BurnoutandItsRelationshipWithDepressiveSymptomsinMedicalStaffDuringtheCOVID-19EpidemicinChina.pdf

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ORIGINAL RESEARCHpublished: 04 March 2021

doi: 10.3389/fpsyg.2021.616369

Edited by:Andrew E. P. Mitchell,

University of Chester, United Kingdom

Reviewed by:Claudia Carmassi,

University of Pisa, ItalyJelena Bakusic,

KU Leuven, BelgiumHakan Eren,

Ankara University, Turkey

*Correspondence:Tiebang Liu

[email protected] Yang Zhang

[email protected]

†These authors have contributedequally to this work

Specialty section:This article was submitted to

Psychology for Clinical Settings,a section of the journalFrontiers in Psychology

Received: 12 October 2020Accepted: 08 February 2021

Published: 04 March 2021

Citation:Huo L, Zhou Y, Li S, Ning Y,

Zeng L, Liu Z, Qian W, Yang J,Zhou X, Liu T and Zhang XY (2021)

Burnout and Its Relationship WithDepressive Symptoms in Medical

Staff During the COVID-19 Epidemicin China. Front. Psychol. 12:616369.

doi: 10.3389/fpsyg.2021.616369

Burnout and Its Relationship WithDepressive Symptoms in MedicalStaff During the COVID-19 Epidemicin ChinaLijuan Huo1†, Yongjie Zhou2†, Shen Li3, Yuping Ning1,4, Lingyun Zeng2, Zhengkui Liu5,Wei Qian5, Jiezhi Yang6, Xin Zhou7, Tiebang Liu2* and Xiang Yang Zhang5*

1 Department of Psychiatry, Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital),Guangzhou, China, 2 Department of Psychiatric Rehabilitation, Shenzhen Kangning Hospital, Shenzhen, Guangdong, China,3 Department of Psychiatry, College of Basic Medical Sciences, Tianjin Medical University, Tianjin, China, 4 The First Schoolof Clinical Medicine, Southern Medical University, Guangzhou, China, 5 CAS Key Laboratory of Mental Health, Instituteof Psychology, Chinese Academy of Sciences, Beijing, China, 6 Shenzhen Health Development Research Center, Shenzhen,China, 7 Research Center for Psychological and Health Sciences, China University of Geosciences, Wuhan, China

Objective: The large-scale epidemic of Coronavirus Disease 2019 (COVID-19) hastriggered unprecedented physical and psychological stress on health professionals. Thisstudy aimed to investigate the prevalence and risk factors of burnout syndrome, and therelationship between burnout and depressive symptoms among frontline medical staffduring the COVID-19 epidemic in China.

Methods: A total of 606 frontline medical staff were recruited from 133 cities in Chinausing a cross-sectional survey. The Maslach Burnout Inventory (MBI) was used toassess the level of burnout. Depressive symptoms were assessed by the Patient HealthQuestionnaire Depression (PHQ-9).

Results: During the COVID-19 pandemic, 36.5% of the medical staff experiencedburnout. Personal and work-related factors were independently associated withburnout, including age (OR = 0.68, 95% CI: 0.52–0.89, p = 0.004), family income(OR = 0.72, 95% CI: 0.53–0.99, p = 0.045), having physical diseases (OR = 2.16,95% CI: 1.42–3.28, p < 0.001), daily working hours (OR = 1.35, 95% CI: 1.03–1.77,p = 0.033), and profession of nurse (OR = 2.14, 95% CI: 1.12–4.10, p = 0.022). Thecorrelation coefficients between the scores of each burnout subscale and the scoresof depressive symptoms were 0.57 for emotional exhaustion, 0.37 for cynicism, and−0.41 for professional efficacy (all p < 0.001).

Conclusions: Our findings suggest that the prevalence rate of burnout is extremely highamong medical staff during the COVID-19 pandemic, which is associated with otherpsychological disorders, such as depression. Psychological intervention for medical staffis urgently needed. Young and less experienced medical staff, especially nurses, shouldreceive more attention when providing psychological assistance.

