The different impacts of COVID-19 on the mental health of distinct health care worker categories

Abstract

The present study sought to explore the factors associated with the odds of having probable depression and posttraumatic stress disorder (PTSD) related to traumatic COVID-19 experiences and their impact on health care workers in distinct categories. In this cross-sectional study, 1843 health care workers (nurses, nurse technicians, physicians, physical therapists, and other healthcare workers) were recruited via convenience sampling. A survey was administered to obtain information regarding sociodemographic, occupational, and mental health status. Descriptive statistics and multivariable logistic regression were used for the analyses. Being a nurse technician was associated with an odds ratio of 1.76 for probable PTSD. No relation was observed between health care worker categories and the odds of probable depression. Additionally, being female and not receiving adequate PPE were related to greater odds of having probable PTSD and depression.

Keywords

COVID-19 depression health care workers mental health posttraumatic stress disorder

Introduction

Mass traumas mobilize a considerable part of a community, exerting a particularly destructive power in society. The development of mental disorders as a result of these events, in addition to generating intense suffering, leads to major social, economic, and public health impacts (Neria et al., 2008; Qiu et al., 2018; Thabet et al., 2008). Specifically, when COVID-19 was declared a pandemic by the World Health Organization on 20 March 2020, it raised this impact to unprecedented levels in recent world history (Dutheil et al., 2020). In Brazil, one of the most severely affected countries, the COVID-19 pandemic is considered a humanitarian catastrophe (Medicins Sans Frontieres, 2021). Despite the effort of health and research institutions, the lack of efficient leadership to face the epidemic and control virus transmission (The Lancet, 2020) has led to thousands of avoidable deaths (Werneck et al., 2021). The first COVID-19 wave in Brazil was between February and November 2020, with a peak in July 2020, and there were 162,269 deaths during this period (Alves, 2021). Brazil was considered the worst of 98 countries in managing the COVID-19 pandemic according to the COVID performance index (Lowy Institute, 2021).

Although the general population was at risk mentally and physically, front-line health care workers were at greater risk not only of contamination (Nguyen et al., 2020) but also of mental health disorders (Cotrin et al., 2020; Denning et al., 2021; Li et al., 2021; Pappa et al., 2020). For instance, among New York City health care workers, more than half of the sample screened were positive for acute stress, almost half for depression, and one third for anxiety (Shechter et al., 2020). Another study observed that front-line health care workers in Brazil and Spain had increased odds of anxiety or having both anxiety and depression when compared to those essential workers who were not on the front line in the battle against COVID-19 (De Boni et al., 2020). In addition, living in Brazil was associated with increased odds of depression and anxiety when compared to Spain.

Other factors, such as the increased workload, lack of personal protective equipment (PPE), training, and actual understanding of the disease, are common aggravating factors for these healthcare workers in direct contact with infected individuals (Cotrin et al., 2020; Shechter et al., 2020). Shechter et al. (2020) reported that perceived lack of control/uncertainty; treating other healthcare workers for COVID-19; uncertainty about colleagues’ COVID-19 status; unavailability of COVID-19 testing capabilities; limited PPE; and lack of treatment guidelines for patients were all sources of considerable distress. In Brazil, health units lacked treatment protocols, financial support, PPE, and, at the peak of the crisis, oxygen supplies (Biernath, 2021). However, contributing factors are not limited to the clinical environment; for example, in this same study, researchers found that three of every four health care workers were highly distressed by fears about transmitting COVID-19 to family or friends. Another important factor was the social isolation from family or friends that these professionals experienced (Pancani et al., 2021). In a recent study using a machine learning approach, the authors have found that the level of stress due to social isolation predicted the severity of posttraumatic stress and depression symptoms. Professional recognition was found to have a protective role (Portugal et al., 2022).

Sociodemographic factors also play a critical role in the fight against COVID-19. For example, approximately 70% of the health care workforce are women (Lotta et al., 2021a), which leaves them at an increased risk not only of infection but also other issues regarding their mental health, such as heightened levels of distress, anxiety, and depression. Similarly, the professional category can be considered a risk factor for the worsening of mental health. Studies comparing differences in burnout levels between nurses and physicians indicated that nurses have a higher risk of burnout (Chou et al., 2014; Seo et al., 2016; Tunc and Kutanis, 2009). Factors that might contribute to this scenario include the unpredictable nature of their work due to less decision-making power on the hierarchic professional status, excessive workload, and overtime (Chuang et al., 2016). Regarding the COVID-19 pandemic, recent data from Brazil’s health ministry have shown that some occupations are more vulnerable to COVID-19 infection. Nurse technicians are the most vulnerable (n = 42.380; 29.7%), followed by nurses (n = 24.077; 16.8%) and physicians (n = 15.327; 10.7%; Ministério da Saúde, 2021). Nurse technicians and nurses show more pandemic-related fear, have less self-perception of being professionally prepared, have less access to PPE and receive less mental health support than do physicians (Lotta et al., 2021b). In addition, nurse workers showed the highest rates of anxiety, depression, and stress during the pandemic (García-Iglesias et al., 2020; Maciaszek et al., 2020; Osório et al., 2021; Salazar de Pablo et al., 2020). For example, one study observed differences among physicians, nurses, and dentists in relation to anxiety, stress, and anger levels during the pandemic, with nurses and dentists feeling more anxious and nurses feeling angrier than individuals in the other categories (Cotrin et al., 2020). In a similar study, the authors reported high rates of insomnia, anxiety, depression, and posttraumatic stress symptoms for all health care workers, with the nursing staff presenting the highest rates among all of these professionals (Osório et al., 2021).

As mentioned before, many studies have reported high rates of anxiety, depression, and stress in health care workers around the globe (Cotrin et al., 2020; Denning et al., 2021; Li et al., 2021; Pappa et al., 2020; Shechter et al., 2020). Brazil has been one of the most affected countries in the world and is known for being a global epicenter for COVID-19 (Hallal and Victora, 2021). This critical situation calls for studies describing determinant factors that impact the mental health of front-line health care workers. Although some studies have reported factors associated with anxiety, depression, and posttraumatic stress disorder (PTSD) symptoms in health care workers in Brazil (Cotrin et al., 2020; Osório et al., 2021), no study has recorded the traumatic experiences related to the COVID-19 pandemic and evaluated the PTSD symptoms related to it.

