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. 2020 Jul 2;275:210–215. doi: 10.1016/j.jad.2020.06.031

The mental health of frontline and non-frontline medical workers during the coronavirus disease 2019 (COVID-19) outbreak in China: A case-control study

Qi Cai a,1, Hongliang Feng b,1, Jing Huang a, Meiyao Wang c, Qunfeng Wang a,b, Xuanzhen Lu a, Yu Xie a, Xing Wang d, Zhenxing Liu a, Botong Hou a, Keni Ouyang a, Jing Pan e, Qin Li f, Beibei Fu g, Yongchao Deng h, Yumin Liu a,⁎
PMCID: PMC7329671  PMID: 32734910

Highlights

  • •

    Frontline medical workers had higher rates of anxiety, depressed mood and insomnia than non-frontline medical workers.

  • •

    No significant difference in help-seeking and treatment behaviors between frontline and non-frontline medical workers.

  • •

    The timely mental support and intervention should be provided for medical workers, especially for those on the frontline.

Keywords: Help-seeking behavior, Severe acute respiratory syndrome from coronavirus 2, Coronavirus disease 2019, Mental health, Medical workers

Abstract

Background and objective

Coronavirus disease 2019 (COVID-19) is a new infectious disease with high transmissibility and morbidity. It has caused substantial mental distress to medical professionals. We aimed to compare the psychological impact of the COVID-19 outbreak between frontline and non-frontline medical workers in China.

Methods

This case-control study recruited 1173 frontline and 1173 age- and sex-matched non-frontline medical workers during the COVID-19 outbreak (February 11 to 26, 2020). A set of online questionnaires were used to measure mental problems (i.e., anxiety, insomnia, and depressive symptoms), and help-seeking behavior and treatment for these mental problems.

Results

Frontline medical workers had higher rates of any mental problem (52.6% vs. 34.0%, adjusted OR=1.88, 95% CI=1.57–2.25), anxiety symptoms (15.7% vs. 7.4%, adjusted OR=1.95, 95% CI=1.46–2.61), depressed mood (marginally insignificant; 14.3% vs. 10.1%, adjusted OR=1.32, 95% CI=0.99–1.76) and insomnia (47.8% vs. 29.1%, adjusted OR=1.96, 95% CI=1.63–2.36) than non-frontline medical workers. No significant difference was observed in terms of suicidal ideation (12.0% vs. 9.0%, adjusted OR=1.25, 95% CI=0.92–1.71), help-seeking (4.5% vs. 4.5%, adjusted OR=1.00, 95% CI=0.53–1.87) or treatment (3.4% vs. 2.3%, adjusted OR=1.38, 95% CI=0.54–3.52) for mental problems.

Limitations

The case-control nature of the data precludes causal inferences, and there is a possibility of bias related to self-reports.

Conclusions

Frontline medical workers had more mental problems but comparable help-seeking behaviors and treatment for these problems than non-frontline medical workers. These findings highlight the timely mental support and intervention for medical workers, especially for those on the frontline.

1. Introduction

Coronavirus disease 2019 (COVID-19) was first reported in Wuhan, Hubei Province, China, in December 2019 (Phan, 2020), followed by an outbreak throughout the country and beyond. As of February 27, 2020, a total of 3019 medical workers were infected in China with novel coronavirus (including confirmed cases, suspected cases, clinically diagnosed cases, and asymptomatic infected persons), 1688 medical workers have been confirmed to be infected, with 247 (14.6%) critical cases and 5 (0.3%) deaths (Epidemiology Working Group for NCIP Epidemic Response, 2020). Medical workers, especially those who are working in the frontline, may suffer a huge amounts of stress during the fight against COVID-19.

