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Network analysis of comorbid depression and anxiety and their associations with quality of life among clinicians in public hospitals during the late stage of the COVID-19 pandemic in China
Jin, Yu1; Sha, Sha2; Tian, Tengfei2; Wang, Qian2; Liang, Sixiang2; Wang, Zhe2; Liu, Yinqi2; Cheung, Teris3; Su, Zhaohui4; Ng, Chee H.5; Xiang, Yu Tao6,7,8
2022-10-01
Source PublicationJournal of Affective Disorders
ISSN0165-0327
Volume314Pages:193-200
AbstractBackground: Mental health problems are common among clinicians working in public hospitals even in the late stage of the COVID-19 pandemic. Network analysis is a novel approach to explore interactions between mental health problems at the symptom level. This study examined the network structure of comorbid depression and anxiety and their associations with quality of life (QOL) among hospital clinicians in China during the late stage of the COVID-19 pandemic. Methods: A total of 4931 participants were recruited from October 13 to 22, 2020. The nine-item Patient Health Questionnaire (PHQ-9), seven-item Generalized Anxiety Disorder Scale (GAD-7), and the World Health Organization Quality of Life Questionnaire-Brief Version (WHOQOL-BREF) were used to measure depressive and anxiety symptoms, and QOL, respectively. Central and bridge symptoms were identified with centrality and bridge centrality indices, respectively. Network stability was examined using the case-dropping procedure. Results: The prevalence of depression (defined as PHQ-9 total score ≥ 5) was 35.1 % [95 % confidence interval (CI) = 33.73–36.41 %)], the prevalence of anxiety (GAD-7 total score ≥ 5) was 32.5 % (95 % CI = 31.20–33.84 %), while the prevalence of comorbid depression and anxiety was 26.9 % (95 % CI = 25.7–28.2 %). “Impaired motor skills”, “Trouble relaxing” and “Uncontrollable worry” were the central symptoms in the whole depression-anxiety network. “Irritability”, “Feeling afraid” and “Sad mood” were the most key bridge symptoms linking depression and anxiety. Three symptoms (“Fatigue”, “Trouble relaxing” and “Nervousness”) were the most strongly and negatively associated with QOL. Neither gender nor the experiences of caring for COVID-19 patients was associated with network global strength, distribution of edge weights or individual edge weights. Limitations: The causality between variables could not be established. Depressive and anxiety symptoms were assessed by self-report measures, which may result in recall bias and limitations in capturing clinical phenomena. Conclusions: Both the central (i.e., “Impaired motor skills”, “Trouble relaxing” and “Uncontrollable worry”) and bridge symptoms (i.e., “Irritability”, “Feeling afraid” and “Sad mood”) identified in this network analysis should be targeted in specific treatment and preventive measures for comorbid depressive and anxiety symptoms among clinicians in the late stage of the pandemic. Furthermore, “Fatigue”, “Trouble relaxing” and “Nervousness” are key symptoms to address to improve clinicians' QOL.
KeywordAnxiety Clinicians COVID-19 Depression Network analysis
DOI10.1016/j.jad.2022.06.051
URLView the original
Language英語English
Scopus ID2-s2.0-85134484719
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Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.College of Education for the Future, Beijing Normal University, China
2.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, China
3.School of Nursing, Hong Kong Polytechnic University, SAR, Hong Kong
4.School of Public Health, Southeast University, Nanjing, China
5.Department of Psychiatry, The Melbourne Clinic and St Vincent's Hospital, University of Melbourne, Richmond, Australia
6.Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China
7.Centre for Cognitive and Brain Sciences, University of Macau, Macao SAR, China
8.Institute of Advanced Studies in Humanities and Social Sciences, University of Macau, Macao SAR, China
Recommended Citation
GB/T 7714
Jin, Yu,Sha, Sha,Tian, Tengfei,et al. Network analysis of comorbid depression and anxiety and their associations with quality of life among clinicians in public hospitals during the late stage of the COVID-19 pandemic in China[J]. Journal of Affective Disorders,2022,314:193-200.
APA Jin, Yu,Sha, Sha,Tian, Tengfei,Wang, Qian,Liang, Sixiang,Wang, Zhe,Liu, Yinqi,Cheung, Teris,Su, Zhaohui,Ng, Chee H.,&Xiang, Yu Tao.(2022).Network analysis of comorbid depression and anxiety and their associations with quality of life among clinicians in public hospitals during the late stage of the COVID-19 pandemic in China.Journal of Affective Disorders,314,193-200.
MLA Jin, Yu,et al."Network analysis of comorbid depression and anxiety and their associations with quality of life among clinicians in public hospitals during the late stage of the COVID-19 pandemic in China".Journal of Affective Disorders 314(2022):193-200.
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