To fill this gap, our group developed a survey to assess traumatic experiences related to the pandemic. Additionally, we investigated differences in mental health outcomes among physicians, nurses, nurse technicians, physical therapists, and other health care professionals. Since the first four categories have the closest contact with infected patients, especially in emergency rooms and intensive care units, we believed it was important to examine how their mental health was being affected by the COVID-19 pandemic.

In this way, the present study sought to explore determinant factors that might influence the odds of having probable depression and PTSD related to COVID-19 traumatic experiences among various categories of Brazilian health care workers. One of the main strengths of this study is that it assessed PTSD symptoms for traumatic events directly related to COVID-19.

Methods

Study design and participants

The present study is part of larger project with a longitudinal design that aims to investigate the effects of the pandemic on the mental health of professionals working in hospitals or emergency care units and acting directly or indirectly in the fight against COVID-19. The data reported here are cross-sectional and were collected in the first wave of the pandemic between June 2020 and September 2020.

Data were collected by a convenience snowball sampling technique from professionals working in different types of health care facilities in Brazil, including private and public institutions, in which COVID-19 patients were treated. The survey was sent by email, WhatsApp Messenger, and posted on social media. To increase visibility, a social media account and a web page were created for the project, and both contained a link to the online survey. Furthermore, associations of all major health worker groups and professional council boards in Brazil were contacted to publish an invitation to participate in the online survey on their websites and social media. Moreover, interviews in the Brazilian media about the study were conducted to invite people who worked in a hospital environment or emergency unit to participate.

In total, 1843 respondents accessed and completed the web survey. The inclusion criteria consisted of being a professional working in a hospital or an emergency unit (n = 1399). The exclusion criteria included individuals who had not experienced a traumatic event related to COVID-19 (n = 220), failed to fully complete the survey (n = 209), and were not health care workers (n = 29). A total of 125 participants who described having a previous diagnosis of mood disorders were also excluded. We made this exclusion to try to ensure that the symptoms of depression found in the present study were more associated with the pandemic period. For PTSD symptoms, it was not necessary because we evaluated symptoms directly associated with traumatic events of COVID-19 (see Figure 1). The final sample after exclusions consisted of 941 respondents.

Figure 1.

Flow diagram representing the steps to achieve the final sample.

The final sample consisted of physicians, nurses, physical therapists, nurse technicians, and other health care workers. Due to the low number of respondents in some professional categories, we grouped them into a group named “other health care workers,” comprising occupational therapists, radiology technicians, pharmaceutical technicians, health care technicians, surgical instrument technicians, clinical laboratory technicians, nutrition and dietetic technicians, dentists, psychologists, nutritionists, phonoaudiologists, pharmacists, health care students, biologists, social service workers, and elderly caregivers. The characteristics of the sample are available in Table 1.

Table 1.

Characteristics of the whole sample (n = 941).

	Median (IQR)or n (%)
Age	39 (32–48)
PTSD symptoms
<36	698 (74.2)
⩾36	243 (25.8)
Depression symptoms
<9	482 (51.2)
⩾9	459 (48.8)
Sex
Male	223 (23.7)
Female	718 (76.3)
Race
White	628 (66.7)
Nonwhite	313 (33.3)
Health care workers
Physicians	372 (39.5)
Nurses	175 (18.6)
Nurse technicians	132 (14.0)
Physical therapists	91 (9.7)
Other health care workers	171 (18.2)
PPE
Adequate	478 (50.8)
Inadequate	463 (49.2)
PPE divided by professional category
Physicians
Adequate	185 (49.7)
Inadequate	187 (50.3)
Nurses
Adequate	97 (55.4)
Inadequate	78 (44.6)
Nurse technicians
Adequate	54 (40.9)
Inadequate	78 (59.1)
Physical therapists
Adequate	49 (53.8)
Inadequate	42 (46.2)
Other health care workers
Adequate	93 (54.4)
Inadequate	78 (45.6)
Previous mental health disorder
No	670 (71.2)
Yes	271 (28.8)
Region
North	29 (3)
Northeast	110 (12)
Central-west	27 (3)
Southeast	698 (74)
South	77 (8)

PPE: personal protective equipment; IQR: interquartile range.

Assessment instruments

Sociodemographic and occupational questionnaire

A series of individual questions inquired about sex, age, ethnic group, previous mental health disorder, state of residence, professional category, and type of health institution (public, private, or both).

We also asked two questions about the availability of personal protective equipment (PPE) and perceived level of stress when they were not delivered properly.

The participants had to answer if, following the pandemic start, they had received PPE: (1) Sufficiently; (2) Variably, sometimes yes, sometimes no; or (3) Unsatisfactorily, there was always some PPE missing.

In this study, we divided the PPE factor into two levels: adequate, in which the participant received it sufficiently, and inadequate, where the participant received it variably or unsatisfactorily.

Traumatic experiences during the COVID-19 pandemic survey

This questionnaire comprises seven items that investigate traumatic situations experienced during the COVID-19 pandemic. The items are as follows: (1) personally witnessing the death of a patient due to COVID-19; (2) personally witnessing the death of a family member or coworker due to COVID-19; (3) learning, through others, about the death of a family member or a coworker due to COVID-19; (4) experiencing the imminent risk of death of a family member or coworker due to COVID-19; (5) being exposed to critically ill patients infected with COVID-19 whose lives were in danger; (6) being infected with COVID-19; and (7) believing or having confirmation that one may have transmitted the virus someone very close (coworker, partner, friend, or family). All these items are in accordance with DSM-5 criterion A (i.e. exposure to actual or threatened death, serious injury, or sexual violation) for the development of PTSD. Furthermore, after filling out the questionnaire, participants had to choose their worst experience among the items listed above (index trauma) and how long ago the event occurred (less or more than 1 month).

The content validity of our survey of traumatic experiences during the COVID-19 pandemic was examined qualitatively and relied on subjective judgments of PTSD experts’ (two psychiatrists and one psychologist), guided by DSM 5 criteria for PTSD diagnostics. No quantitative approach was used.