Several studies have reported that individuals exposed directly or indirectly to life-threatening situations may have a high risk of psychological morbidities (Bills et al., 2008; Chan and Huak, 2004; Ji et al., 2017; Mak et al., 2009; Ofner-Agostini et al., 2006; Sim et al., 2004; Wang et al., 2009; Wu et al., 2009). For example, during the outbreak of severe acute respiratory syndrome (SARS) in 2003, it was shown that health care workers had a higher rate of SARS infection than other people (Ofner-Agostini et al., 2006), and they were emotionally affected and traumatized during the outbreak (Chan and Huak, 2004; Wu et al., 2009). At present, the severe acute respiratory syndrome from coronavirus 2 (SARS-CoV-2), which has been reported to have more severe transmissibility than SARS-COV (Liu et al., 2020b), puts medical workers, especially the frontline medical staff at very high health risk. With an increasing number of patients, long hours of intensive work and less sleep time, inadequate protection from contamination, and the risk of infection at any time, medical workers have a high risk of physical and mental exhaustion, resulting in a variety of mental health problems. The mental health of medical workers has gained tremendous attention. As this outbreak has highlighted the fragility of psychological resilience, we also need to pay attention to the psychological state of health care workers during epidemics (Ho et al., 2020). The government and hospitals have formulated a series of measures to address this problem (Kang et al., 2020a).

A recent study found that nearly one-sixth of 4679 medical staff had psychological distress and therefore needed to seek help from psychological or psychiatric professionals. The prevalences of psychological distress, anxious symptoms, and depressive symptoms were 15.9%, 16.0%, and 34.6%, respectively (Liu et al., 2020a,b,c). Another study investigating the mental health status of 224 medical staff found that 29.9% of the medical staff that fought against COVID-19 in Wuhan had a high score of anxiety compared with medical staff in Xian (Zhang et al., 2020a, Zhang et al., 2020b). However, the deficiency lies in the lack of systematic assessment of mental problems between frontline and non-frontline medical workers during the COVID-19 outbreak. Since an increasing number of newly infected cases among the medical staff have been observed to date, and since the arduous task of the fight against the COVID-19 might be far from over, timely mental health care for medical staff during the COVID-19 outbreak is urgently needed. The present study attempted to compare the immediate psychological impact of the COVID-19 outbreak on frontline and non-frontline medical workers in China.

2. Methods

2.1. Participants and data collection

This case-control study was conducted between February 11 to 26, 2020, which was approved by the Clinical Research Ethics Committee of Zhongnan Hospital of Wuhan University (Ref. No.: 2,020,030). This study was conducted through a program called Questionnaire Star. The sample was obtained based on a non-probability sampling design. All medical workers participated in the survey through the link or Quick Response (QR) code of Questionnaire Star, which is a bar code that can store the website link of the questionnaire used in this study. Once the questionnaire was submitted, the data would be saved on the questionnaire star server, and the questionnaire creator can download or analyze the data. The requirement for written consent from subjects was waived by the Research Ethics Committee. No identifiable information was collected.

A set of questionnaires were sent to medical workers working in hospitals in China via the QR code of Questionnaire Star. The medical workers included physicians, nurses, and other healthcare workers (e.g., medical technicians, respiratory therapists, or emergency room attendants). Medical workers dealing with COVID-19 were considered frontline medical workers. Otherwise, they were categorized into the non-frontline medical workers group. Other inclusion criteria were as follows: 1) age 18 to 80 years old and 2) Chinese-speaking residents of China. A total of 1173 eligible frontline medical workers and 2118 eligible non-frontline medical workers participated in this study. 55.4% of the non-frontline medical workers (n = 1173) were selected and matched to frontline medical workers by age and sex. The matching was performed using the "MatchIt" package in R (Version 3.5.1; R Foundation for Statistical Computing, Vienna, Austria) (Ho et al., 2007).

2.2. Measures and tools

The study instrument was a structured questionnaire that comprised demographic details, three main self-reported rating scales that have broad credibility, and information about whether the participant sought help or treatment for mental problems. The detailed explanation is as follows.

2.2.1. Demographic information

Participants' demographic characteristics, including age, sex, education level, marital status, jobs, annual household income, living status, and geographic origin, were obtained. The epidemic parameters for the COVID-19 of the areas where the subjects stayed were used to estimate the levels of exposure to the epidemic. The epidemic parameters, including the number of cumulative cases, number of new daily cases, prevalence, and daily incidence, were obtained from the official online platform for controlling the COVID-19 epidemic in China.

