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. 2023 Jan 5;324:600–606. doi: 10.1016/j.jad.2022.12.152

Mental condition and function of resilience among families of frontline medical workers during COVID-19: Potential influencing factors and mediating effect

Peng Cheng a, Nicholas Jasinski b, Wanhong Zheng b, Lirong Wang c, Lingjiang Li a, Lizhi Xu a, Ying Zhou a, Li Zhang a, Weihui Li a,⁎
PMCID: PMC9812468  PMID: 36610594

Abstract

Background

Studying the role of psychological resilience in self-perceived stress and mental disorders among family members of medical workers can help us understand its importance in mental health care and guide us to develop psychological intervention strategies for family members of medical workers.

Methods

A total of 671 family members of medical workers were enrolled. Self-perceived stress, resilience, depression symptoms, anxiety symptoms, and post-traumatic stress disorder (PTSD) symptoms were measured in our research.

Results

The prevalence of anxiety, depression, and PTSD symptoms among relatives of medical workers were 49.0 %, 12.2 %, and 20.3 % respectively during the COVID-19 epidemic. According to the Multivariate regression model, compared with family members of doctor, family members of nurse and medical technologists were more likely to report anxiety symptoms. Female members of medical staff were more likely to have PTSD symptoms than male counterparts; and family members of medical technologist appeared to less likely have PTSD symptoms than family members of either doctor or nurse. The mediation analysis confirmed that mental resilience mediated the relationship between self-perceived stress and anxiety symptoms.

Limitations

Single cross-sectional study design without the follow-up comparative analysis, only self-reported measurements were adopted, and inadequate pre-set demographic variables.

Conclusions

To the best of our knowledge, our study firstly demonstrated the risk of psychological distress present in the family members of medical providers during the COVID-19 epidemic. Meanwhile, our findings highlighted the importance of mental resilience in family members of frontline medical workers as it mediated the relationship between self-perceived stress and anxiety symptoms.

Keywords: Mental health, Psychometrics, Assessment, Resilience, Cross-sectional study

1. Introduction

Medical workers are under enormous pressure, often facing various types of traumatic incidents during the COVID-19 pandemic. Previous epidemiological studies have shown that there has been a non-negligible increase in mental disorders among health care workers since the first outbreak of COVID-19 (Zhang et al., 2020). The commonly reported ones are depression (Wu et al., 2020), anxiety (Lai et al., 2020), and insomnia (Qi et al., 2020). With the increased attention, medical workers have been getting substantial psychological support from their own organizations and various mental health groups in society (Holmes et al., 2020). Unfortunately, family members of medical workers have not been a focus of major mental health support. As most frontline medical workers had increased work time and shifts, their family members were left with an increased workload from household affairs, such as child rearing, caring for elders, etc. Shift work was known to have some negative effects not just on the life quality of medical workers themselves (Brown et al., 2020) but also on the mental health of their family members (Strzemecka et al., 2013). Our study hypothesized that family members of medical workers were also under extreme stress and therefore are likely to suffer from similar psychiatric conditions during the worldwide COVID-19 pandemic.

Psychological resilience is the ability of a human to cope with stress and adversity (Delgado et al., 2017; Aburn et al., 2016) or to return to pre-crisis status quickly. It is considered as a type of benign adaptation to a negative environment and stimulation. In the presence of a negative stimulus, individuals with good mental resilience can actively regulate emotions and minimize maladaptive psychological and physical emotional reactions and changes, thereby reducing the likelihood of adverse psychosocial consequences (Ochsner et al., 2004). Although different models were proposed for the neurobiological basis of resilience to stress (Charney, 2004), the mechanism of the intriguing relationship between stress and psychological resilience remains unclear.