Posttraumatic Stress Disorder Checklist for DSM-5 (PCL-5)

The PCL-5 is a 20-item self-report questionnaire that assesses posttraumatic stress symptoms (Weathers et al., 2013). It measures the four symptom clusters of PTSD according to DSM-5: intrusion, avoidance, negative alterations in cognition and mood, and alterations in arousal and reactivity. The PCL-5 score ranges from 0 to 80 points, and each item is rated on a 5-point scale from 0 (not at all) to 4 (extremely). Symptom severity can be calculated by summing the items in each of the four clusters or summing all 20 items. Here, we used the cross-cultural adaptation for the Brazilian context proposed by Lima et al. (2016).

A dichotomous variable was created from the total score of each participant, with those scoring above or equal to the cutoff point of 36 being considered as probable PTSD. In this study, we use the term “probable PTSD” to refer to those with high PTSD symptoms. Regarding the choice of the cutoff point, a study from Pereira-Lima et al. (2019) demonstrated in a Brazilian sample that this cutoff point presented the highest diagnostic efficiency for predicting a SCID-5-CV diagnosis of PTSD.

The participants chose the worst event reported in the “Traumatic Experiences During COVID-19 Questionnaire” and indicated how each item of the PCL-5 bothered them in the last month.

The internal consistency of the total score assessed by Cronbach’s α was 0.947. Cronbach’s α for the theoretical dimensions of DSM-5 was also high (criterion B = 0.898; criterion C = 0.799; criterion D = 0.895; criterion E = 0.944).

The Patient Health Questionnaire (PHQ)-9

The Patient Health Questionnaire 9 (PHQ-9) is a 9-item self-report questionnaire that assesses symptoms of major depression (Kroenke et al., 2001). The nine items assessed in the questionnaire are depressed mood, anhedonia, problems with sleep, tiredness or lack of energy, change in appetite or weight, feelings of guilt or worthlessness, problems with concentration, feeling slow or restless, and thoughts of suicide. The PHQ-9 score ranges from 0 to 27 points, and each question is rated on a 4-point scale from 0 (not at all) to 3 (nearly every day). Here, we used the Brazilian–Portuguese version of the PHQ-9 (de Lima Osório et al., 2009).

A dichotomous variable was created from the total score of each participant, with those scoring above or equal to the cutoff point of 9 being considered probable depression. In this study, we use the term “probable depression” to refer to those with high depression symptoms. Regarding the choice of the cutoff point, a study from Santos et al. (2013) evaluated the Brazilian version of the PHQ-9 in adults along with the Mini International Neuropsychiatric Interview and identified ⩾9 as the cutoff point with the highest sensitivity and specificity for screening major depressive episodes.

Internal consistency assessed by the standardized Cronbach’s α was 0.902 for the sample used in the depression analyses (n = 816).

Statistical analyses

Descriptive statistics were performed for continuous (median and interquartile range) and categorical data (frequency; Table 1). To explore which sociodemographic and occupational factors would be related to probable PTSD (yes or no according to the cutoff point) and depression (yes or no according to the cutoff point), chi-square tests were performed for categorical data, and Wilcoxon rank-sum tests were performed for continuous data. The sociodemographic and occupational variables included age (in years), sex (male or female), race (white and nonwhite, i.e. all other races and ethnicities grouped together), professional category (physicians, nurses, nurse technicians, physical therapists, or other healthcare professions), a previous mental health disorder diagnosis (yes or no), and receipt of personal protective equipment (adequate or inadequate).

Those variables associated with the mental health outcomes (i.e. probable depression and PTSD) in the previous tests were later included in multivariable logistic regression models to estimate the odds ratio (OR) and 95% confidence intervals (95% CI). The dependent variables of the logistic regression models (probable depression and PTSD) were binary responses: probable outcome or not, according to the cutoff points mentioned in the questionnaires section. All the assumptions for the logistic models were met (e.g. independent predictors, no multicollinearity, linear relationship between the logit of the outcome and continuous predictors).

For the analyses with probable depression as the dependent variable, those reporting being diagnosed with any mood disorder (e.g. major depression, bipolar disorder) in the past were excluded (n = 125). The idea here was to investigate probable depression related to the COVID-19 pandemic.

No exclusions were made for the analyses with probable PTSD as the dependent variable since the symptoms were linked to traumatic experiences related to the COVID-19 pandemic.

All analyses were performed using RStudio version 1.4.1106 (RStudio Team, 2021). All tests were two-sided, and we considered a significance level of 0.05. The R package sjPlot (Lüdecke, 2018) was used to create the forest plot of odds ratios. Other packages used in the analyses were Tidyverse (Wickham et al., 2019), car (Fox and Weisberg, 2019),and psych (Revelle, 2022).

Results

Sample characteristics

Of the 941 health care workers enrolled (see Table 1 for sample characteristics), 718 (76.3%) were female and the median age was 39 years old (IQR = 32–48). Among the whole sample, 372 (39.5%) were physicians, 175 (18.6%) were nurses, 132 (14.0%) were nurse technicians, 91 (9.7%) were physical therapists, and 171 (18.2%) were other health care workers. The majority of the sample was from the southeast region (n = 698, 74%) and worked in a public institution (n = 490, 52.1%).

The prevalence of health care workers with probable PTSD (PCL-5 ⩾ 36) and depression (PHQ-9 ⩾ 9) was 25.8% (n = 243) and 48.8% (n = 459), respectively. Regarding PPE, only 50.8% (n = 478) reported receiving it adequately.

Bivariate analyses

Post-traumatic stress disorder analyses

Regarding the analyses of probable PTSD (Table 2), we observed a significant effect for age (Wilcoxon rank-sum test = 102, p < 0.001); those with probable PTSD were younger (median = 36) than those scoring below the cutoff point (median = 40). There was a relationship between sex and probable PTSD (X2 (1, n = 941) = 11.18, p < 0.001), with females having higher odds of PTSD. No relation was found for race and probable PTSD (X2 (1, n = 941) = 2.34, p = 0.126). We found a relationship between professional category and probable PTSD (X2 (4, n = 941) = 17.48, p = 0.001), with nurse technicians having a higher prevalence of probable PTSD (37.9%). For PPE, we found a significant relationship (X2 (1, n = 941) = 24.08, p < 0.001) between individuals receiving inadequate PPE and the likelihood of having PTSD. As expected, there was an association between having been previously diagnosed with a mental health disorder and probable PTSD (X2 (1, n = 941) = 32.24, p < 0.001).

