Job burnout among Israeli healthcare workers during the first months of COVID-19 pandemic: The role of emotion regulation strategies and psychological distress.

The current worldwide COVID-19 pandemic has elicited widespread concerns and stress. Arguably, healthcare workers are especially vulnerable to experience burnout during these times due to the nature of their work. Indeed, high prevalence of burnout was found among healthcare workers during the outbreak. However, the individual differences predicting burnout among healthcare workers during the pandemic have been understudied. The aim of the current study was, therefore, to identify risk and protective factors contributing to the severity of burnout among healthcare workers, above and beyond levels of current psychological distress. The survey was distributed online during the period April 13-28, 2020, approximately two months after the first COVID-19 case was identified in Israel. Ninety-eight healthcare workers completed an online survey administered cross-sectionally via the Qualtrics platform that included questionnaires assessing habitual emotion regulation strategies (i.e., trait worry, reappraisal, and suppression), psychological distress, COVID-19 related concerns, and burnout. A hierarchical linear regression analysis revealed that only trait worry and psychological distress were significant predictors of job burnout among healthcare workers. These findings highlight the role of maladaptive emotion regulation tendencies, specifically trait worry, in job burnout among healthcare workers. These findings have implications for both the assessment and treatment of healthcare workers. We discuss potential mechanisms and implications for practice.

Introduction

The COVID-19 pandemic began in the city Wuhan (Hubei, China) in December 2019 and since then has spread across the globe. The rapid outbreak of the pandemic has led to concerns about personal safety and the safety of close others. The pandemic was defined by the American Psychological Association as an epidemiological and psychological crisis [1], with significant mental health implications both in the present and in the foreseeable future. Accordingly, the pandemic was found to affect individuals’ well-being and mental health [2], with the potential for long-lasting effects [2-4]. Indeed, mounting evidence across the globe demonstrated high levels of psychological distress, including post-traumatic stress disorder (PTSD) [5], depression and anxiety [6-8], as well as mood swings, irritability, and sleep disorders [2-4].

Healthcare workers may be especially vulnerable to the psychological toll of pandemics, given the nature of their work ([9]; for review and meta-analysis see [10, 11]). Psychological distress among healthcare workers is a key problem for society, as these professionals provide essential services to the general population. This might be especially important during a pandemic outbreak given the growing number of individuals seeking medical, mental, and welfare assistance, resulting in extreme workload among healthcare workers.

Indeed, high prevalence of psychological distress, such as symptoms of depression, anxiety, and insomnia were found among healthcare workers across the globe during the initial stages of the COVID-19 pandemic [6, 10–13], as well as during prior pandemic outbreaks [14-18]. For example, in recent surveys conducted in China one month after the COVID-19 pandemic outbreak in China, healthcare workers treating patients with COVID-19 exhibited a high prevalence of mental health symptoms, including depression, anxiety, insomnia, and distress [6, 19]. In line with these findings, a large national survey of physicians that was administered in Israel approximately one month following the outbreak of the pandemic found high levels of anxiety among respondents [20]. Similar results were obtained among healthcare workers in Italy showing high prevalence of somatization, distress, sleep disorders and psychopathology symptoms [21, 22]. In Australia, five months after the COVID-19 outbreak, healthcare workers showed significant symptoms of moderate to severe levels of depression, anxiety, and post-traumatic stress disorder [23]. Similarly, in a study conducted during the first months of the pandemic in the United Arab Emirates, over a third of healthcare workers reported moderate or severe psychological distress and moderate or severe anxiety, with more than third of the frontline workers reporting higher levels of anxiety [24]. The COVID-19 pandemic continued to take toll on the mental well-being of healthcare workers also during later stages of the pandemic (September to November 2020), as reflected in high levels of general distress and psychopathology symptoms among this population in various countries (e.g., [25-27]).

These difficulties might be the result of specific characteristics of pandemics, which poses extraordinary amounts of pressure on healthcare workers. According to previous studies conducted in the context of SARS or Ebola epidemics, these situations are characterised by increased workload, physical exhaustion, inadequate personal equipment, and the need to make ethically difficult decisions on the rationing of care [9]. These situational demands may entail dramatic effects on the physical and mental well-being of healthcare workers [9]. Furthermore, pandemics may be associated with experiences of isolation and loss of social support, as well as concerns about risk of infection of friends and relatives [7, 12, 13]. There is strong reasoning to assume that these specific pandemic-related situational characteristics put healthcare workers at high risk for developing psychological distress and experience work-related burnout.

Indeed, in addition to the increase in levels of psychological distress, healthcare workers were found to experience high rates of burnout during the COVID-19 pandemic (e.g., [6, 28]). Burnout has been described as a “state of physical, emotional and mental exhaustion that results from long-term involvement in work situations that are emotionally demanding” [29]. Current notions propose a multidimensional approach that sees burnout as consisting of emotional exhaustion, physical fatigue, and cognitive weariness [30, 31]. Burnout is a key occupational health hazard among healthcare workers. It was found to be associated with depression, irritability, helplessness, and anxiety among healthcare workers [29]. In addition, burnout has adverse outcomes for the whole organization ([for review see [32]). Thereby, individuals exhibiting burnout demonstrate a reduction in professional performance, greater probability of medical errors, poor patient satisfaction, higher rates of absenteeism, lower commitment to the job and the employer, lower job satisfaction, higher occurrences of medical leave, and greater personal suffering (for review see [32]).

Given the unique nature of the COVID-19 pandemic being both a medical and a psychological crisis [1], healthcare workers were required to work extensively longer hours than usual, both in the health, welfare, and social services systems. It is therefore not surprising that significant levels of burnout were found among healthcare workers worldwide [13, 25, 28, 33, 34], with more than 50% of healthcare workers reporting mild to high levels of burnout during the COVID-19 pandemic [35, 36]. For example, Navarro-Prados et al. [35] found that the rise in working hours in addition to deterioration in mental and physical health contributed to elevation in burnout levels during the pandemic.