Resilience has a significant negative predictive effect on depression and PTSD symptoms (Wingo et al., 2010; Fredrickson et al., 2003). Some studies demonstrated that depression, anxiety, and PTSD could be considered as the result of failure to use resilience to self-adjust. Research indicated that resilience following natural disasters could be predicted. Those with avoidant and suppressive coping styles were found to have poorer mental health outcomes after the disaster (Kieft, 2021). In this study, we were also interested in whether the psychological resilience among family members of medical workers could act as a protective factor for their overall mental health. We hypothesized that resilience might play a moderating or mediating role between self-perceived stress and psychological disorders. Excessive self-perceived stress is likely to change the level of resilience therefore precipitates a series of mental disorders. Vice Versa, resilience may be also able to regulate the influence of self-perceived stress on psychological disorders.

In this unprecedented prolonged COVID-19 pandemic, the mental conditions of family members of medical workers are worth further investigating. As we know, the psychological well-being of family members can function as an independent protective factor against the distress of medical workers (Dong et al., 2020). Studying the role of mental resilience between self-perceived stress and mental disorders can help us understand its importance in mental health care and give us guidance on developing psychological intervention strategies for certain populations in a public health emergency. The current study aimed to evaluate the mental health of family members of medical workers and some associated factors and to explore the role of psychological resilience in self-perceived stress and various mental symptoms.

2. Methods

2.1. Participants

This study was conducted as a companion study to our published paper in August 2020 (Cheng et al., 2020b). Our family members of frontline medical workers were enrolled at the Second Xiangya Hospital of Central South University, Changsha city, Hunan province, China. This hospital was one of the designated hospitals by the local government to admit suspected COVID-19 febrile patients. Only those family members living with the frontline medical staff who were at high risk of COVID-19 infection were included in this study.

The survey questionnaire consisted of questions on general demographic information and the following measures: the Perceived stress scale-10 (PSS-10), 10-item Connor–Davidson Resilience Scale (CD-RISC-10), Patient Health Questionnaire-2 (PHQ-2), General Anxiety Disorder-7 (GAD-7) and Posttraumatic Stress Disorder Checklist for DSM-5 (PCL-5). This online survey was anonymously distributed through social media platforms (e.g., WeChat, QQ) to all family members living with medical workers in the Second Xiangya Hospital. Participation was voluntary and informed consent was obtained at the beginning of the survey with a brief introduction of the content and purpose of the study. Partially completed surveys were removed and only fully completed questionnaires were included in the final statistical analysis.

The data was collected from February 27th, 2020, to March 1st, 2020. A total of 671 completed questionnaires were obtained and included in the final analysis. This study was approved by the Ethics Committee of the Second Xiangya Hospital, Central South University.

2.2. Measures

Perceived stress scale-10 (PSS-10) and 10-item Connor–Davidson Resilience Scale (CD-RISC-10) were applied to measure self-perceived stress and mental resilience, respectively. Patient Health Questionnaire-2 (PHQ-2) and General Anxiety Disorder-7 (GAD-7), and Posttraumatic Stress Disorder Checklist for DSM-5 (PCL-5) were used to respectively evaluate whether depression, anxiety, and PTSD symptoms existed among family members of frontline medical staff. All these instruments were widely applied and recognized. Sections below were the detailed description of our instruments.

2.2.1. Perceived stress scale-10 (PSS-10)

The PSS-10 is a 10-item, 5-point Likert-type (0 = “never” to 4 = “almost always”) self-report scale with established reliability and validity in measuring the level of current self-perceived stress (Cohen and Williamson, 1988). The total score ranges from 0 to 40, with higher scores indicating higher self-perceived stress. As an easy-to-use questionnaire with established acceptable psychometric properties, the PSS-10 has been widely used in various international settings and various populations, including college students and police officers in China (Lu et al., 2017; Wang et al., 2011). Moreover, Previous studies also indicated the good reliability of PSS-10 with a Cronbach's α of 0.78–0.91 (Lu et al., 2017; Cohen et al., 1983; Wang et al., 2011). In the current study, Cronbach's alpha for the scale was 0.811.

