Anxiety and depressive symptoms among COVID-19 patients in Jianghan Fangcang Shelter Hospital in Wuhan, China

Abstract

Fangcang shelter hospitals were established in China during the coronavirus disease 2019 (COVID-19) pandemic as a countermeasure to stop the spread of the disease. To our knowledge, no research has been conducted on mental health problems among patients in Fangcang shelter hospitals. This study aimed to determine the prevalence and major influencing factors of anxiety and depressive symptoms among COVID-19 patients admitted to Fangcang shelter hospitals. From February 23, 2020, to February 26, 2020, we obtained sociodemographic and clinical characteristics information of COVID-19 patients in Jianghan Fangcang Shelter Hospital (Wuhan, China) and assessed their mental health status and sleep quality. Data were obtained with an online questionnaire. The questionnaire consisted of a set of items on demographic characteristics, a set of items on clinical characteristics, the Self-Rating Anxiety Scale, Self-Rating Depression Scale, and Pittsburgh Sleep Quality Index. Three hundred seven COVID-19 patients who were admitted to Jianghan Fangcang Shelter Hospital participated in this study. The prevalence of anxiety and depressive symptoms were 18.6% and 13.4%, respectively. Poor sleep quality and having ≥ two current physical symptoms were independent risk factors for anxiety symptoms. Female sex, having a family member with confirmed COVID-19, and having ≥ two current physical symptoms were independent risk factors for depressive symptoms. Anxiety and depressive symptoms were found to be common among COVID-19 patients in Fangcang Shelter Hospital, with some patients being at high risk.

About the Authors:

Ling-Ling Dai

Roles Conceptualization, Validation, Writing – original draft

Affiliations Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China, Team of Henan National Emergency Medical Rescue, Zhengzhou, China

Xi Wang

Roles Conceptualization, Writing – review & editing

Affiliation: Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China

Tian-Ci Jiang

Roles Conceptualization, Data curation

Affiliation: Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China

Peng-Fei Li

Roles Conceptualization, Data curation

Affiliation: Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China

Yu Wang

Roles Investigation, Writing – review & editing

Affiliation: Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China

Shu-Jun Wu

Roles Formal analysis, Investigation

Affiliation: Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China

Liu-Qun Jia

Roles Formal analysis, Writing – review & editing

Affiliation: Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China

Meng Liu

Roles Data curation, Formal analysis

Affiliation: Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China

Lin An

Roles Formal analysis, Writing – review & editing

Affiliation: Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China

Zhe Cheng

Roles Investigation, Resources, Supervision, Validation, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China, Team of Henan National Emergency Medical Rescue, Zhengzhou, China

ORCID logo http://orcid.org/0000-0002-0894-2444

Abstract

Fangcang shelter hospitals were established in China during the coronavirus disease 2019 (COVID-19) pandemic as a countermeasure to stop the spread of the disease. To our knowledge, no research has been conducted on mental health problems among patients in Fangcang shelter hospitals. This study aimed to determine the prevalence and major influencing factors of anxiety and depressive symptoms among COVID-19 patients admitted to Fangcang shelter hospitals. From February 23, 2020, to February 26, 2020, we obtained sociodemographic and clinical characteristics information of COVID-19 patients in Jianghan Fangcang Shelter Hospital (Wuhan, China) and assessed their mental health status and sleep quality. Data were obtained with an online questionnaire. The questionnaire consisted of a set of items on demographic characteristics, a set of items on clinical characteristics, the Self-Rating Anxiety Scale, Self-Rating Depression Scale, and Pittsburgh Sleep Quality Index. Three hundred seven COVID-19 patients who were admitted to Jianghan Fangcang Shelter Hospital participated in this study. The prevalence of anxiety and depressive symptoms were 18.6% and 13.4%, respectively. Poor sleep quality and having ≥ two current physical symptoms were independent risk factors for anxiety symptoms. Female sex, having a family member with confirmed COVID-19, and having ≥ two current physical symptoms were independent risk factors for depressive symptoms. Anxiety and depressive symptoms were found to be common among COVID-19 patients in Fangcang Shelter Hospital, with some patients being at high risk.

