Received: 1 February 2021

| Revised: 10 June 2021 | Accepted: 17 July 2021

DOI: 10.1002/jclp.23238

RESEARCH ARTICLE

Psychological distress of mental health workers
during the COVID‐19 pandemic: A comparison
with the general population in high‐ andlow‐incidence regions
Pascale Brillon1|

Frederick L. Philippe1
2,3Marie‐Claude Geoffroy
Isabelle Ouellet‐Morin4,5|

Alison Paradis1|

Massimiliano Orri

3

|

|

1

Department of Psychology, Université duQuébec à Montréal, Montreal, Quebec,
CanadaAbstract
Objective: Despite their essential role during this health2

Department of Educational and Counselling
Psychology, McGill University, Montreal,
Quebec, Canada
3

crisis, little is known about the psychological distress ofmental health workers (MHW).

McGill Group for Suicide Studies,
Department of Psychiatry, McGill University,
Montreal, Quebec, Canada

Method: A total of 616 MHW and 658 workers from the4
Department of Criminology, University ofMontreal, Montreal, Quebec, Canada

cluding depressive, anxiety, irritability, loneliness, and re-5

Research Center of the Montreal Mental
Health University Institute, McGill University,
Montreal, Quebec, Canada
Correspondence
Pascale Brillon, Department of Psychology,
Université du Québec à Montréal, PO
Box 8888, Station Centre‐ville, Montreal, QC
H3C 3P8, Canada.
Email: brillon.pascale@uqam.ca

general population (GP) completed an online survey insilience measures.
Results: Overall, MHW had fewer cases with above cut‐offclinically significant depression (19% MHW vs. 27%) or
anxiety (16% MHW vs. 29%) than the GP. MHW in high‐incidence regions of COVID‐19 cases displayed the samelevels of depressive and anxiety symptoms than the GP andhigher levels compared to MHW from low‐incidence regions. MHW in high‐incidence regions presented higher
levels of irritability and lower levels of resilience than the
MHW in low‐incidence regions. Moreover, MHW in high‐incidence regions reported more feelings of loneliness than
all other groups.
Conclusion: Implications for social and organizational preventive strategies to minimize the distress of MHW intimes of crisis are discussed.

J Clin Psychol. 2021;1–20.

wileyonlinelibrary.com/journal/jclp© 2021 Wiley Periodicals LLC

|

1

2

|

BRILLON ET AL.

KEYWORDS

anxiety, COVID‐19, depression, mental health workers,
psychological distress

1| INTRODUCTION

The coronavirus disease (COVID‐19) pandemic is a global health crisis which, as of July 26, 2021, had claimed morethan 4.1 million lives and infected more than 194 million people worldwide (World Health Organization [WHO],
2020). This pandemic has not only threatened our physical health but has also disrupted many facets of our daily
lives (e.g., social, financial, marital/familial). The implementation of unprecedented strict social distancing andisolation measures aimed at controlling the outbreak has been associated, in cross‐sectional studies, with considerable psychological distress (Alzueta et al., 2020; Rajkumar, 2020): anxiety (Asmundson & Taylor, 2020; Dubeyet al., 2020; Li et al., 2020), depression (Yao et al., 2020; Zhang et al., 2020), avoidance and compulsive behaviors(Holmes et al., 2020; Kar et al., 2020), loneliness and social withdrawal behaviors (Banerjee & Rai, 2020; Berg‐
Weger & Morley, 2020; Holmes et al., 2020), increased alcohol consumption (Clay & Parker, 2020; Da et al., 2020),
chronic stress (Dubey et al., 2020; Fitzpatrick et al., 2020), and increasing levels of domestic violence and separation(Abramson, 2020; Campbell, 2020; Lebow, 2020).
Considering that the COVID‐19 pandemic yielded greater needs in mental health, the role of mental health workers(MHW) is of critical importance now more than ever (Grover et al., 2020). Throughout the pandemic, MHW, such as
psychologists, social workers, psychosocial counselors, and psychiatrists, have been considered essential service workers
and have had to support and treat individuals for whom psychological distress emerged in response to or was exacerbatedby the current conditions. Multiple studies have demonstrated how health professionals (e.g., nurses, physicians, medical
staff, orderlies) worldwide are experiencing sustained and high levels of stress since the onset of the current pandemic andare at higher risk of poorer mental health compared to the general population, with depression and anxiety at its forefront(for a review, see Pappa et al., 2020). While most MHW were not directly on the frontline with healthcare workers treating
COVID patients, they were all confronted on a daily basis with the complex challenges of dealing with the unrelenting
psychological distress of others, potential increases in professional mandates, and disruptive organizational adaptations,while also coping with their own COVID‐related fears and stressors. Despite that MHW have a key role in minimizing the
population's psychological and psychiatric effects of the COVID‐19 pandemic, the mental health of these professionals hasreceived little public and scientific attention (da Silva & Neto, 2020). In fact, to the best of our knowledge, only two studies
have examined the effects of the COVID‐19 pandemic on the mental health of MHW. The first examined vicarious traumaof psychotherapists and found that younger, less experienced therapists were at a greater risk of vicarious trauma (Aafjes‐
van Doorn et al., 2020). The second examined perceived stress and job‐related anxiety in psychotherapists and found that
their stress‐level, but not their job‐related anxiety, was higher than that of the general population (Probst et al., 2020).
While these two studies are useful to understand how MHW have adapted to the pandemic, they have not investigatedkey mental health indicators such as depressive and anxiety symptoms and did not consider the exposure‐related consequences and constraints on the participants' lives. Moreover, it is unknown whether the effect of the pandemic is more
important in regions of high incidence of COVID‐19 versus lower incidence regions. As mental well‐being is a key
determinant of MHW's ability to deliver high‐quality care (Laverdière et al., 2018; Salyers et al., 2017), developing a mental
health profile of MHW in the face of the COVID‐19 pandemic is paramount.
Even before the COVID‐19 pandemic, our knowledge of MHW's mental health had not been fully investigated, andavailable findings had often been contradictory. On one hand, some studies indicate that MHW typically report better
psychological adjustment than the general population, potentially because of their greater coping and regulation strategies
and professional knowledge on how to best activate and maintain these strategies. For instance, Elliot and Guy (1993) haveshown that, despite the fact that psychotherapists reported higher rates of trauma in childhood than did otherBRILLON ET AL.

|

3

professionals, they experienced less anxiety, depression, dissociation, sleep disturbance, and impairment in interpersonal
relationships than did participants from other professions. Even though their findings relied on small sample size (n = 56),
Koller and Hicks (2016) also reported that MHW displayed significantly higher scores on psychological well‐being, optimism, hope, and positive emotional coping strategies than general population workers. Norcross et al. (1986) showed thatpsychologists exhibited a larger repertoire of coping strategies to face psychological distress compared to laypersons.
Manning‐Jones et al. (2016) also showed that psychologists and counselors may have better coping attitudes than otherprofessionals (e.g., doctors and nurses) as they reported using more adaptive coping strategies (use of self‐care, supervision, and support). Finally, Norcross (2005) found that MHWs were more likely to seek psychotherapy than the general
population, which may provide them with the additional emotional and cognitive resources and support to deal withadversity when it arises. Additional studies found similar results in the context of acute stressful events. For example, Dekel
et al. (2007) investigated social workers' psychological adjustment after providing emergency treatment to victims ofterrorist attacks in Israel. Of importance, in this study, the social workers had also experienced the attacks themselves.
Their results indicated that social workers' distress was significantly lower than the general population on all measures, withthe exception of anxiety and phobia (Dekel et al., 2007).
On the other hand, several studies indicate that MHW are not invulnerable, as they may be susceptible toexperience severe symptoms of burnout, compassion fatigue, vicarious traumatization, and severe emotional exhaustion (Ben‐Zur & Michael, 2007; Cocker & Joss, 2016; Figley, 2002; Lloyd et al., 2002). Indeed, several studies
have identified unique stressors to the mental health professions and underlined how emotionally draining thisstudy can be (Bria et al., 2012; Rössler, 2012). MHW that are in constant contact with the emotional distressdisplayed by others can also be subject to increased risk of frustration, helplessness feelings, suicidal thoughts, andprofessional turnovers (Elwood et al., 2011; Ewer et al., 2015; Firth‐Cozens, 2007; Hannigan et al., 2004; Huggard
et al., 2017; Kleespies et al., 2011; Lee et al., 2019; Ramberg & Wasserman, 2000)
The challenges related to the current pandemic crisis in MHW's personal and professional lives, along with theadditional emotional labor associated with their work under the present conditions are hypothesized to affect
MHW's efficacy, judgment, and resilience at a time when these traits and abilities are needed most (Burns &Machin, 2013; Coster & Schwebel, 1997). It is, therefore, crucial to examine whether MHW experience more, less,or similar levels of psychological distress than the general population. In other words, we raise the following
question: Do MHW's professional skills, competencies, and experience play a role in protecting their mental healthfrom COVID‐19's known negative impacts? Or, on the contrary, does the current situation and its organizational
stressors exacerbate the risks of MHW's already emotionally demanding work?
To clarify this issue, the objective of the present study was to evaluate psychological distress among MHW
during the COVID‐19 pandemic. To do so, a sample of MHW was compared to a sample of workers drawn from thegeneral population on distress measures (i.e., anxiety and depressive symptoms, irritability, and loneliness) and on
resilience. Because greater differences may arise based on the severity of the sanitary measures imposed to control
the spread of the virus and on the level of chronic stress that ensue, we further examined whether regional zones
characterized by higher or lower incidence of COVID‐19 cases could account for potential differences in mental
health symptoms. At the time of data collection, the selected high‐incidence regions (Greater Montreal, Canada)
were characterized by the highest rate of COVID‐19 cases and deaths in the country, indoor and outdoor gatherings were completely prohibited, all nonessential businesses (including restaurants, bars, and gyms) were closed,
places of worship, schools and parks were also closed, and patients with COVID‐19 had to be transferred to otherregions to relieve some pressure on the health system. These measures were in stark contrast to those in low‐
incidence regions where less strict measures were implemented and for shorter periods. By the time of the study,
schools and businesses had reopened and they were allowed gatherings outdoors and eventually indoors. These
regions were clearly delimited.
Overall, MHW typically display better mental health than the general population, presumably because of their greater
coping capacities. At the same time, MHW in constant contact with the emotional distress of others might be more
vulnerable to compassion fatigue in times of stress. Given this mixed literature and the novelty of the current COVID‐19

