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. 2021 Jan 25;30(3):724–732. doi: 10.1111/inm.12841

The repercussions of perceived threat from COVID‐19 on the mental health of actively employed nurses

José Jesús Gázquez Linares 1, María del Mar Molero Jurado 2, África Martos Martínez 2, Diana Jiménez‐Rodríguez 3, María del Carmen Pérez‐Fuentes 2,✉
PMCID: PMC8014181  PMID: 33491869

Abstract

In the confrontation with the COVID‐19 pandemic, threat perceived by the nursing population, and its association with sociodemographic and contextual characteristics, must be measured and evaluated as well as their repercussions on their mental health. Therefore, the purpose of this study was to analyse the repercussion of perceived threat from COVID‐19 on the mental health of actively employed nurses, considering a COVID‐19 diagnosis, whether their own or of someone close to them. The sample was comprised of 351 nurses. Sociodemographic data were collected, and the Questionnaire on Perception of Threat from COVID‐19 and the General Health Questionnaire were administered. The three demographic and contextual variables mentioned were related to mental health, mediated in some symptoms by perceived threat. These results provide important information for implementing measures or psychoeducational programs for nurses, essential in the present pandemic for improving psychological adaptation and reducing the effects on their mental health.

Keywords: COVID‐19, mental health, nurses, perceived threat, repercussion

INTRODUCTION

The pandemic caused by the SARS CoV‐2 coronavirus (COVID‐19) originated in Wuhan (China) at the end of 2019 (Huang et al. 2020; WHO, 2020; Zhu et al. 2020). Its powerful transmission and high infection rate have led to rapid worldwide growth in the number of cases (Lotfi et al. 2020), posing a severe public health problem (Wang et al. 2020) and challenging overloaded (Hong et al. 2020) healthcare systems (Nagesh, 2020). The scenario in which healthcare professionals have had to practice their profession has been very demanding (Lima et al. 2020), faced with lack of material resources such as personal protection equipment, beds available in the ICU, mechanical ventilators (Cacchione, 2020; del Rio & Malani, 2020; Saglietto et al. 2020), and an increasing number of infected healthcare workers, with their consequent sick leave. All of this, along with the high influx of patients, has caused healthcare employees to have to work at high risk of contagion with the worldwide outbreak of COVID‐19 (Nagesh, 2020).

In this critical situation, performing healthcare services has been enormously challenged (Jiang et al. 2020) by complicated decisions and work under extreme pressure (Greenberg et al. 2020). Firstline healthcare professionals, along with the patients, are the most vulnerable to the emotional impact of the pandemic (Braquehais et al. 2020; Lima et al. 2020; Xiang et al. 2020). This was also found in other epidemics such as the SARS in 2003 and Ebola in 2014 (Kisely et al. 2020; Maunder et al. 2003). In the current context, recovery, emotion regulation, and psychological adjustment (Castellano et al. 2019; Lai et al. 2020; Pérez‐Fuentes et al. 2019) are of great concern for the mental health of healthcare professionals (El‐Hage et al. 2020; León et al. 2020; Rodríguez‐Leor et al., 2020). Along this line, studies such as the one by Tirado et al. (2019) have underlined that overexertion by healthcare professionals is accompanied by an increase in their health complaints, especially if they feel excessively compromised by the work.

The impact of COVID‐19 on the well‐being of healthcare professionals is of additional concern, because their work is fundamental to both prevention and care of infected patients (Choi et al. 2020). This discomfort can be derived from the disease itself, uncertainty, confinement, and the perception of threat (Molero et al. 2020a; Pérez‐Fuentes et al. 2020; Rodríguez‐Leor et al. 2020). Previous studies have reported increased stress, anxiety, depression, and psychological distress during the pandemic (Duan & Zhu, 2020; Molero et al. 2020b).

However, before any intervention for healthcare workers or contribution to improvement in their mental health during the current COVID‐19 pandemic can be proposed, the risk and protection factors for their psychological well‐being must be known (Kisely et al. 2020; Soriano et al. 2019). Perceived threat is an important variable, because previous studies have shown that perceived threat from COVID‐19 can generate severe psychological maladjustment (Lai et al. 2020; Pérez‐Fuentes et al. 2020).