Keywords: prevalence, medical staff, COVID-19, depression, burnout

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INTRODUCTION

The outbreak of coronavirus disease 2019 (COVID-19) firstappeared in Wuhan, China in December 2019, and has sinceswept the world at an incredible speed. As of December2020, there have been more than 70 million confirmed casesand more than 1.7 million deaths1. Due to high contagionand possible asymptomatic transmission, as well as a lack ofknowledge of the virus, the demand and pressure on frontlinemedical staff have increased dramatically, especially in the earlystages of the pandemic (Hu B. et al., 2020; Li et al., 2020).This condition has seriously aggravated the mental fatigue ofhealthcare professionals.

According to the latest World Health Organization’sInternational Disease Classification (ICD-11), burnout isofficially classified as an occupational health syndrome, whichis characterized by emotional and mental exhaustion due tolong-term workplace stress and negative job perception. Themost recognized definition of burnout is the three-dimensionalpsychological syndrome proposed by Maslach and Jackson(1981) that includes emotional exhaustion, cynicism, andreduced professional efficacy. Medical staff are susceptible to jobburnout, which has attracted more and more attention recently(Dzau et al., 2018). Meta-analyses have shown that the pooledprevalence of burnout among medical staff is estimated to beabout or more than 30% (Dimou et al., 2016; Gómez-Urquizaet al., 2017; O’Connor et al., 2018; Rezaei et al., 2018), a rateof more than twice compared with professionals in other fields(Dzau et al., 2018). Because of the nature of their work, medicalstaff often face a lot of pressure and negative emotions, such asheavy workload, poor doctor-patient relationship (especially inmainland China), and accumulated frustration in the face ofdeath (He and Qian, 2016; Alharbi et al., 2019). Job burnoutreduces working efficiency and increases medical errors (Patelet al., 2018; Tawfik et al., 2019). To make matters worse, burnoutmay lead to other severe mental disorders, including alcoholabuse/dependence, depression, and an increased risk of suicide(Dyrbye et al., 2008; Johnson et al., 2018).

The unprecedented outbreak of COVID-19 has furtherdamaged the mental health of health care workers. Duringthis pandemic, many social and environmental factors lead toburnout of medical staff, such as isolation, expanded workloads,life-threatening workplaces, concern about infecting relatives orcolleagues, and some personal factors (Lai et al., 2020). A numberof insightful commentaries have been published to appeal to themental burden of medical staff, and to propose guidelines andexpert consensus on mental health services (Greenberg et al.,2020; Liu et al., 2020; Raudenská et al., 2020). Many surveyshave also reported that health care workers exposed to COVID-19 suffered from serious psychological disturbances, the mostcommon of which were depression, anxiety, insomnia, and fear(Lai et al., 2020; Que et al., 2020; Tan et al., 2020a; ZhangW. R. et al., 2020). However, so far, few quantitative studies haveinvestigated the symptoms of job burnout among medical staff(Hu D. et al., 2020; Matsuo et al., 2020; Tan et al., 2020b; Zhang

1 https://www.who.int/emergencies/diseases/novel-coronavirus-2019

Y. et al., 2020). These studies evaluated burnout symptoms, andfocused on frontline nurses instead of estimating prevalence (HuD. et al., 2020; Zhang Y. et al., 2020), or collecting informationin one single institution (Matsuo et al., 2020; Zhang Y. et al.,2020). Tan et al. (2020b) started the survey half a year afterthe outbreak of the pandemic in China and 4 months after theoutbreak in Singapore. At that time, the pressure of medical staffwas different (Tan et al., 2020b). Further, they did not separatelyanalyze the three recognized dimensions of burnout due to theuse of other tools.

The purposes of this study were: (1) to explore the prevalenceof burnout in the frontline medical staff in China during theearly stage of COVID-19 epidemic; (2) to identify the individualand job-related determinants of burnout in this population,and (3) to determine the relationship between burnout anddepressive symptoms.

MATERIALS AND METHODS

Study Design and ParticipantsThis was a cross-sectional survey designed to assess the jobburnout and other mental conditions of frontline medicalworkers in China during the COVID-19 epidemic. In orderto avoid face-to-face interaction, an online questionnaire wasconstructed and distributed via WeChat, one of the mostimportant social tools in mainland China. Data were collectedfrom February 14 to March 29, 2020. A total of 606 frontlinemedical workers were recruited from 133 cities across thecountry. Doctors, nurses, or medical technicians in hospitals,aged 18 years or above were included in this study.

The study was approved by the Institute of Psychology,Chinese Academy of Sciences. Each participant signed anelectronic informed consent form before the survey. Theinformation of all respondents was confidential.

