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Abstract

Background

Burnout has been prevalent among healthcare workers (HCWs). However, the effect of the Coronavirus Disease (COVID-19) pandemic on this phenomenon in HCWs is unclear.

Objective

This systematic review aims to evaluate the impact of COVID-19 on burnout of HCWs using Maslach Burnout Inventory (MBI).

Methods

A systematic search was performed on PubMed database for articles published between 1 December 2019 and 30 June 2021. Search strategy combined terms for HCWs, COVID-19, burnout, and MBI. The main outcome of interest was burnout, including both mean prevalence and MBI scores for high emotional exhaustion (EE), high depersonalisation (DP) and low personal accomplishment (PA).

Results

Four cohort studies, 90 cross-sectional studies and one randomised-controlled trial were included for review. Only one cohort study compared burnout data among HCWs before and during COVID-19. It reported a statistically significant increase in mean EE and PA scores from 21.9 to 24.8 (p = .001), and 42.7 to 48.7 (p = .001), respectively. The remaining studies only evaluated burnout data during COVID-19 but were missing burnout data prior to the pandemic for comparison. Across these studies, the overall mean prevalence of burnout among HCWs was 39.95%, with mean MBI EE scores of 22.07, DP scores of 7.83, and PA scores of 32.53. Burnout outcomes were generally comparable across specific healthcare professions such as doctors and nurses.

Conclusion

Whilst quality research elucidating the effect of pandemic on burnout is lacking, current burnout prevalence among HCWs during COVID-19 is notable.

Keywords

burnout coronavirus disease healthcare workers Maslach Burnout Inventory

Background

Burnout is defined in the 11^th Revision of the International Classification of Diseases (ICD-11) as an occupational phenomenon usually due to prolonged and unmanaged workplace stress.¹ It has three dimensions: emotional exhaustion (EE), depersonalization (DP) and low personal accomplishment (low PA).^2,3 An individual is said to experience EE when one feels emotionally drained and is unable to help others at a psychological level,^2,4 which prompts one to dissociate oneself from work to manage the emotional overload.⁵ An individual develops DP when one objectifies the clients whom one interacts with to mitigate the distress from the emotional burdens of that interaction.^4,5 Lastly, an individual who experiences low PA usually evaluates oneself negatively and feels discontented about one’s work or performance.^2,4

Several studies conducted between 2005 and 2017 reported that healthcare workers (HCWs) are at high risk of burnout,⁶ with the prevalence of burnout ranging from 30% to 70% among doctors,^7,8 33.3% among nurses,⁹ and often more than 50% among pharmacists.^10–12 This is likely due to the immense emotional and psychological burden resulting from HCWs’ responsibility for their patients’ overall health. Burnout symptoms may manifest in HCWs in terms of negative mental health effects such as stress, psychological distress,^13,14 and anxiety,^5,15 or job withdrawal behaviors such as absenteeism and reduced productivity.⁵

Since December 2019, the global Coronavirus disease (COVID-19) pandemic has strained healthcare systems and HCWs.^16–19 Healthcare institutions face occupational stressors such as having risks of insufficient personal protective equipment, inadequate manpower and increased workload.^17,18,20 Furthermore, HCWs face increased emotional demands such as worry for their own health^21–23 or fear of infecting others,^21,23 and these worries can contribute to burnout.²⁴

Despite increased awareness of HCWs’ well-being during the pandemic,²⁵ the impact of COVID-19 on burnout of HCWs remains unclear. This systematic review aims to evaluate the impact of COVID-19 on burnout of HCW measured using Maslach Burnout Inventory (MBI), a validated tool.^4,26,27

Methods

A team of four researchers performed a systematic review of primary literature evaluating the impact of COVID-19 on the burnout of HCWs. This review was conducted in accordance with “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) guidelines.²⁸

Eligibility criteria

We retrieved articles that contained at least one of the following terms: (a) HCWs, (b) COVID-19 and (c) burnout or MBI scores. Our target population was HCWs. The exposure and/or comparator was presence of COVID-19, while the primary outcome of interest was MBI score. Studies were included if they recruited HCWs and had burnout data measured using MBI during COVID-19. Studies that were missing pre-COVID 19 historical comparator data were also included for the descriptive analysis. Studies that were not written in English language were excluded. Protocols, commentaries, editorials or unpublished studies were also excluded.

Search strategy, information sources and study selection

On 19 July 2021, one researcher performed a comprehensive systematic search on PubMed electronic database using the following keywords: “health personnel” OR “health occupations” AND “COVID-19” OR “SARS-CoV-2” AND “burnout” OR “Maslach Burnout Inventory” OR “MBI” OR “mental health”. The full list of search terms can be viewed in Supplementary Appendix Table A1.

Studies published between 1 December 2019 to 30 June 2021 were retrieved. Additional studies from the reference lists of included reviews were also retrieved. Screening of titles and abstracts of studies and removing of duplicates were performed manually by two independent reviewers. Any disagreements throughout the process were resolved through consensus with a senior researcher. Subsequently, the same reviewers performed full-text screening of the remaining studies to assess their eligibility for inclusion.

Data collection process, data items and quality appraisal

Two independent reviewers extracted data from included studies and compiled them in a standardized Excel template. The data extracted included: name of author(s), publication year, country, study design, period of data collection, sample size, age (mean ± standard deviation), sex distribution, healthcare profession(s) involved and burnout outcomes. A sample list of the data collected from included studies can be viewed in Supplementary Appendix Table A2.

Risk of bias (ROB) was performed simultaneously during full-text screening and data extraction of included articles. The quality of studies was assessed by the same two reviewers using the 8-item, 11-item, and 13-item Joanna Briggs Institute (JBI) critical appraisal tools for cross-sectional studies, cohort studies and randomized controlled trials, respectively.²⁹ While the ROB was assessed for all studies, measuring the extent of exposure to COVID-19 stressors could not be done reliably and objectively. Hence, a score of zero was allocated for these items. Studies were categorised as low (13–16), moderate (7–12) and high ROB (0–6) based on their tabulated scores.³⁰ The ROB assessment for all included studies can be viewed in Supplementary Appendix Table A3.

Study outcomes and summary measures

Maslach Burnout Inventory is a validated tool to measure burnout, comprising a 22-item, self-reported questionnaire based on a 7-point Likert scale that assesses EE, DP, and PA subscales.^4,26 There are several variations of the MBI, of which MBI-Human Services Survey (MBI-HSS) and MBI-Human Services Survey (Medical Personnel) (MBI-HSS(MP)) are validated and most used for HCWs.^31,32 In our review, studies that used MBI-HSS or MBI-HSS(MP) were grouped together under MBI-HSS due to their near identical question set, differing only in choice of noun describing clients as patients.³² Another included variation was the MBI-General Survey (MBI-GS).

To our knowledge, based on previous systematic reviews published on burnout evaluated with MBI, there is often no standardized definition of burnout across different studies.^33–36 There is also a lack of consensus on the MBI cut-off scores defining high EE, high DP, and low PA, with MBI’s authors acknowledging the lack of diagnostic validity of cut-off scores in defining burnout.³⁷ Despite these issues limiting comparison across different studies, we sought to organize burnout data from identified studies to quantify the mean prevalence of burnout and mean MBI scores for its three subscales (EE, DP and PA) as defined by the study’s authors. For each identified study, we obtained the authors’ defined MBI cut-off scores for high EE, high DP, and low PA, and used these cut-off scores to review the said study’s data. Corresponding authors of studies that did not report cut-off scores or had missing burnout data were contacted by email for further clarification. These studies were omitted if the authors did not respond. As burnout among HCWs is more commonly defined as high EE score of ≥27, high DP ≥ 10, and/or low PA ≤ 33 based on MBI, studies that used these specific MBI cut-off scores for burnout were planned to be grouped together to assess the pooled effects and for subsequent sensitivity analysis.

