The Relationship Between Occupational Burnout and Negative Affective Responses of Nurses During the Public Health Crisis


avatar Mohammadrasoul Khalkhali ORCID 1 , avatar Shaghayegh Pourali ORCID 1 , avatar Leila Alirahimi ORCID 1 , avatar Hassan Farrahi ORCID 1 , *

Department of Psychiatry, Kavosh Cognitive Behavior Sciences and Addiction Research Center, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran

how to cite: Khalkhali M, Pourali S, Alirahimi L, Farrahi H. The Relationship Between Occupational Burnout and Negative Affective Responses of Nurses During the Public Health Crisis. J Nurs Midwifery Sci. 2024;11(1):e143199.



Long-term exposure of nurses to coronavirus disease 2019 (COVID-19) and the lack of necessary and sufficient facilities to deal with the disease have had significant negative effects on their occupational and mental health.


The present study aimed to investigate the association between occupational burnout and negative affective responses, including depression, anxiety, and stress, in nurses during the recent pandemic.


A total of 270 nurses who worked at Razi hospital, one of the principal referral hospitals for COVID-19 patients in the northern province of Guilan, Iran, throughout 2021 - 2022, were included in this study. These nurses were selected using convenience sampling and were assigned to one of three wards: COVID-19 (n = 43), emergency (n = 55), or other wards (n = 172). In addition to providing their sociodemographic information, the participants completed two assessments: The Maslach Burnout Inventory-Human Services Survey (MBI-HSS) and the Depression, Anxiety, and Stress Scales-42 (DASS-42).


The correlation matrix showed that all MBI-HSS and DASS-42 scores, except in one case, had a positive correlation with each other (P < 0.0001). In the multiple analysis of variance, gender (P = 0.17), education (P = 0.005), hospital ward (P = 0.048), social support (P = 0.001), family support (P < 0.0001), financial support (P = 0.01), occupational satisfaction (P = 0.044), social respect (P < 0.0001), history of death in the family (P = 0.006) and relatives (P = 0.043), and having a child in primary school age (P = 0.04) created a significant difference in MBI-HSS and DASS-42 scores.


In general, nurses tend to be considerably affected by the negative effects of the recent public health crisis, especially occupational burnout, and it is necessary to make arrangements to improve their mental health and reduce the level of occupational burnout in them.

1. Background

Coronavirus disease 2019 (COVID-19) is a new type of coronavirus that led to a health crisis at the end of 2019 (1). By mid-2023, about seven million individuals have died due to this virus (2). The increasing mortality resulting from the spread of the viral disease and its consequences have affected the mental health of individuals and led to numerous psychological responses (3). Healthcare workers suffer more psychological burdens due to direct and continuous contact with patients, compared to the general population (4). Reports indicate that in the early stage of the outbreak of COVID-19, 29% of all hospitalized patients were healthcare workers. Additionally, healthcare workers are exposed to a significant amount of fake news and rumors, all of which increase their anxiety or other negative psychological responses (5, 6). Undiagnosed or untreated psychological problems can have long-term effects on their health and reduce the quality of healthcare services for patients (7).

In recent years, due to several problems, such as the lack of medical facilities and increased workload, burnout has increased among healthcare workers (8). Burnout is a psychological syndrome characterized by decreased energy, increased mental distance from work, and decreased professional efficiency (9). Emergency situations, such as epidemics and pandemics, can easily cause exhaustion (10). Current studies confirm the high prevalence of burnout among nurses and other healthcare workers during the outbreak of COVID-19 (11). With the increase in the level of burnout among them, the prevalence of related symptoms and/or disorders has been reported (12). In the midst of the recent pandemic, nurses played a critical role in various wards and units related to COVID-19 (13). Nurse burnout is important because, more than any other factor, it can threaten patients' improvement process (14).