2.2.2. Three main rating scales measuring mental health status

The Beck Anxiety Inventory (BAI) was used to measure anxiety symptoms over the last seven days (Beck et al., 1988; Chinese version: Che et al., 2006). This scale has a total of 21 self-report items with responses rated on a 4-point Likert scale ranging from 0 (not at all) to 3 (severely). Higher scores reveal a higher level of anxiety. The following cut-off scores were used to assess different levels of anxiety: (1) scores between 0 and 7 denote no anxiety; (2) scores between 8 and 15 denote mild anxiety; (3) 16–25 denotes moderate anxiety; (4) 26–63 denote severe anxiety (Ahmed et al., 2020). The presence of anxiety was defined as a BAI score > 15 in our study.

The Insomnia Severity Index (ISI) was used to assess participants’ perceptions of insomnia over the past two weeks (Chahoud et al., 2017). It has seven items targeting the subjective symptoms and daytime consequences of insomnia, as well as the degree of distress caused by these difficulties. Each item of this scale is rated on a 5-point Likert scale of 0–4, and higher scores indicate greater insomnia severity (Morin et al., 2011; Chinese version: Li et al., 2019). The optimal cut-off point of ISI for detecting clinical insomnia in the Chinese population was a total score of 9 (Chung et al., 2011). Therefore, an ISI score higher than nine was chosen as the cut-off for insomnia for this study.

The Patient Health Questionnaire-9 (PHQ-9) was used to measure depressive symptoms over the past two weeks (Michel and Gordon, 2014). All nine items are scored from 0 to 3, and the total scores range from 0 to 27, with a higher score indicating more severe symptoms (Kroenke et al., 2001; Chinese version: Min et al., 2013). Scores of 0–4 indicate no depression, scores of 5–9 indicate mild depression, scores of 10–14 indicate moderate depression, scores of 15–19 indicate moderately severe depression, and scores of 20–27 indicate severe depression (Xia et al., 2019). Participants with a PHQ-9 > 10 were defined as depressed in our study.

The Chinese versions of the three abovementioned rating scales have been proven to have satisfactory reliability and validity (Chung et al., 2011; Liang et al., 2018; Wang et al., 2014). In addition, suicidal ideations were measured by one question: “Over the past two weeks, have you ever had suicidal thoughts?” The responses to this question were “Once/several times” or “Never” (Hassan, 2015).

2.2.3. Help-seeking or treatment for mental health during the COVID-19 outbreak

Whether participants sought help or received treatment for mental problems, including anxiety symptoms, depressed mood, suicidal ideation, and insomnia, during the COVID-19 outbreak was recorded. The question “Have you ever sought help from psychiatrists or clinical psychologists since the outbreak of COVID-19 began?” was used to estimate help-seeking behavior. The question “Have you ever received any treatment for psychiatric or psychological problems since the outbreak of COVID-19 began?” was used to measure treatment history for mental problems.

2.3. Statistical analysis

Mann–Whitney U test and t-test were used to compare means of two groups of non-normally and normally distributed variables, respectively. Chi-square test was used to compare the inter-group differences for categorical variables. Univariate and multivariate logistic regressions were performed to evaluate the relationships of frontline medical workers (vs. non-frontline medical workers) with mental problems, and help-seeking behaviors and treatment for mental problems. A value of two-tailed P < 0.05 was considered statistically significant. In Table 2, P values for multivariate logistic regressions were further adjusted using a false discovery rate (FDR) method (Bernhard, 2019). An FDR of 5% using q values would mean that 5% of results called significant (P < 0.05) are false-positives (Benjamini and Hochberg, 1995). All statistical tests were performed using SPSS version 24.0 for Windows (Armonk, NY: IBM Corp) and R (version 3.5.1).

Table 2.

Mental disorders, help-seeking and treatment for mental problems of medical workers during COVID-19.