2.2.2. 10-item Connor–Davidson Resilience Scale (CD-RISC-10)

The CD-RISC-10 is a 10-item self-report measure used to assess psychological resilience, which was defined as the ability to cope with adversity (Connor and Davidson, 2003). CD-RISC-10 is composed of 10 items, each of which is scored on a 5-point Likert scale from 0, representing not true at all, to 4, representing true nearly all time. The total score of CD-RISC-10 ranges from 0 to 40, with higher scores meaning a higher level of resilience (Campbell-Sills and Stein, 2007). The reliability and validity of this scale have been tested for earthquake victims (Wang et al., 2010) as well as depression patients and college students in China (Cheng et al., 2020a). The internal consistency of CD-RISC-10 was high in our study, with Cronbach's alpha = 0.96.

2.2.3. Patient Health Questionnaire-2 (PHQ-2)

The PHQ-2 is a widely used, efficient, and simple two-item assessment for depression experienced over the past two weeks (Kroenke et al., 2003). Responses are rated on a four-point Likert scale (0 = Not at all, 3 = Nearly every day). The PHQ-2 has been demonstrated to be a reliable and valid screening tool for depressive symptoms among the general population in Hong Kong (Yu et al., 2011). During the COVID-19 pandemic, PHQ-2 has also been shown to be useful and valid in the assessment of medical health workers during the COVID-19 pandemic (Zhang et al., 2020). The cutoff score of PHQ-2 for depression symptoms was 3 (Kroenke et al., 2010). The Cronbach's alpha of PHQ-2 in our research was 0.806, indicating good internal consistency.

2.2.4. General Anxiety Disorder-7 (GAD-7)

The GAD-7 is a seven-item screening measure used in assessing symptoms of generalized anxiety over the past two weeks (Spitzer et al., 2006). Individuals are asked to rate how frequently they experience the symptoms described in the item statement using a four-point Likert scale ranging from zero (not at all) to three (nearly every day). The GAD-7 has been widely tested and used in China. The reliability and validity of the Chinese version of GAD-7 have been documented (Yu et al., 2018) in Chinese general hospital patients. The cutoff score for anxiety symptoms was 5 (Spitzer et al., 2006). The Cronbach's alpha of GAD-7 in our study was reliable at 0.929.

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

PCL-5 is a self-report measure based on the DSM-5 criteria for PTSD. It consists of 20 items divided into four subscales, corresponding to different symptom clusters in the DSM-5. Participants rate how much a problem described in the item statement bothered them over the past month using a five-point Likert scale ranging from zero (not at all) to four (extremely). Item scores are summed to yield a total score ranging from 0 to 80, higher scores mean severe PTSD symptoms. Based on the recommended guidelines when using the PCL-5 (Weathers et al., 2013), a score of 31 or above was used to determine the presence of possible PTSD. Previous work by our research group about the psychometric property of PCL-5 has demonstrated that PCL-5 had good reliability and validity for measuring PTSD symptoms during the COVID-19 pandemic (Cheng et al., 2020b).

2.3. Statistical analysis

Statistical analyses were conducted with SPSS version 25.0 (IBM Corp. New York, USA.). Descriptive statistics were used to summarize the sample in terms of demographic background information, as well as category of relationship with medical worker, Job of medical worker, and Working duration of medical worker in the frontline. Univariate analysis of Chi-square test was performed to test the detection difference of depression, anxiety, and PTSD symptoms across the categorical variables mentioned above. Variables with a P value of <0.20 in the Chi-square test were considered as potential factors for inclusion in the multivariate logistic model. Then, Multivariate logistic regression analysis was adopted to figure out the factors which independently related to depression, anxiety, and PTSD symptoms among these potential factors.

Following Hayes guidelines (Hayes, 2013), SPSS PROCESS macro with the bootstrapping method was applied to assess the mediation model among mental symptoms, self-perceived stress, and resilience. According to the initial hypothesis of mediation model in our study, mental symptoms were set as dependent variables, self-perceived stress was set as the independent variable, and resilience was set as the mediating variable.