4|

BRILLON ET AL.

crisis, we did not make specific hypotheses regarding which population would display greater distress and lower resources.
However, we expected individuals in high‐incidence regions to display greater symptoms and lower resources (lower
resilience, more loneliness) than those in low‐incidence regions (e.g., Lai et al., 2020).

2| M E TH O D| Participants

2.1

A total of 1274 workers completed an online survey (616 MHW vs. 658 workers from the general population) between
May 1st and July 20th 2020. Inclusion criteria for both MHW and other workers from the general population were to be
20 years old or more, to be currently working and to not have experienced temporary or permanent work stoppage due to
COVID‐19. Among MHW, 204 were psychologists (33.1%), 137 psychosocial counselors (22.2%), 74 social workers(12.0%), 55 clinical counselors (8.9%), and 146 (23.8%) were other types of mental health providers (e.g., psychiatrists, art
therapists, criminologists). Using participants' reported postal code, participants were classified according to their geographic locations as either living in an area of high or low incidence of COVID‐19 cases. At the start of the study on May
30th, 2020, there were 1227 COVID‐19 cases per 100,000 persons in the Greater Montreal (Montreal and Laval), 672
cases per 100,000 persons in regions surrounding Montréal and 224 cases per 100,000 persons in other Quebec regions(Institut National de Santé Publique du Québec, 2020). There were thus twice as many cases of COVID‐19 in GreaterMontreal than in the second most affected regions in the province and more than five times that of other regions.

| Procedure

2.2

Two different recruitment strategies were used in this study. First, workers from the general population wererecruited through social media advertisements (Facebook, Instagram). These workers were from various professions(e.g., managers, clerical workers, service, and sales). Only 7.58% of this sample from the general population reported
working as mental health professionals and they were removed from the sample. Second, MHW were recruited bycontacting various professional associations of MHW who shared our participation invitation to their members (e.g.,
Order of psychologists of Quebec, Order of social workers of Quebec, etc.). Included MHW consisted of psychologists, psychiatrists, therapists, counselors, and social workers.
A total of 62.1% of MHW reported that they now performed their clinical work through telehealth, whereas
37.9% were still seeing patients in person. This proportion of in‐person patients was significantly higher in the low‐
incidence regions (41.3%) than in the high‐incidence regions (30.3%), χ2(1) = 6.62; p = 0.01. However, even after
accounting for regions, there were no significant differences in mental health outcomes when comparing thoseworking via telehealth to those still providing face‐to‐face interventions, Also, there was no significant Teleworking
× Regions interaction for all outcomes. Therefore, this variable will not be further investigated. This project wasapproved by the research ethics board of the university and participants signed an informed consent form.

2.3
2.3.1

| Measures| Demographic information

Age, biological sex, education (graduate degree or not), marital status (single or in a romantic relationship), prior self‐
reported diagnosis of an emotional disorder (depression, anxiety, or any other emotional disorders that required
treatment), number of health‐related vulnerabilities to known complications of COVID‐19 (hypertension, cardiac

BRILLON ET AL.

|

5disease, immune disease, diabetes, obesity), and number of constraints experienced due to COVID‐19 confinement
and social distancing measures (presence of children at home due to school closure, salary reduction, cancellation ofimportant events like a marriage, medical appointments, travels reduction in health services, quarantine, interdictions to visit senior relatives) were collected.

2.3.2| Fear of COVID‐19 for the community

A short two‐item measure devised for the purpose of the present study assessed the participants' COVID‐19
related fear for their community. The items “I am afraid for the health of people in my community” and “I am afraid
for the lives of people in my community” were responded to by the participants on a Likert scale ranging from 1“Strongly disagree” to 7 “Strongly agree.” Both items were correlated at r = 0.86, p < 0.001. These items were used
to assess the level of apprehension that may vary in certain regions and helped to confirm that the low‐ and high‐incidence regions, as characterized by the official data on COVID‐19 cases, would be accompanied by differences inthe subjective experience of fear for communities' well‐being.

2.3.3| Depressive symptoms

Depressive symptoms were measured via the English and French versions of the Patient Health Questionnaire(PHQ‐9; Carballeira et al., 2007; Kroenke et al., 2001) which assesses symptoms of depression (as described in
DSM‐IV) in the past 2 weeks. Participants were asked to rate nine symptom items (e.g., feeling down, depressed, or
hopeless) on a Likert scale ranging from 0 = “Never” to 3 = “Almost every day”. The total score ranged from 0 to 27
with a cut‐off score of ≥10 for moderate or severe depression symptoms. The Cronbach's alpha for the PHQ‐9 inthis study was adequate (α = 0.86).

2.3.4| Anxiety symptoms

Anxiety symptoms were assessed via the English and French versions of the Generalized Anxiety Disorder 7 (GAD‐
7; Micoulaud‐Franchi et al., 2016; Spitzer et al., 2006), which is a brief self‐report measure assessing the presence
and severity of anxiety symptoms in the past 2 weeks. Participants rated seven symptom items (e.g., “Not being able
to stop or control worrying”) on a scale ranging from 0 to 3 (0 = “Not at all”, 1 = “Several days”, 2 = “Over half thedays,” and 3 = “Nearly every day”). The total score ranged from 0 to 21 with a cut‐off score of ≥10 for moderate orsevere anxiety disorder. The Cronbach's alpha for the GAD‐7 in this study was adequate (α = 0.90).

2.3.5| Irritability

Irritability symptoms were assessed via the English and French versions of the Brief Irritability Test (BITe; Holtzman
et al., 2015) which is a brief self‐report measure assessing the degree to which participants experienced frustrationand irritability in the last 2 weeks. Participants were presented with five items (e.g., “I have been grumpy” or “I havebeen feeling irritable”) rated on a six‐point Likert scale (1 = “Never”, 6 = “Always”). The BITe has been validated inboth healthy and patient samples and has demonstrated adequate evidence of validity and reliability (Holtzman
et al., 2015). The Cronbach's alpha for the BITe in this study was adequate (α = 0.92).

6

|

2.3.6

BRILLON ET AL.

| Loneliness

The three‐item English and French versions of the UCLA Loneliness Scale (de Grâce & Joshi, 1990; Hughes et al.,2004) were used to assess the frequency of loneliness. Participants rated each item on a three‐point scale ranging
from 1 “Almost Never” to 3 “Very often”. Higher scores for the three items (i.e., “How often have you felt a lack ofcompanionship”, “How often have you felt left out”, “How often have you felt isolated from others”) indicated amore frequent feeling of loneliness. The Cronbach's alpha for the UCLA Loneliness Scale in this study was adequate (α = 0.86).

2.3.7| Resilience

The English and French versions of the Connor–Davidson Resilience Scale (CD‐RISC; Connor & Davidson, 2003;
Hébert et al., 2018) is a brief, self‐rated measure of resilience. Participants were asked to indicate their degree ofagreement with each of the 10 items (e.g., “I can deal with whatever comes my way”, “I am not easily discouraged by
failure”, “I am able to handle unpleasant or painful feelings like sadness, fear, and anger”) on a scale ranging from 1
to 5. The Cronbach's alpha for the CD‐RISC in this study was excellent (α = 0.90).