Assessments for Burnout andDepressive SymptomsDemographic and work-related information was collected,including residence, age, sex, height, weight, ethnicity, maritalstatus, education, annual family income, occupation, department,length of service, and daily working hours. At the sametime whether relatives or friends were infected, financialloss, and whether they had experienced SARS outbreakswere also collected.

The Chinese version of the Maslach Burnout Inventory-General Survey (MBI-GS)(Maslach and Jackson, 1981; Schutteet al., 2000) was used to assess job burnout, which has been widelyused among healthcare workers in China, and has satisfactoryreliability and validity (Wu et al., 2007). The MBI-GS consists of15 items, measuring three dimensions of occupational burnout:emotional exhaustion (EE), which means being emotionallydepleted at work; cynicism (CY), which means negative or cynicalattitudes toward work; professional efficacy (PE), which meansa positive sense of success/achievement at work. Each item isscored using a 7-point frequency range scale (0 = never to6 = daily). The total score of each subscale is stratified into high,

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moderate, or low tertiles. Based on the previous large samplestudies on Chinese healthcare workers (Wu et al., 2014), thecutoffs for each tertile of burnout were determined as follows: lowEE < 9, moderate EE 9–13, high EE > 13; low CY < 3, moderateCY 3–9, high CY > 9; low PE > 30, moderate PE 30–18, highPE < 18. A score in the highest tertiles of EE, in combinationwith the highest tertiles of CY or the lowest tertiles of PE indicatesburnout syndrome, according to the “exhaustion + 1” criterion(Brenninkmeijer and VanYperen, 2003). Since the definition ofburnout varies considerably in the literature, the prevalence ofburnout was also calculated using an alternative formula, a morerestrictive definition, that is, a combination of a high EE andhigh CY and low PE subscale score (Lin et al., 2019). PatientHealth Questionnaire-9 (PHQ-9) was applied to assess depressivesymptoms (Kroenke et al., 2001). PHQ-9 consists of 9 items, eachwith a score from 0 to 3. People with a total score of 4 or more areidentified to have depressive symptoms.

Statistical AnalysisThe chi-square test and analysis of variance (ANOVA) wereused to compare the demographic and work-related variables ofparticipants between the burnout group and the non-burnoutgroup. The binary logistic regression model was used to find outfactors independently related to burnout experience. Then, inorder to further identify the independent factors associated withMBI-GS scores, stepwise multivariate linear regression modelswere used, with the MBI-GS subscores as dependent variables,and other variables with potential correlation (p < 0.1) with MBI-GS scores as independent factors. Associations between MBI-GSsubscale scores and PHQ-9 scores were examined using Pearsoncorrelation analysis and then linear regression model. Bonferronicorrections were applied to adjust multiple tests. A two-tailed testat p < 0.05 was set to be statistically significant. All statisticalanalyses were conducted using SPSS (version 24.0).

RESULTS

Demographic CharacteristicsAmong all the participants, 492 (81.2%) were female and 114(18.8%) were male. The age of participants ranged from 22 to65 years old, with an average age of 35.77 ± 8.13 years. Theaverage BMI was 23.34 ± 5.61 Kg/m2. More detailed informationabout the demographic and job-related characteristics ofparticipants is shown in Table 1.

Prevalence of Burnout in Medical StaffsBurnout was defined as a high EE combing with a high CY or lowPE subscale scores. During the epidemic of COVID-19, 36.5%of medical staff met the criteria for burnout in our sample. Theprevalence of burnout in female workers was significantly higherthan that in male workers, whether it was the inclusive criteria(38.8% vs. 26.3%, χ2 = 6.25, p = 0.012) or the restrictive one(30.5% vs. 16.7%, χ2 = 8.79, p = 0.003). For each componentof burnout, the prevalence of EE, CY, and PE was 40.9, 63.7,and 46%, respectively. In addition, under the strictest definition,

combining the highest level of EE and CY and the lowest level ofPE, the overall prevalence of burnout was 27.8%.