3. Results

3.1. Demographic characteristics and univariate analysis

Details of demographic information are summarized in Table 1 . A total of 671 participants were included in our research. Information on six variables was collected in our research, including gender, age, educational level, category of relationship with medical worker, job of medical worker, and working duration of medical worker in the frontline. More than half of the sample were female (53.9 %); the largest age band was 31–50 years old (57.2 %). In terms of education, those with bachelor degrees (39.8 %) and high school diplomas (30.6 %) made up the majority of our sample. As for the category of relationship with medical worker, most participants were parents (41.0 %) or spouses (39.5 %) of medical workers. For job of medical worker, family members of nurse (44.4 %) counted nearly half of our sample; Regarding of working duration of medical worker in the frontline, most of our sample was family members of medical workers who worked in the frontline from one week to one month (49.9 %).

Table 1.

Demographic characteristics and univariates analysis.

Demographic variables n (%) Anxiety symptoms
 P Depression symptoms
 P PTSD symptoms
 P
<5 (n = 342) ≥5 (n = 329) <3 (n = 589) ≥3 (n = 82) <31 (n = 535) ≥31 (n = 136)
Gender 0.394 0.444 0.01
 Male 309 (46.1 %) 163 (52.8 %) 146 (47.2 %) 268 (86.7 %) 41 (13.3 %) 233 (75.4 %) 76 (24.6 %)
 Female 362 (53.9 %) 179 (49.4 %) 183 (50.6 %) 321 (88.7 %) 41 (11.3 %) 302 (83.4 %) 60 (16.6 %)
Age 0.497 0.124 0.189
 <18 9 (1.3 %) 3 (33.3 %) 6 (66.7 %) 6 (66.7 %) 3 (33.3 %) 6 (66.7 %) 3 (33.3 %)
 18–30 163 (24.3 %) 78 (47.9 %) 85 (52.1 %) 139 (85.3 %) 24 (14.7 %) 122 (74.8 %) 41 (25.2 %)
 31–50 384 (57.2 %) 198 (51.6 %) 186 (48.4 %) 343 (89.3 %) 41 (10.7 %) 313 (81.5 %) 71 (18.5 %)
 51–60 115 (17.1 %) 63 (54.8 %) 52 (45.2 %) 101 (87.8 %) 14 (12.2 %) 94 (81.7 %) 21 (18.3 %)
Educational level 0.388 0.126 0.649
 Secondary school or below 121 (18.0 %) 70 (57.9 %) 51 (42.1 %) 112 (92.6 %) 9 (7.4 %) 94 (77.7 %) 27 (22.3 %)
 High school 205 (30.6 %) 99 (48.3 %) 106 (51.7 %) 172 (83.9 %) 33 (16.1 %) 169 (82.4 %) 36 (17.6 %)
 Bachelor 267 (39.8 %) 133 (49.8 %) 134 (50.2 %) 237 (88.8 %) 30 (11.2 %) 209 (78.3 %) 58 (21.7 %)
 Master or above 78 (11.6 %) 40 (51.3 %) 38 (48.7 %) 68 (87.2 %) 10 (12.8 %) 63 (80.8 %) 15 (19.2 %)
Category of relationship with medical worker 0.312 0.05 0.007
 Children 131 (19.5 %) 59 (45.0 %) 72 (55.0 %) 108 (82.4 %) 23 (17.6 %) 92 (70.2 %) 39 (29.8 %)
 Spouses 265 (39.5 %) 140 (52.8 %) 125 (47.2 %) 241 (90.9 %) 24 (9.1 %) 222 (83.8 %) 43 (16.2 %)
 Parents 275 (41.0 %) 143 (52.0 %) 132 (48.0 %) 240 (87.3 %) 35 (12.7 %) 221 (80.4 %) 54 (19.6 %)
Jobs of medical worker 0.006 0.085 0.006
 Doctor 182 (27.1 %) 111 (61.0 %) 71 (39.0 %) 166 (91.2 %) 16 (8.8 %) 137 (75.3 %) 45 (24.7 %)
 Nurse 298 (44.4 %) 142 (47.7 %) 156 (52.3 %) 263 (88.3 %) 35 (11.7 %) 231 (77.5 %) 67 (22.5 %)
 Medical technologist 191 (28.5 %) 89 (46.6 %) 102 (53.4 %) 160 (83.8 %) 31 (16.2 %) 167 (87.4 %) 24 (12.6 %)
Working duration of medical worker in the frontline 0.85 0.238 0.782
 <1 week 91 (13.6 %) 44 (48.4 %) 47 (51.6 %) 75 (82.4 %) 16 (17.6 %) 75 (82.4 %) 16 (17.6 %)
 1 week-1 month 335 (49.9 %) 171 (51.0 %) 164 (49.0 %) 296 (88.4 %) 39 (11.6 %) 265 (79.1 %) 70 (20.9 %)
 >1 month 245 (36.5 %) 127 (51.8 %) 118 (48.2 %) 218 (89 %) 27 (11.0 %) 195 (79.6 %) 50 (20.4 %)
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Note: P values that were <0.20 were marked in bold.