Occupational burnout might be associated with some negative affective responses, such as depression, anxiety, and stress. Interestingly, there is a remarkable similarity or overlap between depression and burnout (15). Some symptoms of burnout, such as loss of interest or pleasure, fatigue, and decreased energy, are similar to symptoms of depression (16). The literature indicates that 58% of individuals with occupational burnout also suffer from a mood disorder (17). Another factor that has not been studied as much as depression is anxiety (18). According to previous studies, 59% of individuals with occupational burnout also have an anxiety disorder, although Teo et al. indicated that the level of anxiety did not show a significant increase (17, 19). In addition, the nursing profession is considered one of the most stressful jobs (13). Acute stress can severely affect the mental health of nurses who are responsible for the continuous and sometimes unprotected care of patients (6). Sarboozi et al. observed that the level of occupational stress of nurses in COVID-19 wards increased significantly, compared to nurses in other wards, and this stress was related directly to the level of occupational burnout (20).

Altogether, although studies confirm the increase in occupational burnout among Iranian nurses during the pandemic (21), to the best of our knowledge, only one study in southern Iran has investigated the relationship between affective responses and occupational burnout. The results of the aforementioned study showed that burnout did not change significantly, compared to the previous situation of it (22).

2. Objectives

This study focused on the mental health of nurses during the COVID-19 pandemic. It investigates the relationship between occupational burnout and depression, anxiety, and stress in nurses working at a major COVID-19 referral center in Guilan province, Iran. The findings of the study can be applied to prevent burnout and ensure high-quality care services during crises, such as the COVID-19 pandemic.

3. Methods

3.1. Research Design and Sample

This cross-sectional study was conducted on nurses in Rasht's Razi hospital during 2021 - 2022. The research sample consisted of 270 nurses working in COVID-19 (n = 43), emergency (n = 55), or other (n = 172) wards of the hospital, selected using convenience sampling. The inclusion criteria were working as a nurse in one of the wards of Razi hospital, an age range of 20 to 60 years, and willingness to participate in the study. The exclusion criterion was not completing the study measures. First, the participants were asked to answer questions on a checklist regarding age, gender, marital status, education, years of employment, hospital ward, working hours in the last 3 months, history of being infected with COVID-19, the severity of the disease if infected, the level of perceived social, family, and financial support during the pandemic, occupational satisfaction from the nursing profession, social respect for the nursing profession after the pandemic, the effect of vaccination in reducing the fear of contracting the coronavirus, the effect of the pandemic on the lives of individuals and their gatherings, the death history of first-degree relatives and close friends/colleagues, the severity of discomfort on hearing the news of the death of their compatriots, and having a child in primary school. Then, the participants were asked to answer the Maslach Burnout Inventory-Human Services Survey (MBI-HSS) (23) and the Depression, Anxiety, Stress Scale (24) to assess occupational burnout and three negative affective responses, namely stress, anxiety, and depression, respectively. The project was explained to all participants, and informed consent was obtained. Statistical data were analyzed using SPSS software version 22.

3.2. Instruments

A checklist developed by present researchers was used to gather the sociodemographic information. The checklist included the following variables: age, gender, marital status, education, years of employment, hospital ward, working hours in the last 3 months, COVID-19 infection, infection severity, social support, family support, financial support, occupational satisfaction, social respect, vaccination effect, COVID-19 effect on life, COVID-19 effect on parties, family member death, relative death, discomfort about family member or relative death, and having child in primary school.

3.2.1. Maslach Burnout Inventory-Human Services Survey

This 22-item inventory is a widely used inventory developed to measure the frequency and severity of burnout among human service professionals in three dimensions: emotional exhaustion (EE) (9 items; measures feelings of being emotionally overextended and exhausted by one's work), depersonalization (DP) (5 items; measures an unfeeling and impersonal response toward patients), and reduced personal accomplishment (RPA) (8 items; measures reduced feelings of competence and achievement in one's work) (23). The answers are on a seven-point Likert scale (from 0 to 6). Higher item scores in EE, DP, and RPA correspond to high levels of burnout. The total internal consistency of the MBI-HSS is 0.83, and the validity of its subscales is reported as 0.92 - 0.71.23 In Iran. Amini reported Cronbach's alpha of its subscales as 0.86 - 0.81 (25).