Chi-squared tests also revealed that there were significantdifferences between burnout and non-burnout groups in termsof age, annual family income, physical disease, occupation, andservice time (all p < 0.05). The burnout rates of each typeof variables were shown in Table 1. Specifically, medical staffwith younger age, female gender, lower family income, moresevere physical disease, shorter service, and nursing professionhad more severe syndrome of burnout. Individuals havingrelatives or friends infected with COVID-19 were at a marginallyhigher risk experiencing burnout (p = 0.058). There was nosignificant difference in BMI, education, marital status, ethnicity,experienced SARS or not, and daily working hours (all p > 0.05)between the burnout and non-burnout groups.

Further, the binary logistic regression model revealed that thefollowing variables were independently associated with burnout,including age (OR = 0.68, 95% CI: 0.52–0.89, p = 0.004), familyincome (OR = 0.72, 95% CI: 0.53–0.99, p = 0.045), having physicaldisease (OR = 2.16, 95% CI: 1.42–3.28, p < 0.001), daily workinghours (OR = 1.35, 95% CI: 1.03–1.77, p = 0.033), and professionof nurse (OR = 2.14, 95% CI: 1.12–4.10, p = 0.022).

Factors Associated With Burnout and ItsThree Components in Medical StaffsThe average burnout score was 11.94 ± 6.47 on EE subscale,10.27 ± 4.74 on CY subscale, and 19.25 ± 6.72 on PEsubscale. MBI-GS subscale scores after grouping according todemographics and work-related variables were present in Table 2.Then multiple linear regressions were performed to identifyindependent related factors to each MBI-GS subscore. EE wasindependently correlated with age (β = −0.13, t = −2.87,p = 0.004), physical diseases (β = 0.12, t = 3.0, p = 0.003),professional role of nurses (β = 0.09, t = 2.16, p = 0.031),and daily working hours (β = 0.14, t = 3.57, p < 0.001). CYwas independently correlated with professional role of nurses(β = 0.21, t = 4.90, p < 0.001), age (β = −0.11, t = −2.45,p = 0.015), and family income (β = −0.10, t = −2.40, p = 0.017).PE was independently correlated with age (β = 0.13, t = 3.06,p = 0.002) and professional role of nurses (β = −0.30, t = −7.18,p < 0.001). Taken together, younger age and nursing professionwere independently correlated with all dimensions of burnout.

The Association Between Burnout andDepressive Symptoms in Medical StaffsThe mean score of PHQ-9 was 6.46 ± 5.57. With the cut-offscore of 4, the overall prevalence of depressive symptoms inmedical staff was 57.6%. The correlation coefficients betweenthe score of each MBI-GS subscale and the score of PHQ-9 were 0.57 for EE, 0.37 for CY, and −0.41 for PE (allp < 0.001, Figure 1). These associations remained significantafter Bonferroni corrections. Stepwise multiple regression modelshowed that scores of EE (β = 0.51, t = 12.12) and PE (β = 0.51,t = 12.12) were independently associated with PHQ-9 score.These two components of burnout together accounted for 32.8%of the variance (adjusted R2) in PHQ-9 (F = 148.75, p < 0.001).

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DISCUSSION

Although there has been a large number of studies on mentalhealth problems caused by the COVID-19 pandemic, only afew have investigated burnout syndrome, which was particularlyprevalent in medical staff even before this pandemic. To ourknowledge, this is the first nationwide cross-sectional survey onjob burnout of medical staff during the COVID-19 pandemic,with a total of 606 participants. The main findings of this study

were: (1) up to 36.5% of the respondents met the criteria ofburnout; (2) personal factors (i.e., age, sex, physical diseases,and family income) and job-related factors (daily working hours,length of service, and nursing profession) were associated withburnout; (3) the burnout levels were associated with the severityof depressive symptoms.

Our results showed an extremely high prevalence (36.5%) ofburnout, which made medical workers psychologically vulnerablein this pandemic. Consistently, previous studies have revealed

TABLE 1 | Demographic data of participants with and without burnout.