The prevalence of anxiety, depression, and PTSD symptoms in our sample was 49.0 %, 12.2 %, and 20.3 %, respectively. Univariate analysis of the differences in anxiety, depression, and PTSD symptoms across variables are shown in Table 1. For anxiety symptoms, job of medical worker was the only variable with statistical significance (P = 0.006). For depression symptoms, the detection of depression symptoms varied significantly in the subgroups of age (P = 0.124), educational level (P = 0.126), category of relationship with medical worker (P = 0.05), and job of medical worker (P = 0.085). For PTSD symptoms, the prevalence of PTSD symptoms was statistically different in the subgroups of gender (P = 0.01), age (P = 0.089), category of relationship with medical worker (P = 0.007), and job of medical worker (P = 0.006).

3.2. Multivariable logistic regression analysis

Only factors observed to be statistically significant in univariate analysis would be included in the logistic regression model. Multivariable logistic regression results are shown in Table 2 . Compared with family members of doctor, family members of nurse (OR = 1.718, 95 % CI: 1.181–2.498) and medical technologists (OR = 1.792, 95 % CI: 1.187–2.705) were more likely to report anxiety symptoms. No variables were statistically significant in the logistic regression model of depression symptoms. In terms of PTSD symptoms, female relatives of medical staff (OR = 0.659, 95 % CI: 0.448–0.970) and family members of medical technologist (OR = 0.455, 95 % CI: 0.262–0.789) appeared to less likely have PTSD symptoms.

Table 2.

Multivariable logistic regression models of symptoms of anxiety, depression and PTSD.

Variables OR P value
 95%CI
Category Overall
GAD-7, anxiety symptoms
Jobs of medical workers
 Doctor 1 [Reference] NA 0.007 NA
 Nurse 1.718 0.005 1.181–2.498
 Medical technologist 1.792 0.006 1.187–2.705



PHQ-2, depression symptoms
Age
 <18 1 [Reference] NA 0.098 NA
 18–30 0.261 0.093 0.055–1.250
 31–50 0.178 0.025 0.039–0.805
 51–60 0.215 0.055 0.045–1.030
Educational level
 Secondary school or below 1 [Reference] NA 0.119 NA
 High school 2.495 0.023 1.135–5.484
 Bachelor 1.752 0.187 0.762–4.024
 Master or above 2.364 0.09 0.874–6.394
Category of relationship with medical worker
 Children 1 [Reference] NA 0.293 NA
 Spouse 0.479 0.211 0.151–1.519
 Parent 0.638 0.502 0.172–2.370
Job of medical workers
 Doctor 1 [Reference] NA 0.070 NA
 Nurse 1.465 0.247 0.768–2.796
 Medical technologist 2.166 0.024 1.107–4.234



PCL-5, PTSD symptoms
Gender
 Male 1 [Reference] NA 0.035 NA
 Female 0.659 0.035 0.448–0.970
Age
 <18 1 [Reference] NA 0.310 NA
 18–30 0.778 0.734 0.183–3.303
 31–50 0.529 0.381 0.127–2.196
 51–60 0.546 0.422 0.124–2.396
Category of relationship with medical worker
 Children 1 [Reference] NA 0.066 NA
 Spouse 0.391 0.073 0.140–1.092
 Parent 0.561 0.32 0.180–1.753
Job of medical workers
 Doctor 1 [Reference] NA 0.015 NA
 Nurse 0.855 0.485 0.552–1.326
 Medical technologist 0.455 0.005 0.262–0.789
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Note: GAD-7: General Anxiety Disorder-7; PHQ-2: Patient Health Questionnaire-2; PCL-5: Posttraumatic Stress Disorder Checklist for DSM-5; OR: Odds ratio.