The Common Sense Model of Self‐Regulation (CSM) explains the processes by which people perceive threat to their health, derived perceptions, their corresponding affective responses, and how they cope with that threat (Leventhal et al. 2016). Thus, the perception of threat depends on the interpretation of experience and individual action, which influences one’s psychological state (Pérez‐Fuentes et al. 2020). Perceived threat is, therefore, a key component in individual response (Barr et al. 2008). Previous studies have analysed perception of threat and its relationship with mental health (Duan & Zhu, 2020; Pérez‐Fuentes et al. 2020). Perception of high risk of illness, which could have very negative consequences, in particular, has been associated with the presence of hypochondriac, peritraumatic distress, depression, and anxiety symptoms (Arnáez et al. 2019; Pakenham et al. 2020). In view of the above, the first hypothesis posed in this study was that there is a relationship between perceived threat and the presence of mental health symptoms (H1).

Another factor related to perceived threat, as in previous pandemics (Barr et al. 2008; De Zwart et al. 2007), is gender, as women seem to perceive a greater threat from the virus (Molero et al. 2020a). Other studies have not found this variable to be relevant in the perception of threat from COVID‐19 (Mertens et al., 2020). Aksoy and Hoҫak (2020) showed that among nurses, women perceive more danger from COVID‐19 than men. So it is important to know whether fear of the virus affects men and women differently and to what extent, to be able to propose and implement effective action based on its effects on individuals (Wenham et al. 2020). Rodríguez‐Rey et al. (2020) also suggested a greater need for attention to those individuals who perceive themselves to be vulnerable. Perceived risk to loved ones and anxiety about one’s own health has been linked to an increase in fear and threat from COVID‐19 (Mertens et al. 2020) as well. This leads to another of our hypotheses, that female professionals who have themselves been diagnosed as COVID‐19 positive or someone personally close to them has, will perceive stronger threat from the virus (H2). Studies, such as the one by Pakenham et al. (2020), have suggested that even though there are certain sociodemographic and contextual variables, such as being a woman, having been diagnosed with COVID‐19 oneself or having an infected family member, that affect one’s psychological health, other individual factors also affect that relationship. Therefore, our third hypothesis was that perceived threat is a mediating variable in the relationship between a positive diagnosis of COVID‐19 (the worker or someone close) and the manifestation of psychological symptoms (H3).

The purpose of this study was to analyse the repercussion of perceived threat from COVID‐19 on the mental health of actively employed nurses, considering the presence of a COVID‐19 positive diagnosis or someone personally close diagnosed as positive. All this, understanding the importance of the threat perceived in the psychological regulation and well‐being of health professionals, and its decisive role in the fight against the current pandemic.

Figure 1 shows the hypothesized mediation model.

Fig. 1.

Fig. 1

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Hypothesized mediation model.

METHOD

Participants

Originally, a total of 505 nurses agreed to fill out the questionnaire. After review, 154 questionnaires had to be discarded because 148 were unfinished and six had incoherent answers to the control questions inserted at random throughout the questionnaire.

Thus, the study sample was made up of a total of 351 nurses aged 22 to 64, with a mean age of 40.91 (SD = 10.98), all of them residents of Spain. Of the total sample, 86% (n = 302) were women, with a mean age of 40.81 (SD = 11.16) years, and 41.49 (SD = 9.88) for men. The marital status of the sample was 61.3% (n = 215) married or with a common‐law partner, 32.5% (n = 114) single, 5.1% (n = 18) separated or divorced, and 1.1% (n = 4) widowed.

COVID‐19 had been diagnosed in 9.1% (n = 32) of the participants (90.6% women and 9.4% men), and all were asked whether anyone close to them had been diagnosed as positive, which was the case for 62.7% (n = 220) (85.9% women and 14.1% men).

Instruments

An ad hoc questionnaire collected the sample sociodemographic data, including sex, age, and marital status. They were also asked if they had ever been diagnosed with COVID‐19 and whether anyone close to them had been.

The Questionnaire on Perception of Threat from COVID‐19 (Pérez‐Fuentes et al. 2020) was applied to evaluate perceived threat and worry about COVID‐19 in the adult Spanish population. It consists of five items (e.g. How much is the disease affecting your life?), which are answered on a 10‐point Likert‐type scale, providing a single dimension: perceived threat from the disease, where higher scores show greater perceived threat. In this study, the instrument showed a reliability of ω = 0.69; GLB = 0.74.

