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Status | 已發表Published |
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 | |
Cai, Hong1,2,3; Zhao, Yan Jie1,2,3; Xing, Xiaomeng4; Tian, Tengfei4; Qian, Wang4; Liang, Sixiang4; Wang, Zhe4; Cheung, Teris5; Su, Zhaohui6; Tang, Yi Lang7,8; Ng, Chee H.9; Sha, Sha4; Xiang, Yu Tao1,2,3 | |
2022-08-04 | |
Source Publication | Nature and Science of Sleep |
ISSN | 1179-1608 |
Volume | 14Pages:1351-1362 |
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. |
Keyword | Anxiety Depression Health Personnel Network Analysis Sleep |
DOI | 10.2147/NSS.S367974 |
URL | View the original |
Indexed By | SCIE |
Language | 英語English |
WOS Research Area | Neurosciences & Neurology |
WOS Subject | Clinical Neurology ; Neurosciences |
WOS ID | WOS:000835674900001 |
Publisher | DOVE MEDICAL PRESS LTD, PO BOX 300-008, ALBANY, AUCKLAND 0752, NEW ZEALAND |
Scopus ID | 2-s2.0-85135459787 |
Fulltext Access | |
Citation statistics | |
Document Type | Journal article |
Collection | Faculty of Health Sciences |
Co-First Author | Cai, Hong; Zhao, Yan Jie; Xing, Xiaomeng |
Corresponding Author | Ng, Chee H.; Sha, Sha |
Affiliation | 1.Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao Special Administrative Region, China 2.Centre for Cognitive and Brain Sciences, University of Macau, Macao Special Administrative Region, China 3.Institute of Advanced Studies in Humanities and Social Sciences, University of Macau, Macao Special Administrative Region, China 4.The National Clinical Research Center for Mental Disorder & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China 5.School of Nursing, Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China 6.School of Public Health, Southeast University, Nanjing, China 7.Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, United States 8.Atlanta VA Medical Center, Decatur, United States 9.Department of Psychiatry, The Melbourne Clinic and St Vincent’s Hospital, University of Melbourne, Richmond, Australia |
First Author Affilication | Faculty of Health Sciences; University of Macau |
Recommended Citation GB/T 7714 | Cai, Hong,Zhao, Yan Jie,Xing, Xiaomeng,et al. 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[J]. Nature and Science of Sleep, 2022, 14, 1351-1362. |
APA | Cai, Hong., Zhao, Yan Jie., Xing, Xiaomeng., Tian, Tengfei., Qian, Wang., Liang, Sixiang., Wang, Zhe., Cheung, Teris., Su, Zhaohui., Tang, Yi Lang., Ng, Chee H.., Sha, Sha., & Xiang, Yu Tao (2022). 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. Nature and Science of Sleep, 14, 1351-1362. |
MLA | Cai, Hong,et al."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".Nature and Science of Sleep 14(2022):1351-1362. |
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