3.2.2. Depression, Anxiety, and Stress Scales-42

This well-known and widely used measure was designed to assess symptoms of depression, anxiety, and stress in adolescents and adults (24). The internal consistency of Depression, Anxiety, and Stress Scales-42 (DASS-42) in a clinical sample of 437 individuals was excellent (0.89 - 0.96 for three scales), and its test-retest reliability was favorable (0.71 - 0.81 for three scales) (26). Additionally, exploratory factor analysis supported its three-factor structure. In Iran, Afzali et al. reported the alpha coefficient of three scales as 0.88 - 0.85 (27).

3.3. Ethical Consideration

The present study was approved by the scientific and ethical committees of Guilan University of Medical Sciences (code: IR.GUMS.REC.1400.334). Before implementing the study assessments, sufficient information was provided to the participants, and written consent was obtained.

3.4. Statistical Analysis

To analyze the data, we conducted an evaluation of descriptive statistics and Pearson's correlation coefficient. Then, multiple analysis of variance (MANOVA) was performed to assess differences among participants based on the obtained scores. To further investigate, Levene's test was utilized to verify or refute the assumption of homogeneity of variances. Ultimately, as this assumption was confirmed for all scores (P > 0.05), Tukey's test was employed for the scores that showed differences between groups, as indicated by the MANOVA.

4. Results

The mean and standard deviation of the age of 270 participants were 35.87 and 7.33 years, respectively. The demographic information of the participants is presented in Table 1.

Table 1.

Frequency (No.) and Percentage (%) of Participants’ Demographic Characteristics

VariablesNo. (%)
20 - 3083 (30.7)
31 - 40115 (42.6)
41 - 5065 (24.1)
51 - 607 (2.6)
Female216 (80)
Male54 (20)
Marital status
Single96 (35.6)
Married174 (64.4)
Bachelor of science214 (79.3)
Master of science56 (20.7)
Years of employment
1 - 10125 (46.3)
11 - 20108 (40)
21 - 3037 (13.7)
Hospital ward
COVID - 1943 (15.9)
Emergency55 (20.4)
Other172 (63.7)
Working hours in last 3 months
100 - 25013 (4.8)
251 - 40065 (24.1)
401 - 550188 (69.6)
551 - 7004 (1.5)
COVID-19 infection
No77 (28.5)
Yes193 (71.5)
Infection severity
Free symptom5 (2.5)
Moderate symptom172 (86.9)
Sever symptom21 (10.6)
Social support
No change9 (3.3)
Poor109 (40.4)
Moderate126 (46.7)
High26 (9.6)
Family support
No change2 (0.7)
Poor10 (3.7)
Moderate102 (37.8)
High156 (57.8)
Financial support
No change10 (3.7)
Poor89 (33)
Moderate120 (44.4)
High51 (18.9)
Occupational satisfaction
No change3 (1.1)
Poor92 (34.1)
Moderate142 (52.6)
High33 (12.2)
Social respect
No change19 (7)
Poor46 (17)
Moderate173 (64.1)
High32 (11.9)
Vaccination effect
Low8 (3)
Moderate171 (63.3)
High91 (33.7)
COVID-19 effect on life
No change1 (0.4)
Low5 (1.9)
Moderate109 (440.4)
High155 (57.4)
COVID-19 effect on parties
Low3 (1.1)
Moderate97 (35.9)
High170 (63)
Family member death
No279 (92.2)
Yes21 (7.8)
Relatives death
No207 (77)
Yes62 (23)
Friends death
No166 (61.5)
Yes104 (38.5)
Low4 (1.5)
Moderate133 (49.3)
High133 (49.3)
Child in primary school
No207 (76.7)

Pearson's correlation coefficient was used to examine the correlation between participants' scores in MBI-HSS and DASS-42. As observed in Table 2, all MBI-HSS and DASS-42 scores have a positive correlation with each other (P < 0.0001). However, the only non-significant association was the correlation between the subscales of reduced personal accomplishment subscale and the depression (P = 0.832).

Table 2.