Nonetheless, within a similar context, some individuals are more susceptible to burnout than others [37]. Most of the research conducted in the field of professional burnout has been focused on environmental factors [38], as well as on the interactions between environmental and demographic factors [39-42]. However, the research addressing individual differences, such as emotion regulation tendencies that contribute to burnout is relatively sparse [43]. Furthermore, while there is mounting evidence for the rise in burnout levels among healthcare workers during pandemics, and COVID-19 in specific (e.g., [6, 28, 44, 45]), little is known about the risk and protective mechanisms underlying burnout among this population under this specific situational context. In the current work we therefore focused on the role of adaptive and maladaptive emotion regulation strategies in predicting job burnout among this population.

Emotion regulation is defined as the processes by which individuals modify their emotional experiences, expressions, and physiology [46]. Current evidence points at the importance of emotion regulation in predicting one’s ability to produce appropriate responses to the ever-changing demands posed by the environment [46]. Such responses may ultimately predict the absence or the presence of psychopathology [46, 47]. In consistence with this idea, difficulties in emotion regulation among healthcare workers are associated with high levels of emotional exhaustion, depersonalization, and lack of personal accomplishment [48], as well as difficulties to verbalize and manage their feelings [49]. Indeed, there is a correlative relationship between emotion regulation tendencies and burnout in healthcare workers [43, 48, 50–53]. However, a recent review depicted that the measures used to assess emotion regulation were highly heterogeneous, making it difficult to draw conclusions about the specific emotion regulation strategies significantly associated with burnout [43]. In the current study, we therefore focused on specific components of emotion regulation, by assessing three main emotion regulation strategies: reappraisal, suppression, and tendency to worry.

Reappraisal is an antecedent focused emotion regulation strategy that involves cognitively construing a potentially emotion-eliciting situation in a way that changes its emotional impact [54]. Reappraisal is effective in reducing negative emotions [55] and has been positively related to psychological wellbeing and health, and negatively related to depressive symptoms [56-58]. A few studies have shown a potential link between reappraisal and burnout among healthcare workers and other professionals such as teachers [59-63], suggesting that a higher tendency to use reappraisal may serve as a protective factor against burnout. Nevertheless, no study to date has examined the association between reappraisal use and burnout during the unique context of intensive stress, as exemplified in the COVID-19 pandemic. This examination is especially important as intensive stress was previously shown to impair individuals’ capacity to use reappraisal under intense emotional situations [64], as well as individuals’ ability to employ reappraisal [65].

Suppression is a response-focused emotion regulation strategy that involves an active effort to reduce or inhibit the expression of affect after it is aroused [54]. Considerable research has identified suppression as a risk factor for depression [66], anxiety [67, 68], discomfort [69], and heightened sympathetic arousal [70-72]. Previous studies demonstrated the role of suppression in predicting higher levels of perceived stress among healthcare workers [73] and higher levels of burnout among teachers [61]. Nonetheless, while suppression is usually associated with higher levels of psychological distress, there is some evidence that during COVID-19, the ability to suppress emotions is presumably efficient to wellbeing [74]. For example, elevated suppression was found to be associated with lower levels depression, anxiety, and stress [74], as well as with reduced burnout risk among healthcare workers [74]. Therefore, given these contradicting results, further research should assess the role of suppression in predicting job burnout among healthcare workers during the COVID-19 pandemic.

The tendency to worry can be defined as a chain of relatively uncontrollable thoughts that involve attempts to find solutions for an issue whose outcome is uncertain, but may entail negative outcomes [75]. Trait worry is characterized by a reduced tendency to let go of negative feelings [76], and can therefore lead to anxiety, stress, and, depression [77-79]. Chaukos et al. [80] showed higher levels of worry among healthcare residents that have also reported high levels of burnout. This is in line with studies showing a similar relation between worry and burnout among highly demanding professions, such as athletes [81] and university students [82]. Consistently, prior studies have also suggested a strong relationship between trait anxiety and burnout [83-85]. Thus, individuals with high trait anxiety were found to perceive situations in ways that elevate their anxious state, leading eventually to burnout [86].

The current study

Tying these threads together, the current study aimed to examine whether individual differences in habitual use of emotion regulation strategies play a role in predicting job burnout among healthcare workers in the unique context of the COVID-19 pandemic. Identifying the psychological predictors underlying the vulnerability or resilience to experience burnout may potentially serve as a base for psychosocial interventions for healthcare personnel. As job burnout is closely linked to situational psychological distress [29], especially among populations that experience work-related stress [87], we controlled for episodic COVID-19 related concerns and current psychological distress in our analyses. This allowed us to examine the unique contribution of emotion regulation tendencies to burnout. The following hypotheses were proposed: 1) higher use of reappraisal would be associated with lower levels of burnout; 2) higher levels of suppression would be associated with higher levels of burnout; and 3) higher levels of trait worry would also be associated with higher levels of burnout. We expected to find these results above and beyond levels of current psychological distress.

Materials and methods

Participants

Nighty-eight healthcare workers participated in the study (Mean age = 36 years, SD = 8, 87% female). None of the participants was diagnosed with COVID-19, but nine of the 98 participants reported being in quarantine due to exposure to a person who is carrying the COVID-19, while answering the survey. The study was conducted following APA ethical standards and with approval of the ethics committee of the Faculty of Education at [masked for review]. See Table 1 for demographic characteristics of the sample.