Some studies reported median values for burnout prevalence and MBI scores. Based on the Central Limit Theorem,³⁸ if the sample size of the individual study exceeded 30, we estimated the median value to be close to the mean, hence these median values would be pooled with mean estimates listed in other studies.

Data analysis and synthesis of results

Burnout prevalence and MBI scores for EE, DP and PA were evaluated as continuous data, with the data presented as weighted mean (minimum - maximum). For meta-analysis, we planned to assess the heterogeneity of included studies via visual inspection of forest plots, calculated I² statistic and 95% confidence interval. Similar studies would be grouped together for sub-group analyses based on study design and healthcare profession. Pooled means of burnout prevalence and MBI scores would be calculated using fixed-effects and random-effects models, for similar studies and those with large heterogeneity, respectively.

Publication bias and additional analyses

Assessment of publication bias across studies using funnel plot and additional analyses for profession were conducted.

Results

Study selection

A total of 6150 articles were retrieved for title and abstract screening, of which 2337 were retained for full-text review. Total of 95 articles were eventually included in this review. Figure 1 shows the PRISMA Flow Diagram for the inclusion and exclusion of articles.

Figure 1.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram. n_studies: number of studies.

Study characteristics

Study design and demographics

A total of 95 studies, comprising of four cohort studies,^39–42 90 cross-sectional studies, and one randomised controlled trial (RCT)⁴³ were included in this review, involving 61,401 HCWs.

Only one cohort study by Leskovic et al.³⁹ addressed the primary aim of this review. It recruited a mixed population of nurses and healthcare assistants, involving 1009 participants, of which 328 completed both questionnaires before and during COVID-19. Across the participants, the percentage of females was 95.0% and the mean age was 41.3 years. Burnout among HCWs was assessed using MBI scores and compared between before and during COVID-19 to evaluate the impact of the pandemic on HCWs’ burnout.

Among the remaining three cohort studies, two studies^40,41 involved only doctors, while the last study⁴² involved mixed professions. While all three studies assessed burnout before and during COVID-19 using MBI scores, Baro et al.⁴⁰ and Mills et al.⁴¹ used an abbreviated MBI, which is not validated. The cohort study by Kok et al.⁴² collected pre-COVID-19 burnout data close to the start of COVID-19 (defined in this review as 1 December 2019). Hence, the data was treated as two cross-sectional datasets for burnout assessment during COVID-19 instead as it was hard to remove the risk of bias with the baseline burnout data from that study. In the pooled data for all four cohort studies, the percentage of females was 88.2% and the mean age was 41.8 years.

All 90 cross-sectional studies measured burnout among HCWs only during COVID-19, but not before. Nevertheless, burnout data reported in the period of COVID-19 as mean prevalence and MBI scores were analysed. Among the studies, 37 of them included only one healthcare profession, mainly doctors^44–63 (number of studies, n_studies = 20, number of participants, n_participants = 6142), and nurses^64–74 (n_studies = 11, n_participants = 18,971). Other professions or job roles included pharmacists,^75,76 therapists,^77,78 healthcare trainees⁷⁹ and social workers.⁸⁰ In the pooled data for these 37 studies, the percentage of females was 79.3% and the mean age was 35.2 years. The remaining 53 studies had a variety or mix of healthcare professions in their populations, primarily composed of doctors (n_studies = 45, n_participants = 14,877), nurses (n_studies = 39, n_participants = 9421), and others. In the pooled data for studies with mixed professions, the percentage of females was 71.4% and the mean age was 39.1 years.

The sole RCT⁴³ identified in this review examined the impact of a mobile application on burnout outcomes among HCWs with mixed professions during COVID-19, comprising an intervention group and a control group. While the study did not match the primary aim of this review, its reported burnout scores were treated as two cross-sectional datasets for analysis. Across its population, the percentage of females was 83.2% and the mean age was 41.4 years.

Burnout outcomes for analysis

This review focused on burnout measured with the MBI. Different definitions of burnout, variations of MBI and MBI cut-off scores defining high EE, high DP, and low PA were used to assess burnout among HCWs.

Fifty-nine out of the total 95 studies (62%) used MBI-HSS (MBI-HSS: n_studies = 50, MBI-HSS(MP): n_studies = 9^{59,69,81–87}). Eight studies (8%) used MBI-GS.^{67,72,73,88–92} The remaining 28 studies (29%) used a wide range of non-validated abbreviated or modified forms of MBI (modified MBI), such as single-item questionnaire to 21-item measures.^{40,41,45,48,49,52,54,55,57,58,61,68,77–79,93–105} Such studies were excluded for all statistical analysis due to difficulty in pooling data and lack of external validity.

Prevalence of burnout based on definitions and MBI cut-off scores

Across the studies, definitions used to categorise HCWs with burnout and HCWs who met the cut-off scores for high EE, high DP, and low PA were different.

Table 1 presents the definitions of burnout used in the various studies, and the respective overall reported burnout prevalence among HCWs during COVID-19. Out of 90 cross-sectional studies, those that had missing data or used modified MBI (n_studies = 61) were excluded.

Table 1.

Definitions of burnout, number of studies, and overall burnout prevalence (n_studies = 29).

Definitions	Number of studies	Overall burnout prevalence
High EE, high DP, and low PA	11^a	25.76%
High EE, and/or high DP	9	46.02%
High EE, or high DP, or low PA	6	61.63%
High EE, and high DP/Low PA	3^a	26.95%
High EE, and high DP	1	Not specified

EE: emotional exhaustion; DP: depersonalisation; PA: personal accomplishment; MBI: maslach burnout inventory; n_studies: number of studies.

^aDenoted a study that used both definitions.

From Table 1, most studies defined burnout as having high EE, high DP, and low PA,^{53,56,64,73,80,81,83,106–109} reporting an overall burnout prevalence of 25.76% among HCWs during COVID-19. Approximately a third of the studies used high EE, and/or high DP to categorise burnout instead,^{15,54,57,86,110–114} with an overall prevalence of 46.02%. Some studies also defined burnout as having high EE, high DP, or low PA,^{46,55,59,65,67,76} with an overall burnout prevalence of 61.63%.

Aside from the definitions of burnout, the studies also used different MBI cut-off scores to categorize high EE, high DP, and low PA. Table 2 presents the mean MBI cut-off scores for the three subscales, stratified by the MBI variant.

Table 2.

Mean cut-off scores for high EE, high DP, and low PA stratified by the MBI variant [n_studies = 67].

MBI variant	High EE cut-off score^a	High DP cut-off score^a	Low PA cut-off score^a
MBI-HSS or MBI-HSS(MP) [n_studies = 59]	26.40 (23–30) [n_studies = 42]	10.94 (6–17) [n_studies = 42]	30.32 (29–37) [n_studies = 41]
MBI-GS [n_studies = 8]	17.38 (11–27) [n_studies = 4]	10.00 (not reported) [n_studies = 3]	23.99 (17–33) [n_studies = 3]

EE: emotional exhaustion; DP: depersonalisation: PA: personal accomplishment; MBI-HSS: maslach burnout inventory-human services survey; MBI-HSS(MP): maslach burnout inventory-human services survey (medical personnel); MBI-GS: maslach burnout inventory-general survey; n_studies: number of studies.

^aValues are listed as mean (minimum – maximum), excluding outliers.

From Table 2, across studies that used MBI-HSS or MBI-HSS(MP), the mean cut-off scores that characterize burnout among HCWs during COVID-19 were 26.40 (mode: 27) for high EE, 10.94 (mode: 10) for high DP and 30.32 (mode: 33) for low PA. Across studies that used MBI-GS,^{67,72,73,88–92} the mean cut-off scores were 17.38, 10.00 and 23.99 for high EE, high DP, and low PA respectively. Due to the limited data available for MBI-GS, the modes could not be calculated.