Correlation Matrix Between Maslach Burnout Inventory-Human Services Survey (MBI-HSS) and Depression, Anxiety, and Stress Scales-42 (DASS-42) Scores

DP0.460 a1
RPA0.452 a0.337 a1
MBI0.869 a0.656 a0.788 a1
DS0.385 a0.376 a-0.0130.299 a1
AS0.373 a0.396 a0.174 a0.383 a0.712 a1
SS0.536 a0.345 a0.404 a0.565 a0.606 a0.663 a1

Multiple analysis of variance was used to examine the differences in MBI-HSS and DASS-42 scores in terms of demographic variables. As shown in Table 3, several variables show statistically significant relationships with the MBI-HSS and DASS-42 scores (P < 0.05). for example, financial support, occupational satisfaction, social respect, education, years of employment, hospital ward, social support, family support, family member death, relative’s death, and having a child in primary school age all have significant relationships with either the MBI-HSS or DASS-42 scores.

Table 3.

Multiple Analysis of Variance (MANOVA) Between Demographic Variables and Maslach Burnout Inventory-Human Services Survey (MBI-HSS) and Depression, Anxiety, and Stress Scales-42 (DASS-42) Scores

Gender 2.6360.017
Marital status0.1030.996
Years of employment0.7390.713
Hospital ward1.7850.048
Working hours in the last 3 months1.6120.052
COVID-19 infection0.9370.469
Infection severity0.9180.556
Social support2.3410.001
Family support3.1520.000
Financial support1.9650.010
Occupational satisfaction1.6480.044
Social respect3.3130.000
Vaccination effect0.9240.523
COVID-19 effect on life1.0300.423
COVID-19 effect on parties0.7890.662
Family member death3.1170.006
Relative death2.2110.043
Friend death0.7120.640
Child in primary school age2.2450.040

Tukey's post-hoc test was used to further analyze the data. The results showed that gender had a significant effect on reduced personal accomplishment and total occupational burnout, with women scoring higher in both categories. Education also had a significant effect on depersonalization, reduced personal accomplishment, and total occupational burnout, with participants with a bachelor's degree scoring higher than those with a master's degree. The hospital ward only had a significant effect on reduced personal accomplishment, with nurses in COVID-19 wards scoring the highest and those in emergency wards scoring the lowest. Social support had a significant effect on anxiety and stress, with the group with high support scoring higher. Family support had a significant effect on emotional exhaustion, depersonalization, total occupational burnout, depression, anxiety, and stress, with moderate to high support leading to lower scores in these categories. Financial support had a significant effect on reduced personal accomplishment and total occupational burnout, with nurses with moderate to high support scoring lower. Occupational satisfaction only had a significant effect on emotional exhaustion, with higher satisfaction resulting in lower scores. Social respect had a significant effect on emotional exhaustion, depersonalization, total occupational burnout, depression, anxiety, and stress, with moderate to high respect leading to lower scores. The history of the death of a family member due to COVID-19 also had a significant effect on emotional exhaustion, depersonalization, depression, anxiety, and stress, with those with such a history scoring higher. The death of relatives due to COVID-19 had a significant effect on emotional exhaustion, with those with a history of this scoring higher. Finally, having a primary school child had a significant effect on anxiety, with those with a primary school child scoring higher (Table 4).

Table 4.

Test of Between-Subject Effects

Hospital ward
Social support
Family support
Financial support
Occupational satisfaction
Social respect
Family member death
Relatives death
Child in primary school age

5. Discussion

The recent pandemic has increased the nurses’ workload in many countries and has caused many of them to experience burnout and its negative affective consequences (8, 28-30). The present study aimed to examine the association between occupational burnout and depression, anxiety, and stress in nurses in one of the most important referral centers for patients with COVID-19 in the north of Iran. The findings of the present study showed a strong positive correlation between occupational burnout and depression, anxiety, and stress. In addition, according to the MANOVA test, most demographic variables of the study created a significant difference in occupational burnout and depression, anxiety, and stress scores.