P values less than 0.05 are bold.

3.3. Mediation effect analysis

Before the mediation effect analysis, Correlational analyses among self-perceived stress, mental resilience, and mental symptoms measured in our study were conducted to identify possible candidates for mediation effect analysis. Given the PHQ-2 scale was mainly used for screening depression, instead of evaluating the severity of depression, which was improper for the mediation analysis, only anxiety and PTSD symptoms were brought into the correlational analyses. Details in Table 3 .

Table 3.

The correlation statistics of measurements.

M SD PSS-10 CDRISC-10 GAD-7 PCL-5
PSS-10 15.92 5.99 1
CDRISC-10 26.22 9.05 0.248⁎⁎ 1
GAD-7 4.88 4.57 0.368⁎⁎ −0.182⁎⁎ 1
PCL-5 19.54 21.45 −0.009 −0.174⁎⁎ 0.201⁎⁎ 1
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Note: PSS-10: Perceived stress scale-10; CD-RISC-10: 10-item Connor–Davidson Resilience Scale; GAD-7: General Anxiety Disorder-7; PCL-5: Posttraumatic Stress Disorder Checklist for DSM-5; M: Mean value; SD: Standard deviation.

⁎⁎

p < 0.01.

Results indicated that self-perceived stress was positively correlated with mental resilience and anxiety symptoms, without a statistically significant relationship with PTSD symptoms. At the same time, mental resilience was negatively correlated with anxiety and PTSD symptoms. The statistically significant correlations among self-perceived stress, mental resilience, and anxiety symptoms met the pre-condition of meditation analysis, meanwhile based on our previous hypothesis, we tested the mediation model that mental resilience as the mediator, self-perceived stress as the independent factor, and anxiety symptoms as the dependent factor among family members of frontline medical workers.

Detailed parameters of the mediation model of mental resilience between self-perceived stress and anxiety symptoms are shown in Table 4 . Background variables were set as covariates enrolled in the process of building a mediation model to control the bias. Results demonstrated that self-perceived stress was positively related to anxiety symptoms (B = 0.285, t = 10.266, P < 0.01) and mental resilience (B = 0.369, t = 6.442, P < 0.01). The mediation test confirmed that mental resilience mediated the relationship between self-perceived stress and anxiety symptoms (B = -0.148, t = −8.212, P < 0.01). After controlling for the effect of mental resilience, the direct coefficient of self-perceived stress on anxiety symptoms was changed (B = 0.340, t = 12.440, P < 0.01). The mediation effect of mental resilience was confirmed by the coefficient change of self-perceived stress. Fig. 1 depicts the output model for the mediation effect of resilience between self-perceived stress and anxiety symptoms.

Table 4.

Mediation model of resilience in self-perceived stress and anxiety symptoms.

Anxiety symptoms Anxiety symptoms Resilience
Covariates B T B T B T
 Gender 0.333 1.054 0.316 0.953 0.117 0.171
 Age −0.219 −0.597 −0.371 −0.967 1.033 1.307
 Educational level −0.159 −0.617 −0.269 −0.998 0.749 1.345
 Category of relationship with medical worker 0.410 0.965 0.271 0.608 0.945 1.030
 Jobs of medical workers 0.348 1.623 0.402 1.783 −0.360 −0.777
 Working duration of medical worker in the frontline 0.133 0.234 0.077 0.301 0.377 0.731
Self-perceived stress 0.340 12.440⁎ 0.285 10.266⁎ 0.369 6.442⁎
Resilience −0.148 −8.212⁎
R2 0.229 0.387 0.08
F 24.513 16.707 8.284
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Note: B: Regression coefficient; T: T statistic for coefficient; R2: coefficient of determination for the model fitting; F: F statistic for the total regression model.