Table 2.

Bivariate analyses for the PTSD symptoms sample (n = 941).

	PTSD		p-Value
	<36	⩾36	p-Value
Age (median, IQR)	40 (32–49)	36 (31–42.5)	<0.001
PHQ-9 (median, IQR)	6 (3–10)	17 (12–21)	<0.001
Sex (n, %)
Male	185 (83.0)	38 (17.0)	<0.001
Female	513 (71.4)	205 (28.6)	<0.001
Race (n, %)
White	476 (75.8)	152 (24.2)	0.126
Nonwhite	222 (70.9)	91 (29.1)	0.126
Health care workers (n, %)
Physicians	295 (79.3)	77 (20.7)	0.001
Nurses	128 (73.1)	47 (26.9)
Nurse technicians	82 (62.1)	50 (37.9)
Physical therapists	62 (68.1)	29 (31.9)
Other health care workers	131 (76.6)	40 (23.4)
PPE (n, %)
Adequate	388 (81.2)	90 (18.8)	<0.001
Inadequate	310 (67.0)	153 (33.0)	<0.001
Previous mental health disorder (n, %)
No	532 (79.4)	138 (20.6)	<0.001
Yes	166 (61.3)	105 (38.7)	<0.001

PTSD: posttraumatic stress disorder; PPE: personal protective equipment; IQR: interquartile range.

Depression analyses

There was a significant effect for age (Wilcoxon rank-sum test = 985, p < 0.001); individuals with probable depression were younger (median = 37) than those scoring below the cutoff point (median = 41). There was an association between sex and probable depression (X2 (1, n = 816) = 27.55, p < 0.001), with females being more likely to have a depression diagnosis. No association was found between race and probable depression (X2 (1, n = 816) = 0.126, p = 0.722). There was a relationship between profession category and probable depression (X2 (4, n = 816) = 12.83, p = 0.012), with nurse technicians having a higher prevalence of probable depression (56%). An association between PPE and depression was found (X2 (1, n = 816) = 11.69, p < 0.001), with those receiving inadequate PPE being more likely to have probable depression. Despite the exclusion of health care workers diagnosed with previous mood disorders, we found a relationship between having been previously diagnosed with other mental disorders and probable depression (X2 (1, n = 816) = 15.80, p < 0.001), with those reporting a mental health disorder diagnosis (others than mood disorders) being more likely to have probable depression (Table 3).

Table 3.

Bivariate analyses for depression symptoms sample (n = 816).

	Depression symptoms		p-Value
	<9	⩾9	p-Value
Age (median, IQR)	41 (33–50)	37 (31–44)	<0.001
PCL-5 (median, IQR)	13 (7–20.25)	34 (24–47)	<0.001
Sex (n, %)
Male	143 (71.1)	58 (28.9)	<0.001
Female	305 (49.6)	310 (50.4)	<0.001
Race (n, %)
White	301 (55.4)	242 (44.6)	0.722
Nonwhite	147 (53.8)	126 (46.2)	0.722
Health care workers (n, %)
Physicians	195 (60.9)	125 (39.1)	0.012
Nurses	80 (53.0)	71 (47.0)
Nurse technicians	51 (44.0)	65 (56.0)
Physical therapists	38 (46.9)	43 (53.1)
Other health care workers	84 (56.8)	64 (43.2)
PPE (n, %)
Adequate	251 (60.9)	161 (39.1)	<0.001
Inadequate	197 (48.8)	207 (51.2)	<0.001
Previous mental health disorder other than mood disorders (n, %)
No	390 (58.2)	280 (41.8)	<0.001
Yes	58 (39.7)	88 (60.3)	<0.001

PPE: personal protective equipment; IQR: interquartile range.

Logistic regression models

The multivariable logistic regression with PTSD (Table 4 and Figure 2) depicted that age was associated with an odds ratio of 0.97 (p < 0.001) for probable PTSD. Being a nurse technician was associated with an odds ratio of 1.76 (p = 0.017) for probable PTSD, considering physicians as the reference level. Being a female was also related to an odds ratio of 1.72 (p = 0.009) for probable PTSD. Receiving inadequate PPE was associated with an odds ratio of 2.39 (p < 0.001) for probable PTSD. Finally, being previously diagnosed with a mental health disorder was associated with an odds ratio of 2.61 (p < 0.001) for probable PTSD.

Table 4.

Multivariable logistic regression with probable PTSD (PCL-5 ⩾ 36) as the dependent variable (n = 941).

	Odds ratio	95% CI	p-Value
Age	0.97	0.95–0.98	<0.001
Health care workers
Physicians	Reference
Nurse technicians	1.76	1.11–2.80	0.017
Nurses	1.17	0.75–1.83	0.496
Physical therapists	1.56	0.90–2.69	0.109
Other healthcare workers	0.99	0.62–1.57	0.969
Sex
Male	Reference
Female	1.72	1.14–2.60	0.009
PPE
Adequate	Reference
Inadequate	2.39	1.74–3.28	<0.001
Previous mental health disorder
No	Reference
Yes	2.61	1.88–3.62	<0.001

PTSD: posttraumatic stress disorder; PPE: personal protective equipment.

Figure 2.

Forest plot depicting the odds ratios of the multivariable logistic regression with probable PTSD (PCL-5 ⩾ 36) as the dependent variable (n = 941).

The multivariable logistic regression with probable depression (Table 5 and Figure 3) depicted that age was associated with an odds ratio of 0.97 (p < 0.001) for probable depression. Being a female was also associated with an odds ratio of 2.38 (p < 0.001) for probable depression. Receiving inadequate PPE was associated with an odds ratio of 1.86 (p < 0.001) for probable depression. Finally, being previously diagnosed with a mental health disorder (but not a mood disorder) was associated with an odds ratio of 2.20 (p < 0.001) for probable depression. No professional category had a significant odds ratio for probable depression.