Figures

Fig 1

Table 1

Table 2

Fig 1

Table 1

Table 2

Fig 1

Table 1

Table 2

Citation: Dai L-L, Wang X, Jiang T-C, Li P-F, Wang Y, Wu S-J, et al. (2020) Anxiety and depressive symptoms among COVID-19 patients in Jianghan Fangcang Shelter Hospital in Wuhan, China. PLoS ONE 15(8): e0238416. https://doi.org/10.1371/journal.pone.0238416

Editor: Amir H. Pakpour, Qazvin University of Medical Sciences, ISLAMIC REPUBLIC OF IRAN

Received: June 23, 2020; Accepted: August 16, 2020; Published: August 28, 2020

Copyright: © 2020 Dai et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

Originating as a cluster of unexplained cases of pneumonia, coronavirus disease 2019 (COVID-19) was first identified in Wuhan, Hubei Province, China in December 2019 [1]. Spreading rapidly worldwide, the COVID-19 pandemic is a global health threat with devastating consequences that can potentially impact the citizens of all nations [2].

Widespread outbreaks of infectious diseases, such as Ebola virus disease and severe acute respiratory syndrome, are not only associated with physical illness but also with psychological distress and symptoms of mental illness [3, 4]. Results from prospective studies have consistently suggested that psychological distress is a predictor of future health and disease outcomes [5]. As with other infectious diseases, preliminary evidence suggests that COVID-19 also causes public panic and mental health stress; symptoms of anxiety and depression are common psychological reactions to the COVID-19 pandemic, and may be associated with sociodemographic factors and sleep quality [6–9]. However, previous studies have focused mainly on COVID-19-related mental health issues among the general population, medical staff, children, pregnant women with their husbands, people with mental illness and individuals in self-isolation [10–13]. We know very little about the psychological effects of the disease on patients with COVID-19 [14].

To control the spread of infection and save lives, China has implemented COVID-19 countermeasures, including the establishment of Fangcang shelter hospitals in Hubei Province [15]. Fangcang shelter hospitals are a novel public health concept. These hospitals were established in China to assist in the country’s management of COVID-19 [16]. The Fangcang shelter hospitals are large, temporary hospitals built by converting public venues, such as stadiums and exhibition centers, into healthcare facilities to receive non-seriously ill individuals with positive SARS-CoV-2 tests from their families and communities, while providing disease monitoring, medical care, food, shelter, and social activities [16,17]. Fangcang shelter hospitals have been crucial to the quick containment of COVID-19 in China, relieving some of the enormous pressure on the healthcare system, and providing an encouraging example for other countries [18]. As the COVID-19 pandemic spreads globally, some countries, such as Serbia, have also built Fangcang shelter hospitals. Moreover, other countries, such as Iran, the United States, the United Kingdom, and Spain, have implemented similar measures [16].

Based on the evidence from previous research on the general population and on medical staff, we speculate that the mental health of the Fangcang shelter hospital patients is affected by the COVID-19 pandemic. To our knowledge, no previous studies have been conducted on the mental health of Fangcang shelter hospital patients during the COVID-19 pandemic. A better understanding of the psychosocial problems of Fangcang shelter hospital patients can provide important guidance in carrying out timely psychological interventions for targeted populations in need and in the management of the Fangcang shelter hospitals in any future outbreaks. Therefore, this study aimed to determine the prevalence and major influencing factors of anxiety and depressive symptoms among COVID-19 patients admitted to Fangcang shelter hospitals.

2. Methods

2.1 Design, setting, and participants

This was a cross-sectional study performed via an anonymous online questionnaire from February 23, 2020, to February 26, 2020, in Jianghan Fangcang Shelter Hospital in Wuhan, China. The study was designed and conducted by doctors who worked at the hospital, and was approved by the ethics committees of the First Affiliated Hospital of Zhengzhou University (no.2020-KY-169). All study respondents were made aware that participation in the study was voluntary and provided prior written informed consent online.

The inclusion criterion was a COVID-19 diagnosis based on the guidelines of the National Health Commission of the People’s Republic of China [19]. Exclusion criteria included a previously diagnosed severe psychiatric illness (e.g., schizophrenia, bipolar disorder, anxiety disorder, or depression disorder), inability to complete or failure to complete the online questionnaire, currently taking oral medication for a chronic disease (e.g., metoprolol, reserpine, prednisone, and methylprednisolone) that can cause side effects associated with anxiety, depression, and insomnia [20–22].