Table 1

Demographic characteristics of the participants (N = 98).

		n	%
Gender	Male	13	13%
	Female	85	87%
Education	Undergraduate degree	45	46%
	Graduate degree	53	54%
Job	Medical staff (doctors, nurses)	33	34%
	Paramedical staff (physiotherapists, pharmacists, speech therapists)	13	13%
	Clinicians (Psychologists and social workers)	30	31%
	Others	22	22%
Job experience	Less than one year	12	12%
	1–5 years	29	30%
	5–10 years	16	16%
	10–15 years	19	20%
	15–20 years	6	6%
	Above 20 years	16	16%
Job percentage	Full time	64	65%
	Part time	18	19%
	Half time	8	8%
	Other	8	8%
Salary	Below average	22	22.70%
	Average	34	35.10%
	Above average	36	37.10%
	Far above average	5	5.20%

Procedure

Participants completed an online survey administered via the Qualtrics platform (Qualtrics, Provo, UT). The survey was distributed in social media platforms including Facebook groups of healthcare workers, and by emails using a convenience and a snowball sampling (chain-referral sampling). The survey was distributed during the period April 13–28, 2020, approximately two months after the first case of the COVID-19 pandemic was identified in Israel. During this period, the number of people diagnosed with COVID-19 in Israel ranged between 11,586 and 15,728, and the number of deaths ranged between 116 and 210. Legal restrictions on the public included closing schools and entertainment places such as restaurants and shopping centers. The public was asked to maintain social distance by remaining within a 100-meter radius from home, except for essential workers (87% of the individuals in our sample continued going to work). Prior to completing the questionnaire, participants received a detailed explanation regarding the study and signed an informed consent form. The questionnaire took approximately 15 to 20 minutes to complete. The survey included additional questionnaires that are not prominent to the current examination. All data have been made publicly available via the Open Science Framework and can be accessed at https://osf.io/zejwb/.

Measures

Demographic questionnaire

This questionnaire included demographic questions such as age, gender, marital status, religion, job, salary and work experience. Furthermore, this questionnaire included questions related to the COVID-19 pandemic (e.g., "have you been diagnosed with COVID-19?", "Have you recently met someone diagnosed with COVID-19?", "Are you in quarantine?").

COVID-19 concerns questionnaire (For a similar questionnaire, see [88])

This questionnaire included questions related to concerns arising from the COVID-19 pandemic: health concerns (own and relatives) and economic concerns (own, relatives and national), as well as concerns about relationships, personal appearance and the ability of the country and the world to cope with the COVID-19 pandemic (e.g., "to what extent do you worry about getting infected with COVID-19?"). Participants responded on a 5-point scale ranging from 1 (not at all) to 5 (very much) (Cronbach α = .87).

The Depression Anxiety Stress Scale (DASS; [89])

The DASS consists of a general factor of psychological distress and orthogonal specific factors of depression, anxiety, and stress [90]. The items on the depression scale include, for example, questions about dysphoria (e.g., “I felt I had lost interest in just about everything”) and low self-esteem (“I felt I wasn’t worth much as a person”). The items on the anxiety scale assess somatic and subjective responses to anxiety and fear (e.g., “I had difficulty breathing” and “I felt scared without any good reason”). The items on the stress scale measure negative affectivity responses such as nervous tension and irritability, which are characteristic of both depression and anxiety (e.g., “I found it difficult to relax” and “I felt that I was rather touchy”). The respondents rate how often they experienced each item in the past week on a four-point scale ranging from 0 (did not apply to me at all) to 3 (applied to me very much or most of the time). Given a strong correlation between the three subscales (ranging from r = .64 to r = .75), we used the general factor for psychological distress (total DASS score). Cronbach α in our sample for the total DASS score is .93.

The Penn State Worry Questionnaire (PSWQ; [91]

The PSWQ is a 16-item measure of trait worry. The items on the scale assess the occurrence, intrusiveness and pervasiveness of worrisome thoughts (e.g., “When I am under pressure I worry a lot”; “My worries overwhelm me”). Participants are instructed to indicate the degree to which each item is typical of them on a five-point scale ranging from 1 = “not at all typical of me” to 5 = “very typical of me”. High internal reliability was found between items (Cronbach α = .84).

Emotion Regulation Questionnaire (ERQ; [54])

The ERQ consists of 10 statements that assess two emotion regulation strategies: reappraisal and suppression. Reappraisal is the ability to change the way one thinks about a situation, in order to change how one feels (e.g., "I control my emotions by changing the way I think about the situation I am in"). Suppression is the ability to mask one’s feelings and emotional expression (Gross, 1998; e.g., "I control my emotions by not expressing them"). Participants are asked to rate whether they agree or disagree with each statement on a scale of 1 to 7 (1 = strongly disagree, 7 = strongly agree). Cronbach α = .79 for reappraisal; Cronbach α = .77 for suppression.

The Shirom-Melamed Burnout Measure (SMBM; [31])

The SMBM contains 16 items divided into three subscales: physical fatigue (six items: e.g., “I feel physically drained” or “I feel fed-up”), cognitive weariness (six items: e.g., “I feel I am not thinking clearly” or “I have difficulty concentrating”) and emotional exhaustion (four items: e.g., “I feel I am unable to be sensitive to the needs of coworkers and customers” or “I feel I am not capable of being sympathetic to coworkers and customers”). Respondents answer on a seven-point scale ranging from 1 = “almost never” to 5 = “almost always”. No significant differences were found between the three factors (physical, emotional, cognitive) and therefore the general score was used. High internal reliability was found between the items (Cronbach α = .94).

Analytical strategy

Missing data were replaced with maximum likelihood (ML) estimations based on all variables in the model via Statistical Package for Social Science (SPSS) 27 given that Little’s Missing Completely at Random (MCAR) test [92] showed that data were missing completely at random, χ2 (33) = 21.70, p = .93. Hierarchical linear regression analysis was performed to determine the role of emotion regulation in burnout while controlling for psychological distress, COVID-19 concerns, and demographic variables (age and gender). In step one, age and gender were entered to the model. In step two, psychological distress (total DASS score) and COVID-19 concerns were added. In step three, the emotion regulation strategies (reappraisal, suppression and worry) were added to the model.