2.4| Statistical analyses

Demographic variables were compared between MHW and workers from the general population using
analysis of variance or the χ2 test. A total of five 2 (Regions: High‐incidence vs. Low‐Incidence) × 2(Occupation: MHW vs. Other occupation) general linear models were conducted to test the presence of meandifferences in anxiety, depression, irritability, loneliness, and resilience. Anxiety, depression, and irritability
were log‐transformed to meet the assumption of normality of the general linear model given their positively
skewed distribution. A Bonferroni adjustment of the level of significance was used to account for multiple
testing (α = 0.05/5 tests = 0.01). Therefore, with two‐tailed testing, findings were considered statisticallysignificant at α = 0.01. Moreover, posthoc tests were corrected with a Bonferroni adjustment to account for
multiple comparisons and effect sizes for significant differences were estimated with Cohen's d (Cohen,1988). All analyses were performed in SPSS 27. The model was adjusted for age, biological sex, education,
marital status (single or in a romantic relationship), prior diagnosis of an emotional disorder (depression,anxiety, or other emotional disorders), number of physical vulnerabilities to COVID‐19, and number of important personal constraints experienced due to COVID‐19.
Moreover, to investigate whether results were sensitive to the date of completion, time of completion from thelaunch of the study (in days) was added as a covariate in separate analyses. Results were also analyzed with themonth of completion (May, June, or July) as between factors. We also investigated whether results would differ as afunction of population density instead of as a function of regions with a high or low incidence of COVID‐19 cases.

3
3.1| RESULTS| Sample characteristics

Table 1 presents the overall demographic characteristics of the sample, means, and standard deviations of eachmeasure of distress, including the prevalence of depression and anxiety across groups, as defined by the clinicalcutoff score on the PHQ‐9 and GAD‐7. Overall, participants in the study had a mean age of 42.06 years

BRILLON ET AL.

|

7(SD = 12.58; range = 20–74). Most were women (n = 1 136; 89.2%), in a relationship (n = 908; 71.3%), and 43.01%
had graduate‐level education (masters and doctorate; n = 548).
As shown in Table 1, several significant differences were found in the demographic variables among groups.
While there were no differences between workers or between regions in the number of constraints experienced
due to the pandemic, COVID‐related fear for the community was significantly greater for participants living in high‐incidence regions, t(1274) = −3.75, p < 0.001.
Results also showed that 23.0% (n = 293) of the total sample met the PHQ‐9 clinical cutoff for depression andthat approximately one in five (22.4%; n = 286) met the GAD‐7 clinical cut off for anxiety. Workers from the general
population were more likely than MHW to meet the clinical cutoff for depression (27.2% vs. 18.5%; χ2[1] = 13.59;
p < 0.001) and anxiety disorder (28.9% vs. 15.6%; χ2[1] = 32.28; p < 0.001). However, compared to workers whoreported living in a low‐incidence region, MHW living in high‐incidence regions had significantly higher prevalenceof clinically significant levels of depression (26.0% vs. 20.8%; χ2[1] = 4.75; p = 0.029) and anxiety (26.1% vs. 19.7%;
χ2[1] = 7.51; p = 0.006) symptoms.

3.2| Psychological distress as a function of occupation and region

Table 2 shows the results of the five 2 × 2 generalized linear models for mental health outcomes (depression,anxiety, irritability, loneliness, and resilience) across occupations (MHW vs. general population of workers) andregions (high‐incidence regions vs. low‐incidence regions) to test whether the differences in psychological distressbetween the MHW and workers from the general population varied according to regions more or less affected by
the pandemic in terms of the number of COVID‐19 cases. All analyses were adjusted for the control variables (i.e.,age, biological sex, education, marital status, prior diagnosis of emotional disorder, physical vulnerabilities to
COVID‐19, and number of constraints experienced due to COVID‐19). Figure 1 shows the plots of adjusted mean z‐scores for each mental health outcome by occupation and region.

3.2.1| Depressive symptoms

In terms of depressive symptoms, there were marginal main effects of occupations, but a significant interaction
between occupations regions. Posthoc tests with Bonferroni corrections revealed that MHW from high‐incidence
regions had more depressive symptoms than those working in low‐incidence regions t(614) = 3.30, p = 0.001,
d = 0.27. Other types of workers' depressive symptoms did not differ between regions, t(656) = 0.68, p = 0.49. Of
note, there was no significant difference in depressive symptoms between MHW and other workers in high‐incidence regions, t(545) = 0.20, p = 0.84, but in low‐incidence regions, MHW reported significantly less depressive
symptoms than other workers, t(725) = −4.16, p < 0.001, d = 0.31.

3.2.2| Anxiety symptoms

There was a main effect of occupation showing that MHW reported significantly lower anxiety symptoms
than other types of workers. However, this main effect was qualified by a significant Occupations × Regionsinteraction. Posthoc analyses revealed that MHW in high‐incidence regions reported significantly higher
anxiety symptoms than MHW in low‐incidence regions, t(614) = 2.72, p = 0.007, d = 0.22, whereas othertypes of workers did not differ by regions in their reported anxiety symptoms, t(656) = 1.68, p = 0.094. Again,
in high‐incidence regions, there was no significant difference in anxiety symptoms between MHW and other0.21 (0.51)

1.43 (1.22)

4.19 (1.55)

6.44 (5.06)

Physical vulnerabilities (0‐5)

Constraints due to COVID‐19(0‐7)

COVID‐related fear forcommunity (1‐7)

Depression (0‐27)

Irritability (1–6)

Moderate or severe (%/n)

Anxiety (0–21)

2.84 (1.09)

22.4 (286)6.10 (5.01)

23.0 (293)0.22 (0.52)

Prior emotional disorder (0‐3)

Moderate or severe (%/n)

43.01 (548)71.27 (908)

Graduate degree (%/n)

Education

In a relationship (%/n)

Marital status89.2 (1136)

42.06 (12.58)

2.86 (1.01)

15.6 (96)5.22 (4.46)

18.5 (114)

5.66 (4.73)

4.14 (1.50)

1.43 (1.21)

0.18 (0.49)

0.15 (0.43)

55.4 (341)76.5 (471)89.9 (554)40.84 (11.15)

2.82 (1.16)

28.9 (190)

6.92 (5.35)

27.2 (179)

7.18 (5.25)

4.23 (1.60)

1.43 (1.22)

0.23 (0.53)

0.29 (0.59)

31.5 (207)66.4 (437)88.4 (582)43.21 (13.70)

M (SD)

M (SD)

M (SD)

General population ofworkers (n = 658)

Occupation
Mental health
Total (n = 1274) workers (n = 616)

Sample characteristics and differences across occupation and region

Female (%/n)

SexAge (20–74)

TABLE 1

M (SD)

26.0 (142)6.50 (5.27)
26.1 (143)

0.000
0.000
0.000

2.87 (1.16)

6.90 (5.24)

0.000

0.481

4.37 (1.51)

1.38 (1.19)

0.349

0.980

0.20 (0.52)

0.24 (0.54)

0.000
0.099

48.6 (282)67.1 (367)87.6 (479)

0.000

0.000

0.394

0.001 41.40 (12.99)

pa

RegionHigh
incidence (n = 547)

2.82 (1.04)

19.7 (143)5.80 (4.79)

20.8 (151)

6.10 (4.90)

4.04 (1.56)

1.47 (1.23)

0.21 (0.51)

0.21 (0.51)

38.8 (266)74.4 (541)90.4 (657)42.57 (12.25)

M (SD)

Low
incidence (n = 727)

0.490

0.006

0.014

0.029

0.005

0.000

0.215

0.524

0.290

0.000

0.004

0.111

0.101

pa

8

|
BRILLON ET AL.

at or χ2.

Note: Bold values indicate significant results.

3.72 (0.69)

Resilience (1–5)

3.82 (0.62)

2.39 (0.91)
3.63 (0.74)

2.08 (0.70)

M (SD)

M (SD)

M (SD)

General population ofworkers (n = 658)

Occupation
Mental health
Total (n = 1274) workers (n = 616)

2.23 (0.82)(Continued)

Loneliness (1–4)

TABLE 1

2.19 (0.79)
3.67 (0.71)

0.000

M (SD)

0.000

pa

RegionHigh
incidence (n = 547)

3.76 (0.68)

2.26 (0.84)

M (SD)

Low
incidence (n = 727)

0.026

0.182

pa

BRILLON ET AL.

|
9

a

−0.306 (0.050)−0.053 (0.051)a0.408 (0.071)−0.093 (0.073)

LonelinessResilience

0.188 (0.047)

0.177 (0.045)

0.011 (0.047)−0.196 (0.045)

b

c

b

b

−0.182 (0.045)b

M (SE)

Low‐incidence regions
Mental healthworker (n = 431)

−0.150 (0.050)

a−0.138 (0.056)d0.008 (0.057)b0.188 (0.055)a0.122 (0.055)a

M (SE)

General population ofworkers(n = 296)

0.005 0.22

6.11*

0.005 2.53

–

–

–

.839 –

77.32***** 0.058 0.19

6.71*

RegionF
η20.005 4.00* .003

12.86***** 0.01

6.18*

Occupation
Fη2

Main and Interaction Effects

10.92***

13.07*****

7.18*

10.06***

8.73***

0.009

0.010

0.006

0.008

0.007

Occupation × RegionFη2*p < 0.05.; **p < 0.01.; ***p < 0.001.