2.2 Measures

The participants scanned the quick response codes with their mobile phones and completed the questionnaires. The study questionnaire consisted of five main components: a set of items on demographic characteristics, a set of items on clinical characteristics, the Self-Rating Anxiety Scale (SAS), the Self-Rating Depression Scale (SDS), and the Pittsburgh Sleep Quality Index (PSQI).

Using the questionnaire, we collected data on the physical symptoms and comorbidities that had been discussed in previous literature [23]. Participants were asked to indicate whether they were currently experiencing any of the 14 listed physical symptoms (fever, coughing, sputum production, shortness of breath, chest pain, fatigue, soreness or discomfort in the throat, nasal congestion, conjunctival congestion, hemoptysis, headache, diarrhea, abdominal pain, myalgia, and arthralgia) or had any of the 9 listed comorbidities (chronic bronchitis or chronic obstructive pulmonary disease, asthma, hypertension, diabetes, coronary heart disease, cerebrovascular disease, connective tissue diseases, chronic renal disease, and cancer).

Anxiety and depressive symptoms were assessed using the Chinese versions of the SAS and SDS. The Chinese versions of the SAS and SDS have been proven to be effective instruments and have good psychometric properties when used in China (Cronbach's α coefficient was 0.82 and, 0.83 respectively) [24,25]. The SAS and SDS both contain 20 items, with responses based on a 4-point scale. For both scales, each question is based on mood experiences in the previous 7 days. An aggregate score of 20 is multiplied by 1.25, with higher scores indicating more severe levels of anxiety and depression [26]. Cutoff scores of ≥50 in SAS and ≥53 in SDS represent a positive screen for depression and anxiety symptoms [26].

Sleep quality was assessed using the Chinese version of the PSQI. The Chinese version of the PSQI has adequate reliability, with an internal consistency Cronbach’s α of 0.77 to 0.84 [27]. The PSQI consists of seven domains: sleep quality, sleep duration, sleep latency, habitual sleep efficiency, sleep disturbance, use of sleeping medications, and daytime dysfunction [28]. Responses to each item are based on a 3-point scale, with the total score ranging from 0 to 21. Higher scores indicate lower sleep quality. Poor sleep quality was defined as a total score ≥6 [29].

2.3 Statistical analysis

All statistical analyses were performed using IBM SPSS version 25 (IBM Corporation, Armonk, NY, USA). Continuous data that were normally distributed were presented as mean ± standard deviation, non-normally distributed data were described as median and first, third quartile: M (Q1, Q3); t-tests were used to compare the normal distribution of continuous data. Univariate analyses of anxiety and depression symptoms were performed using the chi-squared (χ2) test. Covariates with P <0.10 in the univariate analyses were included in the multivariate analyses. The multivariable logistic regression models were built using the forward LR variable selection method to identify independent factors associated with anxiety and depression. A P-value <0.05 was considered statistically significant.

3. Results

3.1 General characteristics and prevalence of anxiety and depressive symptoms

A total of 307 patients participated in the study. Among them, 57 (18.6%) experienced anxiety symptoms, and 41 (13.4%) experienced depressive symptoms. Two hundred sixty (84.7%) had poor sleep quality, as determined with the PSQI. The three most common coexisting illnesses were hypertension (16.0%), chronic bronchitis or chronic obstructive pulmonary disease (13.0%), and diabetes (4.6%), as shown in Fig 1A. There were 20 currently asymptomatic patients. The three most common current physical symptoms were coughing (26.4%), shortness of breath (24.4%), and soreness or discomfort in the throat (17.9%) (see Fig 1B).

[Figure omitted. See PDF.]

Fig 1. Histogram of the frequency distribution of comorbidities and current physical symptoms.

a: Histogram of the frequency distribution of comorbidities of patients in Jianghan Fangcang Shelter Hospital in Wuhan, China. b: Histogram of the frequency distribution of current physical symptoms of patients in Jianghan Fangcang Shelter Hospital in Wuhan, China. COPD: Chronic obstructive pulmonary disease.

https://doi.org/10.1371/journal.pone.0238416.g001

Data on the demographic and clinical characteristics of the patients, and on the differences in incidence of anxiety and depressive symptoms among different groups are shown in Table 1. Based on covariates with P < 0.10 as screening covariates, having a family member who has been confirmed with COVID-19, number of current physical symptoms, symptoms change after hospitalization, and poor sleep quality were the related factors of anxiety symptoms, and gender, education level, smoking history, drinking history, having a family member who has been confirmed COVID-19, number of current physical symptoms, symptoms change after hospitalization, and poor sleep quality were the related factors of depressive symptoms (see Table 1).