Results

Hierarchical linear regression analysis was performed to identify the significant predictors of burnout among healthcare workers (see Table 2). Burnout scores served as dependent variable. The first step, which included age and gender, did not account for significant variance in burnout, R = 0.02, F(2, 95) = .72, p = .49. The second step, in which psychological distress and COVID-19 concerns were added, was significant, F(4, 93) = 15.58, p < .001, and accounted for 40% of the variance in burnout. This step added significantly to the model, accounting for an additional 39% of the variance in burnout score, Fchange (2, 93) = 30.00, p < .001. In this step, only psychological distress (total DASS score) significantly predicted burnout (β = .60, t = 6.21, p < .001). The third step, which included also emotion regulation strategies, was also significant, F(7, 90) = 10.97, p < .001, and accounted for 46% of the variance in burnout. This step added significantly to the model, accounting for an additional 6% of the variance in burnout score, Fchange (3, 90) = 3.30, p < .05. In this step, only worry (β = .24, t = 2.57, p < .05) and psychological distress (β = .49, t = 4.71, p < .001) significantly predicted burnout.

Table 2

Predictors of burnout: Hierarchical regression.

	Predictors	R2	B	S.E	β	t	p	Confidence Intervals
								Lower Bound	Upper Bound
Step 1		.02						21.49	67.29
	Age		-.12	.19	-.06	-.61	.54	-.51	.27
	Gender		5.30	5	.11	1.06	.29	-4.63	15.23
Step 2		0.4						15.07	60.15
	Age		-.15	.15	-.78	3.31	.34	-.46	.16
	Gender		1.47	4	.30	-.96	.72	-6.49	9.43
	COVID-19 Concerns		.95	1.94	.05	.49	.63	-2.91	4.80
	Psychological Distress		.84	.14	.60	6.21	.00	.57	1.11
Step 3		.46						-10.38	44.26
	Age		-.10	.15	-.05	-.69	.49	-.41	.19
	Gender		.49	4.05	.10	.12	.91	-7.56	8.54
	COVID-19 Concerns		.38	1.98	.02	.19	.85	-3.55	4.30
	Psychological Distress		.69	.15	.49	4.71	.00	.39	.98
	Reappraisal		-.07	.22	-.02	-.29	.77	-.51	.38
	Suppression		.46	.28	.14	1.71	.09	-.07	.99
	Worry		.43	.17	.24	2.57	.01	.09	.75

Discussion

The recent global spread of the coronavirus (COVID-19) has generated a great deal of chaos and stress, particularly among healthcare workers (e.g., [10, 11]). Recent studies identified moderate to severe levels of psychological distress and burnout among healthcare workers in Israel and worldwide [20, 23–25]. The current investigation was conducted in Israel during April 2020, when the number of confirmed cases of COVID-19 rose rapidly, leading to a national lockdown. The main objective of the current study was to examine whether individual differences in habitual use of emotion regulation strategies play a role in predicting job burnout among healthcare workers. We hypothesized that emotion regulation strategies would predict burnout above and beyond levels of psychological distress, COVID-19 concerns, and demographic variables. The results partially support our hypotheses. Specifically, the findings suggest that trait worry and psychological distress were significant predictors of job burnout, whereas habitual reappraisal and suppression did not predict burnout.

Findings from the current study are in agreement with previous results showing an association between levels of worrying and job burnout among healthcare residents [80]. A link between worry and burnout was also found among highly demanding professions, such as athletes [81] and university students [82]. Worry involves concerns about upcoming events and distress that is yet to come. Therefore, given the unique characteristics of COVID-19, including the ambiguity surrounding its nature, the way it spreads, and its treatment, at least in the early stages of the outbreak, it is reasonable to assume that individuals with a high tendency to worry spent many of their time and energy, as well as their cognitive resources on concerns about the future. This might be especially true given their role as healthcare professionals, expected by their patients to provide answers, whilst dealing with their clients’ concerns that might actually mirror their own worries. Thereby, presumably further enhancing their worries. Hence, healthcare workers who tend to worry are presumably more vulnerable for accumulating stress, which eventually leads to elevated levels of burnout [93].

While previous studies have exemplified the presence of episodic worries among healthcare workers during COVID-19 pandemic (e.g., [94, 95]), to the best of our knowledge, this study is the first to examine the contribution of trait worry to job burnout among healthcare workers. Importantly, in the current study trait worry was a significant predictor of burnout even when controlling for psychological distress and COVID-19 related concerns. This finding suggests that worry is a prominent risk factor for burnout, independently of current symptoms of distress. Therefore, the current investigation adds to the literature on the relationship between burnout and individual differences in emotion regulation (e.g., [50, 53, 96]) by showing that the tendency to worry is associated with job burnout. Therefore, the current findings add to the accumulating evidence regarding the psychological variables that contribute to job burnout [97-100].

Furthermore, our findings are in line with previous studies that demonstrated positive correlations between psychological distress and burnout [101-103]. Recent studies have showed that healthcare workers experience both high levels of psychological distress, as well as fatigue and burnout during the COVID-19 pandemic [13, 22]. An additional study also demonstrated a link between psychological distress and burnout during the pandemic [23]. Levels of psychological distress often have a negative impact on the health, performance, and productivity of workers, what can influence the quality of care provided by them, and ultimately, patients’ health [104]. Importantly, although psychological distress was found to be a significant predictor of burnout in our model, levels of worry, a trait-like aspect [91, 105], predicted burnout above and beyond levels of psychological distress.

Surprisingly, the current study did not exemplify a link between the habitual use of reappraisal and burnout levels. This is in contrast to previous studies consistently demonstrating a protective impact of reappraisal on burnout among healthcare workers and other professionals in general [59-63], and in COVID-19 in specific [106]. These findings, however, corroborates the idea that under intense emotional situations, individuals do not tend to rely on reappraisal as a main mechanism to regulate their emotions, but tend to use other emotion regulation strategies such as distraction [64]. Specifically, it may be that the extreme psychological distress caused by the COVID-19 made reappraisal less effective or accessible [65], thus lowering the potential contribution of reappraisal on lowering job burnout, as showed in previous studies. This suggestion, however, is speculative and should be tested in future studies.

Furthermore, unlike prior findings showing associations between suppression and burnout among teachers and healthcare workers [61, 74], the results of the current study did not support a link between habitual use of suppression and burnout levels. In contrary to previous studies that distinguished between adaptive and maladaptive emotion regulation strategies, to date, researchers emphasize that mental health depends on one’s ability to modulate emotional response under situational demands [107-113]. Therefore, adaptation depends on one’s ability to flexibly enhance or suppress emotional reactions in accordance with the contextual demands [111]. Indeed, in a recent study conducted in Italy by Lenzo et al. [114], it was found that the ability to flexibility enhance or suppress emotional response decreased burnout risk in the context of palliative home care [114].