The results of the present study regarding the association between nurses' occupational burnout and depression, anxiety, and stress during COVID-19 are consistent with the results of many other studies. Zhu et al. showed that the anxiety of nurses was significantly higher than that of physicians; however, there was no difference in depression between them (31). Zerbini et al. showed higher levels of fatigue, stress, depression, and low job satisfaction in nurses than other healthcare workers (32). Noh et al. also demonstrated that more than half of frontline nurses had burnout, and 59.6%, 23.0%, 36.0%, and 17.4% of nurses experienced insomnia, depression, anxiety, and stress, respectively (33). The results of several Iranian studies are consistent with the above-mentioned findings and have shown an increase in occupational burnout and its negative psychological correlates, especially anxiety, stress, and depression (20, 22, 34). In addition to nurses, this experience has been reported by other healthcare workers. In a qualitative study with a literature review approach, Ulfa et al. indicated that healthcare workers experienced more depression, stress, and burnout than other health workers who did not have personal involvement in medical work during the COVID-19 pandemic (35).

The other finding of the current study, which to some extent complements the above-mentioned finding, is the reduced personal accomplishment in nurses working in COVID-19 wards. Although burnout in emergency wards has been documented in the pre-COVID-19 (36), in the present study, nurses in COVID-19 and emergency wards obtained the highest and lowest scores in reduced personal accomplishment, respectively. This finding is consistent with some findings of the relevant literature and inconsistent with another one. A Chinese study showed that vulnerability measures of physiological and psychological responses in frontline nurses were significantly lower than those of non-frontline nurses (37). In a hospital study at the University of Augsburg, Germany, nurses in COVID-19 wards reported higher stress, fatigue, and depressed mood and lower work-related satisfaction than their colleagues in other wards (32). In addition, a systematic review by Bagheri et al. indicated that nurses in the intensive care unit experienced more psychological problems than other nurses due to high workload and more exposure to patients with COVID-19 (13).

In the research literature, some speculations have been made, and some findings have been obtained about the psychological correlates of occupational burnout. In Ariapooran et al.'s study, 56.41% of nurses intended to leave their jobs due to the burnout caused by COVID-19; however, a much larger number of them (86.41%) suffered from burnout (38). In a systematic review by Bagheri Sheykhangafshe et al., high workload, lack of personal protective equipment, sleep deprivation of work pressure, activity in the coronary special ward, history of psychological disorders, being a woman, fear of being infected with COVID-19 and transmitting it to family and relatives, social isolation, and lack of familiarity and sufficient previous training for dealing with epidemics and pandemics were among the factors that increased occupational burnout and reduced the mental health of nurses during the outbreak of COVID-19 (13). They have emphasized that these factors can lead to symptoms, such as anxiety and depression (13). In addition, another review indicated that heavy workload, lack of personal protective equipment, environmental problems of hospitals, and concern about the risk of disease transmission are among the causes of burnout and, as a result, its negative psychological consequences (39).

The results of the current study showed a significant difference in occupational burnout in terms of gender; accordingly, female nurses obtained higher scores. This result has also been obtained in many other studies. Female nurses are more likely to experience emotional distress and burnout. In a study in China, male subjects had less burnout than female medical staff (31). In a study, nurses were twice as likely to be depressed as other healthcare workers and female nurses working on the frontlines of caring for COVID-19 patients had the highest rates of depression, anxiety, insomnia, and distress (40). In addition, a review study showed more burnout in female nurses (39). However, in some studies, the opposite has been reported. For example, in Ariapooran et al.'s study, male nurses reported more occupational burnout during COVID-19 and had more intentions to leave their jobs (38). Various reasons have been mentioned as to why female nurses are more affected by COVID-19. Female nurses have a greater probability than male nurses of suffering from emotional exhaustion and symptoms of depression (30, 38). It has been shown that female nurses develop higher levels of stress than other healthcare workers when dealing with patients with COVID‐19 (30).

The present study has several limitations. Firstly, the sample size was relatively small and selected from a hospital in the north of Iran, and this might limit the generalizability of the results. Secondly, due to limited access to nurses under COVID-19 restrictions, we could not use structured diagnostic tools for evaluating emotional syndromes, and as a result, we inevitably used a self-report scale for measuring depression, anxiety, and stress. However, we are aware of the limitations of self-report measures in assessing psychological constructs. Thirdly, we did not pay due attention to the ethnicity of the participants in this study, and this can also limit the generalizability of its results. According to some findings regarding the importance of ethnicity in mental health during COVID-19 (38), it is recommended that this variable be paid sufficient attention in future studies.