Prevalence of burnout based on the MBI variant

Figure 2 shows the box-and-whisker plot of the weighted means for the prevalence of overall burnout, high EE, high DP, and low PA across all studies (n_studies = 67), excluding those that used modified MBI (n_studies = 28).^{40,41,45,48,49,52,54,55,57,58,61,68,77–79,93–105} Based on the authors’ definitions of burnout and MBI cut-off scores across included studies, the mean burnout prevalence measured among HCWs during COVID-19 regardless of MBI variant was 39.95% (range: 6.00%–90.40%). The mean prevalence for high EE, high DP, and low PA were 35.92% (range: 5.61%–70.30%), 32.33% (range: 1.87%–77.01%) and 39.80% (range: 0.16%–89.09%), respectively.

Figure 2.

Box-and-whisker plot of the prevalence of overall burnout, high EE, high DP, and low PA across all studiesa (n_studies = 67). EE: Emotional Exhaustion; DP: Depersonalisation; PA: Personal Accomplishment; MBI-HSS: Maslach Burnout Inventory-Human Services Survey; MBI-HSS(MP): Maslach Burnout Inventory-Human Services Survey (Medical Personnel). Values are listed as weighted mean (minimum - maximum) excluding outliers. n_studies, number of studies. ^aExcluded studies using abbreviated or modified MBI. ^bIncluded one RCT with two cross-sectional datasets.

Table 3 shows the weighted mean prevalence of overall burnout, high EE, high DP, and low PA stratified by the MBI variant. Across studies that used MBI-HSS or MBI-HSS (MP), the mean burnout prevalence among HCWs during COVID-19 was 39.48%. The mean prevalence for high EE, high DP, and low PA were 36.69% (range: 5.61%–70.30%), 32.75% (range: 1.87%–77.01%) and 40.56% (range: 0.16%–89.09%), respectively. Across studies that used MBI-GS,^{67,72,73,88–92} the mean burnout prevalence among HCWs during COVID-19 was 44.10% (range: 36.50%–51.70%).

Table 3.

Prevalence of overall burnout, high EE, high DP and low PA stratified by the MBI variant [n_studies = 67].

MBI variant	Burnout^a	High EE^a	High DP^a	Low PA^a
MBI-HSS or MBI-HSS(MP) [n_studies = 59]	39.48% (6.00%–90.40%) [n_studies = 26]	36.69% (5.61%–70.30%) [n_studies = 42^b]	32.75% (1.87%–77.01%) [n_studies = 42^b]	40.56% (0.16%–89.09%) [n_studies = 41^b]
MBI-GS [n_studies = 8]	44.10% (36.50%–51.70%) [n_studies = 2]	24.80% (14.53%–38.35%) [n_studies = 3]	22.28% (18.09%–26.47%) [n_studies = 2]	23.80% (1.15%–46.46%) [n_studies = 2]

EE: emotional exhaustion; DP: depersonalisation; PA: personal accomplishment: MBI-HSS: maslach burnout inventory-human services survey; MBI-HSS(MP): maslach burnout inventory-human services survey (medical personnel); MBI-GS: maslach burnout inventory-general survey; n_studies: number of studies.

^aValues are listed as weighted mean (minimum – maximum), excluding outliers.

^bIncluded one RCT with two cross-sectional datasets.

Prevalence of burnout based on healthcare profession

Figure 3 shows the box-and-whisker plot, while Table 4 provides the quantitative data of the weighted mean prevalence of overall burnout, high EE, high DP, and low PA across studies that used MBI-HSS or MBI-HSS(MP), stratified by profession. Studies with burnout data on non-mixed professions (n_studies = 21) and examined specifically doctors (n_studies = 11)^{44,46,47,50,51,53,56,59,60,62,63} or nurses (n_studies = 7)^{64–66,69–71,74} were analysed together in the figure below. Studies that examined other professions^75,76,80 were omitted from the figure due to limited data.

Figure 3.

Box-and-whisker plot of the prevalence of overall burnout, high EE, high DP, and low PA across studies that used MBI-HSS or MBI-HSS(MP) for overall population, doctors and nurses (n_studies = 59). EE: Emotional Exhaustion; DP: Depersonalisation; PA: Personal Accomplishment; MBI-HSS: Maslach Burnout Inventory-Human Services Survey; MBI-HSS(MP): Maslach Burnout Inventory-Human Services Survey (Medical Personnel); n_studies, number of studies. ^aIncluded one RCT with two cross-sectional datasets.

Table 4.

Prevalence of overall burnout, high EE, high DP, and low PA across studies that used MBI-HSS or MBI-HSS(MP) for overall population, doctors and nurses [n_studies = 59].

Population groups	Burnout^a	High EE^a	High DP^a	Low PA^a
Overall population [n_studies = 59^b]	39.48% (6.00%–90.40%) [n_studies = 26]	36.69% (5.61%–70.30%) [n_studies = 42^b]	32.75% (1.87%–77.01%) [n_studies = 42^b]	40.56% (0.16%–89.09%) [n_studies = 41^b]
Doctors [n_studies = 11]	45.50% (6.00%–90.40%) [n_studies = 9]	40.43% (23.00%–84.35%) [n_studies = 9]	37.17% (9.00%–70.65%) [n_studies = 9]	46.83% (22.09%–89.09%) [n_studies = 9]
Nurses [n_studies = 7]	42.50% (31.50%–68.00%) [n_studies = 4]	36.61% (5.61%–52.56%) [n_studies = 6]	32.03% (1.87%–42.72%) [n_studies = 6]	53.08% (31.00%–99.25%) [n_studies = 6]

EE: emotional exhaustion; DP: depersonalisation. PA: personal accomplishment; MBI-HSS: maslach burnout inventory-human services survey; MBI-HSS(MP): maslach burnout inventory-human services survey (medical personnel); n_studies: number of studies.

^aValues are given as mean (minimum – maximum) excluding outliers.

^bIncludes one RCT with two cross-sectional datasets.

As seen from Table 4, the mean burnout prevalence among doctors (45.50%) and nurses (42.50%) were both higher than that reported for the overall population (39.48%) during COVID-19. However, as seen from Figure 3, there were wide ranges reported across the professions, suggesting large heterogeneity across the studies.

Quantitative MBI scores measuring burnout subscales

Out of four cohort studies, only one study by Leskovic et al.³⁹ matched the review criteria. The study compared MBI-HSS scores in HCWs working in Slovenian nursing homes in rural areas, before COVID-19 in Spring 2013 (n_participants = 556), versus during COVID-19 in Spring 2020 (n_participants = 781). They reported a significant increase in mean EE from 21.9 to 24.8 (p = .001), but significant increase in mean PA from 42.7 to 48.7 (p = .001). There was no significant change in DP from 8.1 to 8.2 (p = .467). While the increase in EE signalled a worsening of burnout, the increase in PA suggested an improvement.

Two of the remaining cohort studies used modified MBI ^40,41 and hence were excluded for analysis. The last cohort study ⁴² examined burnout scores among HCWs before and during COVID-19. However, this study was excluded from analysis as the pre-COVID-19 data was collected during the start of the pandemic, hence not considered as a fair comparator. Instead, the data from this cohort study was treated as a cross-sectional dataset to assess burnout during COVID-19.

Excluding studies that used modified MBI to measure burnout,^{40,41,45,48,49,52,54,55,57,58,60,68,77–79,93–105} weighted mean MBI scores from the remaining 67 studies were analysed and reported in Table 5, stratified by the MBI variant.

Table 5.

Mean MBI scores for overall EE, overall DP, and overall PA across studies stratified by the MBI variant [n_studies = 67].

MBI variant	EE score^a	DP score^a	PA score^a
MBI-HSS or MBI-HSS(MP) [n_studies = 59]	22.07 (12.27–32.21) [n_studies = 36^b]	7.83 (2.00–17.14) [n_studies = 36^b]	32.53 (18.53–48.70) [n_studies = 35^b]
MBI-GS [n_studies = 8]	8.88 (2.05–19.10) [n_studies = 5]	4.59 (1.27–10.27) [n_studies = 5]	8.70 (0.94–19.25) [n_studies = 5]

EE: emotional exhaustion; DP: depersonalisation; PA: personal accomplishment; MBI-HSS: maslach burnout inventory-human services survey; MBI-HSS(MP): maslach burnout inventory-human services survey (medical personnel); MBI-GS: maslach burnout inventory-general survey; n_studies: number of studies.