Note: Age, sex, marital status, education, prior emotional disorder, physical vulnerabilities, and constraints due to COVID‐19 were controlled for in all models. Means with different
superscripts (a, b, c, d) differ significantly at p < 0.05 following a Bonferroni correction. All dependent variables were z‐scored.

b−0.117 (0.051)

a0.190 (0.073)

Irritabilityb0.064 (0.049)

a

a

a

0.030 (0.071)

0.072 (0.049)a

M (SE)M (SE)

0.089 (0.070)a

General population ofworkers(n = 362)

High‐incidence regions
Mental healthworkers (n = 185)

Adjusted mean z‐scores (with posthoc tests) and generalized linear models results for mental health outcomes as a function of occupation and region

Anxiety

Depression

TABLE 2

10|
BRILLON ET AL.

BRILLON ET AL.

|

11

F I G U R E 1 Graphical representation of the adjusted mean for psychological distress outcomes (z‐scores) by
Occupation and Region. Error bars are standard errors

workers, t(545) = 0.39, p = 0.70, but in low‐incidence regions, MHW reported significantly less anxiety
symptoms than the general population, t(727) = −5.33, p < 0.001, d = 0.40.

3.2.3| Irritability

Results revealed a main effect of occupations, such that MHW were significantly more irritable than the general
population workers. In addition, a significant Occupations × Regions interaction emerged. Posthoc analyses revealed that MHW in high‐incidence regions, reported significantly higher irritability than those in low‐incidence
regions, t(614) = 2.08, p = 0.037, d = 0.17. Other workers in high‐incidence regions did not differ from other workers
in low‐incidence regions, t(656) = 1.64, p = 0.10. Incidentally, in high‐incidence regions, MHW reported significantly
higher levels of irritability than the general population, t(545) = 3.42, p < 0.001, d = 0.29. In low‐incidence regions,
MHW and other workers did not differ significantly in their reported levels of irritability (p = 0.96).

3.2.4| Loneliness

There was a significant main effect of occupations, such that other types of workers reported significantly lower
loneliness than MHW. This main effect was qualified by a significant Occupations × Regions interaction. Posthoc
analyses revealed that MHW in high‐incidence regions reported significantly greater loneliness than MHW in low‐
incidence regions, t(614) = 2.78 p = 0.006, d = 0.22. Other workers in high‐incidence regions reported lower
loneliness than other workers in low‐incidence regions, t(656) = −2.27, p = 0.023, d = 0.18). Of note, both MHW in

12|

BRILLON ET AL.

high‐ and low‐incidence regions reported higher loneliness than other workers in their regions, t(545) = 8.11,
p < 0.001, d = 0.69 and t(725) = 4.30, p < 0.001, d = 0.32, respectively. However, the group difference in loneliness
was larger for MHW in high‐incidence regions than MHW in low‐incidence regions.

3.2.5| Resilience

Analyses showed a significant main effect of occupations, such that MHW were significantly more resilient thanother workers. In addition, a significant Occupations × Regions interaction emerged. Posthocs showed that MHW inhigh‐incidence regions showed lower scores of resilience than MHW from low‐incidence regions, t(614) = −3.26,
p < 0.001, d = 0.28). The general population workers from high‐incidence regions did not differ from the general
population workers in low‐incidence regions, in terms of their resilience scores, t(656) = 1.26, p = 0.21. MHW from
low‐incidence regions actually showed the highest score of resilience compared to all groups and reported significantly more resilience than other workers in low‐incidence regions, t(725) = 4.51, p < 0.001, d = 0.033). Finally, inhigh‐incidence regions, there was no significant difference between MHW workers and other workers in terms ofresilience scores (p = 0.66).

3.3| Sensitivity analyses

To test the robustness of the above‐reported findings, the analyses were conducted again using the date ofcompletion as covariate (in days) or as between factor (in months). All results remained unchanged with theinclusion of this variable in the analyses. Given that high‐incidence regions include densely populated cities and that
COVID‐19 cases are more likely to spread in densely populated areas, these two factors may be confounded. To
examine whether population density might account for the results, we reanalyzed the data from the low‐incidence
regions, which differed more importantly by population density, and examined whether occupation would interact
with population density in these low‐incidence regions. There were no interactions between occupation anddensity and occupation remained a significant predictor of the outcomes (except for irritability, which did not
significantly differ by occupation in the low‐incidence regions in the above analyses).

4| G E N E R A L D IS C U S S IO N

Studies have shown that the COVID‐19 pandemic has had a profound negative impact on the population withalarming implications for individual and collective mental health and social functioning (Alzueta et al., 2020;
Asmundson & Taylor, 2020; Dubey et al., 2020; Yao et al., 2020; Zhang et al., 2020). This study aimed to investigate
the psychosocial burden of MHW working during the COVID‐19 crisis (compared to the general population) and totest whether they were differently affected by the pandemic, depending on their geographic location (i.e., regionswith higher or lower incidence of COVID‐19 cases).
Some past research has shown that, in the absence of stressful events, MHW reported lower distress symptoms than the general population (Elliot & Guy, 1993; Koller & Hicks, 2016; Norcross et al., 1986). These findings
were replicated in the present study, as MHW reported overall significantly lower depressive and anxiety symptoms
than workers from the general population. This result was more pronounced in the low‐incidence regions, withMHW reporting significantly less distress and more resilience. However, results revealed that MHW living in high‐incidence regions reported levels of anxiety and depressive symptoms that were comparable to the levels of thegeneral population. Furthermore, when compared to MHW from low‐incidence regions, those in the high‐incidence
regions were significantly more anxious and depressed. The observation that in the context of the pandemic, MHW

BRILLON ET AL.

|

13from high‐incidence regions reported levels of distress that were equal or higher to those of the general populationsuggests that MHW might be more severely impacted by the crisis. Our results are also congruent with previous
studies that have shown how providing emotional help or being involved in the care of psychologically distressed
patients in a stressful context can place MHW at risk of developing distress of their own (Bria et al., 2012; Cocker &Joss, 2016; Elwood et al., 2011; Hannigan et al., 2004; Huggard et al., 2017; Lee et al., 2019).
One noteworthy finding was that, across all regions, MHW reported higher levels of loneliness than workers
from the general population did. This was especially true for MHW in the high‐incidence region group, whoreported the highest levels of loneliness among the four groups. This is worrisome considering that loneliness has
been shown to be detrimental to occupational well‐being (Soler‐Gonzalez et al., 2017). Moreover, levels of irritability were the highest among MHW in the high‐incidence region. This is consistent with previous work that has
highlighted a negative association between perceived social support and hostility, and a positive association between mental fatigue and anger (Tzeletopoulou et al., 2019) for MHW.
A source of concern is that MHW from high‐incidence regions (who theoretically should have the same
personal adaptive resources as MHW from low‐incidence regions) appear to be less effective at using theseresources, and present lower levels of resilience. Recent research has suggested that resilience may protect fromdepression and anxiety during the current COVID‐19 pandemic in both healthcare providers and in the general
population (Barzilay et al., 2020). While resilience is often pictured as a stable trait (Block & Kremen, 1996), it is infact a positive orientation toward life‐changing circumstances, and this orientation can change over time and can bealtered by prolonged stress (Connor & Davidson, 2003). Thus, while a resilient attitude can play a significant role incircumventing the negative effects of MHW's work‐related stress in intrinsically challenging environments when
coping is appropriate (Collins, 2007; Kinman & Grant, 2011), too much unregulated stress may also decrease
resilience over time. Therefore, MHW that face greater stress in regions with a high incidence of COVID‐19 cases
may be at risk of seeing their resilience decrease and their psychological distress increase. Future research isneeded, however, to better investigate this potential feedback loop between managed and unmanaged stress andresilience.
Overall and considering the several control variables used in the present study (i.e., age, biological sex, education, marital status, prior diagnosis of emotional disorder, physical vulnerabilities to COVID‐19, number of personal constraints experienced due to COVID‐19, and population density), we speculate that the differences
between MHW working in high‐ and low‐incidence regions could be explained by three possible factors. First,
MHW in high‐incidence regions could be more exposed to chronic professional stressors brought on by the
pandemic (e.g., more requests, more contact with patients who are more distressed and who present more serious
and complex problems, changing procedures, lack of control on the working process, organizational stressors, andless gratification and job satisfaction). In this context of chronic stress, multiple external demands to adapt to everexpanding needs, requests, restrictions, and changes at work may represent an additional burden to MHW in high‐incidence regions. The pandemic has called for great occupational reorganization from MHW, with novel andheavier tasks and sometimes unpredictable changes in the type of work requested from them in at‐risk areas.
Interestingly, although MHW in high‐incidence regions largely turned to telehealth for their clinical practice(consistent with Pierce et al., 2020; Piotrowski, 2021), this was not associated with differences in distress levels.
This finding is in line with recent studies (Békés et al., 2020; Probst et al., 2020). Future studies should investigate
whether the numerous changes and the accumulation of demands might have contributed to increased distress.
Second, it is also plausible that the MHW in high‐incidence regions may be surrounded by more stressed,
worried, and exhausted staff and professional networks, which diminishes the quantity and quality of social support
they receive. Social support has been shown to be particularly important in reducing distress and maximizing
resilience of humanitarian workers, first responders, and victims in times of adversity (Brewin et al., 2000; Eriksson
et al., 2009; Kaspersen et al., 2003; Prati & Pietrantoni, 2010). Therefore, it is possible that this poorer social
support (or lack thereof) may have contributed to exacerbating distress among MHWs in high‐incidence regions.