5.1. Conclusions

In general, the findings show that nurses during the recent public health crisis were significantly affected by professional burnout, and this is associated with negative affective responses. Considering that burnout affects professional performance, it is expected that it has a detrimental effect on nurses' performance in caring for patients and their appropriate adaptation to stressful clinical conditions. Given that nurses are on the frontline of public health crises, it is necessary to pay attention, especially at an organizational scale, to the common vulnerabilities and the best way to deal with them. It seems that arrangements, such as training about dealing with diseases before the occurrence of health crises, providing personal protective equipment, increasing multifaceted support for workers, training emotion regulation techniques, and reducing long working hours, can have a positive effect on managing occupational burnout and negative emotional states associated with it.



  • 1.

    Meyerowitz EA, Richterman A, Gandhi RT, Sax PE. Transmission of SARS-CoV-2: A Review of Viral, Host, and Environmental Factors. Ann Intern Med. 2021;174(1):69-79. [PubMed ID: 32941052]. [PubMed Central ID: PMC7505025].

  • 2.

    World Health Organization. WHO Cronovirus (COVID-19) Dashboard. Geneva, Switzerland: World Health Organization; 2023, [cited 2023]. Available from:

  • 3.

    Zhang J, Wu W, Zhao X, Zhang W. Recommended psychological crisis intervention response to the 2019 novel coronavirus pneumonia outbreak in China: a model of West China Hospital. Precis Clin Med. 2020;3(1):3-8. [PubMed ID: 35960676]. [PubMed Central ID: PMC7107095].

  • 4.

    Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395(10223):507-13. [PubMed ID: 32007143]. [PubMed Central ID: PMC7135076].

  • 5.

    Schwartz J, King CC, Yen MY. Protecting Healthcare Workers During the Coronavirus Disease 2019 (COVID-19) Outbreak: Lessons From Taiwan's Severe Acute Respiratory Syndrome Response. Clin Infect Dis. 2020;71(15):858-60. [PubMed ID: 32166318]. [PubMed Central ID: PMC7108122].

  • 6.

    Zhu Z, Xu S, Wang H, Liu Z, Wu J, Li G, et al. COVID-19 in Wuhan: Sociodemographic characteristics and hospital support measures associated with the immediate psychological impact on healthcare workers. EClinicalMedicine. 2020;24:100443. [PubMed ID: 32766545]. [PubMed Central ID: PMC7311903].

  • 7.

    Kibret S, Teshome D, Fenta E, Hunie M, Tamire T. Prevalence of anxiety towards COVID-19 and its associated factors among healthcare workers in a Hospital of Ethiopia. PLoS One. 2020;15(12). e0243022. [PubMed ID: 33290427]. [PubMed Central ID: PMC7723255].

  • 8.

    Embriaco N, Azoulay E, Barrau K, Kentish N, Pochard F, Loundou A, et al. High level of burnout in intensivists: prevalence and associated factors. Am J Respir Crit Care Med. 2007;175(7):686-92. [PubMed ID: 17234905].

  • 9.

    Edu-Valsania S, Laguia A, Moriano JA. Burnout: A Review of Theory and Measurement. Int J Environ Res Public Health. 2022;19(3). [PubMed ID: 35162802]. [PubMed Central ID: PMC8834764].

  • 10.

    Kim JS, Choi JS. Factors Influencing Emergency Nurses' Burnout During an Outbreak of Middle East Respiratory Syndrome Coronavirus in Korea. Asian Nurs Res (Korean Soc Nurs Sci). 2016;10(4):295-9. [PubMed ID: 28057317]. [PubMed Central ID: PMC7104920].

  • 11.

    Hu D, Kong Y, Li W, Han Q, Zhang X, Zhu LX, et al. Frontline nurses' burnout, anxiety, depression, and fear statuses and their associated factors during the COVID-19 outbreak in Wuhan, China: A large-scale cross-sectional study. EClinicalMedicine. 2020;24:100424. [PubMed ID: 32766539]. [PubMed Central ID: PMC7320259].