Limitations

Findings of this study should be evaluated in the light of several methodological limitations. The sample size was relatively small, predominantly female, which likely limited the generalizability of results. In addition, the current study was cross-sectional in nature, which does not allow for examining directionality between variables. Prospective research with larger samples is needed to untangle directionality of current findings. Although all study measures were assessed via the use of commonly and validated questionnaires, it is possible that they represent self-perception and conscious subjective processes.

Implications

Findings of this study may contribute to the understanding of the psychological dynamics accruing in the context of an epidemiological and psychological crisis and have important implications. Taken together, the results of the present study provide further knowledge regarding the risk factors that might enhance healthcare workers’ vulnerability to professional burnout at times of crisis. Thus, emphasize the need for novel interventions for preventing psychological distress and promoting well-being among populations whose ability to function is crucial at times of crisis. Our results suggest that in order to reduce the risk of burnout and improve the well-being of healthcare workers, intervention planning should integrate programs that address Person-centered interventions aimed at reducing the tendency to worry [115].

13 Dec 2021

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Reviewer #1: This manuscript “Job Burnout among Israeli Healthcare Workers during the COVID-19 Pandemic: The Role of Emotion Regulation Strategies and Psychological Distress” describes the results of a cross-sectional investigation of work burnout and emotion regulation strategies, as well as worries, depression, anxiety and stress, among Israeli healthcare workers (HCW) during the initial stage of the COVID-19 pandemic in Israel. The researchers found associations among burnout with the rest of the study variables, except for reappraisal. I believe that this is an important study which can add to the relatively less-investigated body of knowledge regarding emotion regulation strategies of HCW during COVID-19. Yet, I do have some concerns which I believe should be addressed in order to improve this paper:

In my opinion, the weakness of this manuscript is its analytic approach. The choice to conduct a stepwise regression model is unclear to me from several reasons: first, this is an exploratory approach in its nature, and as such it suffers from all the pitfalls of fishing expedition. Moreover, the choice of this method is surprising since the researchers have some very clear hypotheses, which are not being addressed properly this way. As a result- the researchers’ interpretation of their results is incorrect. Stepwise does not locate the most prominent predictors of a dependent variable, but rather creates the best combination of factors, but on the way some extremely important factors are being omitted (for example- anxiety, stress and the ERQ subscales). If the authors wish to avoid multicollinearity there are other ways- from using the standardized residuals of regressed independent variables, to combining highly correlated variables or even conducting a series of simple regressions with alpha corrections.

More importantly, there are several factors that simply cannot be excluded from the model: the first are age and sex (which is crucial since the sample is biased in favor of women). The second is the emotion regulation strategies, which are the focus of the paper! I suggest that the authors will conduct a standard regression model with the fixed factors that were decided a-priori, and will address the issue of multicollinearity in a different way. Of course, if you decide to do so the discussion should be adjusted to your renewed results. Also, there is no need to conduct both regression and correlations, so I believe that the authors should focus on one model with their variables of interest.

On a similar note, I think that some of the information presented in Table 3 is redundant. For example- there is no need to present both tolerance and VIF (which is calculated as 1/tolerance). A simple report of the VIF is enough (and to my taste even this is unnecessary unless there is an issue of multicollinearity in the model itself). The presentation of the confidence interval (upper and lower limit) in unstandardized scores is not informative, and it is much preferred if it would be presented in standardized scores (as the second beta column). The constant is not interesting and can be hidden from the table. Also, I don’t see the point of presenting the excluded factors in such a detailed manner. In Table 2- notice that you are not consistent with the number of decimal points (.296 vs. .64 etc.).

Some additional notes:

Introduction:

1. The review of the situation of HCW during COVID-19 is a bit lack. Many papers have been published since the outbreak and there are many reviews, meta-analyses and high-quality surveys on the experiences of HCW. I think that it’s a shame to address in such details to three specific surveys (page 4 lines 67-75) that were published very close to the first emergence of the outbreak and are not representative to the Israeli population nor do they capture a global snapshot of the situation, especially if one is from MedRxiv and haven’t been peer-reviewed.

2. Page 4 line 89- not “during pandemics” but “during the COVID-19 pandemic”

3. Page 5 line 114- you claim that “the research addressing individual differences that may potentially contribute to burnout is relatively sparse”, please provide a reference to support this claim. Maybe a review or meta-analysis of some kind. To the best of my knowledge there have been numerous investigations of risk factors for burnout among HCW, but your uniqueness is the focus on emotion regulation.

4. Page 8 line 188- not “personal” but “personnel”.

Methods:

1. Under procedure- your survey was not conducted “approximately one month after the outbreak of the COVID-19 pandemic in Israel”, as claimed, but rather almost two months after the first case was discovered in late February, and almost one month into the national lockdown.

2. The Cronbach’s alphas for the ERQ are only moderate, is it similar to the questionnaire’s psychometrics in other studies? If not- can you offer an explanation for this?

Discussion:

1. Page 13 line 297- the lockdown in Israel was by no way partial, but rather a full lockdown in which only a small group of essential workers was excluded.

2. “in the stepwise regression analysis only the tendency to worry and levels of depression remained significant predictors of burnout”- As mentioned earlier, this interpretation is incorrect. The variables should be examined in a fixed model which includes all of the predictors in order to determine their relationship with burnout and one another.

“Habitual reappraisal, however, was not linked to burnout”- this conclusion is drawn from the correlations, but again- in a standard regression you can include it and reach this conclusion without the need to run both regression and correlations.

3. Page 14 line 316- write “patients” instead of “clients”

4. Page 14 second paragraph (“Importantly, in the current study…”)- again I believe that you interpret exploratory results in an incorrect way, and claim that worry predicted burnout “independently of anxiety and stress”, even though they were not included in the model! Please revise this passage in accordance with your actual results.