The General Health Questionnaire (GHQ‐28; Goldberg & Hillier, 1979; Spanish adaptation validated by Lobo et al. 1986) was used as a measure of mental health. It has 28 items with four answer choices. Likert‐type scoring was used, rating each answer choice from 0 to 3. In addition to a total score on general mental health, the questionnaire provides information on subscales: somatic symptoms (e.g. Have you felt exhausted and unable to do anything?), anxiety and insomnia (e.g. Have you had trouble staying asleep all night long?), social dysfunction (e.g. Have you been able to enjoy your normal day‐to‐day activities?), and depression (e.g. Have you felt that life is not worth living?). The instrument’s reliability in this study was ω = 0.92 and GLB = 0.95 for the complete scale, and the following on each of the subscales: somatic symptoms (ω = 0.87; GLB = 0.91), anxiety and insomnia (ω = 0.89; GLB = 0.94), social dysfunction (ω = 0.75; GLB = 0.82), and depression (ω = 0.88; GLB = 0.93).

Procedure

A CAWI survey (Computer Aided Web Interviewing) was used for data collection. Participation was voluntary. Information on the study and its purpose was presented on the first page, before the questionnaire itself. The participants gave their informed consent by marking a box designed for the purpose, which then gave them access to the questionnaire. They were asked to answer sincerely and the anonymity of their answers was guaranteed. Random or incongruent answers were detected with control questions included throughout the questionnaire. This study was approved by the University of Almeria Research Ethics Committee (Ref. UALBIO2020/032).

Data analysis

Reliability of the instruments used for data collection was estimated using the McDonald’s Omega, following Ventura‐León and Caycho (2017). The Greatest Lower Bound (GLB) was also calculated.

Descriptive and correlational (Pearson’s) analyses were performed. For between‐group comparisons (sex, COVID‐19 positive diagnosis and someone close positive) of perceived threat from the disease, an independent samples t‐test was applied and the effect size was determined with Cohen’s d (1988): <0.50 small, 0.50–0.80 medium, and ≥0.80 large effect.

The Bayesian alternative was also computed to estimate evidence in favour of the hypotheses using the Bayes Factor.

Then mediation analyses were performed with a predictor for each model (COVID‐19 positive diagnosis, personally close positives), perceived threat from COVID‐19 as the mediator, and as result variables, the GHQ‐28 dimensions: somatic symptoms, anxiety/insomnia, social dysfunction, and depression. JASP ver. 0.11.1 (2019), based on lavaan software (Rosseel, 2012), was used. To test the indirect effects, bias‐corrected percentile bootstrap confidence intervals were calculated following Biesanz et al. (2010).

RESULTS

Perceived threat from COVID‐19 and mental health of nurses

First, the sociodemographic characteristics were examined. No correlation was found between perceived threat and participant age (r = 0.02, P = 0.658). However, statistically significant differences were found by sex (t (349) = 2.28, P < 0.05, d = 0.35), where women had a higher mean score (M = 33.26, SD = 6.28) than men (M = 31.06, SD = 5.93). To test the weight of the evidence available in favour of the alternative hypothesis (H1) of between‐group differences compared to the null hypothesis (H0), the Bayes Factor was calculated (BF 10 = 1.863), revealing evidence 1.86 times higher in favour of H1 over H0. The marital status variable was dichotomized for group comparison into partner (married or common‐law partner) and no partner (single, separated/divorced or widowed). No significant between‐group differences were found (I (349) = 0.40, P = 0.683).

When perceived threat was compared by positive diagnosis or someone close diagnosed positive, statistically significant differences were found (Table 1). Both nurses who were COVID‐19 positive (Figure 2a), and those who said someone close to them was positive (Figure 2b), perceived the most threat from COVID‐19. In this case, the Bayes Factor revealed very strong evidence in favour of H1, COVID‐19 positive, over H0 (BF10 = 98.888), and strong for a positive diagnosis in someone close (B10 = 27.722).

TABLE 1.

Perceived threat and presence of COVID‐19 positive. Student's t‐test

Have you been diagnosed as COVID‐19 positive?
No Yes
N M SD N M SD
319 32.56 6.10 32 36.81 6.71
t (349) = −3.71, p < 0.001, d = −0.68
Has anyone close to you been diagnosed as COVID‐19 positive?
131 31.50 7.06 220 33.81 5.59
t (349) = −3.38, P < 0.001, d = −0.37
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Fig. 2.

Fig. 2

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(a) Perceived threat and personal COVID‐19 diagnosis. (b) Perceived threat and someone close diagnosed with COVID‐19.