Table 5.

Multivariable logistic regression with probable depression (PHQ-9 ⩾ 9) as the dependent variable. (n = 16).

	Odds ratio	95% CI	p Value
Age	0.97	0.95–0.98	<0.001
Health care workers
Physicians	Reference
Nurse technicians	1.37	0.87–2.17	0.175
Nurses	1.02	0.67–1.55	0.922
Physical therapists	1.34	0.79–2.27	0.275
Other healthcare workers	0.91	0.59–1.39	0.658
Sex
Male	Reference
Female	2.38	1.66–3.43	<0.001
PPE
Adequate	Reference
Inadequate	1.86	1.39–2.50	<0.001
Previous mental health disorder other than mood disorders
No	Reference
Yes	2.21	1.50–3.25	<0.001

PPE: personal protective equipment.

Figure 3.

Forest plot depicting the odds ratios of the multivariable logistic regression with probable depression (PHQ-9 ⩾ 9) as the dependent variable (n = 816).

Discussion

The present study investigated how different factors were associated with the odds of probable PTSD and depression among front-line healthcare workers during the COVID-19 pandemic. Age, sex, PPE availability, and a previous mental health disorder diagnosis were consistent predictors of probable PTSD and depression. Importantly, nurse technicians seem to be at increased risk of scoring above the cutoff point for probable PTSD, even when controlling for other factors such as age, sex, PPE availability, and previous mental health disorder. For probable depression, there was no difference among the health care worker categories.

We observed a high prevalence of probable PTSD and depression, at 26% and 49%, respectively. Data were collected during the first months of the pandemic in Brazil, when there was a high level of uncertainty about the disease consequences and no available vaccines. Importantly, participants answered the PCL-5 anchored to traumas specifically related to the COVID-19 pandemic. A systematic review and meta-analysis revealed a PTSD rate of 21.5% and a depression rate of 31.1% among health care professionals after the beginning of the COVID-19 pandemic (Marvaldi et al., 2021). In another systematic review, the occurrence of PTSS among health care professionals ranged between 2.1% and 73.4% (d’Ettorre et al., 2021). In the context of the COVID-19 pandemic, the higher risk of contamination, the isolation from their families and the need to make critical care decisions could generate fear, guilt, and stress in levels above their capacity for healthy self-regulation and, therefore, enhance the risk of developing mental disorders.

As we observed in our study, nurse technicians seem to be at increased odds of having probable PTSD. Usually, hierarchically subordinate positions exhibit more odds of having PTSD symptoms (Luceño-Moreno et al., 2020). A recent review compared nurses versus medical doctors in terms of PTSD and depression, among other disorders. They found higher prevalence rates for nurses in both disorders. More specifically, 13 out of 18 studies revealed higher rates of PTSD for nurses. Only one study showed a higher rate of PTSD for medical doctors (Kunz et al., 2021). One possible explanation is that since sense of control is considered a protective factor associated with emotional regulation (Horn and Feder, 2018) and these work positions involve less control over decisions (Luceño-Moreno et al., 2020), they could be more vulnerable to work-related stress. They also receive fewer years of training than nurses and physicians. In addition, these findings could also be explained by the higher risk of contamination involved in the nature of the work performed by nurse technicians in Brazil. Commonly, their duty is to execute the mechanical work of nurses, which means close physical contact with patients, such as placement of peripheral venous catheters, drug administration according to physicians’ prescriptions, and blood collection for laboratory tests, among other tasks that require close and long-term contact (Araújo et al., 2020; Conselho Federal de Enfermagem, 2014). The close contact thus represents a higher actual and perceived risk of contamination for this category. Taking into consideration the time when the present data were collected (June–September 2020), there was not enough information about COVID-19, and the uncertainty added to the close contact with infected patients could be an explanation why nurse technicians are at increased distress. In addition, nurse technicians were the most prevalent professional category reporting inadequate PPE (59%, see Table 1). Furthermore, those receiving inadequate PPE were twice (OR = 2.39) as likely to have probable PTSD than those receiving adequate PPE. The lack of adequate PPE impacts the work and safety of health care workers, leaving them at increased risk of becoming infected by the virus. This can elevate their perception of contagion risk and enhance the risk of PTSD. Nguyen et al. (2020) reported that health care workers reusing or receiving inadequate PPE were at increased risk of reporting a positive test for COVID-19 when compared to health care workers receiving adequate PPE. Importantly, PPE predicted not only probable PTSD but also depression. Those receiving inadequate PPE were 1.86 times more likely to have probable depression as well.

Interestingly, there was no difference between health care worker categories regarding the risk for probable depression. Similar to our results, Palgi et al. (2009) observed that there were no differences between nurses and physicians regarding depressive symptoms but showed that nurses were at increased risk for PTSD when compared to physicians. The authors argue that it is possible that PTSD symptoms were connected to exposure to traumatic stress, but depressive symptoms were high due to prolonged stress and were relatively equivalent across all groups. Regarding the present study, nurse technicians are often at greater exposure to infected patients than physicians; however, the prolonged stress from the pandemic could equally affect mood regulation in all health care workers. Furthermore, as depression symptoms are high in our sample, any differences between professional categories may be difficult to observe due to a ceiling effect. In contrast, a recent study on the COVID-19 pandemic from Chatzittofis et al. (2021) observed that nurses were more likely than physicians to suffer from depression (adjusted prevalence ratio 1.7) and PTSD (adjusted prevalence ratio 2.51). However, it is important to consider that Cyprus (the country where the study was located) had a relatively limited impact from COVID-19 on the population and the health care system when compared to other countries (Chatzittofis et al., 2021).

Sex was also a contributing factor to increased odds of probable PTSD and depression, with females being 1.72 times more likely to have probable PTSD and 2.38 times more likely to suffer depression. These data are in accordance with other studies showing that being a woman is considered a risk factor for developing depression or PTSD (Luceño-Moreno et al., 2020). Females are more vulnerable to discrimination and stereotyping, especially in work settings (Baker, 2014; Ellemers, 2018; Heilman, 2012). In addition, marriage and family demands are higher in females than in males (Hamed et al., 2020), which can enhance stress levels.