^aValues are given as mean (minimum – maximum) excluding outliers.

^bIncludes one RCT with two cross-sectional datasets.

Figure 4 shows the mean EE, DP and PA scores across studies that used MBI-HSS or MBI-HSS(MP) to measure burnout. The mean MBI scores for EE, DP and PA among HCWs during COVID-19 were 22.07, 7.83 and 32.53, respectively. Adopting the most common cut-off scores of 27 for high EE, 10 for high DP and 33 for low PA, a high extent of burnout was not reflected based on the mean scores. Only five out of 36 studies^{62,75,115–117} met the criteria for high EE (13.9%), 10 out of 36 studies^{15,60,62,64,76,81,82,115,117,118} met for high DP (27.8%) and 16 out of 37 studies^{15,44,51,62,64,67,70,71,73,74,82,87–90,116–121} met for low PA (43.2%).

Figure 4.

Box-and-whisker plot of the mean MBI scores for overall EE, overall DP, and overall PA across studies that used MBI-HSS or MBI-HSS(MP) (nstudies = 59). EE: Emotional Exhaustion; DP: Depersonalisation; PA: Personal Accomplishment; MBI-HSS: Maslach Burnout Inventory-Human Services Survey; MBI-HSS(MP): Maslach Burnout Inventory-Human Services Survey (Medical Personnel); n_studies: number of studies. ^aIncluded one RCT with two cross-sectional datasets.

Due to the limited number of studies that used MBI-GS^{67,72,73,88–92} and the difficulties in comparing and relating MBI-GS scores to MBI-HSS or MBI-HSS(MP) scores, burnout data from MBI-GS was not reported.

Assessment of risk of bias of included studies

Among the studies, only one study⁴³ had low risk of bias, 86 studies had moderate risk of bias (90.5%) and eight studies^{40,41,52,61,79,84,100,122} had high risk of bias (8.4%).

Of note, the cohort study by Leskovic et al.³⁹ had a moderate risk of bias due to the possibility of data integrity concerns in view that the mean score of PA reported exceeded the maximum possible score of 48 based on MBI-HSS. The authors have yet to respond to clarifications on this discrepancy, hence the moderate risk of bias rating.

Most studies included in this review were cross-sectional by design and had no comparator, hence a meta-analysis could not be conducted.

Discussion

This systematic review aimed to evaluate the impact of COVID-19 on the burnout of HCW using MBI. However, only Leskovic et al.’s³⁹ cohort study addressed the primary aim. The remaining studies only reported burnout data during COVID-19, but not before. This limited our ability to explore the change in burnout levels due to COVID-19. Nevertheless, we could were able to determine the overall burnout prevalence measured using MBI among HCWs during COVID-19.

Summary of evidence

Burnout in overall HCW population

Our review found that the mean prevalence of burnout among HCWs during COVID-19 was 39.95%, with a wide range of 6.00%–90.40% (Figure 2). Based on burnout data reported by previous studies conducted before COVID-19, this mean prevalence falls within the commonly reported range of 30%–70%.^7–12 The wide range in burnout prevalence reported reflects large heterogeneity in burnout measured across the studies, and we are hence unable to evaluate and confidently conclude the impact of COVID-19 on HCW burnout. Moreover, most studies were not designed to compare burnout before and during COVID-19 among HCWs, except for Leskovic et al.’s cohort study.³⁹ That study reported a significant increase in EE and PA among HCWs, suggesting a worsening of burnout based on EE but a slight improvement in burnout based on PA. Based on this single study, however, we are unable to evaluate the impact of COVID-19 on the burnout of HCWs. More studies adopting the appropriate methodology of having historical comparators would be required to address this research question. However, if historical data of pre-COVID-19 period is absent, it is likely that this research question may stay unresolved. For the studies that publish MBI burnout data during COVID-19, it is imperative that there is subsequent follow-up when the pandemic situation improves to reassess the change in the burnout indices to understand the effects of the pandemic on burnout among HCWs.

Aside from prevalence of burnout, mean MBI scores were also examined (Table 5 and Figure 4). Based on the commonly used MBI cut-off scores for high EE ≥ 27, high DP ≥ 10, and low PA ≤ 33, our results suggest that HCWs may not experience burnout across all subscales. However, the wide range of scores reported suggests that local context and unique setting factors may also be important drivers of the burnout in HCWs beyond COVID-19-related factors.

Burnout stratified by healthcare profession

Differences in job scope between healthcare professions prompted us to stratify our burnout data by profession to gain further insight on the impact of COVID-19. Although it is difficult to conduct conclusive comparisons between professions due to the wide ranges reported across burnout and its subscales based on mean prevalence (Figure 3), average MBI scores were generally comparable across professions. Hence, more studies with largely representative sample populations of HCWs can minimise heterogeneity in the burnout data gathered and thus benefit future reviews evaluating the impact of COVID-19 on the burnout of HCWs stratified by profession.

Challenges and limitations

The challenges to this systematic review include achieving a consensus regarding burnout measured using different variations of MBI, burnout definitions and MBI cut-off scores.

While several variations of MBI were adopted across the studies, MBI-HSS and MBI-HSS(MP) were most used as they are specifically designed for HCWs working in the human services sector and assess mainly on worker-client interaction.¹²⁴ Studies which used modified MBI^{40,41,45,48,49,52,54,55,57,58,61,68,77–79,93–105} were initially included in the review because burnout is a specialized field of research, with only a few studies examining this phenomenon among HCWs during COVID-19. However, these studies could not be used for statistical analyses, as there were a wide range of non-validated scales used – ranging from single-item to 21-item measures. This made it difficult to pool the data from these studies and evaluate COVID-19’s impact on the burnout of HCWs. While MBI is the most validated tool to measure burnout, there is currently no standardized definition in using the scores obtained to categorize the presence or severity of burnout and its three dimensions. These contribute to the large heterogeneity across studies and limits effective comparisons regarding burnout outcomes. Hence, obtaining a standardized definition of burnout will be helpful in consolidating this research. In this review, we identified six definitions of burnout commonly adopted across studies (Table 1), similar to that adopted in previous studies conducted before COVID-19.^10,11,31 Looking at the collection of research on this topic, adopting a standardized definition of burnout will provide a common point of reference for comparing burnout data among HCWs before, during and/or after COVID-19. Future studies can adopt the most used definition of burnout presented in this review which is high EE, high DP, and low PA, for expanding the research in this field.

This systematic review has some limitations. Firstly, some articles may have been missed due to different terms used to describe burnout, thus limiting the comprehensiveness of results presented. Secondly, many studies included had high risk of bias due to non-randomized methods when recruiting participants and the presence of confounders. Additionally, there is likely publication bias as burnout research may not be highly prioritized in an already burnout healthcare system, hence the data may not be well-established in the published literature. As reflected by the wide range of intervals reported for burnout measures, it appears the studies have large heterogeneity. Finally, there is insufficient studies with pre-COVID-19 data to evaluate the impact of COVID-19 on the burnout of HCWs. This highlights the need for studies to have appropriate comparators or longitudinal follow-up, for instance pre-COVID-19 and post-COVID-19, to better understand impact factors of burnout in HCWs.

Conclusion

Only one cohort study evaluated the impact of COVID-19 on the burnout of HCWs. Despite the lack of studies with pre-COVID-19 data, burnout remains prevalent among HCWs during COVID-19. Comparable outcomes were observed among specific professions, such as doctors and nurses. Future studies examining burnout among HCWs measured with MBI incorporating comparisons between this period and post-COVID-19 are needed to help us better understand the impact of COVID-19 on burnout of HCWs.