In addition, the correlation analysis (Table 2) showed a positive relationship between perceived threat and mental health problems, represented by the four GHQ‐28 dimensions. Thus, high perceived threat from COVID‐19 was related to high scores in somatic symptoms, anxiety/insomnia, social dysfunction, and depression.

TABLE 2.

Perceived threat and health. Pearson’s correlation pairs and descriptive statistics

BIP‐Q GHQ‐28 Pearson's r Lower 95% CI Upper 95% CI Mean Stand. Dev.
Perceived Threat M = 32.95, SD = 6.27 Somatic symptoms 0.532*** 0.453 0.603 9.64 4.82
Anxiety/ insomnia 0.541*** 0.463 0.611 10.61 5.00
Social dysfunction 0.286*** 0.186 0.379 8.02 3.20
Depression 0.245*** 0.144 0.341 2.21 3.42
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***

P < 0.001.

COVID‐19, Mental health and the mediating effect of perceived threat

A diagnosis of COVID‐19 positive, as shown in Table 3, had a direct effect on two of the four health dimensions analysed, somatic symptoms, and social dysfunction.

TABLE 3.

COVID‐19 positive diagnosis and mental health. Direct, indirect, and total effects

Estimate Std. Error z‐value P 95% CI
Lower Upper
Direct effects
graphic file with name INM-30-724-g001.jpg
GHQ‐SS 0.482 0.158 3.054 0.002 0.130 0.838
GHQ‐AI 0.065 0.159 0.411 0.681 −0.273 0.346
GHQ‐SD 0.485 0.179 2.710 0.007 0.070 0.948
GHQ‐D −0.053 0.183 −0.291 0.771 −0.353 0.347
Indirect effects
graphic file with name INM-30-724-g001.jpg
PTCOVID‐19 → GHQ‐SS 0.342 0.097 3.535 <0.001 0.135 0.557
PTCOVID‐19 GHQ‐AI 0.364 0.102 3.554 <0.001 0.155 0.601
PTCOVID‐19 → GHQ‐SD 0.175 0.058 2.990 0.003 0.066 0.341
PTCOVID‐19 → GHQ‐D 0.168 0.058 2.923 0.003 0.068 0.322
Total effects
graphic file with name INM-30-724-g001.jpg
GHQ‐SS 0.824 0.180 4.580 <0.001 0.432 1.232
GHQ‐AI 0.429 0.184 2.335 0.020 0.003 0.823
GHQ‐SD 0.660 0.182 3.632 <0.001 0.253 1.120
GHQ‐D 0.115 0.185 0.621 0.534 −0.223 0.595
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Inline graphic, COVID‐19 positive; GHQ‐AI, Anxiety / insomnia; GHQ‐D, Depression; GHQ‐SD, Social dysfunction; GHQ‐SS, Somatic symptoms; PTCOVID‐19, Perceived Threat COVID‐19. [Note. Delta method standard errors, bias‐corrected percentile bootstrap confidence intervals].

The indirect effects, on the other hand, showed that perceived threat from COVID‐19 mediated in the relationship between a positive diagnosis and mental health indicators, significant in all cases.

The total effects of the model showed significance for a COVID‐19 diagnosis on somatic symptoms, anxiety/insomnia, and social dysfunction. Explained variance of endogenous variables included in the mediation model was: 30.2% (R 2 = 0.302) for somatic symptoms, 29.3% (R 2 = 0.293) for anxiety/insomnia, 10% (R 2 = 0.100) for social dysfunction, 6% (R 2 = 0.060) for depression, and 3.4% (R 2 = 0.038) with perceived threat as a mediator.

As observed in Table 4, someone close with COVID‐19 as the predictor variable showed no direct significant effects on the health indicators. However, there were significant indirect effects with perceived threat as the mediator between the predictor variable and the four dimensions of the GHQ‐28. Finally, the total effect of the model was only significant for anxiety/insomnia.

TABLE 4.