5. Page 14 lines 305-319- I find it peculiar that you do not address any findings from COVID-19. There are tons of recent evidence that link to your findings, which I believe should be discussed here.

6. There are a few grammatical errors throughout the paper (“although depression was found a significant predictor”, instead of “was found to be a…”). Please revise the text and address them.

7. Page 14 line 337- you claim that worries are a trait-like aspect while depression is more episodic- please provide a reference to support this claim. Otherwise, one might insist that worries are also an episodic state, a claim which sounds reasonable to me.

8. Limitations- power is not one of your limitations, despite your small sample size. It is visible in table 2 that where a respectable effect size was detected, the result was statistically significant. Therefore, I do not believe that insignificant results in your study ensue from type-II errors.

To conclude, I honestly believe that this study has a lot of potential and is of great value, but the interesting data presented here should be analyzed and interpreted a bit more rigorously in order to draw reliable and accurate conclusions. I am looking forward to reading the revised version of the manuscript.

Reviewer #2: This is my review on the manuscript entitled “Job Burnout among Israeli Healthcare Workers during the COVID-19 Pandemic: The Role of Emotion Regulation Strategies and Psychological Distress”.

Burn out is a serious problem with devastating effects not only on healthcare workers but also to the health system as well. Thus, this study is important and provides significant information regarding the main risk and protective factors that contributes to burn out and psychological deterioration.

The current investigation took place 3 months after the start of the pandemic and one month after the declaration of the Covid-19 situation as a pandemic by the WHO (March 11th, 2020). Since it is almost 2 years after the appearance of Covid-29 in Wuhan, I recommend that the title should be modified accordingly. For instance, “Job Burnout among Israeli Healthcare Workers during the first months of COVID-19 Pandemic: The Role of Emotion Regulation Strategies and Psychological Distress”.

The introduction is well written. Materials and methods are sufficient. You should mention the population target as you distributed the survey through Facebook and emails (not through a collective source like hospital emails etc.). Was it accessible by everyone from Facebook? Was it through a Healthcare workers Facebook group, or personal message? Statistics are fine. Table 1 needs to be presented with the number of each demographic characteristic alongside with percent.

Discussion is interesting. You should include a small paragraph with a country-based comparison to Israeli Healthcare workers by including these studies:

1. Dobson H, et al. Burnout and psychological distress amongst Australian healthcare workers during the COVID-19 pandemic. Australas Psychiatry. 2021 Feb;29(1):26-30. doi: 10.1177/1039856220965045. Epub 2020 Oct 12. Erratum in: Australas Psychiatry. 2021 May 11;:10398562211011741. PMID: 33043677; PMCID: PMC7554409.

2. Cheristanidis S, et al. Psychological Distress in Primary Healthcare Workers during the COVID-19 Pandemic in Greece. Acta Med Acad. 2021 Aug;50(2):252-263. doi: 10.5644/ama2006-124.341. PMID: 34847678.

3. Saddik B, et al. Psychological Distress and Anxiety Levels Among Health Care Workers at the Height of the COVID-19 Pandemic in the United Arab Emirates. Int J Public Health. 2021 Nov 11;66:1604369. doi: 10.3389/ijph.2021.1604369. PMID: 34840553; PMCID: PMC8615074.

4. Firew T, 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 Oct 21;10(10):e042752. doi: 10.1136/bmjopen-2020-042752. PMID: 33087382; PMCID: PMC7580061.

Language is good.

**********

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Reviewer #1: Yes: Nimrod Hertz-Palmor

Reviewer #2: No

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2 Feb 2022

Thank you for your e-mail offering us the opportunity to revise and resubmit our paper entitled “Job Burnout Among Israeli Healthcare Workers During First Months of COVID-19 Pandemic: The Role of Emotion Regulation Strategies and Psychological Distress” to PLOS ONE. We found the reviewers’ comments highly informative and helpful, and below we have specified how we have addressed each of them.

We believe that the manuscript is much improved following the reviewers’ comments and the changes we made. In the revised manuscript, the changes that have been made are marked.

Comments of Reviewer #1

This manuscript “Job Burnout among Israeli Healthcare Workers during the COVID-19 Pandemic: The Role of Emotion Regulation Strategies and Psychological Distress” describes the results of a cross-sectional investigation of work burnout and emotion regulation strategies, as well as worries, depression, anxiety and stress, among Israeli healthcare workers (HCW) during the initial stage of the COVID-19 pandemic in Israel. The researchers found associations among burnout with the rest of the study variables, except for reappraisal. I believe that this is an important study which can add to the relatively less-investigated body of knowledge regarding emotion regulation strategies of HCW during COVID-19. Yet, I do have some concerns which I believe should be addressed in order to improve this paper:

Response: We thank the reviewer for pointing out the strengths of our work and for his insightful comments.

In my opinion, the weakness of this manuscript is its analytic approach. The choice to conduct a stepwise regression model is unclear to me from several reasons: first, this is an exploratory approach in its nature, and as such it suffers from all the pitfalls of fishing expedition. Moreover, the choice of this method is surprising since the researchers have some very clear hypotheses, which are not being addressed properly this way. As a result- the researchers’ interpretation of their results is incorrect. Stepwise does not locate the most prominent predictors of a dependent variable, but rather creates the best combination of factors, but on the way some extremely important factors are being omitted (for example- anxiety, stress and the ERQ subscales). If the authors wish to avoid multicollinearity there are other ways- from using the standardized residuals of regressed independent variables, to combining highly correlated variables or even conducting a series of simple regressions with alpha corrections.

More importantly, There are several factors that simply cannot be excluded from the model: the first are age and sex (which is crucial since the sample is biased in favor of women). The second is the emotion regulation strategies, which are the focus of the paper! I suggest that the authors will conduct a standard regression model with the fixed factors that were decided a-priori, and will address the issue of multicollinearity in a different way. Of course, if you decide to do so the discussion should be adjusted to your renewed results. Also, there is no need to conduct both regression and correlations, so I believe that the authors should focus on one model with their variables of interest.