14|

BRILLON ET AL.

Finally, the third possible factor that may account for the differences between MHW from high and low‐
incidence is the fact that MHW find themselves in the highly unusual and complex situation of treating patients
who are experiencing many stressful aspects of the current social crisis that MHW are themselves experiencing intheir personal life. The current pandemic is unprecedented in scope with MHW facing the same reality andassociated challenges of quarantine, isolation, and social distancing as their patients. It has been previously hypothesized that when MHW and their patients share similar experiences on a personal level (e.g., divorce, child with
an illness, experiences of trauma (Bell & Robinson, 2013; DeGeorge & Constantino, 2012) or on a collective level(following natural disasters; Boulanger, 2013; Jaimes et al., 2019), it can cause a negative dynamic that affects theirefficacy, empathy, and increases risks of burnout, vicarious trauma, and compassion fatigue. However, there is very
little empirical evidence on the experience of MHW in shared contexts when facing a crisis. The present study is thefirst to our knowledge to unveil this reality within such a global context.
Moreover, MHW work in jobs that promote or even encourage contact with the plight of others, which is not
the case for most other jobs. Thus, MHW are not just surrounded by more stressed people, they must also support
and treat patients who are suffering more and who present more complex and treatment‐resistant problems(Brillon, 2020; Posluns & Gall, 2020).
Our results showed that MHW in high‐incidence regions exhibited more distress than their colleagues in low‐
incidence regions. Consequently, these results stress the importance of implementing measures specifically targeting MHW in high‐incidence regions to mitigate their anxiety and depressive symptoms, counter their lonelinessand irritability, and maximize their resilience. Indeed, similarly to several authors who have highlighted the importance of implementing prevention strategies for MHW (Aarons et al., 2012; Bloomquist et al., 2015; Brillon,
2020; Lynch et al., 2005; Surya et al., 2017), we recommend that specific measures be put in place, such as regularpeer‐support meetings, promotion of self‐care behaviors, activities fostering social support, as well as positive teambuilding activities in community organizations, mental health clinics, psychological units, and psychiatric hospitals inhigh‐incidence regions. Moreover, more than ever, an implementation of strategies, such as reducing MHW's workoverload, teaching them social support enhancement skills, offering free clinical supervision sessions, and increasing
their work's recognition and appreciation, is crucial (Morse et al., 2012). These measures have been proposed as
being effective in reducing the risks of distress, burnout, compassion fatigue, isolation, and sick leave among MHW
and humanitarian workers (Barnett et al., 2007; Bloomquist et al., 2015; Brooks et al., 2015; Comoretto et al., 2015;
Posluns & Gall, 2020) and can be leveraged as preventive measures in the face of future waves of COVID‐19 or in
the face of another social crisis of similar magnitude.

4.1| Future directions

Our study calls for a more in‐depth investigation of having to support and treat the mental health of the population
while working in a shared context, such as a global pandemic. There is a need for a better understanding of MHW's
emotional distress and the contexts in which this distress is more likely to emerge. Moreover, we need to better
identify personal and organization‐based strategies that could protect or exacerbate the vulnerability of MHW incase of another social crisis. As such, emotional regulation abilities, psychological flexibility, and coping strategies
have been stressed as significant protective factors against MHW's distress in past studies (Biron & Van Veldhoven,2012; Cengil, 2019; Collins, 2008; Pow & Cashwell, 2017; Rodriguez & Carlotto, 2017). We also know that low job
and salary satisfaction and the use of passive coping strategies predict greater emotional exhaustion among childprotection workers and in‐home caregivers (Jenaro et al., 2007). Moreover, past research has also shown thatpeople who present an integrative regulation style tend to accept and tolerate negative events or emotions without
feeling overwhelmed, disorganized, or defensive. These skills are linked to psychological well‐being and growthover time (Houle & Philippe, 2020), even throughout stressful collective events, such as natural disasters (Philippe &Houle, 2020). Other potential protective factors, such as self‐care practices, should also be empirically examined

BRILLON ET AL.

|

15(Barnett et al., 2007; Bloomquist et al., 2015; Bober et al., 2006; Posluns & Gall, 2020; Saakvitne & Pearlman, 1996).
Further research on these personal protective behaviors will help develop more effective and more specific prevention and treatment strategies for MHW in distress.

5| L IM I TAT I ONSThe findings of this study should be interpreted with the following limitations in mind. First, although we controlled
for several confounding variables (i.e., age, biological sex, education, marital status, prior diagnosis of emotional
disorder, physical vulnerabilities to COVID‐19, number of personal constraints due to the pandemic, and population
density), without prepandemic data, it is not possible to infer causal inferences and attribute the findings to the
COVID‐19 crisis. Indeed, as our study used a cross‐sectional design, we need to be cautious in interpreting regional
differences as we do not know whether these gaps are attributable to the pandemic or whether they existed before.
It remains possible that other noncontrolled confounds are at play and that the occupation or region factors only
acted as proxies for these confounds. Second, our sample from the general population was not a fully representative one and was potentially biased by the characteristics of social media users interested in participating in
psychological studies. The external validity of this general population should therefore be interpreted with caution.
Third, indicators of psychological distress were assessed using self‐report measures only. Individuals, even MHW,
can sometimes have limited self‐knowledge, and clinician‐administered assessments is a more objective way ofassessing symptoms of mental health (Donaldson & Grant‐Vallone, 2002; Paulhus & Vazire, 2007; Spector, 1994).
Fourth, self‐selection biases (nonresponders maybe not interested or too stressed to participate) could haveconstrained the generalization of our results. This limitation is exacerbated by the fact that it was impossible toassess the response rates due to the online nature of our survey.

6| C ONC LUS I ON

Altogether, our study showed preliminary evidence that MHW in areas particularly affected by COVID‐19 displayed similar or higher levels of psychological distress (greater depression, anxiety, irritability, and loneliness, andlower resilience) as the general population. Our study provides interesting leads in terms of clinical and social
implications. Considering that the COVID‐19 pandemic is accompanied by an onslaught of mental health needs inthe population, which many believe will last for years after the disease has subsided (Asmundson & Taylor, 2020), it
is crucial to address the specific psychological needs of the MHW who are responsible for providing health services
in the general population. This could help prevent the deleterious effects of future waves in the fight against
COVID‐19 or of similar collective stressful events.
CO NFL I CT OF INTERES T S
The authors declare that there are no conflict of interests.
D A TA A V A I L A B I L I T Y S T A T E M E N T
The data that support the findings of this study are available from the corresponding author upon reasonable
request.
PE ER RE VIEW S TATE MENTThe peer review history for this article is available at https://publons.com/publon/10.1002/jclp.23238

16|

BRILLON ET AL.