[Figure omitted. See PDF.]

Table 1. General characteristics of the sample.

https://doi.org/10.1371/journal.pone.0238416.t001

3.2 Risk factors for anxiety and depressive symptoms

Results of the multivariate logistic regression analyses to determine the risk factors for anxiety and depressive symptoms are presented in Table 2. Poor sleep quality (odds ratio [OR], 3.655, 95% confidence interval [CI], 1.074–12.433; P = 0.038) and having ≥ two current physical symptoms (OR, 3.504; 95% CI, 1.919–6.398; P < 0.01) were independent risk factors for anxiety symptoms. The Omnibus Test of Model Coefficients showed that the model was significant, (χ2 = 23.905, P < 0.001). The Hosmer and Lemeshow test showed that the model had perfect goodness of fit (χ2 = 0.118, P = 0.943; see Table 2). Female sex (OR, 5.878; 95% CI, 2.657–13.005; P < 0.001), having a family member with confirmed COVID-19 (OR, 2.81; 95% CI, 1.337–5.911; P = 0.006), having ≥ two current physical symptoms (OR, 4.145; 95% CI, 1.994–8.616; P < 0.001) were independent risk factors for depressive symptoms. The Omnibus Test of Model Coefficients showed that model was significant, (χ2 = 40.508, P < 0.001). The Hosmer and Lemeshow test showed that the model had perfect goodness of fit (χ2 = 4.344, P = 0.630, see Table 2).

[Figure omitted. See PDF.]

Table 2. Multivariate logistic regression analysis of factors influencing anxiety and depressive symptoms.

https://doi.org/10.1371/journal.pone.0238416.t002

4. Discussion

This cross-sectional study examined the prevalence of anxiety, depression, and poor sleep quality among 307 patients in Jianghan Fangcang Shelter Hospital in Wuhan, China, 2 months after the start of the COVID-19 pandemic. Of all the participants, 18.57%, 13.36%, and 84.69% had anxiety symptoms, depressive symptoms, and poor sleep quality, respectively. In addition, using one-sample-tests, it was determined that both SAS (42.92±7.30) and SDS (39.77±10.11) scores of the participants of our study were higher than Chinese norms (SAS, 29.78±10.07, n = 1158; SDS, 33.46±8.55, n = 1340) (both P<0.001) [26], indicating more severe levels of anxiety and depressive symptoms among COVID-19 patients admitted to Fangcang hospitals, compared with the general public. Clearly, anxiety and depressive symptoms were common responses to the COVID-19 outbreak, and patients in the Jianghan Fangcang Shelter Hospital had severe levels of anxiety and depressive symptoms. The reason for this may be related to many factors: differing viewpoints on mask wearing, misperceptions in society, shortage of personal protective equipment, uncertainty about the progression of the pandemic, and fear of a difficult recovery from the disease [30–33].

In one previous Chinese study conducted in the initial stage of the pandemic, which reported a high prevalence of moderate to severe depressive symptoms, anxiety symptoms were found to be 16.5% and 28.8% among the general population, respectively [8]. In another Chinese study, the prevalence of anxiety and depressive symptoms among healthcare workers treating patients with COVID-19 was 44.6% and 50.4%, respectively [34]. This is in sharp contrast to the low prevalence of anxiety and depressive symptoms found in the present study. However, one Chinese study conducted within the same study period as that of the present study reported prevalence rates of anxiety and depressive symptoms among all the participants (including medical health workers and nonmedical health workers) of 10.4% and 10.6%, respectively [35]. Therefore, differences in prevalence rates may be due to differences in study periods. With the COVID-19 pandemic, the government of China has provided appropriate information and knowledge in a timely manner. Transparency and open communication can efficiently lower fear, anxiety, stigmatization, and discrimination [36]. Moreover, the National Health Commission of China has performed psychological crisis intervention through the general deployment of disease prevention and mental health professionals and expert groups providing psychological intervention for different subpopulations, including patient isolation in Fangcang shelter hospitals [16, 37]. Early psychological crisis intervention has reduced the prevalence of negative psychological outcomes caused by the COVID-19 outbreak.