Another factor associated with a higher risk of developing probable PTSD and depression was age. Those with probable depression and PTSD were younger than those scoring below the cutoff point. Other studies corroborate our findings (Luceño-Moreno et al., 2020). The demand increase generated by the pandemic resulted in a lack of healthcare staff, forcing young and inexperienced health professionals to deal with the difficult work demands in a context in which their own internal demands were high. In fact, the lack of well-trained and experienced professionals was a problem in health care units during the COVID-19 outbreak, especially in the ICU (Itodo et al., 2020).

Taken together, these findings corroborate the need to address issues that aim to protect health professionals from the psychological consequences of such a catastrophic context. In addition to their own suffering, psychological problems impair the quality of service (Tawfik et al., 2019), adding extra stress to patients. Interventions in the work environment (e.g. adequate provisioning of PPE), work position inequality, professional sense of self-confidence and self-emotional regulation might have the potential to make those professionals more prepared to cope with pandemic circumstances. Changes in the work environment should include more equality between work positions in terms of PPE offerings, in addition to valorization in terms of salary and appreciation, which could impact self-confidence. Psychological adaptation might arise from active listening by the organization and persistent psychological support.

The present work has some limitations. First, this is a retrospective study with a cross-sectional design, which limits inferences about causality and is prone to recall bias. The second limitation is that although only healthcare professionals working in hospitals or emergency care units were included in the study, there is no confirmatory question asking them if they were in direct contact with patients infected with COVID-19. Third, the present study has a selection bias toward location and sex. The majority of the sample comes from the southeast region (74%), and approximately 76% of the sample is female. However, in regard to sex, our data seem to be representative of the global trend, in which females are predominant in the health workforce (Lotta et al., 2021a). Race was also another limitation factor since most of the sample was white (66.7%). Last, we did not acquire enough participants in other health care professional categories, limiting the generalization of our results.

In conclusion, we observe that there are differences among health care workers when it comes to the odds of having probable PTSD after experiencing a traumatic event related to COVID-19, with nurse technicians being at increased risk. Moreover, our study corroborates the impact of some determinants described in the literature as being important to the development of mental health problems. Here we observe that being female, young, lack of adequate PPE, and a previous history of mental illness are factors related to greater odds of having probable PTSD and depression.

Research Data

sj-csv-4-hpq-10.1177_13591053221120968 – for The different impacts of COVID-19 on the mental health of distinct health care worker categories

sj-csv-4-hpq-10.1177_13591053221120968 for The different impacts of COVID-19 on the mental health of distinct health care worker categories by Arthur Viana Machado, Raquel Menezes Gonçalves, Camila Monteiro Fabricio Gama, Liliane Maria Pereira Vilete, William Berger, Roberta Benitez Freitas Passos, Mauro Vito Mendlowicz, Gabriela Guerra Leal Souza, Mirtes Garcia Pereira, Izabela Mocaiber and Leticia de Oliveira in Journal of Health Psychology

This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).

Research Data

sj-html-3-hpq-10.1177_13591053221120968 – for The different impacts of COVID-19 on the mental health of distinct health care worker categories

sj-html-3-hpq-10.1177_13591053221120968 for The different impacts of COVID-19 on the mental health of distinct health care worker categories by Arthur Viana Machado, Raquel Menezes Gonçalves, Camila Monteiro Fabricio Gama, Liliane Maria Pereira Vilete, William Berger, Roberta Benitez Freitas Passos, Mauro Vito Mendlowicz, Gabriela Guerra Leal Souza, Mirtes Garcia Pereira, Izabela Mocaiber and Leticia de Oliveira in Journal of Health Psychology

Research Data

sj-pdf-1-hpq-10.1177_13591053221120968 – for The different impacts of COVID-19 on the mental health of distinct health care worker categories

sj-pdf-1-hpq-10.1177_13591053221120968 for The different impacts of COVID-19 on the mental health of distinct health care worker categories by Arthur Viana Machado, Raquel Menezes Gonçalves, Camila Monteiro Fabricio Gama, Liliane Maria Pereira Vilete, William Berger, Roberta Benitez Freitas Passos, Mauro Vito Mendlowicz, Gabriela Guerra Leal Souza, Mirtes Garcia Pereira, Izabela Mocaiber and Leticia de Oliveira in Journal of Health Psychology

Research Data

sj-r-5-hpq-10.1177_13591053221120968 – for The different impacts of COVID-19 on the mental health of distinct health care worker categories

sj-r-5-hpq-10.1177_13591053221120968 for The different impacts of COVID-19 on the mental health of distinct health care worker categories by Arthur Viana Machado, Raquel Menezes Gonçalves, Camila Monteiro Fabricio Gama, Liliane Maria Pereira Vilete, William Berger, Roberta Benitez Freitas Passos, Mauro Vito Mendlowicz, Gabriela Guerra Leal Souza, Mirtes Garcia Pereira, Izabela Mocaiber and Leticia de Oliveira in Journal of Health Psychology

Research Data

sj-rmd-2-hpq-10.1177_13591053221120968 – for The different impacts of COVID-19 on the mental health of distinct health care worker categories

sj-rmd-2-hpq-10.1177_13591053221120968 for The different impacts of COVID-19 on the mental health of distinct health care worker categories by Arthur Viana Machado, Raquel Menezes Gonçalves, Camila Monteiro Fabricio Gama, Liliane Maria Pereira Vilete, William Berger, Roberta Benitez Freitas Passos, Mauro Vito Mendlowicz, Gabriela Guerra Leal Souza, Mirtes Garcia Pereira, Izabela Mocaiber and Leticia de Oliveira in Journal of Health Psychology

Footnotes

Data sharing statement

The current article is accompanied by the relevant raw data generated during and/or analysed during the study, including files detailing the analyses and either the complete database or other relevant raw data. These files are available in the Figshare repository and accessible as Supplemental Material via the SAGE Journals platform. Ethics approval, participant permissions, and all other relevant approvals were granted for this data sharing.