ORCID
Pascale Brillon

http://orcid.org/0000-0002-0175-095X

Frederick L. Philippe
Alison Paradis

http://orcid.org/0000-0001-6997-8072

http://orcid.org/0000-0001-9001-0058

Marie‐Claude Geoffroy
Massimiliano Orri

http://orcid.org/0000-0002-8587-8378

http://orcid.org/0000-0003-1389-2610

Isabelle Ouellet‐Morin

http://orcid.org/0000-0003-4591-3199

REFERENCES
Aafjes‐van Doorn, K., Békés, V., Prout, T. A., & Hoffman, L. (2020). Psychotherapists' vicarious traumatization during the
COVID‐19 pandemic. Psychological Trauma: Theory, Research, Practice, and Policy, 12(S1), S148–S150. https://doi.org/
10.1037/tra0000868
Aarons, G. A., Fettes, D. L., Sommerfeld, D. H., & Palinkas, L. A. (2012). Mixed methods for implementation research:
Application to evidence‐based practice implementation and staff turnover in community‐based organizations
providing child welfare services. Child maltreatment, 17(1), 67–79. https://doi.org/10.1177/1077559511426908
Abramson, A. (2020). How COVID‐19 may increase domestic violence and child abuse. http://www.apa.org/topics/covid-19/
domestic-violence-child-abuse
Alzueta, E., Perrin, P., Baker, F. C., Caffarra, S., Ramos‐Usuga, D., Yuksel, D., & Arango‐Lasprilla, J. C. (2020). How the
COVID‐19 pandemic has changed our lives: A study of psychological correlates across 59 countries. Journal of ClinicalPsychology, 77(3), 556–570. https://doi.org/10.1002/jclp.23082
Asmundson, G. J., & Taylor, S. (2020). How health anxiety influences responses to viral outbreaks like COVID‐19: What all
decision‐makers, health authorities, and health care professionals need to know. Journal of Anxiety Disorders, 71,
102211. https://doi.org/10.1016/j.janxdis.2020.102211
Banerjee, D., & Rai, M. (2020). Social isolation in Covid‐19: The impact of loneliness. International Journal of Social
Psychiatry, 66(6), 525–527. https://doi.org/10.1177/0020764020922269
Barnett, J. E., Baker, E. K., Elman, N. S., & Schoener, G. R. (2007). In pursuit of wellness: The self‐care imperative.
Professional Psychology: Research and Practice, 38(6), 603–612. https://doi.org/10.1037/0735-7028.38.6.603
Barzilay, R., Moore, T. M., Greenberg, D. M., DiDomenico, G. E., Brown, L. A., White, L. K., Gur, R. C., & Gur, R. E. (2020).
Resilience, COVID‐19‐related stress, anxiety and depression during the pandemic in a large population enriched for
healthcare providers. Translational Psychiatry, 10(1), 1–8. https://doi.org/10.1038/s41398-020-00982-4
Bell, C. H., & Robinson, III, E. H. (2013). Shared trauma in counseling: Information and implications for counselors. Journal of
Mental Health Counseling, 35(4), 310–323. https://doi.org/10.17744/mehc.35.4.7v33258020948502
Ben‐Zur, H., & Michael, K. (2007). Burnout, social support, and coping at work among social workers, psychologists, andnurses: The role of challenge/control appraisals. Social Work in Health Care, 45(4), 63–82. https://doi.org/10.1300/
j010v45n04_04
Berg‐Weger, M., & Morley, J. E. (2020). Loneliness and social isolation in older adults during the Covid‐19 pandemic:
Implications for gerontological social work. The Journal of Nutrition, Health & Aging, 24(5), 456–458. https://doi.org/
10.1007/s12603-020-1366-8
Biron, M., & Van Veldhoven, M. (2012). Emotional labour in service work: Psychological flexibility and emotion regulation.
Human Relations, 65(10), 1259–1282. https://doi.org/10.1177/0018726712447832
Block, J., & Kremen, A. M. (1996). IQ and ego‐resiliency: Conceptual and empirical connections and separateness. Journal of
Personality and Social Psychology, 70, 349–361. https://doi.org/10.1037/0022-3514.70.2.349
Bloomquist, K. R., Wood, L., Friedmeyer‐Trainor, K., & Kim, H. W. (2015). Self‐care and professional quality of life:
Predictive factors among MSW practitioners. Advances in Social Work, 16(2), 292–311. https://doi.org/10.18060/
18760
Bober, T., Regehr, C., & Zhou, Y. R. (2006). Development of the coping strategies inventory for trauma counselors. Journalof Loss and Trauma, 11(1), 71–83. https://doi.org/10.1080/153250-20500358225
Boulanger, G. (2013). Fearful symmetry: Shared trauma in New Orleans after Hurricane Katrina. Psychoanalytic Dialogues,
23(1), 31–44. https://doi.org/10.1080/10481885.2013.752700
Brewin, C. R., Bernice, A., & John, D. A. (2000). Meta‐analysis of risk factors for posttraumatic stress disorder among
trauma‐exposed adults. Journal of Consulting and Clinical Psychology, 68(5), 748–766. https://doi.org/10.1037/0022006x.68.5.748
Bria, M., Baban, A., & Dumitrascu, D. L. (2012). Systematic review of burnout risk factors among European healthcare
professionals. Cognition, Brain, Behavior: An Interdisciplinary Journal, 16(3), 423–452.

BRILLON ET AL.

|

17

Brillon, P. (2020). Entretenir ma vitalité d'aidant: Guide pour prévenir la fatigue de compassion et la détresse professionnelle(Maintaining our vitality as caregivers: A guide to preventing compassion fatigue and job distress). Editions de l'Homme.
Brooks, S. K., Dunn, R., Sage, C. A. M., Amlôt, R., Greenberg, N., & Rubin, G. J. (2015). Risk and resilience factors affecting
the psychological wellbeing of individuals deployed in humanitarian relief roles after a disaster. Journal of Mental
Health, 24(6), 385–413. https://doi.org/10.3109/09638237.2015.1057334
Burns, R. A., & Machin, M. A. (2013). Psychological wellbeing and the diathesis‐stress hypothesis model: The role ofpsychological functioning and quality of relations in promoting subjective well‐being in a life events study. Personality
and Individual Differences, 54(3), 321–326. https://doi.org/10.1016/j.paid.2012.09.017
Békés, V., Aafjes–van Doorn, K., Prout, T. A., & Hoffman, L. (2020). Stretching the analytic frame: Analytic therapists'
experiences with remote therapy during Covid‐19. Journal of the American Psychoanalytic Association, 68(3), 437–446.
Campbell, A. M. (2020). An increasing risk of family violence during the Covid‐19 pandemic: Strengthening community
collaborations to save lives. Forensic Science International: Reports, 2, 100089. https://doi.org/10.1016/j.fsir.2020.
100089Carballeira, Y., Dumont, P., Borgacci, S., Rentsch, D., de Tonnac, N., Archinard, M., & Andreoli, A. (2007). Criterion validity of
the French version of Patient Health Questionnaire (PHQ) in a hospital department of internal medicine. Psychology
and Psychotherapy: Theory, Research and Practice, 80(1), 69–77. https://doi.org/10.1348/147608306X103641
Cengil, A. C. (2019). Secondary traumatic stress among mental health workers in Turkey: Moderating role of emotion regulationon the relationship between empathy and secondary traumatic stress. [Master thesis, Istanbul University].
Clay, J. M., & Parker, M. O. (2020). Alcohol use and misuse during the COVID‐19 pandemic: a potential public health crisis?
The Lancet Public Health, 5(5):e259. https://doi.org/10.1016/S2468-2667(20)30088-8
Cocker, F., & Joss, N. (2016). Compassion fatigue among healthcare, emergency and community service workers: A
systematic review. International Journal of Environmental Research and Public Health, 13(6), 618. https://doi.org/10.
3390/ijerph13060618
Cohen, J.(1988). Statistical power analysis for the behavioral sciences (2nd ed.). : Lawrence Earlbaum Associates.
Collins, S. (2007). Social workers, resilience, positive emotions and optimism. Practice: Social Work in Action, 19(4), 255–269.
https://doi.org/10.1080/09503150701728186
Collins, S. (2008). Statutory social workers: Stress, job satisfaction, coping, social support and individual differences. British
Journal of Social Work, 38, 1173–1193. https://doi.org/10.1093/bjsw/bcm047
Comoretto, A., Crichton, N., & Albery, I. (2015). Resilience in humanitarian id workers: Understanding processes ofdevelopment. Transactions on Occupational Ergonomics and Human Factors, 3(3‐4), 197–209. https://doi.org/10.1080/
21577323.2015.1093565
Connor, K. M., & Davidson, J. R. T. (2003). Development of a new resilience scale: The Connor‐Davidson Resilience Scale(CD‐RISC). Depression and Anxiety, 18(2), 76–82. https://doi.org/10.1002/da.10113
Coster, J. S., & Schwebel, M. (1997). Well‐functioning in professional psychologists. Professional Psychology: Research andPractice, 28(1), 5–13. https://doi.org/10.1037/0735-7028.28.1.5
Da, B. L., Im, G. Y., & Schiano, T. D. (2020). Coronavirus disease hangover: A rising tide of alcohol use disorder and alcohol‐
associated liver disease. Hepatology, 72, 1102–1108. https://doi.org/10.1002/hep.31307
da Silva, F. C. T., & Neto, M. L. R. (2020). Psychological effects caused by the COVID‐19 pandemic in health professionals: A
systematic review with meta‐analysis. Progress in Neuro‐Psychopharmacology and Biological Psychiatry, 104, 110062.
https://doi.org/10.1016/j.pnpbp.2020.110062
DeGeorge, J., & Constantino, M. J. (2012). Perceptions of analogue therapist empathy as a function of salient experiencesimilarity. Journal of Psychotherapy Integration, 22(1), 52–59. https://doi.org/10.1037/a0027365
de Grâce, G., & Joshi, P. (1990). Adaptation Française de l’Échelle de Solitude UCLA Auprès des Personnes Agées. IVe
Congrès international francophone de gérontologie: Montréal.
Dekel, R., Hantman, S., Ginzburg, K., & Solomon, Z. (2007). The cost of caring? Social workers in hospitals confront ongoingterrorism. British Journal of Social Work, 37(7), 1247–1261. https://doi.org/10.1093/bjsw/bcl081
Donaldson, S. I., & Grant‐Vallone, E. J. (2002). Understanding self‐report bias in organizational behavior research. Journal ofBusiness and Psychology, 17(2), 245–260.
Dubey, S., Biswas, P., Ghosh, R., Chatterjee, S., Dubey, M. J., Chatterjee, S., Lahiri, D., & Lavie, C. J. (2020). Psychosocial
impact of COVID‐19. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(5), 779–788. https://doi.org/10.
26524/royal.37.15
Elliot, D. M., & Guy, J. D. (1993). Mental health professionals: Childhood trauma and adult functioning. Professional
Psychology: Research and Practice, 24(1), 83–90. https://doi.org/10.1037/0735-7028.24.1.83
Elwood, L. S., Mott, J., Lohr, J. M., & Galovski, T. E. (2011). Secondary trauma symptoms in clinicians: A critical review of theconstruct, specificity, and implications for trauma‐focused treatment. Clinical Psychology Review, 31(1), 25–36.
https://doi.org/10.1016/j.cpr.2010.09.004