Someone close who is COVID‐19 positive and mental health. Direct, indirect, and total effects

Estimate Std. Error z‐value P 95% CI
Lower Upper
Direct effects
graphic file with name INM-30-724-g004.jpg
GHQ‐SS 0.004 0.095 0.043 0.966 −0.183 0.213
GHQ‐AI 0.035 0.094 0.373 0.709 −0.140 0.234
GHQ‐SD −0.202 0.107 −1.891 0.059 −0.424 −0.005
GHQ‐D −0.149 0.108 −1.376 0.169 −0.370 0.093
Indirect effects
graphic file with name INM-30-724-g004.jpg
PTCOVID‐19 → GHQ‐SS 0.196 0.060 3.258 0.001 0.076 0.326
PTCOVID‐19 → GHQ‐AI 0.198 0.061 3.263 0.001 0.082 0.332
PTCOVID‐19 → GHQ‐SD 0.112 0.038 2.938 0.003 0.040 0.211
PTCOVID‐19 → GHQ‐D 0.095 0.034 2.795 0.005 0.038 0.181
Total effects
graphic file with name INM-30-724-g004.jpg
GHQ‐SS 0.200 0.110 1.822 0.068 −0.014 0.416
GHQ‐AI 0.233 0.109 2.130 0.033 0.026 0.445
GHQ‐SD −0.090 0.110 −0.821 0.412 −0.297 0.128
GHQ‐D −0.054 0.110 −0.489 0.625 −0.273 0.189
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Inline graphic, someone close COVID‐19 positive; GHQ‐AI, Anxiety / insomnia; GHQ‐D, Depression; GHQ‐SD, Social dysfunction; GHQ‐SS, Somatic symptoms; PTCOVID‐19, Perceived Threat COVID‐19. [Note. Delta method standard errors, bias‐corrected percentile bootstrap confidence intervals].

Explained variance for the endogenous variables in the model was 28.3% (R 2 = 0.283) of the variance for somatic symptoms, 29.3% (R 2 = 0.293) for anxiety/insomnia, 9.1% (R 2 = 0.091) for social dysfunction, 6.5% (R 2 = 0.065) for depression, and 3.2% (R 2 = 0.032) with perceived threat as the mediator.

DISCUSSION

This study analysed the repercussions of perceived threat from COVID‐19 on the mental health of actively employed nurses, considering whether they had a positive COVID‐19 diagnosis or someone close to them had. The results confirmed the original hypotheses. Thus, women showed significantly higher perceived threat than men, and both nurses who had been diagnosed with COVID‐19 and those who said they had someone close who was, perceived a stronger threat from the disease. Along this line, previous studies done both in the general population and with nurses have suggested that women show stronger perceived threat from COVID‐19 (Aksoy & Hoҫak, 2020; Molero et al. 2020a), and that fear of the virus increases when there is a positive diagnosis of either the individuals themselves or someone close to them (Pakenham et al. 2020).

According to our results, high perceived threat would be related to high scores on somatic symptoms, anxiety/insomnia, social dysfunction, and depression. Previous studies on the psychological impact during the first stages of the COVID‐19 crisis have found that severity and perceived risk are significantly associated with stress, anxiety, and depression (Pakenham et al. 2020; Rodríguez‐Rey et al. 2020). Pérez‐Fuentes et al. (2020) also showed that perceived threat from COVID‐19 was related positively to emotional states, such as sadness‐depression, anxiety and anger‐hostility, and these early data on the pandemic in the general population are in agreement with our results for nurses.

Finally, this study found that the presence of a positive diagnosis had a negative impact on mental health indicators, where the perceived threat of COVID‐19 acted as a mediating variable. Thus COVID‐19 nearby or in the workers themselves affected the level of perceived threat from the disease, and this in turn impacted on the mental health of the workers. With someone close diagnosed with COVID‐19, the total effect of the model was significant for anxiety/insomnia. As far as we know, to date there are no previous studies analysing the relationship of these variables. Authors such as Pakenham et al. (2020) have shown that individual factors such as cognitive inflexibility, marked by harmful and uncontrollable thoughts and feelings, moderated the relationship between a COVID‐19 positive diagnosis, or someone close who has been infected, and mental health. This study, therefore, adds to the inquiry into variables exacerbating or mitigating the effects that a positive COVID‐19 diagnosis of themselves or of someone close to them can have on the psychological well‐being of nurses, one of the labour groups most affected by the pandemic in Spain.

Our results contribute important information for designing intervention programs to reduce the level of perceived threat and its effects on the mental health of nurses, who are performing indispensable work during this pandemic, (Choi et al. 2020), demonstrating their capacity to cope with this unprecedented situation, and making complex decisions (Greenberg et al. 2020).