Response: We thank the reviewer for this important comment. Following the reviewer's advice, we have now calculated a total score for the DASS questionnaire, which represents overall psychological distress, instead of entering the different subscales into the analysis. This idea is consistent with previous works that look at the total DASS score (e.g., Lamuri et al., 2021). In addition, we omitted the correlation table from the manuscript. Furthermore, we changed the analytical plan and now report the results of a hierarchical linear regression instead of the stepwise regression. The new analysis consists of three steps: In the first step, in line with the reviewer's suggestion, we included age and gender in the model. In the second step, we added total DASS scores and COVID-related concerns. In the third step, as the reviewer suggested, we added the emotion regulation measures (suppression, reappraisal, and worry). The pattern of results remained consistent with the previous results, showing that only worry and psychological distress predict job burnout, even when controlling for age and gender.

On a similar note, I think that some of the information presented in Table 3 is redundant. For example- there is no need to present both tolerance and VIF (which is calculated as 1/tolerance). A simple report of the VIF is enough (and to my taste even this is unnecessary unless there is an issue of multicollinearity in the model itself). The presentation of the confidence interval (upper and lower limit) in unstandardized scores is not informative, and it is much preferred if it would be presented in standardized scores (as the second beta column). The constant is not interesting and can be hidden from the table. Also, I don’t see the point of presenting the excluded factors in such a detailed manner.

Response: We thank the reviewer for pointing this out. After combining the different DASS subscales into a single measure there was no multicollinearity. Therefore, we do not report VIF or tolerance.

In Table 2- notice that you are not consistent with the number of decimal points (.296 vs. .64 etc.).

Response: We made sure that all values contain 2 decimal points.

The review of the situation of HCW during COVID-19 is a bit lack. Many papers have been published since the outbreak and there are many reviews, meta-analyses and high-quality surveys on the experiences of HCW. I think that it’s a shame to address in such details to three specific surveys (page 4 lines 67-75) that were published very close to the first emergence of the outbreak and are not representative to the Israeli population nor do they capture a global snapshot of the situation, especially if one is from MedRxiv and haven’t been peer-reviewed.

Response: We have updated the literature review and added investigations conducted both immediately and later on during the COVID-19 pandemic (page 3-5, lines 62-84).

Page 4 line 89- not “during pandemics” but “during the COVID-19 pandemic”.

Response: This sentence has been modified.

Page 5 line 114- you claim that “the research addressing individual differences that may potentially contribute to burnout is relatively sparse”, please provide a reference to support this claim. Maybe a review or meta-analysis of some kind. To the best of my knowledge, there have been numerous investigations of risk factors for burnout among HCW, but your uniqueness is the focus on emotion regulation.

Response: Indeed, there are numerous investigations addressing personal factors predicting burnout among healthcare workers. We have added references regarding environmental and personal factors that contribute to burnout (page 6, lines 122-134). We also added a sentence clarifying that the research addressing the emotion regulation tendencies that may potentially contribute to burnout is relatively sparse.

Page 8 line 188- not “personal” but “personnel”.

Response: Thank you. we changed the word accordingly.

Under procedure- your survey was not conducted “approximately one month after the outbreak of the COVID-19 pandemic in Israel”, as claimed, but rather almost two months after the first case was discovered in late February, and almost one month into the national lockdown.

Response: We thank the reviewer for this clarification. We have changed the text accordingly (page 10, lines 223-224).

The Cronbach’s alphas for the ERQ are only moderate, is it similar to the questionnaire’s psychometrics in other studies? If not- can you offer an explanation for this?

Response: The Cronbach’s alphas reliabilities (.79 for reappraisal and .77 for suppression) we received in our sample are similar to those found in prior research (e.g., Gross and John, 2003; range between .75 to .82 for reappraisal and range between .68 to .76 for suppression). It seems that in the previous version, there was a typo in the reliability written for suppression (which is .77 and not .73). We apologize for that.

Page 13 line 297- the lockdown in Israel was by no way partial, but rather a full lockdown in which only a small group of essential workers was excluded.

Response: Thank you. We have changed the text accordingly.

“In the stepwise regression analysis only the tendency to worry and levels of depression remained significant predictors of burnout”- As mentioned earlier, this interpretation is incorrect. The variables should be examined in a fixed model which includes all of the predictors in order to determine their relationship with burnout and one another. “Habitual reappraisal, however, was not linked to burnout”- this conclusion is drawn from the correlations, but again- in a standard regression you can include it and reach this conclusion without the need to run both regression and correlations.

Response: As noted above, we have changed the analytic strategy in line with the reviewer's suggestions.

Page 14 line 316- write “patients” instead of “clients”.

Response: Ass suggested, we have replaced the word "clients" with the word "patient".

Page 14 second paragraph (“Importantly, in the current study…”)- again I believe that you interpret exploratory results in an incorrect way, and claim that worry predicted burnout “independently of anxiety and stress”, even though they were not included in the model! Please revise this passage in accordance with your actual results.

Response: As mentioned earlier, we conducted a hierarchical regression analysis. This analysis showed that worry predicts burnout above and beyond psychological distress.

Page 14 lines 305-319- I find it peculiar that you do not address any findings from COVID-19. There are tons of recent evidence that link to your findings, which I believe should be discussed here.

Response: Although previous research emphasized the role of worries related to the COVID-19 pandemic, our study is the first, to our knowledge, that looked at worry as a trait characteristic. Nevertheless, we now included papers on COVID-19 related worries and clarified the unique contribution of the current investigation.

There are a few grammatical errors throughout the paper (“although depression was found a significant predictor”, instead of “was found to be a…”). Please revise the text and address them.

Response: Thank you. The manuscript was sent for an English editing before submission.

Page 14 line 337- you claim that worries are a trait-like aspect while depression is more episodic- please provide a reference to support this claim. Otherwise, one might insist that worries are also an episodic state, a claim which sounds reasonable to me.