Non-frontline medical workers(n = 1173) Frontline medical workers(n = 1173) Crude odds ratio [95% confidence interval] Adjusted odds ratio [95% confidence interval]a q valuec
Any mental problemsb 399 (34.0) 617 (52.6) 2.15 [1.82–2.54] 1.88 [1.57–2.25] < 0.01
Anxiety symptoms (BAI score > 15) 87 (7.4) 184 (15.7) 2.32 [1.77–3.04] 1.95 [1.46–2.61] < 0.01
Depressed mood (PHQ-9 > 10) 119 (10.1) 168 (14.3) 1.48 [1.15–1.90] 1.32 [0.99–1.76] 0.06
Suicidal ideation 105 (9.0) 141 (12.0) 1.39 [1.06–1.82] 1.25 [0.92–1.71] 0.16
Insomnia symptoms (ISI > 9) 341 (29.1) 561 (47.8) 2.24 [1.89–2.65] 1.96 [1.63–2.36] < 0.01
Help-seeking for mental problemsb 18/399 (4.5) 28/617 (4.5) 1.01 [0.55–1.84] 1.00 [0.53–1.87] 0.99
Treatment for mental problemsb 9/399 (2.3) 21/617 (3.4) 1.53 [0.69–3.37] 1.38 [0.54–3.52] 0.51
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Data are presented as n (%).

Abbreviations: COVID-19: Coronavirus Disease 2019; BAI: the Beck Anxiety Inventory; PHQ-9: the 9-item Patient Health Questionnaire; ISI: the Insomnia Severity Index.

a

Adjusted for jobs, income level, living alone, geographic origin, prevalence of the COVID-19.

b

Mental problems include anxiety symptoms, depressed mood, suicidal ideation, and insomnia.

c

q values: P values adjusted by false discovery rate (FDR) method. A q value of 5% would mean that 5% of results called significant (P values < 0.05) are false-positives.

3. Results

A total of 2346 participants were enrolled in our study, including 1173 frontline workers and 1173 age- and sex- matched non-frontline medical workers. Table 1 presents the demographic characteristics of the participants. There were no differences in education years and unmarried status between non-frontline and frontline medical workers (all P > 0.05). However, frontline medical workers had a higher proportion of medical staff (mainly including doctors and nurses) than non-frontline medical workers (98.6% vs. 93.4%, P < 0.01). Frontline medical workers showed higher proportions of annual household income of < 11,255 USD per head (71.9% vs. 67.1%, P = 0.01) and living alone (30.9% vs. 17.5%, P < 0.01) than non-frontline medical workers. Compared with non-frontline medical workers, frontline medical workers had higher proportions of participants from Wuhan and Hubei province (excluding Wuhan) (P < 0.01). In addition, frontline medical workers had higher exposure levels of the COVID-19 epidemic, including larger numbers of cumulative cases and daily new cases, higher prevalence, and higher daily incidence than subjects from other areas (all P < 0.01).

Table 1.

Demographic characteristics and the exposure of the COVID-19 epidemic of non-frontline and frontline medical workers.

Non-frontline medical workers(n = 1173) Frontline medical workers(n = 1173) Degree of freedom (df) P value
Male 348 (29.7) 354 (30.2) 1 0.79
Age (years) 30.5 ± 8.7 30.6 ± 8.8 2344 0.83
Education years 16.8 ± 2.2 16.8 ± 2.1 2344 0.49
Unmarried status 259 (22.1) 265 (22.6) 1 0.77
Jobs 1 < 0.01
 Medical staff 1095 (93.4) 1156 (98.6)
 Other medical workers 78 (6.6) 17 (1.4)
Annual household income <11,255 (USD, per head) 787 (67.1) 843 (71.9) 1 0.01
Living alone 205 (17.5) 363 (30.9) 1 < 0.01
Geographic origin 2 < 0.01
 Wuhan City 169 (14.4) 264 (22.5)
 Hubei province (excluding Wuhan City) 690 (58.8) 809 (69.0)
 Other areas in Chinaa 314 (26.8) 100 (8.5)
The exposure of the COVID-19 epidemicb
 Number of cumulative cases 13,886.6 ± 10,018.7 17,982.0 ± 9021.0 2344 < 0.01
 Number of daily new cases 2766.6 ± 4419.5 3994.0 ± 5104.9 2344 < 0.01
 Prevalence (‱) 7.0 ± 12.1 10.3 ± 14.1 2344 < 0.01
Daily incidence (per 10,000) 2.3 ± 5.2 3.5 ± 6.1 2344 < 0.01
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Data are presented as mean ± standard deviation or n (%).