Declaration of conflicting interests

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

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported in part by federal and state Brazilian research agencies Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES 001, CAPES/PRINT, Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ).

Ethics approval

The present work was approved by the Ethics Research Committee of Universidade Federal Fluminense (UFF) under the number CAAE 31044420.9.0000.5243.

Informed consent

All participants signed an online informed consent form to participate in the study.

ORCID iD

Arthur Viana Machado

References

Alves

JED

(2021) Diário da Covid-19: Após um ano de pandemia, Brasil registra mais de uma morte por minuto. Projeto Colabora. Available at: https://projetocolabora.com.br/ods3/um-ano-de-pandemia-e-mais-de-uma-morte-por-minuto/ (acessed 8 March 2022).

Araújo

Medeiros

Costa

, et al (2020) Analysis of the guiding rules of the nurse technician’s practice in Brazil. Revista Brasileira de Enfermagem 73(3): e20180322.

Baker

(2014) Stereotyping and women’s roles in leadership positions. Industrial and Commercial Training 46(6): 332–337.

Biernath

(2021) “Pandemia no Brasil foi diferente do resto do mundo”, diz diretora de Médicos Sem Fronteiras. Available at: https://www.bbc.com/portuguese/brasil-56937229 (acessed 8 March 2022).

Chatzittofis

Karanikola

Michailidou

, et al (2021) Impact of the COVID-19 pandemic on the mental health of healthcare workers. International Journal of Environmental Research and Public Health 18(4): 1435.

Chou

(2014) Job stress and burnout in hospital employees: Comparisons of different medical professions in a regional hospital in Taiwan. BMJ Open 4(2): e004185.

Chuang

C-H

Tseng

P-C

Lin

C-Y

, et al (2016) Burnout in the intensive care unit professionals. Medicine 95(50): e5629.

Conselho Federal de Enfermagem (2014) Parecer de câmara técnica No 07/2014/CTLN/COFEN. COFEN. Available at: http://www.cofen.gov.br/parecer-n-072014cofenctln_50330.html (acessed 8 March 2022).

Cotrin

Moura

Gambardela-Tkacz

, et al (2020) Healthcare workers in Brazil during the COVID-19 pandemic: A cross-sectional online survey. INQUIRY: The Journal of Health Care Organization, Provision, and Financing 57: 1–11.

10.

De Boni

Balanzá-Martínez

Mota

, et al (2020) Depression, anxiety, and lifestyle among essential workers: A web survey from Brazil and Spain during the COVID-19 pandemic. Journal of Medical Internet Research 22(10): e22835.

11.

de Lima Osório

Vilela Mendes

Crippa

, et al (2009) Study of the discriminative validity of the PHQ-9 and PHQ-2 in a sample of Brazilian women in the context of primary health care. Perspectives in Psychiatric Care 45(3): 216–227.

12.

Denning

Goh

Tan

, et al (2021) Determinants of burnout and other aspects of psychological well-being in healthcare workers during the Covid-19 pandemic: A multinational cross-sectional study. PLoS One 16(4): e0238666.

13.

d’Ettorre

Ceccarelli

Santinelli

, et al (2021) Post-traumatic stress symptoms in healthcare workers dealing with the COVID-19 pandemic: A systematic review. International Journal of Environmental Research and Public Health 18(2): 601.

14.

Dutheil

Mondillon

Navel

(2020) PTSD as the second tsunami of the SARS-Cov-2 pandemic. Psychological Medicine 51(10): 1773–1774.

15.

Ellemers

(2018) Gender stereotypes. Annual Review of Psychology 69: 275–298.

16.

Fox

Weisberg

(2019) An R Companion to Applied Regression. Thousand Oaks, CA: SAGE.

17.

García-Iglesias

Gómez-Salgado

Martín-Pereira

, et al (2020) Impact of SARS-CoV-2 (Covid-19) on the mental health of healthcare professionals: A systematic review. Revista Española de Salud Pública 94: e202007088.

18.

Hallal

Victora

(2021) Overcoming Brazil’s monumental COVID-19 failure: An urgent call to action. Nature Medicine 27(6): 933.

19.

Hamed

Abd Elaziz

Ahmed

(2020) Prevalence and predictors of burnout syndrome, post-traumatic stress disorder, depression, and anxiety in nursing staff in various departments. Middle East Current Psychiatry 27(1): 36.

20.

Heilman

(2012) Gender stereotypes and workplace bias. Research in Organizational Behavior 32: 113–135

21.

Horn

Feder

(2018) Understanding resilience and preventing and treating PTSD. Harvard Review of Psychiatry 26(3): 158–174.

22.

Itodo

Enitan

Oyekale

, et al (2020) COVID-19 among healthcare workers: Risk of exposure, impacts and biosafety measures – A review. International Journal of Health, Safety and Environment 6(4): 534–548.

23.

Kroenke

Spitzer

Williams

JBW

(2001) The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine 16(9): 606–613.

24.

Kunz

Strasser

Hasan

(2021) Impact of the coronavirus disease 2019 pandemic on healthcare workers: Systematic comparison between nurses and medical doctors. Current Opinion in Psychiatry 34(4): 413–419.

25.

Scherer

Felix

, et al (2021) Prevalence of depression, anxiety and post-traumatic stress disorder in health care workers during the COVID-19 pandemic: A systematic review and meta-analysis. PLoS One 16(3): e0246454.

26.

Lima

Vasconcelos

Berger

, et al (2016) Cross-cultural adaptation of the posttraumatic stress disorder checklist 5 (PCL-5) and life events checklist 5 (LEC-5) for the Brazilian context. Trends in Psychiatry and Psychotherapy 38(4): 207–15.

27.

Lotta

Fernandez

Pimenta

, et al (2021a) Gender, race, and health workers in the COVID-19 pandemic. The Lancet 397(10281): 1264.

28.

Lotta

Fernandez

Rocha

, et al (2021b) Nota técnica: A pandemia de covid-19 e os(as) profisionais de saúde pública no Brasil - 5º fase. Available at: https://neburocracia.files.wordpress.com/2021/10/rel12-saude-covid-19-fase5-v3.pdf (accessed 8 March 2022).

29.

