Network Analysis of Comorbid Anxiety and Insomnia Among Clinicians with Depressive Symptoms During the Late Stage of the COVID-19 Pandemic: A Cross-Sectional Study

Hong Cai, Yan Jie Zhao, Xiaomeng Xing, Tengfei Tian, Wang Qian, Sixiang Liang, Zhe Wang, Teris Cheung, Zhaohui Su, Yi Lang Tang, Chee H. Ng, Sha Sha, Yu Tao Xiang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)

Abstract

Background: A high proportion of clinicians experienced common anxiety, insomnia and depression during the COVID-19 pandemic. This study examined the item-level association of comorbid anxiety and insomnia symptoms among clinicians who suffered from depressive symptoms during the late stage of the COVID-19 pandemic using network analysis (NA). Methods: Clinicians with depressive symptoms (with a Patients Health Questionnaire (PHQ-9) total score of 5 and above) were included in this study. Anxiety and insomnia symptoms were measured using the Generalized Anxiety Disorder Scale-7-item (GAD-7) and Insomnia Severity Index (ISI), respectively. Network analysis was conducted to investigate the network structure, central symptoms, bridge symptoms, and network stability of these disturbances. Expected influence (EI) was used to measure the centrality of index. Results: Altogether, 1729 clinicians were included in this study. The mean age was 37.1 [standard deviation (SD)=8.04 years], while the mean PHQ-9 total score was 8.42 (SD=3.33), mean GAD-7 total score was 6.45 (SD=3.13) and mean ISI total score was 8.23 (SD=5.26). Of these clinicians, the prevalence of comorbid anxiety symptoms (GAD-7≥5) was 76.8% (95% CI 74.82–78.80%), while the prevalence of comorbid insomnia symptoms (ISI≥8) was 43.8% (95% CI: 41.50–46.18%). NA revealed that nodes ISI7 (“Interference with daytime functioning”) (EI=1.18), ISI4 (“Sleep dissatisfaction”) (EI=1.08) and ISI5 (“Noticeability of sleep problem by others”) (EI=1.07) were the most central (influential) symptoms in the network model of comorbid anxiety and insomnia symptoms in clinicians. Bridge symptoms included nodes PHQ3 (“Sleep”) (bridge EI=0.55) and PHQ4 (“Fatigue”) (bridge EI=0.49). Gender did not significantly influence the network structure, but “having the experience of caring for COVID-19 patients” significantly influenced the network structure. Conclusion: Central symptoms and key bridge symptoms identified in this NA should be targeted in the treatment and preventive measures for clinicians suffering from comorbid anxiety, insomnia and depressive symptoms during the late stage of the COVID-19 pandemic.

Original languageEnglish
Pages (from-to)1351-1362
Number of pages12
JournalNature and Science of Sleep
Volume14
DOIs
Publication statusPublished - Aug 2022

Keywords

  • anxiety
  • depression
  • health personnel
  • network analysis
  • sleep

ASJC Scopus subject areas

  • Applied Psychology
  • Behavioral Neuroscience

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