Abbreviations: Other medical workers: support staff, patient care staff and so on; COVID-19: Coronavirus Disease 2019; Medical staff: mainly including doctors and nurses;.

a

Other areas in China: including 22 provinces, 5 autonomous regions, 4 municipalities and 2 special administrative regions.

b

The participants’ exposure to the COVID-19 epidemic was estimated by the regional epidemic parameters.

Table 2 shows the comparison in mental problems, help-seeking behavior and treatment for mental problems between the two groups. Compared with non-frontline medical workers, frontline medical workers had higher rates of any mental problems (52.6% vs. 34.0%, adjusted OR = 1.88, 95% CI = 1.57–2.25), anxiety symptoms (15.7% vs. 7.4%, adjusted OR = 1.95, 95% CI = 1.46–2.61), depressed mood (marginally insignificant; 14.3% vs. 10.1%, adjusted OR = 1.32, 95% CI = 0.99–1.76), and insomnia symptoms (47.8% vs. 29.1%, adjusted OR = 1.96, 95% CI = 1.63–2.36). However, there was no significant difference in suicidal ideation (12.0% vs. 9.0%, adjusted OR = 1.25, 95% CI = 0.92–1.71), help-seeking (4.5% vs. 4.5%, adjusted OR = 1.00, 95% CI = 0.53–1.87) and treatment for mental problems (3.4% vs. 2.3%, adjusted OR = 1.38, 95% CI = 0.54–3.52) between the two groups (Table 2).

4. Discussion

The psychological impact of acute infection outbreaks on medical workers has aroused considerable concern from the government, the public, and medical professionals. The current study has shown that frontline medical workers directly dealing with patients confirmed or suspected of having COVID-19 had a higher level of various mental problems than those non-frontline medical workers. In addition, the two groups had comparable low rates of help-seeking behaviors and treatment for their mental problems.

Data from the present study showed that the mental health of frontline medical workers was particularly worrying. The rate of mental problems, such as anxiety, depression, and insomnia, was significantly increased in frontline medical workers, compared with non-frontline medical workers. In this study, about 15.7% of enrolled frontline medical workers experienced anxiety symptoms, and the prevalence is lower than the general population during the COVID-19 outbreak (28.8% experienced moderate to severe anxiety symptoms) (Wang et al., 2020a, Wang et al., 2020b). Similarly, about 14.3% of enrolled frontline medical workers experienced depressive symptoms, and the prevalence is slightly lower than the general population during the COVID-19 outbreak (16.5% reported moderate to severe depressive symptoms) (Wang et al., 2020a, Wang et al., 2020b). The higher prevalence of anxiety and depression in the general public could be due to less access to personal protection equipment as compared to frontline medical workers.

A great deal of evidence demonstrates the dramatic psychological impact of the epidemic on healthcare workers, and the importance of dedicated interventions to deal with mental problems, such as stress, anxiety, depressive symptoms (Xiang et al., 2020; Kang et al., 2020a, Kang et al., 2020b; Samantha et al., 2020; Liu et al., 2020a, Liu et al., 2020b, Liu et al., 2020c). Our findings are consistent with those reported Zhu et al., who found a significant percentage of psychiatric symptoms during the COVID-19 pandemic, 29.8% for stress, 13.5% for depression, and 24.1% for anxiety among healthcare workers (Zhu et al., 2020). A recent study indicated poor sleep quality among frontline clinical nurses fighting with the COVID-19(Wu et al., 2020). In contrast, a recent study conducted in Singapore found that there was a higher prevalence of anxiety among non-medical healthcare workers compared to medical personnel (Tan et al., 2020). The opposite findings in Singapore could be due to the fact that COVID-19 was a less severe problem in Singapore as compared to China and frontline healthcare workers encountered lower level of anxiety and depression.

Compared with non-frontline medical workers, frontline medical workers might be exposed to much more physical and mental stresses, which may contribute to their higher rates of mental problems. For example, frontline medical workers have had to be extra vigilant when working in the fever clinics or infectious wards, ensuring that suspected patients were timely identified and transferred to the designated hospital to reduce exposure risk for others. In addition, the rapid increase of the infected patients and the uncertainty of transmission in the early stage of the outbreak increased the enormous workload and psychological burden of medical workers (Yang et al., 2020). During the COVID-19 outbreak, many medical staff were infected (Wang et al., 2020a,b), which may have increased the psychological stress of their colleagues. Moreover, inadequate protective materials against the virus, negative emotions from the patients, quarantine, and lack of contact with their families also added to the psychological burden of frontline medical workers. Furthermore, mental problems could interact with each other. For example, sleep disorders were reported to be related to anxiety (Bélanger et al., 2004; Papadimitriou and Linkowski, 2005).