Supplemental Material

Supplemental Material - Evaluating the impact of coronavirus disease on burnout among healthcare workers using maslach burnout inventory tool: A systematic review

Supplemental Material for Evaluating the impact of coronavirus disease on burnout among healthcare workers using maslach burnout inventory tool: A systematic review by Reanne Tang Mei Jun, Aiwen Wang, Ouyuan Feng and Jin Jian Chong in Proceedings of Singapore Healthcare

Abbreviations

COVID-19

Coronavirus Disease

Depersonalisation

Emotional Exhaustion

HCW

Healthcare Worker

HCWs

Healthcare Workers

ICD-11

11th Revision of the International Classification of Diseases

JBI

Joanna Briggs Institute

MBI

Maslach Burnout Inventory

MBI-HSS

Maslach Burnout Inventory-Human Services Survey

MBI-HSS(MP)

Maslach Burnout Inventory-Human Services Survey (Medical Personnel)

MBI-GS

Maslach Burnout Inventory-General Survey

nstudies

Number of studies

nparticipants

Number of participants

Personal Accomplishment

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

ROB

Risk of Bias

RCT

Randomised Controlled Trial

SARS-CoV-2

Severe Acute Respiratory Syndrome Coronavirus 2

Footnotes

Author contributions

WA was involved in conception of systematic review. RT, FO, CJJ, WA were involved in design of systematic review, literature review, critical analysis and interpretation of literature.

Declaration of conflicting interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Jin Jian Chong

Ouyuan Feng

Aiwen Wang

Supplemental material

Supplemental material for this article is available online.

References

World Health Organization . Burn-out an "Occupational phenomenon": International Classification of Diseases, https://www.who.int/news/item/28-05-2019-burn-out-an-occupational-phenomenon-international-classification-of-diseases (2019, Accessed 30 April 2022).

Maslach

Jackson

Leiter

. The Maslach Burnout Inventory Manual. Palo Alto, CA: Consulting Psychologists, 1997, pp. 191–218.

Mind Garden

. Burnout, https://www.mindgarden.com/276-burnout (2021, Accessed 30 April 2022).

Maslach

Jackson

. The measurement of experienced burnout. J Occup Behav 1981; 2: 15–113.

Maslach

Schaufeli

Leiter

. Job burnout. Annu Rev Psychol 2001; 52: 397–422. DOI: 10.1146/annurev.psych.52.1.397

Dyrbye

Shanafelt

Sinsky

, et al. Burnout among health care professionals: a call to explore and address this underrecognized threat to safe, high-quality care. Natl Acad Medicine 2017; 31: 2020.

Mattei

Fiasca

Mazzei

, et al. Stress and burnout in health-care workers after the 2009 l'aquila earthquake: a cross-sectional observational study. Front Psychiatry 2017; 8: 98. DOI: 10.3389/fpsyt.2017.00098

Doolittle

Windish

Seelig

. Burnout, coping, and spirituality among internal medicine resident physicians. J Grad Med Educ 2013; 5: 257–261. DOI: 10.4300/jgme-d-12-00136.1

Tay

Earnest

Tan

, et al. Prevalence of Burnout among Nurses in a Community Hospital in Singapore: a cross-sectional study. Proc Singapore Healthc 2014; 23: 93–99. DOI: 10.1177/201010581402300202

10.

Jones

Roe

Louden

, et al. Factors associated with burnout among US Hospital Clinical Pharmacy Practitioners: results of a nationwide pilot survey. Hosp Pharm 2017; 52: 742–751. DOI: 10.1177/0018578717732339

11.

Neumann

Mau

Virani

, et al. Burnout, moral distress, work-life balance, and career satisfaction among hematopoietic cell transplantation professionals. Biol Blood Marrow Transpl 2018; 24: 849–860. DOI: 10.1016/j.bbmt.2017.11.015

12.

Durham

Bush

Ball

. Evidence of burnout in health-system pharmacists. Am J Health-System Pharm 2018; 75: S93–S100. DOI: 10.2146/ajhp170818

13.

Talevi

Socci

Carai

, et al. Mental health outcomes of the CoViD-19 pandemic. Rivista di psichiatria 2020; 55: 7–144. DOI: 10.1708/3382.33569

14.

Mind Garden

. The Problem with Cut-Offs for the Maslach Burnout Inventory, https://www.mindgarden.com/documents/MBI-Cutoff-Caveat.pdf (2018, Accessed 30 April 2022).

15.

Jalili

Niroomand

Hadavand

, et al. Burnout among healthcare professionals during COVID-19 pandemic: a cross-sectional study. Int Arch Occup Environ Health 2021; 94: 1345–1352. DOI: 10.1007/s00420-021-01695-x

16.

AFP

. COVID-19 Timeline: Development of a Pandemic, https://www.facebook.com/AFPnewsenglish/posts/timeline-of-covid-19key-developments-as-the-pandemic-spread-across-the-worldafp-/3479492668755378/ (2020, Accessed 30 April 2022).

17.

AbelsonCovid Overload

: U.S. Hospitals Are Running Out of Beds for Patients. The New York Times. https://www.nytimes.com/2020/11/27/health/covid-hospitals-overload.html. Published 27 November, 2020. Updated 22 September, 2021. Accessed 4 April 2022.

18.

Yong

‘No One Is Listening to Us’. The Atlantic. https://www.theatlantic.com/health/archive/2020/11/third-surge-breaking-healthcare-workers/617091/. Published 13 November, 2020. Accessed 4 April 2022.

19.

Hollingsworth

Yang

Thomas

. ‘We'll Admit Them if They're Dying: Virus Outbreak Pushes China's Stretched Health Care Workers to Breaking Point. Cable News Network, Inc. https://edition.cnn.com/2020/01/30/asia/chinese-health-care-virus-intl-hnk/index.html Updated 31 January 2021. Acessed 30 April 2022.

20.

Sanghera

Pattani

Hashmi

, et al. The impact of SARS-CoV-2 on the mental health of healthcare workers in a hospital setting-a systematic review. J Occup Health 2020; 62: e12175. DOI: 10.1002/1348-9585.12175

21.

Pedrosa

Bitencourt

Fróes

ACF

, et al. Emotional, Behavioral, and Psychological Impact of the COVID-19 Pandemic. Front Psychol 2020; 11: 566212. DOI: 10.3389/fpsyg.2020.566212

22.

Dsouza

Quadros

Hyderabadwala

, et al. Aggregated COVID-19 suicide incidences in India: Fear of COVID-19 infection is the prominent causative factor. Psychiatry Res 2020; 290: 113145. DOI: 10.1016/j.psychres.2020.113145

23.

Mamun

Ullah

. COVID-19 suicides in Pakistan, dying off not COVID-19 fear but poverty? - The forthcoming economic challenges for a developing country. Brain Behav Immun 2020; 87: 163–166. DOI: 10.1016/j.bbi.2020.05.028

24.

National Academy of Medicine . Clinician Burnout Crisis Before, During, and After COVID-19: Insights From the Frontlines of Care. National Academy of Medicine, 2021, https://nam.edu/initiatives/clinician-resilience-and-well-being/clinician-burnout-crisis-in-the-era-of-covid-19/.

25.

National Academies of Sciences, Engineering, and Medicine . Taking Action against Clinician Burnout: A Systems Approach to Professional Well-Being. Washington, DC: National Academies Press, 2019.

26.

National Academy of Medicine . Valid and Reliable Survey Instruments to Measure Burnout, Well-Being, and Other Work-Related Dimensions. National Academy of Medicine, 2021, https://nam.edu/valid-reliable-survey-instruments-measure-burnout-well-work-related-dimensions/.

27.

Maslach

Jackson

Leiter

. The maslach burnout inventory manual. In: Zalaquett

Wood

(eds) Evaluating Stress: A Book of Resources. 3rd ed. United States of America: The Scarecrow Press, 1997, pp. 191–218.

28.

Page

Moher

Bossuyt

, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ 2021; 29: 372.

29.

JBI Joanna Briggs Institute . Critical Appraisal Tools: Checklist for Cohort Studies, https://jbi.global/critical-appraisal-tools (2021, Accessed 30 April 2022).