  • 12.

    Alharbi J, Jackson D, Usher K. Compassion fatigue in critical care nurses. An integrative review of the literature. Saudi Med J. 2019;40(11):1087-97. [PubMed ID: 31707404]. [PubMed Central ID: PMC6901773].

  • 13.

    Bagheri Sheykhangafshe F, Saeedi M, Ansarifar N, Savabi Niri V, Deldari Alamdari M. [Evaluation of Post-traumatic Stress Disorder, Depression and Anxiety of Nurses during Coronavirus 2019 Pandemic: A Systematic Review]. Iran J Nurs Res. 2021;16(5):58-70. Persian.

  • 14.

    Vahey DC, Aiken LH, Sloane DM, Clarke SP, Vargas D. Nurse burnout and patient satisfaction. Med Care. 2004;42(2 Suppl):II57-66. [PubMed ID: 14734943]. [PubMed Central ID: PMC2904602].

  • 15.

    Bianchi R, Laurent E. Emotional information processing in depression and burnout: an eye-tracking study. Eur Arch Psychiatry Clin Neurosci. 2015;265(1):27-34. [PubMed ID: 25297694].

  • 16.

    Bakusic J, Schaufeli W, Claes S, Godderis L. Stress, burnout and depression: A systematic review on DNA methylation mechanisms. J Psychosom Res. 2017;92:34-44. [PubMed ID: 27998510].

  • 17.

    Maske UE, Riedel-Heller SG, Seiffert I, Jacobi F, Hapke U. [Prevalence and Comorbidity of Self-Reported Diagnosis of Burnout Syndrome in the General Population - Results of the German Health Interview and Examination Survey for Adults (DEGS1)]. Psychiatr Prax. 2016;43(1). e1. German. [PubMed ID: 26200429].

  • 18.

    Sun W, Fu J, Chang Y, Wang L. Epidemiological study on risk factors for anxiety disorder among Chinese doctors. J Occup Health. 2012;54(1):1-8. [PubMed ID: 22156318].

  • 19.

    Teo I, Chay J, Cheung YB, Sung SC, Tewani KG, Yeo LF, et al. Healthcare worker stress, anxiety and burnout during the COVID-19 pandemic in Singapore: A 6-month multi-centre prospective study. PLoS One. 2021;16(10). e0258866. [PubMed ID: 34679110]. [PubMed Central ID: PMC8535445].

  • 20.

    Sarboozi Hoseinabadi T, Kakhki S, Teimori G, Nayyeri S. Burnout and its influencing factors between frontline nurses and nurses from other wards during the outbreak of Coronavirus Disease -COVID-19- in Iran. Invest Educ Enferm. 2020;38(2). [PubMed ID: 33047546]. [PubMed Central ID: PMC7883923].

  • 21.

    Mohammadnahal L, Mirzaei A, Khezeli MJ. The effect of caring for COVID-19 patients on nurses' productivity and burnout. Nurs Midwifery J. 2021;18(11):859-72. Persian.

  • 22.

    Zakeri MA, Rahiminezhad E, Salehi F, Ganjeh H, Dehghan M. Burnout, Anxiety, Stress, and Depression Among Iranian Nurses: Before and During the First Wave of the COVID-19 Pandemic. Front Psychol. 2021;12:789737. [PubMed ID: 34899542]. [PubMed Central ID: PMC8654725].

  • 23.

    Maslach C, Jackson SE, Leiter MP. Maslach burnout inventory. Maryland , USA: Scarecrow Education; 1997.

  • 24.

    Lovibond PF, Lovibond SH. The structure of negative emotional states: comparison of the Depression Anxiety Stress Scales (DASS) with the Beck Depression and Anxiety Inventories. Behav Res Ther. 1995;33(3):335-43. [PubMed ID: 7726811].

  • 25.

    Amini F. [The Relationship between Resiliency and Burnout in Nurses]. J Res Dev Nurs Midw. 2013;10(2):94-102. Persian.

  • 26.

