Network Analysis of Insomnia in Chinese Mental Health Professionals During the COVID-19 Pandemic: A Cross-Sectional Study

Wei Bai; Yanjie Zhao; Fengrong An; Qinge Zhang; Sha Sha; Teris Cheung; Calvin Pak-Wing Cheng; Chee H Ng; Yu-Tao Xiang

doi:10.2147/NSS.S326880

Network Analysis of Insomnia in Chinese Mental Health Professionals During the COVID-19 Pandemic: A Cross-Sectional Study

Nat Sci Sleep. 2021 Oct 28:13:1921-1930. doi: 10.2147/NSS.S326880. eCollection 2021.

Authors

Wei Bai^#^{1

2

3}, Yanjie Zhao^#^{1

2

3}, Fengrong An^#⁴, Qinge Zhang^#⁴, Sha Sha^#⁴, Teris Cheung⁵, Calvin Pak-Wing Cheng⁶, Chee H Ng⁷, Yu-Tao Xiang^{1

2

3}

Affiliations

¹ Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, People's Republic of China.
² Centre for Cognitive and Brain Sciences, University of Macau, Macao SAR, People's Republic of China.
³ Institute of Advanced Studies in Humanities and Social Sciences, University of Macau, Macao SAR, People's Republic of China.
⁴ The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, School of Mental Health, Beijing, People's Republic of China.
⁵ School of Nursing, Hong Kong Polytechnic University, Hong Kong SAR, People's Republic of China.
⁶ Department of Psychiatry, University of Hong Kong, Hong Kong SAR, People's Republic of China.
⁷ Department of Psychiatry, The Melbourne Clinic and St Vincent's Hospital, University of Melbourne, Richmond, VIC, Australia.

^# Contributed equally.

Abstract

Purpose: The coronavirus disease 2019 (COVID-19) pandemic is associated with increased risk of insomnia symptoms (insomnia hereafter) in health-care professionals. Network analysis is a novel approach in linking mechanisms at the symptom level. The aim of this study was to characterize the insomnia network structure in mental health professionals during the COVID-19 pandemic.

Patients and methods: A total of 10,516 mental health professionals were recruited from psychiatric hospitals or psychiatric units of general hospitals nationwide between March 15 and March 20, 2020. Insomnia was assessed with the insomnia severity index (ISI). Centrality index (ie, strength) was used to identify symptoms central to the network. The stability of network was examined using a case-dropping bootstrap procedure. The network structures between different genders were also compared.

Results: The overall network model showed that the item ISI7 (interference with daytime functioning) was the most central symptom in mental health professionals with the highest strength. The network was robust in stability and accuracy tests. The item ISI4 (sleep dissatisfaction) was connected to the two main clusters of insomnia symptoms (ie, the cluster of nocturnal and daytime symptoms). No significant gender network difference was found.

Conclusion: Interference with daytime functioning was the most central symptom, suggesting that it may be an important treatment outcome measure for insomnia. Appropriate treatments, such as stimulus control techniques, cognitive behavioral therapy and relaxation training, could be developed. Moreover, addressing sleep satisfaction in treatment could simultaneously ameliorate daytime and nocturnal symptoms.

Keywords: COVID-19; SARS-CoV-2; insomnia; physicians; sleep.

Grants and funding

The study was supported by the National Science and Technology Major Project for investigational new drug (2018ZX09201-014), the Beijing Municipal Science & Technology Commission (No. Z181100001518005), the University of Macau (MYRG2019-00066-FHS), Faculty-allocated funds for PIs (FAF), and the Fundamental Research Funds for the Central Universities (2020YJ065).