30.

Misra

Kolappa

Prasad

, et al. Frequency of neurologic manifestations in COVID-19: a systematic review and meta-analysis. Neurology 2021; 97(23): e2269–e2281.

31.

McQuade

Reed

DiDomenico

, et al. Feeling the burn? A systematic review of burnout in pharmacists. J Am Coll Clin Pharm 2020; 3(3): 663–675.

32.

Maslach

Christina

Jackson

Susan E.

Leiter

Michael P.

, et al. Maslach Burnout Inventory (MBI), https://www.mindgarden.com/117-maslach-burnout-inventory-mbi (2021, Accessed 30 April 2022).

33.

Chigwedere

Sadath

Kabir

, et al. The impact of epidemics and pandemics on the mental health of healthcare workers: a systematic review. Int J Environ Res Public Health 2021; 18(13): 6695. DOI: 10.3390/ijerph18136695

34.

Danet Danet

. Psychological impact of COVID-19 pandemic in Western frontline healthcare professionals. a systematic review. Med Clin 2021; 156: 449–458. DOI: 10.1016/j.medcle.2020.11.003

35.

Fiest

Parsons Leigh

Krewulak

, et al. Experiences and management of physician psychological symptoms during infectious disease outbreaks: a rapid review. BMC Psychiatry 2021; 21: 91. DOI: 10.1186/s12888-021-03090-9

36.

Galanis

Vraka

Fragkou

, et al. Nurses' burnout and associated risk factors during the COVID-19 pandemic: a systematic review and meta-analysis. J Adv Nurs 2021; 77: 3286–3302. DOI: 10.1111/jan.14839

37.

Doulougeri

Georganta

Montgomery

. Diagnosing burnout among healthcare professionals: can we find consensus? Cogent Med 2016; 3: 1. DOI: 10.1080/2331205X.2016.1237605

38.

Chan

. Biostatistics 101: data presentation. Singapore Medical Journal 2003; 44(6): 280–285.

39.

Leskovic

Erjavec

Leskovar

, et al. Burnout and job satisfaction of healthcare workers in Slovenian nursing homes in rural areas during the COVID-19 pandemic. Ann Agric Environ Med 2020; 27: 664–671. DOI: 10.26444/aaem/128236

40.

Baro Vila

Burgos

Sigal

, et al. Burnout syndrome in cardiology residents. impact of the COVID-19 Pandemic on burnout syndrome in cardiology residents. Curr Probl Cardiol 2021; 47: 100873. DOI: 10.1016/j.cpcardiol.2021.100873

41.

Mills

Peterson

McNair

, et al. Virtually serving the underserved: resident perceptions of telemedicine use while training during Coronavirus Disease 2019. Telemed J E Health 2021; 28: 391–398. DOI: 10.1089/tmj.2021.0112

42.

Kok

van Gurp

Teerenstra

, et al. Coronavirus Disease 2019 immediately increases burnout symptoms in ICU professionals: a longitudinal cohort study. Crit Care Med 2021; 49: 419–427. DOI: 10.1097/ccm.0000000000004865

43.

Fiol-DeRoque

Serrano-Ripoll

Jiménez

, et al. A mobile phone-based intervention to reduce mental health problems in health care workers during the COVID-19 pandemic (PsyCovidApp): randomized controlled trial. JMIR Mhealth Uhealth 2021; 9: e27039. DOI: 10.2196/27039

44.

Abdelhafiz

Ali

Ziady

, et al. Prevalence, associated factors, and consequences of burnout among Egyptian physicians during COVID-19 pandemic. Front Public Health 2020; 8: 590190. DOI: 10.3389/fpubh.2020.590190

45.

Al-Humadi

Bronson

Muhlrad

, et al. Depression, suicidal thoughts, and burnout among physicians during the COVID-19 pandemic: a survey-based cross-sectional study. Acad Psychiatry 2021; 45: 557–565. DOI: 10.1007/s40596-021-01490-3

46.

Azoulay

De Waele

Ferrer

, et al. Symptoms of burnout in intensive care unit specialists facing the COVID-19 outbreak. Ann Intensive Care 2020; 10: 110. DOI: 10.1186/s13613-020-00722-3

47.

Buran

Altın

. Burnout among physicians working in a pandemic hospital during the COVID-19 pandemic. Leg Med 2021; 51: 101881. DOI: 10.1016/j.legalmed.2021.101881

48.

Coleman

Abdelsattar

Glocker

, et al. COVID-19 pandemic and the lived experience of surgical residents, fellows, and early-career surgeons in the American College of Surgeons. J Am Coll Surg 2021; 232: 119–135. DOI: 10.1016/j.jamcollsurg.2020.09.026

49.

de Wit

Mercuri

Wallner

, et al. Canadian emergency physician psychological distress and burnout during the first 10 weeks of COVID-19: a mixed-methods study. J Am Coll Emerg Phys Open 2020; 1: 1030–1038. DOI: 10.1002/emp2.12225

50.

Dimitriu

MCT

Pantea-Stoian

Smaranda

, et al. Burnout syndrome in Romanian medical residents in time of the COVID-19 pandemic. Med Hypotheses 2020; 144: 109972. DOI: 10.1016/j.mehy.2020.109972

51.

Dinibutun

. Factors Associated with burnout among physicians: an evaluation during a period of COVID-19 pandemic. J Healthc Leadersh 2020; 12: 85–94. DOI: 10.2147/jhl.S270440

52.

Doherty

Colleran

Durcan

, et al. A pilot study of burnout and long covid in senior specialist doctors. Ir J Med Sci 2021; 191: 1–5. DOI: 10.1007/s11845-021-02594-3

53.

Elghazally

Alkarn

Elkhayat

, et al. Burnout impact of COVID-19 pandemic on health-care professionals at Assiut University Hospitals. Int J Environ Res Public Health 2020 18: 5368. DOI: 10.3390/ijerph18105368

54.

Elhadi

Msherghi

Elgzairi

, et al. The mental well-being of frontline physicians working in civil wars under Coronavirus Disease 2019 pandemic conditions. Front Psychiatry 2020; 11: 598720. DOI: 10.3389/fpsyt.2020.598720

55.

Elhadi

Msherghi

Elgzairi

, et al. Burnout syndrome among hospital healthcare workers during the COVID-19 pandemic and civil war: a cross-sectional study. Front Psychiatry 2020; 11: 579563. DOI: 10.3389/fpsyt.2020.579563

56.

Guercovich

Piazzioni

Waisberg

, et al. Burnout syndrome in medical oncologists during the COVID-19 pandemic: Argentinian national survey. Ecancermedicalscience 2021; 15: 1213. DOI: 10.3332/ecancer.2021.1213

57.

Khalafallah

Lam

Gami

, et al. Burnout and career satisfaction among attending neurosurgeons during the COVID-19 pandemic. Clin Neurol Neurosurg 2020; 198: 106193. DOI: 10.1016/j.clineuro.2020.106193

58.

Khalafallah

Lam

Gami

, et al. A national survey on the impact of the COVID-19 pandemic upon burnout and career satisfaction among neurosurgery residents. J Clin Neurosci 2020; 80: 137–142. DOI: 10.1016/j.jocn.2020.08.012

59.

Khan

Palepu

Dodek

, et al. Cross-sectional survey on physician burnout during the COVID-19 pandemic in Vancouver, Canada: the role of gender, ethnicity and sexual orientation. BMJ Open 2021; 11: e050380. DOI: 10.1136/bmjopen-2021-050380

60.

Lange

Joo

Couette

, et al. Impact on mental health of the COVID-19 outbreak among general practitioners during the sanitary lockdown period. Ir J Med Sci 2022; 191: 93–96. DOI: 10.1007/s11845-021-02513-6

61.

Ofei-Dodoo

Loo-Gross

Kellerman

. Burnout, depression, anxiety, and stress among family physicians in kansas responding to the COVID-19 pandemic. J Am Board Fam Med 2021; 34: 522–530. DOI: 10.3122/jabfm.2021.03.200523

62.