Response: In the current study we chose to use a questionnaire assessing worry as a trait characteristic (i.e., PSWQ; Meyer et al., 1990). In order to assess worries specifically related to COVID-19 (and therefore episodic in nature) we also included a COVID-19 concerns questionnaire. We clarified in the text that worry was assessed as a trait factor. As can be seen from the results, trait worry predicted burnout above and beyond levels of episodic (COVID-19-related) concerns.

Limitations- power is not one of your limitations, despite your small sample size. It is visible in table 2 that where a respectable effect size was detected, the result was statistically significant. Therefore, I do not believe that insignificant results in your study ensue from type-II errors.

Response: We changed the sentence about power according to the suggestion.

To conclude, I honestly believe that this study has a lot of potential and is of great value, but the interesting data presented here should be analyzed and interpreted a bit more rigorously in order to draw reliable and accurate conclusions. I am looking forward to reading the revised version of the manuscript.

Response: We wish to thank the reviewer for emphasizing the importance of our work and for his insightful comments.

Comments of Reviewer #2:

This is my review on the manuscript entitled “Job Burnout among Israeli Healthcare Workers during the COVID-19 Pandemic: The Role of Emotion Regulation Strategies and Psychological Distress”. Burnout is a serious problem with devastating effects not only on healthcare workers but also to the health system as well. Thus, this study is important and provides significant information regarding the main risk and protective factors that contributes to burn out and psychological deterioration. The current investigation took place 3 months after the start of the pandemic and one month after the declaration of the Covid-19 situation as a pandemic by the WHO (March 11th, 2020). Since it is almost 2 years after the appearance of Covid-29 in Wuhan, I recommend that the title should be modified accordingly. For instance, “Job Burnout among Israeli Healthcare Workers during the first months of COVID-19 Pandemic: The Role of Emotion Regulation Strategies and Psychological Distress”.

Response: We thank the reviewer for highlighting the importance of the current work and for the helpful comments. We changed the title according to the reviewer's suggestion.

The introduction is well written. Materials and methods are sufficient.

Response: Many thanks.

You should mention the population target as you distributed the survey through Facebook and emails (not through a collective source like hospital emails etc.). Was it accessible by everyone from Facebook? Was it through a Healthcare workers Facebook group, or personal message?

Response: The survey was distributed in social media platforms including Facebook groups of Healthcare workers and via snowball sampling (chain-referral sampling). We have now included this information in the text (page 10, lines 220-225).

Statistics are fine. Table 1 needs to be presented with the number of each demographic characteristic alongside with percent.

Response: We have added this information to the table.

Discussion is interesting. You should include a small paragraph with a country-based comparison to Israeli Healthcare workers by including these studies:

1. Dobson H, et al. Burnout and psychological distress amongst Australian healthcare workers during the COVID-19 pandemic. Australas Psychiatry. 2021 Feb;29(1):26-30. doi: 10.1177/1039856220965045. Epub 2020 Oct 12. Erratum in: Australas Psychiatry. 2021 May 11;10398562211011741. PMID: 33043677; PMCID: PMC7554409.

2. Cheristanidis S, et al. Psychological Distress in Primary Healthcare Workers during the COVID-19 Pandemic in Greece. Acta Med Acad. 2021 Aug;50(2):252-263. doi: 10.5644/ama2006-124.341. PMID: 34847678.

3. Saddik B, et al. Psychological Distress and Anxiety Levels Among Health Care Workers at the Height of the COVID-19 Pandemic in the United Arab Emirates. Int J Public Health. 2021 Nov 11;66:1604369. doi: 10.3389/ijph.2021.1604369. PMID: 34840553; PMCID: PMC8615074.

4. Firew T, 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 Oct 21;10(10):e042752. doi: 10.1136/bmjopen-2020-042752. PMID: 33087382; PMCID: PMC7580061.

Response: We thank the reviewer for providing these references. We have updated the literature review and added a

paragraph in the introduction discussing distress of HCW in different countries.

Language is good.

Response: Thank you.

Submitted filename: cover letter 27-1-22 final.docx

Click here for additional data file.

21 Feb 2022

26 Feb 2022

I thank the authors for taking my comments into consideration and for revising the manuscript so thoroughly. I believe the current version is much improved. A few minor comments about the results section:

1. Please refer to R square as 0.02, and not 2%.

2. When reporting the steps of the hierarchical regression, please include the R square change value, which is crucial to get an idea about your effect size.

Response: We thank the reviewer for the time and effort he invested in reviewing our manuscript. We changed the R2 value to 0.02 and also added details about R2 change.

Page 13: “Burnout scores served as dependent variable. The first step, which included age and gender, did not account for significant variance in burnout, R2 = 0.02, F(2, 95) = .72, p = .49. The second step, in which psychological distress and COVID-19 concerns were added, was significant, F(4, 93) = 15.58, p < .001, and accounted for 40% of the variance in burnout. This step added significantly to the model, accounting for an additional 39% of the variance in burnout score, Fchange (2, 93) = 30.00, p < .001. In this step, only psychological distress (total DASS score) significantly predicted burnout (β = .60, t = 6.21, p < .001). The third step, which included also emotion regulation strategies, was also significant, F(7, 90) = 10.97, p < .001, and accounted for 46% of the variance in burnout. This step added significantly to the model, accounting for an additional 6% of the variance in burnout score, Fchange (3, 90) = 3.30, p < .05. In this step, only worry (β = .24, t = 2.57, p < .05) and psychological distress (β = .49, t = 4.71, p < .001) significantly predicted burnout.”

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

7 Mar 2022

Job Burnout Among Israeli Healthcare Workers During the First Months of COVID-19 Pandemic: The Role of Emotion Regulation Strategies and Psychological Distress

PONE-D-21-27667R2

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Reviewer #1: All comments have been addressed

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Reviewer #1: Yes

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Reviewer #1: Yes: Nimrod Hertz-Palmor

15 Mar 2022

PONE-D-21-27667R2

Job Burnout Among Israeli Healthcare Workers During the First Months of COVID-19 Pandemic: The Role of Emotion Regulation Strategies and Psychological Distress

Dear Dr. Cohen:

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