Lowy Institute (2021) Covid performance index. 2021. Available at: https://interactives.lowyinstitute.org/features/covid-performance/ (acessed 8 March 2022).

30.

Luceño-Moreno

Talavera-Velasco

, et al (2020) Symptoms of posttraumatic stress, anxiety, depression, levels of resilience and burnout in spanish health personnel during the COVID-19 pandemic. International Journal of Environmental Research and Public Health 17(15): E5514.

31.

Lüdecke

(2018) sjPlot: Data visualization for statistics in social science. Available at: https://CRAN.R-project.org/package=sjPlot (acessed 7 April 2022).

32.

Maciaszek

Ciulkowicz

Misiak

, et al (2020) Mental health of medical and non-medical professionals during the peak of the COVID-19 pandemic: A cross-sectional nationwide study. Journal of Clinical Medicine 9(8): 2527.

33.

Marvaldi

Mallet

Dubertret

, et al (2021) Anxiety, depression, trauma-related, and sleep disorders among healthcare workers during the COVID-19 pandemic: A systematic review and meta-analysis. Neuroscience & Biobehavioral Reviews 126: 252–264.

34.

Medicins Sans Frontieres (2021) Falhas na resposta à COVID-19 levam Brasil a catástrofe humanitária. Available at: https://www.msf.org.br/noticias/falhas-na-resposta-covid-19-levam-brasil-catastrofe-humanitaria (acessed 8 March 2022).

35.

Ministério da Saúde (2021) Boletim epidemiológico especial 78 - Doença pelo novo coronavírus – COVID-19. Available at: https://www.gov.br/saude/pt-br/media/pdf/2021/setembro/14/boletim_epidemiologico_covid_78-1.pdf (acessed 8 March 2022).

36.

Neria

Nandi

Galea

(2008) Post-traumatic stress disorder following disasters: A systematic review. Psychological Medicine 38(4): 467–480.

37.

Nguyen

Drew

Graham

, et al (2020) Risk of COVID-19 among front-line health-care workers and the general community: A prospective cohort study. The Lancet Public Health 5(9): e475–e483.

38.

Osório

Silveira

ILM

Pereira-Lima

, et al (2021) Risk and protective factors for the mental health of Brazilian healthcare workers in the frontline of COVID-19 pandemic. Frontiers in Psychiatry 12: 662742.

39.

Palgi

Ben-Ezra

Langer

, et al (2009) The effect of prolonged exposure to war stress on the comorbidity of PTSD and depression among hospital personnel. Psychiatry Research 168(3): 262–264.

40.

Pancani

Marinucci

Aureli

, et al (2021) Forced social isolation and mental health: A study on 1,006 Italians under COVID-19 lockdown. Frontiers in Psychology 12: 663799.

41.

Pappa

Ntella

Giannakas

, et al (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.

42.

Pereira-Lima

Loureiro

Bolsoni

, et al (2019) Psychometric properties and diagnostic utility of a Brazilian version of the PCL-5 (complete and abbreviated versions). European Journal of Psychotraumatology 10(1): 1581020.

43.

Portugal

LCL

Gama

CMF

Gonçalves

, et al (2022) Vulnerability and protective factors for PTSD and depression symptoms among healthcare workers during COVID-19: A machine learning approach. Frontiers in Psychiatry 12: 752870.

44.

Qiu

Chu

Mao

, et al (2018) The impacts on health, society, and economy of SARS and H7N9 outbreaks in China: A case comparison study. Journal of Environmental and Public Health 2018: 2710185.

45.

Revelle

(2022) psych: Procedures for Psychological, Psychometric, and Personality Research. Evanston, IL: Northwestern University. Available at: https://CRAN.R-project.org/package=psych (acessed 7 April 2022).

46.

RStudio Team (2021) RStudio: Integrated development environment for R. Rstudio. Available at: http://www.rstudio.com/ (acessed 7 April 2022).

47.

Salazar de Pablo

Vaquerizo-Serrano

Catalan

, et al (2020) Impact of coronavirus syndromes on physical and mental health of health care workers: Systematic review and meta-analysis. Journal of Affective Disorders 275: 48–57.

48.

Santos

Tavares

Munhoz

, et al (2013) Sensibilidade e especificidade do Patient Health Questionnaire-9 (PHQ-9) entre adultos da população geral. Cadernos de Saúde Pública 29(8): 1533–1543.

49.

Seo

Kim

Hwang

, et al (2016) Predictors of job satisfaction and burnout among tuberculosis management nurses and physicians. Epidemiology and Health 38: e2016008.

50.

Shechter

Diaz

Moise

, et al (2020) Psychological distress, coping behaviors, and preferences for support among New York healthcare workers during the COVID-19 pandemic. General Hospital Psychiatry 66: 1–8.

51.

Tawfik

Scheid

Profit

, et al (2019) Evidence relating health care provider burnout and quality of care. Annals of Internal Medicine 171(8): 555–567.

52.

Thabet

Abu Tawahina

El Sarraj

Vostanis

(2008) Exposure to war trauma and PTSD among parents and children in the Gaza strip. European Child & Adolescent Psychiatry 17(4): 191–199.

53.

The Lancet (2020) COVID-19 in Brazil: “So what?” The Lancet 395(10235): 1461.

54.

Tunc

Kutanis

(2009) Role conflict, role ambiguity, and burnout in nurses and physicians at a university hospital in Turkey. Nursing & Health Sciences 11(4): 410–416.

55.

Weathers

Litz

Keane

, et al (2013) The PTSD checklist for DSM-5 (PCL-5). National Center for PTSD. Available at: www.ptsd.va.gov (accessed 8 March 2022).

56.

Werneck

Bahia

Moreira

JPL

, et al (2021) Mortes evitáveis por COVID-19 no Brasil. Available at: https://idec.org.br/sites/default/files/mortes_evitaveis_por_covid-19_no_brasil_para_internet_1.pdf (acessed 8 March 2022).

57.

Wickham

Averick

Bryan

, et al (2019) Welcome to the tidyverse. Journal of Open Source Software 4(43): 1686.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.21 MB

1.19 MB

0.03 MB

0.01 MB

0.02 MB