Park

Kim

Jung

, et al. Psychological distress among infectious disease physicians during the response to the COVID-19 outbreak in the Republic of Korea. BMC Public Health 2020; 20: 1811. DOI: 10.1186/s12889-020-09886-w

63.

Treluyer

Tourneux

. Burnout among paediatric residents during the COVID-19 outbreak in France. Eur J Pediatr 2021; 180: 627–633. DOI: 10.1007/s00431-020-03907-x

64.

Aydin Sayilan

Kulakaç

Uzun

. Burnout levels and sleep quality of COVID-19 heroes. Perspect Psychiatr Care 2021; 57: 1231–1236. DOI: 10.1111/ppc.12678

65.

Bellanti

Lo Buglio

Capuano

, et al. Factors related to nurses' burnout during the first wave of Coronavirus Disease-19 in a University Hospital in Italy. Int J Environ Res Public Health 2021; 18: 5051. DOI: 10.3390/ijerph18105051

66.

Bruyneel

Smith

Tack

, et al. Prevalence of burnout risk and factors associated with burnout risk among ICU nurses during the COVID-19 outbreak in French speaking Belgium. Intensive Crit Care Nurs 2021; 65: 103059. DOI: 10.1016/j.iccn.2021.103059

67.

Chen

Sun

Chen

, et al. A large-scale survey on trauma, burnout, and posttraumatic growth among nurses during the COVID-19 pandemic. Int J Ment Health Nurs 2021; 30: 102–116. DOI: 10.1111/inm.12796

68.

Cortés-Álvarez

Vuelvas-Olmos

. COVID 19: psychological effects and associated factors in mexican nurses. Disaster Med Public Health Prep 2020; 1–7, doi:10.1017/dmp.2020.495

69.

Kong

, 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. DOI: 10.1016/j.eclinm.2020.100424

70.

Kakemam

Chegini

Rouhi

, et al. Burnout and its relationship to self-reported quality of patient care and adverse events during COVID-19: a cross-sectional online survey among nurses. J Nurs Manag 2021; 29: 1974–1982. DOI: 10.1111/jonm.13359

71.

Murat

Köse

Savaşer

. Determination of stress, depression and burnout levels of front-line nurses during the COVID-19 pandemic. Int J Ment Health Nurs 2021; 30: 533–543. DOI: 10.1111/inm.12818

72.

Zare

Kazemi

Izadi

, et al. Beyond the outbreak of COVID-19: factors affecting burnout in nurses in Iran. Ann Glob Health 2021; 87: 51. DOI: 10.5334/aogh.3190

73.

Zhang

Jiang

, et al. Association between resilience and burnout of front-line nurses at the peak of the COVID-19 pandemic: positive and negative affect as mediators in Wuhan. Int J Ment Health Nurs 2021; 30: 939–954. DOI: 10.1111/inm.12847

74.

Zhang

Wang

Pan

, et al. Stress, burnout, and coping strategies of frontline nurses during the COVID-19 epidemic in Wuhan and Shanghai, China. Front Psychiatry 2020; 11: 565520. DOI: 10.3389/fpsyt.2020.565520

75.

Johnston

O'Reilly

Scholz

, et al. Burnout and the challenges facing pharmacists during COVID-19: results of a national survey. Int J Clin Pharm 2021; 43: 716–725. DOI: 10.1007/s11096-021-01268-5

76.

Lange

Joo

Couette

, et al. Impact on mental health of the COVID-19 outbreak among community pharmacists during the sanitary lockdown period. Ann Pharm Fr 2020; 78: 459–463. DOI: 10.1016/j.pharma.2020.09.002

77.

Kotera

Maxwell-Jones

Edwards

, et al. Burnout in professional psychotherapists: relationships with self-compassion, work-life balance, and telepressure. Int J Environ Res Public Health 2021; 18: 5308. DOI: 10.3390/ijerph18105308

78.

Pniak

Leszczak

Adamczyk

, et al. Occupational burnout among active physiotherapists working in clinical hospitals during the COVID-19 pandemic in south-eastern Poland. Work 2021; 68: 285–295. DOI: 10.3233/wor-203375

79.

Osama

Zaheer

Saeed

, et al. Impact of COVID-19 on surgical residency programs in Pakistan; a residents' perspective. do programs need formal restructuring to adjust with the “new normal”? A cross-sectional survey study. Int J Surg 2020; 79: 252–256. DOI: 10.1016/j.ijsu.2020.06.004

80.

Martínez-López

Lázaro-Pérez

Gómez-Galán

. Predictors of burnout in social workers: the COVID-19 pandemic as a scenario for analysis. Int J Environ Res Public Health 2021: 18: 5416. DOI: 10.3390/ijerph18105416

81.

Asghar

Yasmin

Alvi

, et al. Assessing the mental impact and burnout among physicians during the COVID-19 pandemic: a developing country single-center experience. Am J Trop Med Hyg 2021; 104: 2185–2189. DOI: 10.4269/ajtmh.21-0141

82.

Gramaglia

Marangon

Azzolina

, et al. The Mental health impact of 2019-nCOVID on healthcare workers from North-Eastern Piedmont, Italy. focus on burnout. Front Public Health 2021; 9: 667379. DOI: 10.3389/fpubh.2021.667379

83.

Macía-Rodríguez

Alejandre de Oña

Martín-Iglesias

, et al. Burn-out syndrome in Spanish internists during the COVID-19 outbreak and associated factors: a cross-sectional survey. BMJ Open 2021; 11: e042966. DOI: 10.1136/bmjopen-2020-042966

84.

Mushtaque

Raza

Khan

et al. Medical staff work burnout and willingness to work during COVID-19 pandemic situation in Pakistan. Hosp Top 2021; 1–9, doi:10.1080/00185868.2021.1927922

85.

Torrente

Sousa

Sánchez-Ramos

, et al. To burn-out or not to burn-out: a cross-sectional study in healthcare professionals in Spain during COVID-19 pandemic. BMJ Open 2021; 11: e044945. DOI: 10.1136/bmjopen-2020-044945

86.

Wang

Luo

, et al. A comparison of burnout frequency among oncology physicians and nurses working on the frontline and usual wards during the COVID-19 epidemic in Wuhan, China. J Pain Symptom Manage 2020; 60: e60–e65. DOI: 10.1016/j.jpainsymman.2020.04.008

87.

Yörük

Güler

. The relationship between psychological resilience, burnout, stress, and sociodemographic factors with depression in nurses and midwives during the COVID-19 pandemic: a cross-sectional study in Turkey. Perspect Psychiatr Care 2021; 57: 390–398. DOI: 10.1111/ppc.12659

88.

Bredicean

Tamasan

Lungeanu

, et al. Burnout toll on empathy would mediate the missing professional support in the COVID-19 outbreak. Risk Manag Healthc Pol 2021; 14: 2231–2244. DOI: 10.2147/rmhp.S300578

89.

Cotel

Golu

Pantea Stoian

, et al. Predictors of burnout in healthcare workers during the COVID-19 pandemic. Healthcare 2021; 9: 304. DOI: 10.3390/healthcare9030304

90.

Huo

Zhou

, et al. Burnout and its relationship with depressive symptoms in medical staff during the COVID-19 epidemic in China. Front Psychol 2021; 12: 616369. DOI: 10.3389/fpsyg.2021.616369

91.

Lasalvia

Amaddeo

Porru

, et al. Levels of burn-out among healthcare workers during the COVID-19 pandemic and their associated factors: a cross-sectional study in a tertiary hospital of a highly burdened area of north-east Italy. BMJ Open 2021; 11: e045127. DOI: 10.1136/bmjopen-2020-045127

92.

Zhang

Jiang

, et al. Psychological and occupational impact on healthcare workers and its associated factors during the COVID-19 outbreak in China. Int Arch Occup Environ Health 2021; 94: 1441–1453. DOI: 10.1007/s00420-021-01657-3

93.