However, we should mention some limitations. In the first place, hospital, unit, or area where the nurses was working were not included. These job characteristics are related to admission of patients affected by COVID‐19 and could, therefore, affect the level of threat and the psychological health of the nurses. Therefore, we recommend that they be included in future research. The measures used to evaluate the variables were self‐reports, which although they are very useful for large samples and easily applied, and data processing is economical, could be completed with observational measures and interviews with participants, among other methods of collecting information. Another of the limitations of this study was the sex distribution in the sample. However, keeping in mind the general characteristics of the nursing population in Spain, it may be considered representative of a profession which at present is practiced more by women than men. Also, in spite of the large number of studies underway on COVID‐19, to our knowledge, there are no previous studies relating the variables in this study in mediation models, limiting the possibility of comparing our results. Furthermore, its cross‐sectional design did not permit conclusions to be drawn on the evolution of the variables analysed. A longitudinal study would enable progress in the analysis of the variables included in this study.

CONCLUSIONS

Perceived threat from COVID‐19 was higher in nurses who had been diagnosed COVID‐19 positive, those who had someone positive among friends and family, and women. There was also a positive relationship between the level of perceived threat and repercussions on their mental health (somatic symptoms, anxiety/insomnia, social dysfunction, and depression). The results of this study further showed that this threat mediated in the relationship between a positive diagnosis and the mental health indicators studied, but was limited to symptoms of anxiety/insomnia in nurses with someone COVID‐19 positive close to them.

RELEVANCE FOR CLINICAL PRACTICE

Therefore, as nurses have been shown to perform an essential role during the pandemic, which to date is still punishing our country, and are one of the groups most vulnerable to contagion by COVID‐19, knowing these data will enable measures to be implemented that help them cope and maintain their psychological well‐being. In this sense, the formulation and implementation of psychoeducational actions for teaching coping strategies could benefit nurses, reducing perceived threat and the psychological symptoms derived from the pandemic.

Ethics approval and consent to participate

This study was evaluated and approved by the University of Almeria Research Ethics Committee (Ref. UALBIO2020/032).

Declaration of conflict of interest: The authors declare no conflict of interest.

Authorship statement: M.C.P.F., M.M.M.J., A.M.M., and D.J.R. contributed to the concept, design, analysis, and interpretation of the data. A.M.M. contributed to the technical details and manuscript preparation. M.C.P.F., M.M.M.J., and D.J.R. contributed to collecting the data. J.J.G.L. contributed to critically revising the manuscript for important intellectual content and the final approval of the version to be published. All authors accept and agree that the work is original; any methods and data presented are described accurately and honestly; and any relevant interests have been disclosed.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