Variable Total (n = 606) Non-burnout (n = 385) Burnout (n = 221) p-value

Age <0.001

<30 177 (29.2%) 102 (57.6%) 75 (42.4%)

30–40 261 (43.1%) 155 (59.4%) 106 (40.6%)

>40 168 (27.7%) 128 (76.2%) 40 (23.8%)

Sex 0.012

Male/Female (male%) 114/492 (18.8%) 84/301 (21.8%) 30/191 (13.6%)

BMI 0.682

<18.5 43 (7.1%) 29 (67.4%) 14 (32.6%)

18.5–24 379 (62.5%) 243 (64.1%) 136 (35.9%)

>24 183 (30.2%) 112 (61.2%) 71 (38.8%)

Education 0.488

High school degree or lower, n (%) 14 (2.3%) 7 (50%) 7 (50%)

College degree, n (%) 446 (73.6%) 282 (63.2%) 164 (36.8%)

Master or Doctoral degree, n (%) 146 (24.1%) 96 (65.8%) 50 (34.2%)

Marital status 0.455

Single, n (%) 123 (20.6%) 73 (59.3%) 50 (40.7%)

Married, n (%) 456 (74.9%) 293 (64.3%) 163 (35.7%)

Widowed or divorced 27 (4.5%) 19 (70.4%) 8 (29.6%)

Ethnicity 0.493

Han/Non-han population (Han%) 556/50 (91.7%) 351/34 (91.2%) 205/16 (92.8%)

Family income 0.018

Low 106 (17.5%) 56 (52.8%) 50 (47.2%)

Medium 402 (66.3%) 259 (64.4%) 143 (35.6%)

High 98 (16.2%) 70 (71.4%) 28 (28.6%)

Physical diseases 0.003

Yes/No (Yes%) 133/473 (21.9%) 70/315 (18.2%) 63/158 (28.5%)

Infected relatives or friends 0.058

Yes/No (Yes%) 13/593 (2.1%) 5/380 (1.3%) 8/213 (3.6%)

Experienced SARS 0.199

Yes/No (Yes%) 262/344 (43.2%) 174/211 (45.2%) 88/133 (39.8%)

Profession 0.001

Doctor 208 (34.3%) 143 (68.8%) 65 (31.3%)

Nurse 334 (55.1%) 192 (57.5%) 142 (42.5%)

Medical technician 64 (10.6%) 50 (78.1%) 14 (21.9%)

Length of service 0.036

<6 years 110 (18.2%) 69 (62.7%) 41 (37.3%)

6–10 years 163 (26.9%) 92 (56.4%) 71 (43.6%)

11–20 years 194 (32%) 123 (63.4%) 71 (36.6%)

>20 years 139 (22.9%) 101 (72.7%) 38 (27.3%)

Daily working hours 0.190

4–8 284 (46.9%) 190 (66.9%) 94 (33.1%)

8–10 268 (44.2%) 165 (61.6%) 103 (38.4%)

> 10 54 (8.9%) 30 (55.6%) 24 (44.4%)

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FIGURE 1 | Three dimensions of burnout (A) emotional exhaustion, (B) cynicism, and (C) professional efficacy were associated with depressive symptoms (PHQ-9)in medical staff.

that medical workers are particularly prone to burnout. Theprevalence of burnout in healthcare professions varies from 12.6to 76.9% in different studies (Abdulla et al., 2014; Adriaenssenset al., 2015; Elmore et al., 2016; Wen et al., 2016; Gómez-Urquiza et al., 2017). The huge differences across studies notonly result from regional disparities but also result from differentapproaches to define burnout (Rotenstein et al., 2018). It is stillin dispute whether the concept of burnout should be regarded asa unidimensional or multidimensional construct. Some researchdefined burnout as a multidimensional construct, so individualswere considered burnout when meeting the criterion of oneof the three MBI dimensions (Elmore et al., 2016; Gómez-Urquiza et al., 2017). While other studies combine differentdimensions into a unidimensional burnout, which also developmany formulas (Adriaenssens et al., 2015; Wen et al., 2016). Tosolve this problem, Brenninkmeijer and VanYperen (2003) testeddifferent approaches and concluded that “exhaustion + 1” isthe most recommended approach. This means that individualsare determined as burned out when having high levels ofexhaustion and either high levels of cynicism or low levels ofprofessional efficacy. This approach is in line with the ideathat exhaustion is the core symptom of burnout, also the onlydimension present in all different definitions and assessmenttools for burnout. Therefore, exhaustion is a necessary symptomto set the “diagnosis” of burnout.

Due to the substantially various definitions and theimpossibility to compare burnout prevalences across studies, wealso directly compared the burnout scores between our resultsand studies using the same tool. Compared with the specificburnout scores of medical staff in different studies in China,this study found that the scores of medical staff on the EE andCY subscale were extremely higher, while the score on the PEsubscale was lower (Wu et al., 2008, 2011, 2013, 2014; He et al.,2019). Taken together, it is speculated that there is a significantnegative correlation between the long-term COVID-19 pandemicand the burnout experience of medical staff, although the criteriafor the diagnosis of burnout are different.