⁎

p < 0.01.

Fig. 1.

Fig. 1

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Meditating effect of self-perceived stress on anxiety through resilience.

The unstandardized regression coefficients are reported. *p < 0.05, **p < 0.01, ***p < 0.001.

4. Discussion

This study had two primary goals: 1) to investigate the prevalence of reported anxiety, depression, and PTSD symptoms among family members of frontline medical workers during the early-phase of the COVID-19 pandemic and 2) to assess the relationship between mental resilience and its impact on perceived stress and self-report of the aforementioned symptom types. The prevalence of anxiety, depression, and PTSD symptoms in our sample was 49.0 %, 12.2 %, and 20.3 %, respectively, which was higher than the prevalence of these symptoms in the general population of China during non-pandemic periods (Huang et al., 2019) indicating that family members of frontline medical workers during the early phase of the COVID-19 pandemic were experiencing greater distress than usual. Additionally, compared with the overall prevalence of mental symptoms among the general population during COVID-19 demonstrated by a literature review (Tng et al., 2022), our results suggested that the higher incidence of anxiety symptoms (49.0 % vs. 24.8 %), the lower incidence of depression symptoms (12.2 % vs. 23.1 %), and the similar incidence of PTSD symptoms (20.3 % vs. 20.8 %) among family members of medical workers. In general, the prevalence of mental symptoms among family members of medical workers was obviously increased than in the non-COVID-19 period, the trend of which was the same with the general population. But the difference was that the anxiety symptoms prevalence was much higher than other mental symptoms among family members of medical workers, while there was no obvious difference in prevalence among anxiety, depression, and PTSD symptoms in the general population.

The possible reasons for the prevalence changes of mental symptoms among our family member samples were multiple. Firstly, medical workers on the frontline against COVID-19 were at high risk of potentially fatal hospital-related transmission, which could cause different sources of stress among family members of medical workers. Except for the fear of self-infection of COVID-19, the worry regarding possible COVID-19 exposure of their relatives working in the frontline, given frontline medical workers' close proximity to COVID-19 infected patients, is to be expected. This echoes a previous study suggesting that the risk of a family member getting infection was predicted increased stress among health care workers (Liu et al., 2020b). Our results further suggested that this situation also existed among family members of medical workers.

Additionally, because of the highly contagious nature of COVID-19, the general population, including family members of frontline medical workers, was urged to isolate themselves at home by the local government to prevent the unchecked spread of the virus. These now-familiar “lockdowns” prohibited any non-essential activities outside home, which led to significant disruption in individuals' daily lives and a possible reduction in coping strategies for dealing with stress. Previous studies have demonstrated that disruptions in daily routines increase the risk of various mental disorders (Lyall et al., 2018). Disruption of lifestyle routine brought by lengthy home quarantine may lead to heavy psychological stress (Rubin and Wessely, 2020), which can increase the risk of mental disorders, even among individuals without any psychiatric history (Zhang and Ma, 2020; Liu et al., 2020a).

Multivariate regression analysis showed that family members of doctor were less likely to have anxiety symptoms than relatives of nurses or medical technologists. Regarding PTSD symptoms, male family members of medical workers had an increased risk of reporting PTSD symptoms while family members of medical technologist had a lower risk of reporting PTSD symptoms. With regard to our observed gender findings, many past studies suggested that female medical workers were more likely to report PTSD symptoms than male medical workers during COVID-19 (Sun et al., 2021; Liu et al., 2020b), our research found contrary results among the sample of families of medical workers. The reason for this discrepancy is unclear, suggesting that further research regarding differences between symptom reporting rates by medical professionals and their families is worthy of further study.