Results of the multivariate logistic regression analyses indicated that poor sleep quality and having more current physical symptoms were risk factors for anxiety symptoms among patients in Fangcang shelter hospitals. Sleep provides time for the recuperation and rejuvenation of the brain. A substantial body of literature has shown that stressful life events and outbreaks of infectious diseases, including COVID-19, can affect sleep quality [34, 38–41], and 84.69% of the participants in the present study had poor sleep quality. Syntheses of longitudinal studies suggested that sleep quality was bidirectionally related to anxiety [42]. There is a large amount of data on the effects of sleep quality on anxiety symptoms in other populations, such as shift workers, firefighters, paramedics, pregnant females, and older adults. Poor sleep quality was found to be associated with higher risk for anxiety symptoms, and greater anxiety was found to be associated with poorer sleep quality [43–47]. Similarly, anxiety affects sleep quality because anxious people find it hard to fall asleep and wake up frequently [42]. In addition, the present study demonstrated that patients with more physical symptoms of COVID-19 were more vulnerable to anxiety symptoms. possible reasons are as follows: First, common symptoms of COVID-19, such as fever, shortness of breath, and headache can induce anxiety symptoms [48]. Second, patients with more symptoms are generally more serious than asymptomatic patients, and the prevalence of anxiety is also related to the severity of the disease [49,50]. Last, patients with more symptoms are more concerned about the progression of the illness.

Another finding from the present study was that females, patients with family member with confirmed COVID-19, and patients with more current physical symptoms were more likely to have anxiety symptoms. As early as the 1970s, Weissman underscored the gender differences in depression, and noted that females were more likely to experience depression than males [51]. Since then, there has been a proliferation of research and theories on gender differences in depression. One recent meta-analysis showed that females are more vulnerable to depression disorders and depression symptoms [52]. There is now a consensus that gender differences in depression have a multifactorial etiology; for example, there is a confluence of hormonal and neurodevelopmental changes that vary by sex during the pubertal transition and may influence gender differences in depression [52].

In addition, patients with family members diagnosed with COVID-19 were more vulnerable to depressive symptoms, owing to greater family burden and psychological distress [53, 54]. Compared with patients with less physical symptoms, patients with more physical symptoms were more likely to have depressive symptoms because they were more severe and the prevalence of depressive symptoms in relation to the severity of the disease [50].

This study had some limitations. First, this was a cross-sectional study, conducted within a short time frame. Therefore, future longitudinal studies are needed for follow-up and intervention. Second, psychological assessment was based on an online survey with self-report tools that had not been specifically designed for use with COVID-19 patients [55–57]. The use of clinical interviews and instruments designed specifically for COVID-19 patients is encouraged in future studies, in order to produce more comprehensive findings. Third, this was not a multinational, multicenter study, and therefore, further research is needed to produce more data on anxiety and depressive symptoms among patients in Fangcang shelter hospitals.

5. Conclusion

This study identified the prevalence rates and risk factors of anxiety and depressive symptoms among patients in Fangcang shelter hospitals. Anxiety and depressive symptoms were found to be common among the COVID-19 patients in the hospitals. Those with more physical symptoms and poor sleep quality demonstrated more vulnerability to anxiety symptoms. Females, patients with family members who had been diagnosed with COVID-19, and patients with more current physical symptoms were more vulnerable to depressive symptoms. The poorer the sleep quality, the more serious the symptoms of anxiety and depression. Our findings can aid in the development of interventions to reduce the adverse psychological impact of the COVID-19 pandemic on patients in Fangcang shelter hospitals in the future.

Supporting information

[Figure omitted. See PDF.]

S1 Appendix. Data of this research for the values behind the means, standard deviations and other measures reported.

https://doi.org/10.1371/journal.pone.0238416.s001

(XLSX)

Acknowledgments

The authors would like to thank all the patients who participated in this study and Editage (www.editage.com) for English language editing.

Citation: Dai L-L, Wang X, Jiang T-C, Li P-F, Wang Y, Wu S-J, et al. (2020) Anxiety and depressive symptoms among COVID-19 patients in Jianghan Fangcang Shelter Hospital in Wuhan, China. PLoS ONE 15(8): e0238416. https://doi.org/10.1371/journal.pone.0238416

References

1. Nishiura H, Jung SM, Linton NM, Kinoshita R, Yang Y, Hayashi K et al. The Extent of Transmission of Novel Coronavirus in Wuhan, China, 2020. J Clin Med. 2020;9(2). https://doi.org/10.3390/jcm9020330.