18|

BRILLON ET AL.

Eriksson, C. B., Bjorck, J. P., Larson, L. C., Walling, S. M., Trice, G. A., Fawcett, J., Abernethy, A. D., & Foy, D. W. (2009).
Social support, organizational support, and religious support in relation to burnout in expatriate humanitarian aid
workers. Mental Health, Religion, et Culture, 12(7), 671–686. https://doi.org/10.1080/13674670903029146
Ewer, P. L., Teesson, M., Sannibale, C., Roche, A., & Mills, K. L. (2015). The prevalence and correlates of secondary traumaticstress among alcohol and other drug workers in Australia. Drug and Alcohol Review, 34(3), 252–258. https://doi.org/
10.1111/dar.12204
Figley, C. R. (2002). Treating compassion fatigue. Routledge.
Firth‐Cozens, J. (2007). Improving the health of psychiatrists. Advances in Psychiatric Treatment, 13(1), 161–168. https://doi.
org/10.1192/apt.bp.106.003277
Fitzpatrick, K. M., Harris, C., & Drawve, G. (2020). Fear of COVID‐19 and the mental health consequences in America.
Psychological Trauma: Theory, Research, Practice, 12(1), S17–S21. https://doi.org/10.1037/tra0000924
Grover, S., Mehra, A., Sahoo, S., Avasthi, A., Tripathi, A., D'Souza, A., Saha, G., Jagadhisha, A., Gowda, M., Vaishnav, M.,
Singh, O., Dalal, P. K., & Kumar, P. (2020). State of mental health services in various training centers in India during the
lockdown and COVID‐19 pandemic. Indian Journal of Psychiatry, 62(4), 363–369. https://doi.org/10.4103/psychiatry.
indianjpsychiatry_567_20
Hannigan, B., Edwards, D., & Burnard, P. (2004). Stress and stress management in clinical psychology: Findings from asystematic review. Journal of Mental Health, 13(3), 235–245. https://doi.org/10.1080/09638230410001700871
Holmes, E. A., O'Connor, R. C., Perry, V. H., Tracey, I., Wessely, S., Arseneault, L., Ballard, C., Christensen, H.,
Cohen Silver, R., Everall, I., Ford, T., John, A., Kabir, T., King, K., Madan, I., Michie, S., Przybylski, A. K., Shafran, R.,
Sweeney, A., … Bullmore, E. (2020). Multidisciplinary research priorities for the COVID‐19 pandemic: A call for action
for mental health science. The Lancet Psychiatry, 7, 547–560. https://doi.org/10.1016/S2215-0366(20)30168-1
Holtzman, S., O'Connor, B. P., Barata, P. C., & Stewart, D. E. (2015). The Brief Irritability Test (BITe) A measure of irritability
for use among men and women. Assessment, 22(1), 101–115. https://doi.org/10.1177/1073191114533814
Houle, I., & Philippe, F. L. (2020). Can the negative be positive? Or how emotion regulation and integration of negative
memories can positively affect well‐being. Journal of Personality, 88(5), 965–977. https://doi.org/10.1111/jopy.12544
Huggard, P., Law, J., & Newcombe, D. (2017). A systematic review exploring the presence of vicarious trauma, compassion
fatigue, and secondary traumatic stress in alcohol and other drug clinicians. Australian Journal of Disaster & Trauma
Studies, 21(2), 65–72.
Hughes, M. E., Waite, L. J., Hawkley, L. C., & Cacioppo, J. T. (2004). A short scale for measuring loneliness in large surveys:
Results from two population‐based studies. Research on Aging, 26(6), 655–672. https://doi.org/10.1177/
0164027504268574
Hébert, M., Parent, N., Simard, C., & Laverdière, A. (2018). Validation of the French Canadian version of the brief
Connor–Davidson Resilience Scale (CD‐RISC 10). Canadian Journal of Behavioural Science, 50(1), 9–16. https://doi.
org/10.1037/cbs0000092
Institut National de Santé Publique du Québec. (2020). Public Health Expertise and Reference center. https://www.inspq.
qc.ca
Jaimes, A., Hassan, G., & Rousseau, C. (2019). Hurtful gifts? Trauma and growth transmission among local clinicians inpostearthquake Haiti. Journal of Traumatic Stress, 32(2), 186–195. https://doi.org/10.1002/jts.22400
Jenaro, C., Flores, N., & Arias, B. (2007). Burnout and coping in human service practitioners. Professional Psychology:
Research and Practice, 38(1), 80–87. https://doi.org/10.1037/0735-7028.38.1.80
Kar, S. K., Arafat, S. Y., Kabir, R., Sharma, P., & Saxena, S. K. (2020). Coping with mental health challenges during COVID‐19,
Coronavirus disease 2019 (COVID‐19) (pp. 199–213). Springer. https://doi.org/10.1007/978-981-15-4814-7_16
Kaspersen, M., Matthiesen, S. B., & Gotestam, K. G. (2003). Social network as a moderator in the relation between trauma
exposure and trauma reaction: A survey among UN soldiers and relief workers. Scandinavian Journal of Psychology,
44(5), 415–423. https://doi.org/10.1046/j.1467-9450.2003.00362.x
Kinman, G., & Grant, L. (2011). Exploring stress resilience in trainee social workers: The role of emotional and social
competencies. British Journal of Social Work, 41(2), 261–275. https://doi.org/10.1093/bjsw/bcq088
Kleespies, P. M., Van Orden, K. A., Bongar, B., Bridgeman, D., Bufka, L. F., Galper, D. I., Hillbrand, M., & Yufit, R. I. (2011).
Psychologist suicide: Incidence, impact, and suggestions for prevention, intervention, and postvention. Professional
Psychology: Research and Practice, 42(3), 244–251. https://doi.org/10.1037/a0022805
Koller, S. L., & Hicks, R. E. (2016). Psychological capital qualities and psychological well‐being in Australian mental healthprofessionals. International Journal of Psychological Studies, 8(2), 41–53. https://doi.org/10.5539/ijps.v8n2p41
Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ‐9: Validity of a brief depression severity measure. Journal of
General Internal Medicine, 16(9), 606–613. https://doi.org/10.1046/j.1525-1497.2001.016009606.x
Laverdière, O., Kealy, D., Ogrodniczuk, J. S., & Morin, A. J. (2018). Psychological health profiles of Canadian
psychotherapists: A wake up call on psychotherapists’ mental health. Canadian Psychology/psychologie canadienne,
59(4), 315.