Among the related factors of job burnout, job-related factorsare the most concerned and discussed in detail under theburden of the COVID-19 pandemic. First of all, the occupationwas closely related to job burnout. Compared with doctorsand medical technicians, nurses are most likely to experiencejob burnout, which is consistent with many previous studies(Alacacioglu et al., 2009; Wu et al., 2011; Chou et al., 2014;Schooley et al., 2016) and the latest surveys conducted duringthe COVID-19 pandemic (Hu D. et al., 2020; Matsuo et al.,2020; Zhang Y. et al., 2020). Nursing job burnout has becomea global phenomenon. In hospitals in the United States, there isa shortage of nursing staff, resulting in a high patient-to-nurseratio, persistent emotional exhaustion, and job dissatisfaction

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TABLE 2 | MBI-GS subscale scores in grouped demographics andwork-related variables.

Variables EE CY PE

Age, years

<30 12.69 ± 6.70 11.11 ± 4.53 17.77 ± 6.15

30–40 12.41 ± 6.45 10.85 ± 4.44 18.32 ± 6.24

>40 10.43 ± 6.05 8.47 ± 4.96 22.23 ± 7.10

F 6.54** 17.73** 25.18**

Sex

Male 10.79 ± 5.92 8.84 ± 4.70 21.54 ± 6.8

Female 12.21 ± 6.57 10.60 ± 4.70 18.72 ± 6.59

F 4.49* 12.89** 16.73**

BMI

<18.5 11.16 ± 6.03 11.16 ± 4.35 18.05 ± 6.53

18.5–24 11.90 ± 6.5 10.47 ± 4.62 18.99 ± 6.64

>24 12.24 ± 6.54 9.61 ± 5.03 20.05 ± 6.88

F 0.51 2.87 2.26

Education

High school degree or lower 12.71 ± 7.69 11.71 ± 1.90 17.93 ± 3.56

College degree 11.93 ± 6.58 10.71 ± 4.69 18.57 ± 6.60

Master or Doctoral degree 11.91 ± 6.06 8.77 ± 4.79 21.45 ± 6.86

F 0.10 10.11** 10.70**

Marital status

Single 12.55 ± 6.60 10.71 ± 4.84 18.31 ± 6.74

Married 11.78 ± 6.49 10.16 ± 4.71 19.43 ± 6.69

Widowed or divorced 11.85 ± 5.70 9.96 ± 4.94 20.44 ± 6.90

F 0.67 0.69 1.80

Ethnicity

Han population 11.93 ± 6.42 10.36 ± 4.71 19.11 ± 6.73

Non-han population 12.10 ± 7.11 9.18 ± 5.08 20.74 ± 6.48

F 0.32 2.86 2.70

Family income

Low 13.17 ± 6.89 11.42 ± 3.97 18.06 ± 5.62

Medium 11.79 ± 6.35 10.38 ± 4.79 18.99 ± 6.73

High 11.27 ± 6.41 8.55 ± 4.91 21.58 ± 7.25

F 2.57 9.91** 8.06**

Physical diseases

No 11.60 ± 6.46 10.22 ± 4.71 19.26 ± 6.70

Yes 13.18 ± 6.40 10.41 ± 4.89 19.21 ± 6.81

F 6.27* 0.17 0.01

Infected relatives or friends

No 11.90 ± 6.48 10.25 ± 4.72 19.24 ± 6.68

Yes 14.08 ± 6.06 10.77 ± 5.93 19.38 ± 8.72

F 1.44 0.15 0.01

Experienced SARS

No 11.92 ± 6.59 10.52 ± 4.63 18.83 ± 6.79

Yes 11.98 ± 6.33 9.94 ± 4.88 19.79 ± 6.60

F 0.2 2.25 3.08

Profession

Doctor 11.38 ± 6.15 8.54 ± 4.94 22 ± 6.85

Nurse 12.69 ± 6.65 11.43 ± 4.22 17.13 ± 5.89

Medical technician 9.89 ± 6.03 9.77 ± 4.96 21.33 ± 6.53

F 6.36** 26.21** 42.14**

Length of service

<6 years 12.06 ± 7.05 10 ± 5.13 19.47 ± 7.22

(Continued)