REFERENCES

  1. Aksoy, Y. E. & Koҫak, V. (2020). Psychological effects of nurses and midwives due to COVID‐19 outbreak: The case of Turkey. Archives of Psychiatric Nursing, 3 (5), 427–433. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Arnáez, S. , García‐Soriano, G. , López‐Santiago, J. & Belloch, A. (2019). The Spanish validation of the Short Health Anxiety Inventory: Psychometric properties and clinical utility. International Journal of Clinical and Health Psychology, 19, 251–260. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Barr, M. , Raphael, B. , Taylor, M. et al. (2008). Pandemic influenza in Australia: Using telephone surveys to measure perceptions of threat and willingness to comply. BMC Infectious Diseases, 8, 117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Biesanz, J. C. , Falk, C. F. & Savalei, V. (2010). Assessing mediational models: Testing and interval estimation for indirect effects. Multivariate Behavioral Research, 45, 661–701. [DOI] [PubMed] [Google Scholar]
  5. Braquehais, M. D. , Vargas‐Cáceres, S. , Gómez‐Durán, E. et al. (2020). The impact of the COVID‐19 pandemic on the mental health of healthcare professionals. QJM: An International Journal of Medicine, 113 (9), 613–617. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Cacchione, P. Z. (2020). Moral Distress in the Midst of the COVID‐19 Pandemic. Clinical Nursing Research, 29, 215–216. [DOI] [PubMed] [Google Scholar]
  7. Castellano, E. , Muñoz‐Navarro, R. , Toledo, M. S. , Spontón, C. & Medrano, L. A. (2019). Cognitive processes of emotional regulation, burnout and work engagement. Psicothema, 31, 73–80. [DOI] [PubMed] [Google Scholar]
  8. Choi, K. R. , Jeffers, K. S. & Logsdon, M. C. (2020). Nursing and the novel coronavirus: Risks and responsibilities in a global outbreak. Journal of Advanced Nursing, 76, 1486–1487. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences. New York, NY: Routledge. [Google Scholar]
  10. Duan, L. & Zhu, G. (2020). Psychological interventions for people affected by the COVID‐19 epidemic. Lancet Psychiatry, 7, 300–302. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. El‐Hage, W. , Hingray, C. , Lemogne, C. et al. (2020). Health professionals facing the coronavirus disease 2019 (COVID‐19) pandemic: What are the mental health risks? Encephale, 46, S73–S80. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Goldberg, D. & Hillier, V. (1979). A scaled version of the General Health Questionnaire. Psychological Medicine, 9, 139–145. [DOI] [PubMed] [Google Scholar]
  13. Greenberg, N. , Docherty, M. , Gnanapragasam, S. & Wessely, S. (2020). Managing mental health challenges faced by healthcare workers during covid‐19 pandemic. British Medical Journal, 368, m1211. [DOI] [PubMed] [Google Scholar]
  14. Hong, Y. R. , Lawrence, J. , Williams, D. Jr & Mainous, A. III (2020). Population‐Level Interest and Telehealth Capacity of US Hospitals in Response to COVID‐19: Cross‐Sectional Analysis of Google Search and National Hospital Survey Data. JMIR Public Health and Surveillance, 6, e18961. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Huang, X. , Wei, F. , Hu, L. , Wen, L. & Chen, K. (2020). Epidemiology and Clinical Characteristics of COVID‐19. Archives of Iranian Medicine, 23, 268–271. [DOI] [PubMed] [Google Scholar]
  16. JASP Team . (2019). JASP (Version 0.11.1) [Computer software].
  17. Jiang, L. , Broome, M. E. & Ning, C. (2020). The performance and professionalism of nurses in the fight against the new outbreak of COVID‐19 epidemic is laudable. International Journal of Nursing Studies, 107, 103578. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Kisely, S. , Warren, N. , McMahon, L. , Dalais, C. , Henry, I. & Siskind, D. (2020). Occurrence, prevention, and management of the psychological effects of emerging virus outbreaks on healthcare workers: Rapid review and meta‐analysis. BMJ, 369, m1642. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Lai, J. , Ma, S. , Wang, Y. et al. (2020). Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019. JAMA Network Open, 3, e203976. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. León, E. , Neipp, M. C. & Núñez, R. (2020). Psychometric properties of the Spanish version of the Protective Factors of Resilience Scale (PFRS). Annals of Psychology, 36 (3), 468–474. [Google Scholar]
  21. Leventhal, H. , Phillips, L. A. & Burns, E. (2016). The Common‐Sense Model of Self‐Regulation (CSM): A dynamic framework for understanding illness self‐management. Journal of Behavioral Medicine, 39, 935–946. [DOI] [PubMed] [Google Scholar]
  22. Lima, C. K. T. , Carvalho, P. M. M. , Lima, I. A. A. S. et al. (2020). The emotional impact of Coronavirus 2019‐nCoV (new Coronavirus disease). Psychiatry Research, 287, 112915. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Lobo, A. , Pérez‐Echeverría, M. J. & Artal, J. (1986). Validity of the scaled version of the General Health Questionnaire (GHQ‐28) in a Spanish population. Psychological Medicine, 16, 135–140. [DOI] [PubMed] [Google Scholar]