Our results showed poor mental health among frontline medical workers, but contrary to our expectation, we did not observe significantly higher rates of seeking help or receiving treatment for mental problems among these subjects. The phenomenon that medical workers have difficulty accepting and disclosing emotions is not unique to the COVID-19 outbreak (Fridner et al., 2012; King et al., 1992; Tyssen et al., 2004). Emotional distress is common among hospital doctors, many of whom do not seek professional help or support from their colleagues, because they either think they did not need or are embarrassed to seek help and worried about confidentiality (Fridner et al., 2012). These findings remind future psychological intervention providers should pay more attention to medical workers with mental health problems.

The mental health status of medical workers presented in the current study prompts the need for appropriate measures and timely treatment for COVID-19-related psychological problems. According to previous experience with severe infectious diseases (such as SARS and EVD), medical workers with a good awareness of the disease developed relatively fewer psychological symptoms (Chua et al., 2004; Huang et al., 2004; Ji et al., 2017). Therefore, authoritative knowledge about COVID-19 should be disseminated among medical workers as early as possible. Mental health professionals should be deployed in the medical teams to provide psychological support. Furthermore, external material and spiritual support were crucial to confronting psychological symptoms, including virus prevention implementation, living and medical supplies, as well as spiritual support from colleagues, team leaders, family, and friends (Nasser and Overholser, 2005).

Since the start of the COVID-19 outbreak, the Chinese government, hospitals, and psychological and psychiatric centers have taken measurements to address mental health problems (Bao et al., 2020). A national guideline for psychological crisis intervention during the COVID-19 outbreak, in which psychological protection measures for medical workers were provided (National Health Commission of the People's Republic of China 2020b). Psychological intervention teams were set up to deliver mental health services to medical staff. In addition, a variety of online mental health services through communication programs, such as WeChat, Weibo, and TikTok, were gradually put into practice for people in need (Liu et al., 2020a; Zhang et al., 2020a,b). As the development of the epidemic, further psychological support and measurements should be provided, especially for frontline medical workers.

There were several limitations to our study. First, medical workers participated in the investigation via the Internet without random sampling, so the response rate was hard to estimate. However, the relatively large number of participants reduced this potential sampling bias. Second, the mental health status of the participants before the COVID-19 outbreak was not available, making it difficult to know whether their pre-existing mental health status also impacted the posttraumatic morbidity of COVID-19. Third, this study did not address other potential confounding factors, such as personality traits, family history of mental disorders, life events, and social support. Fourth, the case-control nature of the present study did not allow us to make any conclusions regarding causality.

5. Conclusions

The present study highlighted the mental health problems and unmet needs of medical workers during the COVID-19 epidemic in China, especially among frontline medical workers. Further strategies should be provided urgently to alleviate the mental distress of medical workers. Long-term surveillance should be provided to monitor the mental health of frontline and non-frontline medical workers.

Contributors

Qi Cai, Hongliang Feng: involved in study design, performing the study, drafting and revising the manuscript. Meiyao Wang, Qunfeng Wang, Xuanzhen Lu, Jing Pan, Qin Li, Beibei Fu, Yongchao Deng: involved in distributing and recycling questionnaires. Jing Huang, Yu Xie, Xing Wang, Zhenxing Liu, Botong Hou, Keni Ouyang: involved in data analysis. Yumin Liu: involved in study design, revising the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (81371273).

Declaration of Competing Interest

Dr. Hongliang Feng was supported by the Hong Kong Ph.D. Fellowship Scheme of the Research Grants Council (No.: PF16-05347). The other authors have nothing to declare.

Acknowledgements

We are grateful to Professor Jihui Zhang (Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China) for valuable contributions on data processing and the revision of the article. We also thank all the participants in our study.

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