yes | No | Moderate risk of bias |
| Hemmat Panah, A, Tehran, 2021 (65) | Yes | Yes | No | No | High risk of bias |
| Rahmani, R, Zahedan, 2020 (66) | Yes | Yes | Yes | Yes | Low risk of bias |
| Farrokhi, P, 2022 (67) | Yes | Yes | Yes | No | Moderate risk of bias |
| Honarvar, Z, Neishabour, 2022 (56) | Yes | Yes | Yes | No | Moderate risk of bias |
| Hezaveh, Z, Tehran ,2021 (68) | Yes | Yes | Yes | No | Moderate risk of bias |
| Roohi, Gh, Gorgan, 2008 (69) | Yes | Yes | Yes | No | Moderate risk of bias |
3.3. Mean Occupational Burnout
The primary outcome of interest, the prevalence of occupational burnout, was analyzed in 61 studies. Using a random-effects model, the mean score for occupational burnout was calculated as ES: [95% Confidence Interval = 0.36 (0.29 - 0.42)]. The heterogeneity was significant, reported as I2 = 99.66% (P = 0.000), indicating high heterogeneity among these studies (Figure 2). To address this, subgroup analysis was performed based on study quality, levels of occupational burnout, and the duration of employees' activity before and after the COVID-19 pandemic. Despite this, severe heterogeneity persisted (Table 4).
Figure 2.
Burnout in employees and subgroups
Table 4.Prevalence of Burnout in Employees and Subgroups
| Variables | Number of Studies | Heterogeneity Chi-Squared | P-Value | Overall I-Squared, % | z | P-Value | ES (95% CI) | |
|---|---|---|---|---|---|---|---|---|
| Total result | Burn out | 61 | 17675.93 | 0.000 | 99.66 | 10.87 | 0.000 | 0.36 (0.29 - 0.42) |
| Subgroup analysis according to the “period of COVID-19” | Before pandemic | 30 | 5615.88 | 0.000 | 99.48 | 7.00 | 0.000 | 0.39 (0.29 -0.49) |
| After pandemic | 31 | 11254.99 | 0.000 | 98.74 | 7.49 | 0.000 | 0.33 (0.24 - 0.42) | |
| Pandemicsubgroup analysis according to “quality assessment” | Low risk of bias | 31 | 3844.42 | 0.000 | 99.66 | 12.15 | 0.000 | 0.32 (0.27 - 0.37) |
| Moderate risk of bias | 23 | 9029.73 | 0.000 | 99.66 | 4.92 | 0.000 | 0.40 (0.24 - 0.56) | |
| High risk of bias | 4 | 104.48 | 0.000 | 99.66 | 4.33 | 0.000 | 0.35 (0.19 - 0.50 ) | |
| Subgroup analysis according to “level of burnout syndrome” | No burn out | 15 | 1150.24 | 0.000 | 98.70 | 10.84 | 0.000 | 0.29 (0.24 - 0.34) |
| Mild | 33 | 2438.28 | 0.000 | 98.65 | 10.85 | 0.000 | 0.33 (0.27 - 0.39) | |
| Moderate | 4 | 26.62 | 0.000 | 84.98 | 8.93 | 0.000 | 0.31 (0.24 - 0.38) | |
| Severe | 5 | 2329.05 | 0.000 | 99.66 | 4.19 | 0.000 | 0.66 (0.35 - 0.97) | |
3.4. Publication Bias
The Begg method was used to assess publication bias for this outcome. In Begg's chart, which examines the effect of small studies, P-value = 0.000 was reported. Since this value is significant, it indicates the presence of publication bias (adj. Kendall's Score (P-Q) = 885, SD = 160.70, z = 5.51, Pr > |z| = 0.000).
4. Discussion
Our study results indicate that the average job burnout score among healthcare workers in Iran is approximately 0.38 (95% CI 0.30 - 0.46), suggesting a mild to moderate level of burnout in this population. Job burnout has emerged as a significant public health issue and challenge. Identifying risk situations and implementing preventive measures early on is crucial to prevent future damage (7). The combination of work environment stressors and personal fears related to the COVID-19 pandemic has placed a substantial psychological burden on healthcare teams. Providing care in high-risk units, interacting with infected patients, and being in stressful situations can contribute to psychological strain for healthcare workers, potentially leading to mental health issues such as depression, alcohol and substance addiction, and burnout syndrome (7, 14). These conditions can adversely affect patient care quality and system efficiency (16). Consistent with our findings, a similar study reported that nearly half of healthcare workers in Iran experienced job burnout during the COVID-19 pandemic (17).
Another study in Iran found no significant difference in job burnout prevalence between COVID-19 and non-COVID healthcare workers (7). One of the key findings of this study was that the prevalence of job burnout increased with larger sample sizes. Larger studies tend to be more reliable than smaller ones (18) due to reduced sampling errors, making it easier to identify more cases of job burnout.
Compared to other studies, one of the strengths of our research is the use of the standardized "Maslach Burnout Inventory" to assess the severity of job burnout among Iranian healthcare workers. Many similar studies globally use various tools with different measurement criteria, leading to inconsistencies in cut-off points. Another strength is that all included studies were observational and predominantly cross-sectional. However, a notable weakness is the inclusion of a wide range of healthcare and educational staff, which might introduce variability. Additionally, since all studies included in this research were observational, they are susceptible to biases, such as selection bias, and their results can be influenced by confounding variables (18).
Considering the positive impact of moral intelligence on reducing job burnout (19) and the role of resilience in mental health (20-22), it is recommended that training programs be developed to enhance resilience and moral intelligence among health system employees.
4.1. Conclusions
A combination of workplace stressors and personal fears associated with the COVID-19 pandemic appears to have placed a significant psychological burden on healthcare teams. To minimize burnout, it is suggested that supportive approaches, including access to psychosocial support services such as web-based platforms, psychological first aid, psychological support hotlines, and self-care techniques, be provided to individuals throughout their service years.