  24. Lotfi, M. , Hamblin, M. R. & Rezaei, N. (2020). COVID‐19: Transmission, prevention, and potential therapeutic opportunities [published online ahead of print, 2020 May 29]. Clinica Chimica Acta, 508, 254–266. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Maunder, R. , Hunter, J. , Vincent, L. et al. (2003). The immediate psychological and occupational impact of the 2003 SARS outbreak in a teaching hospital. CMAJ, 168, 1245–1251. [PMC free article] [PubMed] [Google Scholar]
  26. Mertens, G. , Gerritsen, L. , Duisdman, S. , Salemink, E. & Engelhard, I. M. (2020). Fear of the coronavirus (COVID‐19): Predictors in an online study conducted in March 2020. Journal of Anxiety Disorders, 74, 102258. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Molero, M. M. , Herrera‐Peco, I. , Pérez‐Fuentes, M. C. & Gázquez, J. J. (2020a). Análisis de la amenaza percibida por la COVID‐19 en población española. Atención Primaria, 55, 515–516. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Molero, M. M. , Pérez‐Fuentes, M. C. , Soriano, J. G. et al. (2020b). Factores psicológicos en situaciones de cuarentena: Una revisión sistemática. European Journal of Health Research, 6, 109–120. [Google Scholar]
  29. Nagesh, S. (2020). Chakraborty, S. Saving the frontline health workforce amidst the COVID‐19 crisis: Challenges and recommendations. Journal of Global Health, 10, e010345. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Pakenham, K. I. , Landi, G. , Boccolini, G. , Furlani, A. , Grandi, S. & Tossani, E. (2020). The moderating roles of psychological flexibility and inflexibility on the mental health impacts of COVID‐19 pandemic and lockdown in Italy. Journal of Contextual Behavior Science, 17, 109–118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Pérez‐Fuentes, M. C. , Molero, M. M. , Gázquez, J. J. & Simón, M. M. (2019). Analysis of burnout predictors in nursing: Risk and protective psychological factors. European Journal of Psychology Applied to Legal Context, 11, 33–40. [Google Scholar]
  32. Pérez‐Fuentes, M. C. , Molero, M. M. , Martos, Á. & Gázquez, J. J. (2020). Threat of COVID‐19 and emotional state during quarantine: Positive and negative affect as mediators in a cross‐sectional study of the Spanish population. PLoS One, 15, e0235305. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. del Rio, C. & Malani, P. N. (2020). COVID‐19‐new insights on a rapidly changing epidemic. JAMA, 323, 1339. [DOI] [PubMed] [Google Scholar]
  34. Rodríguez‐Leor, O. , Cid‐Álvarez, B. , Ojeda, S. et al. (2020). Impact of the COVID‐19 pandemic on interventional cardiology activity in Spain. REC Interventional Cardiology, 2, 82–89. [Google Scholar]
  35. Rodríguez‐Rey, R. , Garrido‐Hernansaiz, H. & Collado, S. (2020). Psychological Impact and Associated Factors During the Initial Stage of the Coronavirus (COVID‐19) Pandemic Among the General Population in Spain. Frontiers in Psychology, 11, 1540. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Rosseel, Y. (2012). Lavaan: An R package for structural equation modeling and more. Version 0.5–12 (BETA). Journal of Statistical Software, 48, 1–36. [Google Scholar]
  37. Saglietto, A. , D'Ascenzo, F. , Zoccai, G. B. & De Ferrari, G. M. (2020). COVID‐19 in Europe: The Italian lesson. Lancet, 395, 1110–1111. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Soriano, J. G. , Pérez‐Fuentes, M. C. , Molero, M. M. , Tortosa, B. M. & González, A. (2019). Beneficios de las intervenciones psicológicas en relación al estrés y ansiedad: Revisión sistemática y metaanálisis. European Journal of Education and Psychology, 12, 191–206. [Google Scholar]
  39. Tirado, G. , Llorente‐Alonso, M. & Topa, G. (2019). Desequilibrio esfuerzo‐recompensa y quejas subjetivas de salud: Estudio exploratorio entre médicos en España. European Journal of Investigation in Health, Psychology and Education, 9, 59–70. [Google Scholar]
  40. Ventura‐León, J. L. & Caycho, T. (2017). El coeficiente Omega: Un método alternativo para la estimación de la confiabilidad. Revista Latinoamericana de Ciencias Sociales, Niñez y Juventud, 15, 625–627. [Google Scholar]
  41. Wang, C. , Horby, P. W. , Hayden, F. G. & Gao, G. F. (2020). A novel coronavirus outbreak of global health concern. Lancet, 395, 470–473. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Wenham, C. , Smith, J. & Morgan, R. (2020). COVID‐19: The gendered impacts of the outbreak. Lancet, 395, 846–848. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. World Health Organization (2020). Coronavirus Disease 2019 (COVID‐19): Situation Report‐70. Available from https://reliefweb.int/sites/reliefweb.int/files/resources/20200330‐sitrep‐70‐covid‐19.pdf. Accessed July 15, 2020. [Google Scholar]
  44. Xiang, Y. T. , Yang, Y. , Li, W. et al. (2020). Timely mental health care for the 2019 novel coronavirus outbreak is urgently needed. Lancet Psychiatry, 7, 228–229. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Zhu, N. , Zhang, D. , Wang, W. et al. (2020). A Novel Coronavirus from Patients with Pneumonia in China, 2019. The New England Journal of Medicine, 382, 727–733. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. de Zwart, O. , Veldhuijzen, I. K. , Elam, G. et al. (2007). Avian influenza risk perception, Europe and Asia. Emerging Infectious Diseases, 13, 290–293. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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