Aebischer

Weilenmann

Gachoud

, et al. Physical and psychological health of medical students involved in the coronavirus disease 2019 response in Switzerland. Swiss Med Wkly 2020; 150: w20418. DOI: 10.4414/smw.2020.20418

94.

Apaydin

Rose

Yano

, et al. Burnout among primary care healthcare workers during the COVID-19 pandemic. J Occup Environ Med 2021; 63: 642–645. DOI: 10.1097/jom.0000000000002263

95.

Cena

Rota

Calza

, et al. Mental health states experienced by perinatal healthcare workers during COVID-19 pandemic in Italy. Int J Environ Res Public Health 2021; 18: 6542. DOI: 10.3390/ijerph18126542

96.

Douglas

Choi

Marcus

, et al. Wellbeing of frontline health care workers after the first SARS-CoV-2 pandemic surge at a neuroscience centre: a cross-sectional survey. J Neurosurg Anesthesiol 2021; 34: 333–338. DOI: 10.1097/ana.0000000000000767

97.

Firew

Sano

Lee

, et al. Protecting the front line: a cross-sectional survey analysis of the occupational factors contributing to healthcare workers' infection and psychological distress during the COVID-19 pandemic in the USA. BMJ Open 2020; 10: e042752. DOI: 10.1136/bmjopen-2020-042752

98.

Liu

Chen

Wang

, et al. COVID-19 outbreak can change the job burnout in health care professionals. Front Psychiatry 2020; 11: 563781. DOI: 10.3389/fpsyt.2020.563781

99.

Lou

Montreuil

Feldman

, et al. Nurses' and physicians' distress, burnout, and coping strategies during COVID-19: stress and impact on perceived performance and intentions to quit. J Contin Educ Health Prof 2021; 42: e44–e52. DOI: 10.1097/ceh.0000000000000365

100.

Lyu

Chen

, et al. Positive functioning at work during COVID-19: posttraumatic growth, resilience, and emotional exhaustion in Chinese frontline healthcare workers. Appl Psychol Health Well Being 2021; 13: 871–886. DOI: 10.1111/aphw.12276

101.

Petrella

Hughes

Fern

, et al. Healthcare staff well-being and use of support services during COVID-19: a UK perspective. Gen Psychiatr 2021; 34: e100458. DOI: 10.1136/gpsych-2020-100458

102.

Spiller

Méan

Ernst

, et al. Development of health care workers' mental health during the SARS-CoV-2 pandemic in Switzerland: two cross-sectional studies. Psychol Med 2020; 52: 1–4. DOI: 10.1017/s0033291720003128

103.

Wang

Harold

Tong

, et al. Moral injury in Chinese health professionals during the COVID-19 pandemic. Psychol Trauma 2021; 14: 250–257. DOI: 10.1037/tra0001026

104.

Weilenmann

Ernst

Petry

, et al. Health care workers' mental health during the first weeks of the SARS-CoV-2 pandemic in Switzerland-a cross-sectional study. Front Psychiatry 2021; 12: 594340. DOI: 10.3389/fpsyt.2021.594340

105.

Zhizhong

Koenig

Yan

, et al. Psychometric properties of the moral injury symptom scale among Chinese health professionals during the COVID-19 pandemic. BMC Psychiatry 2020; 20: 556. DOI: 10.1186/s12888-020-02954-w

106.

Ibar

Fortuna

Gonzalez

, et al. Evaluation of stress, burnout and hair cortisol levels in health workers at a University Hospital during COVID-19 pandemic. Psychoneuroendocrinology 2021; 128: 105213. DOI: 10.1016/j.psyneuen.2021.105213

107.

Meynaar

Ottens

Zegers

, et al. Burnout, resilience and work engagement among Dutch intensivists in the aftermath of the COVID-19 crisis: a nationwide survey. J Crit Care 2021; 62: 1–5. DOI: 10.1016/j.jcrc.2020.11.010

108.

Navarro Prados

Jiménez García-Tizón

Meléndez

. Sense of coherence and burnout in nursing home workers during the COVID-19 pandemic in Spain. Health Soc Care Community 2021; 30: 244–252. DOI: 10.1111/hsc.13397

109.

Pérez-Chacón

Chacón

Borda-Mas

, et al. Sensory processing sensitivity and compassion satisfaction as risk/protective factors from burnout and compassion fatigue in healthcare and education professionals. Int J Environ Res Public Health 2021 18: 611. DOI: 10.3390/ijerph18020611

110.

Giusti

Pedroli

D'Aniello

, et al. The psychological impact of the COVID-19 outbreak on health professionals: a cross-sectional study. Front Psychol 2020; 11: 1684. DOI: 10.3389/fpsyg.2020.01684

111.

Martínez-López

Lázaro-Pérez

Gómez-Galán

, et al. Psychological impact of COVID-19 emergency on health professionals: burnout incidence at the most critical period in Spain. J Clin Med 2020; 9: 3029. DOI: 10.3390/jcm9093029

112.

KYY

Zhou

Tan

, et al. Understanding the psychological impact of COVID-19 Pandemic on patients with cancer, their caregivers, and health care workers in Singapore. JCO Glob Oncol 2020; 6: 1494–1509. DOI: 10.1200/go.20.00374

113.

Rapisarda

Vallarino

Cavallini

, et al. The early impact of the Covid-19 emergency on mental health workers: a survey in Lombardy, Italy. Int J Environ Res Public Health 2020; 17: 8615. DOI: 10.3390/ijerph17228615

114.

Varani

Ostan

Franchini

, et al. Caring advanced cancer patients at home during COVID-19 outbreak: burnout and psychological morbidity among palliative care professionals in Italy. J Pain Symptom Manage 2021; 61: e4–e12. DOI: 10.1016/j.jpainsymman.2020.11.026

115.

Pappa

Athanasiou

Sakkas

, et al. From recession to depression? Prevalence and correlates of depression, anxiety, traumatic stress and burnout in healthcare workers during the COVID-19 pandemic in greece: a multi-center, cross-sectional study. Int J Environ Res Public Health 2021; 18: 2390. DOI: 10.3390/ijerph18052390

116.

Bisesti

Mallardo

Gambazza

, et al. Facing COVID-19 pandemic IN A Tertiary Hospital in Milan: prevalence of burnout in nursing staff working in sub-intensive care units. Int J Environ Res Public Health 2021; 18: 6684. DOI: 10.3390/ijerph18136684

117.

Sagherian

Steege

Cobb

et al. Insomnia, fatigue and psychosocial well-being during COVID-19 pandemic: a cross-sectional survey of hospital nursing staff in the United States. J Clin Nurs 2020, doi:10.1111/jocn.15566

118.

Demartini

Nisticò

D'Agostino

, et al. Early psychiatric impact of COVID-19 pandemic on the general population and healthcare workers in italy: a preliminary study. Front Psychiatry 2020; 11: 561345. DOI: 10.3389/fpsyt.2020.561345

119.

Stocchetti

Segre

Zanier

, et al. Burnout in intensive care unit workers during the second wave of the COVID-19 pandemic: a single center cross-sectional italian study. Int J Environ Res Public Health 2021; 18: 6102. DOI: 10.3390/ijerph18116102

120.

Orrù

Marzetti

Conversano

, et al. Secondary traumatic stress and burnout in healthcare workers during COVID-19 outbreak. Int J Environ Res Public Health 2021 18: 337. DOI: 10.3390/ijerph18010337

121.

Nishimura

Miyoshi

Hagiya

, et al. Burnout of healthcare workers amid the COVID-19 pandemic: a japanese cross-sectional survey. Int J Environ Res Public Health 2021 18: 2434. DOI: 10.3390/ijerph18052434

122.

Barello

Palamenghi

Graffigna

. Burnout and somatic symptoms among frontline healthcare professionals at the peak of the Italian COVID-19 pandemic. Psychiatry Res 2020; 290: 113129. DOI: 10.1016/j.psychres.2020.113129

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