    Brown TA, Chorpita BF, Korotitsch W, Barlow DH. Psychometric properties of the Depression Anxiety Stress Scales (DASS) in clinical samples. Behav Res Ther. 1997;35(1):79-89. [PubMed ID: 9009048].

  • 27.

    Afzali A, Delawar A, Barjali A, Mirzamani M. [Psychometric Properties of DASS-42 as Assessed in a Sample of Kermanshah High School Students]. J Res Behav Sci. 2007;5(2):81-92. Persian.

  • 28.

    Shanafelt TD, Boone S, Tan L, Dyrbye LN, Sotile W, Satele D, et al. Burnout and satisfaction with work-life balance among US physicians relative to the general US population. Arch Intern Med. 2012;172(18):1377-85. [PubMed ID: 22911330].

  • 29.

    Shanafelt TD, Hasan O, Dyrbye LN, Sinsky C, Satele D, Sloan J, et al. Changes in Burnout and Satisfaction With Work-Life Balance in Physicians and the General US Working Population Between 2011 and 2014. Mayo Clin Proc. 2015;90(12):1600-13. [PubMed ID: 26653297].

  • 30.

    Lai J, Ma S, Wang Y, Cai Z, Hu J, Wei N, et al. Factors Associated With Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019. JAMA Netw Open. 2020;3(3). e203976. [PubMed ID: 32202646]. [PubMed Central ID: PMC7090843].

  • 31.

    Zhu J, Sun L, Zhang L, Wang H, Fan A, Yang B, et al. Prevalence and Influencing Factors of Anxiety and Depression Symptoms in the First-Line Medical Staff Fighting Against COVID-19 in Gansu. Front Psychiatry. 2020;11:386. [PubMed ID: 32411034]. [PubMed Central ID: PMC7202136].

  • 32.

    Zerbini G, Ebigbo A, Reicherts P, Kunz M, Messman H. Psychosocial burden of healthcare professionals in times of COVID-19 - a survey conducted at the University Hospital Augsburg. Ger Med Sci. 2020;18:Doc05. [PubMed ID: 32595421]. [PubMed Central ID: PMC7314868].

  • 33.

    Noh EY, Park YH, Chai YJ, Kim HJ, Kim E. Frontline nurses' burnout and its associated factors during the COVID-19 pandemic in South Korea. Appl Nurs Res. 2022;67:151622. [PubMed ID: 36116862]. [PubMed Central ID: PMC9349023].

  • 34.

    Bahmani A. [Investigating the effect of work shifts in coronary conditions on burnout of employees with the mediating role of coronary stress]. Quart J Nurs Manag. 2020;9(4):20-6. Persian.

  • 35.

    Ulfa M, Azuma M, Steiner A. Burnout status of healthcare workers in the world during the peak period of the COVID-19 pandemic. Front Psychol. 2022;13:952783. [PubMed ID: 36211838]. [PubMed Central ID: PMC9532965].

  • 36.

    Aghajani MJ. [The Professional Burnout of Nurses in Different Wards]. J Res Dev Nurs Midw. 2013;9(2):97-104. Persian.

  • 37.

    Li Z, Ge J, Yang M, Feng J, Qiao M, Jiang R, et al. Vicarious traumatization in the general public, members, and non-members of medical teams aiding in COVID-19 control. Brain Behav Immun. 2020;88:916-9. [PubMed ID: 32169498]. [PubMed Central ID: PMC7102670].

  • 38.

    Ariapooran S, Mosavi SV, Amirimanesh M. [Turnover Intention of Nurses in the outbreak of COVID-19: The Role of Compassion Fatigue, Compassion Satisfaction and Burnout]. Quart J Nurs Manag. 2021;10(1). Persian.

  • 39.

    Sahibzadeh M, Moradi B. [Factors associated with burnout in nursing staff during the Covid-19 pandemic and its management strategies: a review study]. Iran J Nurs Res. 2023;18(3):70-86. Persian.

  • 40.

    Janeway D. The Role of Psychiatry in Treating Burnout Among Nurses During the Covid-19 Pandemic. J Radiol Nurs. 2020;39(3):176-8. [PubMed ID: 32837392]. [PubMed Central ID: PMC7377731].