TABLE 2 | Continued

Variables EE CY PE

6–10 years 12.96 ± 6.31 11.61 ± 4.20 17.14 ± 5.30

11–20 years 11.81 ± 6.22 10.36 ± 4.88 19.28 ± 6.67

>20 years 10.84 ± 6.41 8.78 ± 4.96 21.50 ± 7.14

F 2.75* 9.42** 11.14**

Daily working hours

4–8 11.13 ± 6.24 10.43 ± 4.58 19.18 ± 6.56

8–10 12.48 ± 6.43 10.37 ± 4.68 19.09 ± 6.71

>10 13.57 ± 7.38 8.89 ± 5.67 20.39 ± 7.59

F 4.93** 2.52 0.87

*p < 0.05, **p < 0.01. MBI-GS, Maslach Burnout Inventory-General Survey; EE,emotional exhaustion; CY, cynicism; PE, professional efficacy.

(Aiken et al., 2002). A cross-sectional study of 12 Europeancountries found that longer shifts (12 h or more) were associatedwith job burnout (Dall’Ora et al., 2015). The difference inworking environment between countries limits the promotionof research in western countries. According to the few pieces ofliterature in China, the sense of professional efficacy of nurses islower than that of doctors (Wu et al., 2013, 2014). For Chinesenurses, the large population base leads to a high nurse-patientratio. Compared with doctors and medical technicians, nursingis a relatively low-paid profession in China. The reform of healthcare system policy and management strategy is accompaniedby economic reform, which aggravates the great pressure andburnout of nurses (Wu et al., 2010). To make matters worse,in the early days of COVID-19 pandemic, medical personnelwere not equipped with protective equipment and tested forcoronavirus. As the main caregivers of patients, nurses havedirect contact with infected patients many times a day whenperforming their duties. Therefore, compared with other medicalstaff, nurses face greater health risks, and consequently bear morepsychological burden. Another explanation may be that nursesare mainly women, and they may bear more psychopathologicalburdens in outbreaks that threaten the health of family membersor affect the care of children. Previous studies have demonstratedthat women are more likely to suffer from PosttraumaticStress Disorder (PTSD) and Posttraumatic Stress Symptoms(PTSS), and have more depressive and anxiety symptoms inthe face of every coronavirus outbreak (Buselli et al., 2020;Carmassi et al., 2020).

The length of service was significantly correlated with everydimension of the burnout experience. Less than 20 years ofservice was risky for job burnout. The medical staff witha working life of 6–10 years had the strongest sense ofemotional exhaustion and cynicism and the lowest sense ofprofessional efficacy. Rich work experience after long service maycontribute to higher esteem and better emotional regulation.It is reasonable that medical staff with work experience hadenhanced psychological preparation and knowledge of infectioncontrol, and reduced the level of job burnout. The previousstudies found that experienced nurses had a lower risk ofviolence in the workplace and a higher tolerance for patientaggression (Whittington, 2002; Edward et al., 2014). Young and

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inexperienced employees may be more nervous about highlycontagious diseases.

Interestingly, we found that prolonged daily working hourswere only associated with emotional exhaustion, not withcynicism and professional efficacy. As the relationship betweenexcessive workload and a higher level of burnout has been wellproved, many studies have proposed limiting working hours asthe first step to prevent burnout (Gopal et al., 2005; Martiniet al., 2006; Dugani et al., 2018). It should be noted thatreducing working hours may not necessarily reduce cynicismand improve professional effectiveness. Moreover, during theCOVID-19 epidemic, the huge number of infections and theexponential spread of coronavirus made the workload impossibleto reduce. Therefore, during the pandemic, other more feasiblemethods are needed to alleviate the burnout experience.

Another important finding is that during the COVID-19outbreak, job burnout of medical staff was positively correlatedwith depression. The latest report has demonstrated that duringthe COVID-19 outbreak, medical workers are twice as likelyto suffer from depressive symptoms and other psychologicaldisorders as the general population (Lu et al., 2020). Thebi-directional link between burnout and depression has beenwidely recognized. Longitudinal studies have shown that anincrease in burnout levels can predict a subsequent increasein depressive symptoms (Bianchi et al., 2015). As a result, theincrease in depression is likely to be the result of exposureto unprecedented work-related stress during the COVID-19pandemic, and vice versa. It is worth noting that due to the cross-sectional design, this study did not prove the causal relationshipbetween burnout and depression.