2. Rajkumar RP. Ayurveda and COVID-19: where psychoneuroimmunology and the meaning response meet. Brain Behav Immun. 2020. https://doi.org/10.1016/j.bbi.2020.04.056.

3. James PB, Wardle J, Steel A, Adams J. Post-Ebola psychosocial experiences and coping mechanisms among Ebola survivors: a systematic review. Trop Med Int Health. 2019;24(6):671–91. pmid:30843627

4. Gardner PJ, Moallef P. Psychological impact on SARS survivors: Critical review of the English language literature. Canadian Psychology/Psychologie canadienne. 2015;56(1):123–35.

5. Turner AI, Smyth N, Hall SJ, Torres SJ, Hussein M, Jayasinghe SU et al. Psychological stress reactivity and future health and disease outcomes: A systematic review of prospective evidence. Psychoneuroendocrinology. 2020;114:104599. pmid:32045797

6. Bao Y, Sun Y, Meng S, Shi J, Lu L. 2019-nCoV epidemic: address mental health care to empower society. Lancet. 2020;395(10224):e37–e8. pmid:32043982

7. Zhou SJ, Zhang LG, Wang LL, Guo ZC, Wang JQ, Chen JC et al. Prevalence and socio-demographic correlates of psychological health problems in Chinese adolescents during the outbreak of COVID-19. Eur Child Adolesc Psychiatry. 2020. https://doi.org/10.1007/s00787-020-01541-4.

8. Wang C, Pan R, Wan X, Tan Y, Xu L, Ho CS et al. Immediate Psychological Responses and Associated Factors during the Initial Stage of the 2019 Coronavirus Disease (COVID-19) Epidemic among the General Population in China. Int J Environ Res Public Health. 2020;17(5). https://doi.org/10.3390/ijerph17051729.

9. Huang Y, Zhao N. Chinese mental health burden during the COVID-19 pandemic. Asian J Psychiatr. 2020;51:102052. pmid:32361387

10. Rajkumar RP. COVID-19 and mental health: A review of the existing literature. Asian J Psychiatr. 2020;52:102066. pmid:32302935

11. Chen IH, Chen CY, Pakpour AH, Griffiths MD, Lin CY. Internet-Related Behaviors and Psychological Distress Among Schoolchildren During COVID-19 School Suspension [published online ahead of print, 2020 Jun 26]. J Am Acad Child Adolesc Psychiatry. 2020; S0890-8567(20)30385-3. https://doi.org/10.1016/j.jaac.2020.06.007.

12. Ahorsu DK, Imani V, Lin CY, Timpka T, Broström A, Updegraff JA et al. Associations between fear of COVID-19, mental health, and preventive behaviours across pregnant women and husbands: An actor-partner interdependence modelling. Int J Ment Health Addict. 2020.

13. Chang KC, Hou WL, Pakpour AH, Lin CY, Griffiths MD. Psychometric testing of three COVID-19-related scales among people with mental illness. Int J Ment Health Addict. 2020.

14. Yuan R, Xu QH, Xia CC, Lou CY, Xie Z, Ge QM et al. Psychological status of parents of hospitalized children during the COVID-19 epidemic in China. Psychiatry Res. 2020;288:112953. pmid:32302814

15. Peng F, Tu L, Yang Y, Hu P, Wang R, Hu Q et al. Management and Treatment of COVID-19: The Chinese Experience. Canadian Journal of Cardiology. 2020. https://doi.org/10.1016/j.cjca.2020.04.010.

16. Chen S, Zhang Z, Yang J, Wang J, Zhai X, Bärnighausen T et al. Fangcang shelter hospitals: a novel concept for responding to public health emergencies. Lancet. 2020. https://doi.org/10.1016/s0140-6736(20)30744-3.

17. Wang X, Fang J, Zhu Y, Chen L, Ding F, Zhou R et al. Clinical characteristics of non-critically ill patients with novel coronavirus infection (COVID-19) in a Fangcang Hospital. Clin Microbiol Infect. 2020.

18. Prem K, Liu Y, Russell TW, Kucharski AJ, Eggo RM, Davies N et al. The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study. Lancet Public Health. 2020. https://doi.org/10.1016/s2468-2667(20)30073-6.