In terms of occupation, the difference in exposure to possible infection faced by doctors, nurses, and medical technologists may explain our finding that doctors' families were at less risk of reporting anxiety symptoms. Previous literature has suggested that the difference in vulnerability between family members of nurse and family members of doctor, caused by the nature of their respective occupations, should be the major role in difference in the prevalence of anxiety symptoms and PTSD symptoms of them (Carmassi et al., 2020). Additionally, the difference in working schedule of doctors and nurses also affects the incidence of mental symptoms. Previous studies on epidemic also highlighted that the differences in the nature of the work were the factor affecting psychological symptoms among doctors, nurses, and other medical workers, and a lower frequency of mental disorders was observed in various samples of doctors (Maunder et al., 2004; Phua et al., 2005). The finding of our research demonstrated that this contributing factor exists not only in medical workers but also in their family members. The stabilization of family represented as a resilience factor for the mental health of medical workers in previous studies (Lancee et al., 2008; Du et al., 2020) and, as such future psychological intervention should consider family interventions in support of frontline workers during public emergencies.

Another unique finding in the current study was that psychological resilience played a mediating role between self-perceived stress and anxiety symptoms in our family member sample. Previous research has demonstrated that psychological resilience could be a mediating variable affecting stressful life events in individuals' life (Haeffel and Grigorenko, 2007). Zimmerman et al. (2013) proposed that psychological resilience could work in a protective fashion in which psychological resilience modifies the interaction between the risk factor and the psychological outcome events. Results of our research suggest that this conclusion was generalizable to family members of medical workers during the early portion of the COVID-19 pandemic.

5. Limitations

Our study has several limitations which need to be considered. Firstly, due to the cross-sectional nature of this study, baseline data regarding psychological symptoms in our sample during the non-pandemic period was unavailable. As such, we were not able to do the follow-up analysis by comparing baseline data. Secondly, due to the risk of infection of COVID-19 during the pandemic, a web-based and self-reported survey was applied in our study for safety, which might affect the reliability of data as the lack of administration from professional interviewers. Besides, although the PHQ-2 was simple and efficient for screening depression in clinical work, PHQ-2 was improper for evaluating the severity of depression, which hindered us from further analysis of the interaction between psychological properties and depression. Thirdly, the demographic variables of family members of medical workers were relatively lacking. Some detailed description of the relationship between family members and frontline medical workers and occupation information of family members of medical workers was limited, which might be associated with the mental responses to the pandemic. Finally, our data was collected in the very early portion of the initial onset of the COVID-19 pandemic. As such, the current findings may not reflect more longstanding trends or provide information regarding the course of symptoms throughout an ongoing public emergency. Additionally, as there is greater awareness regarding transmission routes of COVID-19, mitigating steps that individuals can take to minimize transmission, the availability of vaccines, and better clarity regarding the severity of illness, it is likely that psychological distress may be different at the current time when compared to the timeframe in which this data was collected.

6. Conclusion

Our study conducted a cross-sectional study among family members of medical workers during the COVID-19 epidemic with findings suggesting that risk of psychological distress was present in the family members of medical providers, an essential public health implication. Additionally, the protective factor of psychological resilience was identified, which is consistent with the robust literature on the defensive nature of this factor. Our results offer novel insights and a potential leverage point for intervention to improve this population's well-being. Future research is encouraged to replicate these findings at this later point in the pandemic to determine if these findings persist or are unique to the early, low-information periods early in a global pandemic.

CRediT authorship contribution statement

Peng Cheng, Lirong Wang: Data collection, literature review, manuscript drafting.

Ying Zhou, Lizhi Xu, Li Zhang: managed the ethical review process.

Wanhong Zheng, Nicholas Jasinski, Lingjiang Li, Weihui Li: manuscript drafting and revision. All the authors read and approved the final manuscript.

Role of the funding source

This study was supported by the Natural Science Foundation of Hunan Province, China (No. 2020JJ5844 to Li Zhang), Natural Science Foundation of Hunan Province, China (No. 2018JJ2592 to Weihui Li) and Hunan Key Research and Development Program (No. 2018SK2136 to Weihui Li).

Conflict of interest

The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.

Acknowledgements

The authors appreciate the effort of all participants who took part in this study.

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