This study has several limitations. First, this cross-sectionalsurvey conducted at a single time point could not compareburnout levels before and after the outbreak. Moreover, there wasrelatively limited information on the specific factors of outbreaksthat contribute to an increase in the prevalence of burnout.Therefore, our findings cannot reveal the causal relationshipbetween the COVID-19 outbreak and high levels of job burnout.Second, as there is no consensus on the diagnosis of job burnout,it is difficult to directly compare the prevalence of job burnout.A recent review found that the existing literature used at least47 different definitions of the prevalence of burnout when usingthe MBI tool to measure burnout (Rotenstein et al., 2018).Therefore, it is necessary in future studies to reach a consensuson how to classify different degrees of job burnout. Third, thelevels of job burnout in the health care profession were not becompared with that of other occupations, as other industries werealmost completely shut down during the pandemic. Therefore,the special impact of the COVID-19 epidemic on medical staffwas not investigated. Fourth, there may be a sampling bias.The sample was composed of most female subjects who weremore vulnerable to traumatic events. Hence, caution should betaken when extending our findings to other populations. Fifth,psychiatric evaluation of the samples was not performed beforethe study. As previously reported, pre-existing mental illness orsusceptibility may have affected the development of burnout anddepressive symptoms during the COVID-19 pandemic (Fiorilloet al., 2020). Sixth, the existence of burnout was investigated

using an online self-administered questionnaire, which maycompromise the reliability and validity of the measurement.

In summary, our report showed that there was a high rateof burnout among medical staff in China, which is likely tointensify during the COVID-19 pandemic. Occupation, lengthof service, working hours, and several individual variables,including age, sex, pre-existing physical diseases, and familyincome, are determinants of job burnout scores. The experienceof burnout hinders the fight against the epidemic situationof COVID-19 and has a lasting negative impact on mentalhealth. During and after the COVID-19 pandemic, interventionmeasures such as mindfulness-based decompression are urgentto deal with stress and solve the job burnout of medical staff.Psychological evaluation and psychological counseling shouldbe carried out for medical staff on a long-term and regularbasis. Our study suggests that when providing mental healthservices, more attention should be paid to young and lessexperienced medical staff, especially nurses. Compared withwestern countries, there are relatively few studies on job burnoutof medical staff in China. Therefore, even after the COVID-19 pandemic, it is necessary to conduct more investigationson the causes and consequences of burnout and take effectiveintervention measures to prevent burnout.

DATA AVAILABILITY STATEMENT

The raw data supporting the conclusions of this article will bemade available by the authors, without undue reservation, to anyqualified researcher.

ETHICS STATEMENT

The studies involving human participants were reviewed andapproved by the Ethics Committee of the Institute of Psychology,Chinese Academy of Sciences. The patients/participants providedtheir written informed consent to participate in this study.

AUTHOR CONTRIBUTIONS

LH and YZ were responsible for statistical analysis andmanuscript drafting. TL and XYZ were responsible for studydesign and writing review. YN, SL, ZL, and WQ were involvedin statistical analysis and the manuscript revision. LZ, JY, andXZ were responsible for data acquirement. All the authorscritically reviewed the manuscript and gave final approval forits publication.

FUNDING

This work was supported by the Sanming Project of Medicinein Shenzhen (No. SZSM202011014), Shenzhen Fund forGuangdong Provincial Highlevel Clinical Key Specialties (No.SZGSP013), and Shenzhen Key Medical Discipline ConstructionFund (No. SZXK072).

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Conflict of Interest: The authors declare that the research was conducted in theabsence of any commercial or financial relationships that could be construed as apotential conflict of interest.

Copyright © 2021 Huo, Zhou, Li, Ning, Zeng, Liu, Qian, Yang, Zhou, Liu and Zhang.This is an open-access article distributed under the terms of the Creative CommonsAttribution License (CC BY). The use, distribution or reproduction in other forumsis permitted, provided the original author(s) and the copyright owner(s) are creditedand that the original publication in this journal is cited, in accordance with acceptedacademic practice. No use, distribution or reproduction is permitted which does notcomply with these terms.

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