BRILLON ET AL.

|

19

Lai, J., Ma, S., Wang, Y., Cai, Z., Hu, J., Wei, N., Wu, J., Du, H., Chen, T., Li, R., Tan, H., Kang, L., Yao, L., Haung, M., Wang, H.,
Wang, G., Liu, Z., & Hu, S.(2020). Factors Associated With Mental Health Outcomes Among Health Care Workers
Exposed to Coronavirus Disease 2019. JAMA Netw Open, 3(3), e203976. https://doi.org/10.1001/jamanetworkopen.
2020.3976
Lebow, J. L. (2020). The challenges of COVID‐19 for divorcing and post‐divorce families. Family Process, 59(3), 967–973.
https://doi.org/10.1111/famp.12574
Lee, Y. R., Lee, J. Y., Kim, J. M., Shin, I. S., Yoon, J. S., & Kim, S. W. (2019). A comparative study of burnout, stress, andresilience among emotional workers. Psychiatry Investigation, 16(9), 686–694. https://doi.org/10.30773/pi.2019.
07.10
Li, W., Yang, Y., Liu, Z. H., Zhao, Y. J., Zhang, Q., Zhang, L., Cheung, T., & Xiang, Y. T. (2020). Progression of mental healthservices during the COVID‐19 outbreak in China. International Journal of Biological Sciences, 16(10), 1732–1738.
https://doi.org/10.7150/ijbs.45120
Lloyd, C., King, R., & Chenoweth, L. (2002). Social work, stress and burnout: A review. Journal of Mental Health, 11(3),
255–265. https://doi.org/10.1080/09638230020023642
Lynch, Jr., M. F., Plant, R. W., & Ryan, R. M. (2005). Psychological needs and threat to safety: Implications for staff andpatients in a psychiatric hospital for youth. Professional Psychology: Research and Practice, 36(4), 415–425. https://doi.
org/10.1037/0735-7028.36.4.415
Manning‐Jones, S., de Terte, I., & Stephens, C. (2016). Secondary traumatic stress, vicarious posttraumatic growth, andcoping among health professionals: A comparison study. New Zealand Journal of Psychology (Online), 45(1), 20–29.
Micoulaud‐Franchi, J. A., Lagarde, S., Barkate, G., Dufournet, B., Besancon, C., Trébuchon‐Da Fonseca, A., Gavaret, M.,
Bartolomei, F., Bonini, F., & McGonigal, A. (2016). Rapid detection of generalized anxiety disorder and major
depression in epilepsy: Validation of the GAD‐7 as a complementary tool to the NDDI‐E in a French sample. Epilepsy &Behavior, 57, 211–216. https://doi.org/10.1016/j.yebeh.2016.02.015
Morse, G., Salyers, M. P., Rollins, A. L., Monroe‐DeVita, M., & Pfahler, C. (2012). Burnout in mental health services: A reviewof the problem and its remediation. Administration and Policy in Mental Health and Mental Health Services Research,
39(5), 341–352. https://doi.org/10.1007/s10488-011-0352-1
Norcross, J. C. (2005). The psychotherapist's own psychotherapy: Educating and developing psychologists. American
Psychologist, 60, 840–850. https://doi.org/10.1037/0003-066x.60.8.840
Norcross, J. C., Prochaska, J. O., & Diclemente, C. C. (1986). Self‐change of psychological distress: Laypersons' vs.
psychologists' coping strategies. Journal of Clinical Psychology, 42(5), 834–840. https://doi.org/10.1002/10974679(198609)42:5<834::aid-jclp2270420527>3.0.co;2-aPappa, S., Ntella, V., Giannakas, T., Giannakoulis, V. G., Papoutsi, E., & Katsaounou, P. (2020). Prevalence of depression,anxiety, and insomnia among healthcare workers during the COVID‐19 pandemic: A systematic review and meta‐
analysis. Brain, Behavior, and Immunity, 88, 901–907. https://doi.org/10.1016/j.bbi.2020.05.026
Paulhus, D. L., & Vazire, S. (2007). The self‐report method. In R. W. Robins, R. C. Fraley, & R. F. Krueger (Eds.), Handbook of
research methods in personality psychology (pp. 224–239). Guilford Press.
Philippe, F. L., & Houle, I. (2020). Cognitive integration of personal or public events affects mental health: Examining
memory networks in a case of natural flooding disaster. Journal of Personality, 88(5), 861–873. https://doi.org/10.
1111/jopy.12531
Pierce, B. S., Perrin, P. B., Tyler, C. M., McKee, G. B., & Watson, J. D. (2020). The COVID‐19 telepsychology revolution: A
national study of pandemic‐based changes in US mental health care delivery. American Psychologist, 76(1), 14–25.
https://doi.org/10.1037/amp0000722
Piotrowski, C.(2021). COVID‐19: An exploratory bibliometric analysis of research indexed in PsycINFO. North American
Journal of Psychology, 23(1), 115–120.
Posluns, K., & Gall, T. L. (2020). Dear mental health practitioners, take care of yourselves: A literature review on self‐care.
International Journal for the Advancement of Counselling, 42(1), 1–20. https://doi.org/10.1007/s10447-019-09382-w
Pow, A. M., & Cashwell, C. S. (2017). Posttraumatic stress disorder and emotion‐focused coping among disaster mental
health counselors. Journal of Counseling & Development, 95(3), 322–331. https://doi.org/10.1002/jcad.12146
Prati, G., & Pietrantoni, L. (2010). The relation of perceived and received social support to mental health among first
responders: A meta‐analytic review. Journal of Community Psychology, 38, 403–417. https://doi.org/10.1002/jcop.
20371
Probst, T., Humer, E., Stippl, P., & Pieh, C. (2020). Being a psychotherapist in times of the novel coronavirus disease.
Frontiers in Psychology, 11, 559100. https://doi.org/10.3389/fpsyg.2020.559100
Rajkumar, R. P. (2020). COVID‐19 and mental health: A review of the existing literature. Asian Journal of Psychiatry, 52,
102066. https://doi.org/10.1016/j.ajp.2020.102066
Ramberg, I. L., & Wasserman, D. (2000). Prevalence of reported suicidal behavior in the general population and mental
health‐care staff. Psychological Medicine, 30(5), 1189–1196. https://doi.org/10.1017/s003329179900238x

20|

BRILLON ET AL.

Rodriguez, S. Y. S., & Carlotto, M. S. (2017). Predictors of burnout syndrome in psychologists. Estudos de Psicologia, 34(1),141–150. https://doi.org/10.1590/1982-02752017000100014
Rössler, W. (2012). Stress, burnout, and job dissatisfaction in mental health workers. European Archives of Psychiatry andClinical Neuroscience, 262(2), 65–69. https://doi.org/10.1007/s00406-012-0353-4
Saakvitne, K. W., & Pearlman, L. A. (1996). Transforming the pain: A workbook on vicarious traumatization. WW Norton & Co.
Salyers, M. P., Bonfils, K. A., Luther, L., Firmin, R. L., White, D. A., Adams, E. L., & Rollins, A. L.(2017). The relationshipbetween professional burnout and quality and safety in healthcare: A meta‐analysis. Journal of General Internal
Medicine, 32, 475–482. https://doi.org/10.1007/s11606-016-3886-9
Soler‐Gonzalez, J., San‐Martín, M., Delgado‐Bolton, R., & Vivanco, L. (2017). Human connections and their roles in theoccupational well‐being of healthcare professionals: A study on loneliness and empathy. Frontiers in Psychology, 8,1475. https://doi.org/10.3389/fpsyg.2017.01475
Spector, P. E. (1994). Using self‐report questionnaires in OB research: A comment on the use of a controversial method.
Journal of Organizational Behavior, 15(5), 385–392. https://doi.org/10.1002/job.4030150503
Spitzer, R. L., Kroenke, K., Williams, J. B., & Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: theGAD‐7. Archives of Internal Medicine, 166(10), 1092–1097. https://doi.org/10.1001/archinte.166.10.1092
Surya, M., Jaff, D., Stilwell, B., & Schubert, J. (2017). The importance of mental well‐being for health professionals during
complex emergencies: It is time we take it seriously. JHSP Journal, 5(2), 188–196. https://doi.org/10.9745/ghsp-d-1700017
Tzeletopoulou, A., Alikari, V., Krikelis, M. I., Zyga, S., Tsironi, M., Lavdaniti, M., & Theofilou, P. (2019). Fatigue and perceived
social support as predictive factors for aggressive behaviors among mental healthcare professionals. Archives ofHellenic Medicine, 36(6), 792–799.
World Health Organization. 2020. https://covid19.who.int/
Yao, H., Chen, J., & Xu, Y. (2020). Patients with mental health disorders in the COVID‐19 epidemic. The Lancet, 7(4):21.
https://doi.org/10.1016/S2215-0366(20)30090-0
Zhang, J., Lu, H., Zeng, H., Zhang, S., Du, Q., Jiang, T., & Du, B. (2020). The differential psychological distress of populations
affected by the COVID‐19 pandemic. Brain, Behavior, and Immunity, 87, 49–50. https://doi.org/10.1016/j.bbi.2020.
04.031

How to cite this article: Brillon, P., Philippe, F. L., Paradis, A., Geoffroy, M., Orri, M., & Ouellet‐Morin, I.
(2021). Psychological distress of mental health workers during the COVID‐19 pandemic: A comparison withthe general population in high‐ and low‐incidence regions. Journal of Clinical Psychology, 1–20.
https://doi.org/10.1002/jclp.23238