19. National Health Commission of the People’s Republic of China. Diagnostic and treatment protocol for Novel Coronavirus Pneumonia (Trial version 6). (in chinese). 19 Feb 2020. http://www.nhc.gov.cn/yzygj/s7653p/202002/8334a8326dd94d329df351d7da8aefc2.shtml. Accessed 20 Feb 2020. 2020.

20. Munjampalli SK, Davis DE. Medicinal-Induced Behavior Disorders. Neurol Clin. 2016;34(1):133–169. pmid:26613997

21. Liu X, Lou X, Cheng X, Meng Y. Impact of metoprolol treatment on mental status of chronic heart failure patients with neuropsychiatric disorders. Drug Des Devel Ther. 2017;11:305–312. Published 2017 Jan 25. pmid:28182127

22. Joëls M. Corticosteroids and the brain. J Endocrinol. 2018;238(3):R121–R130. pmid:29875162

23. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020. https://doi.org/10.1056/NEJMoa2002032.

24. Yu Y, Yang JP, Shiu CS, et al. Psychometric testing of the Chinese version of the Medical Outcomes Study Social Support Survey among people living with HIV/AIDS in China. Appl Nurs Res. 2015;28(4):328–333. pmid:26608434

25. Chen IH, Lin CY, Zheng X, Griffiths MD. Assessing Mental Health for China's Police: Psychometric Features of the Self-Rating Depression Scale and Symptom Checklist 90-Revised. Int J Environ Res Public Health. 2020;17(8):2737.

26. Li L, Wang BQ, Gao TH, Tian J. Assessment of psychological status of inpatients with head and neck cancer before surgery. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi. 2018;53(1):21–6. pmid:29365375

27. Zhu B, Xie M, Park CG, Kapella MC. Adaptation of the Pittsburgh Sleep Quality Index in Chinese adults with type 2 diabetes. J Chin Med Assoc. 2018;81(3):242–247. pmid:29258729

28. Soldatos CR, Paparrigopoulos TJ. Sleep physiology and pathology: Pertinence to psychiatry. International Review of Psychiatry. 2005;17(4):213–28. pmid:16194793

29. Chen HC, Hsu NW, Chou P. Subgrouping Poor Sleep Quality in Community-Dwelling Older Adults with Latent Class Analysis—The Yilan Study, Taiwan. Sci Rep. 2020;10(1):5432. pmid:32214167

30. Huang Y, Zhao N. Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 outbreak in China: a web-based cross-sectional survey. Psychiatry Res. 2020;288:112954. pmid:32325383

31. Rieger MO. To wear or not to wear? Factors influencing wearing face masks in Germany during the COVID-19 pandemic. Soc Health Behav. 2020;3:50–4.

32. Lin CY. Social reaction toward the 2019 novel coronavirus (COVID-19). Soc Health Behav. 2020;3:1–2.

33. Shrivastava SR, Shrivastava PS. COVID-19 pandemic: Responding to the challenge of global shortage of personal protective equipment. Soc Health Behav. 2020;3:70–1.

34. Lai J, Ma S, Wang Y, Cai Z, Hu J, Wei N et al. Factors Associated With Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019. JAMA Netw Open. 2020;3(3): e203976. pmid:32202646

35. Zhang WR, Wang K, Yin L, Zhao WF, Xue Q, Peng M et al. Mental Health and Psychosocial Problems of Medical Health Workers during the COVID-19 Epidemic in China. Psychother Psychosom. 2020. https://doi.org/10.1159/000507639.

36. Lin MW, Cheng Y. Policy actions to alleviate psychosocial impacts of COVID-19 pandemic: Experiences from Taiwan. Soc Health Behav 2020;3:72–3.

37. Li W, Yang Y, Liu ZH, Zhao YJ, Zhang Q, Zhang L et al. Progression of Mental Health Services during the COVID-19 Outbreak in China. Int J Biol Sci. 2020;16(10):1732–8. pmid:32226291

38. Li Y, Gu S, Wang Z, Li H, Xu X, Zhu H et al. Relationship Between Stressful Life Events and Sleep Quality: Rumination as a Mediator and Resilience as a Moderator. Front Psychiatry. 2019;10:348. pmid:31191370

39. Lotsch F, Schnyder J, Goorhuis A, Grobusch MP. Neuropsychological long-term sequelae of Ebola virus disease survivors—A systematic review. Travel Med Infect Dis. 2017;18:18–23. pmid:28478336

40. Chen R, Chou KR, Huang YJ, Wang TS, Liu SY, Ho LY. Effects of a SARS prevention programme in Taiwan on nursing staff's anxiety, depression and sleep quality: a longitudinal survey. Int J Nurs Stud. 2006;43(2):215–25. pmid:15927185

41. Chew NWS, Lee GKH, Tan BYQ, Jing M, Goh Y, Ngiam NJH et al. A multinational, multicentre study on the psychological outcomes and associated physical symptoms amongst healthcare workers during COVID-19 outbreak. Brain Behav Immun. 2020. https://doi.org/10.1016/j.bbi.2020.04.049.

42. Alvaro PK, Roberts RM, Harris JK. A Systematic Review Assessing Bidirectionality between Sleep Disturbances, Anxiety, and Depression. Sleep. 2013;36(7):1059–68. pmid:23814343

43. Khan WAA, Conduit R, Kennedy GA, Jackson ML. The relationship between shift-work, sleep, and mental health among paramedics in Australia. Sleep Health. 2020. https://doi.org/10.1016/j.sleh.2019.12.002.

44. Sanchez SE, Friedman LE, Rondon MB, Drake CL, Williams MA, Gelaye B. Association of stress-related sleep disturbance with psychiatric symptoms among pregnant women. Sleep Med. 2020;70:27–32. pmid:32193051

45. Carey MG, Al-Zaiti SS, Dean GE, Sessanna L, Finnell DS. Sleep problems, depression, substance use, social bonding, and quality of life in professional firefighters. J Occup Environ Med. 2011;53(8):928–33. pmid:21785370

46. Brown JP, Martin D, Nagaria Z, Verceles AC, Jobe SL, Wickwire EM. Mental Health Consequences of Shift Work: An Updated Review. Curr Psychiatry Rep. 2020;22(2):7. pmid:31955278

47. Gould CE, Spira AP, Liou-Johnson V, Cassidy-Eagle E, Kawai M, Mashal N et al. Association of Anxiety Symptom Clusters with Sleep Quality and Daytime Sleepiness. J Gerontol B Psychol. Series B, 2018;73(3):413–20. https://doi.org/10.1093/geronb/gbx020.

48. Fitzgerald PJ. Serious infection may systemically increase noradrenergic signaling and produce psychological effects. Med Hypotheses. 2020;139:109692. pmid:32234608

49. da Silva AM, Vilhena E, Lopes A, Santos E, Gonçalves MA, Pinto C et al. Depression and anxiety in a Portuguese MS population: Associations with physical disability and severity of disease. J Neurol Sci. 2011;306(1):66–70. https://doi.org/10.1016/j.jns.2011.03.042.

50. Piontek K, Ketels G, Albrecht R, Schnurr U, Dybowski C, Brunahl CA et al. Somatic and psychosocial determinants of symptom severity and quality of life in male and female patients with chronic pelvic pain syndrome. J Psychosom Res. 2019;120:1–7. pmid:30929698

51. Weissman MM, Klerman GL. Sex differences and the epidemiology of depression. Arch Gen Psychiatry. 1977;34(1):98–111. pmid:319772

52. Salk RH, Hyde JS, Abramson LY. Gender differences in depression in representative national samples: Meta-analyses of diagnoses and symptoms. Psychol Bull. 2017;143(8):783–822. pmid:28447828

53. Jo M, Song MK, Knafl GJ, Beeber L, Yoo YS, Van Riper M. Family-clinician communication in the ICU and its relationship to psychological distress of family members: A cross-sectional study. Int J Nurs Stud. 2019;95:34–9. pmid:31005678

54. Van der Werf HM, Luttik MLA, Francke AL, Roodbol PF, Paans W. Students growing up with a chronically ill family member; a survey on experienced.

55. Lee SA. Coronavirus Anxiety Scale: A brief mental health screener for COVID-19 related anxiety. Death Stud. 2020;44:393–401. pmid:32299304

56. Lee SA. How much “Thinking” about COVID-19 is clinically dysfunctional? [published online ahead of print]. Brain Behav Immun. 2020. pmid:32353520

57. Ahorsu DK, Lin C-Y, Imani V, Saffari M, Griffiths MD, Pakpour AH. The Fear of COVID-19 Scale: 57. Development and initial validation [published online ahead of print]. Int J Ment Health Addict. 2020.