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The backbone symptoms of depression: a network analysis after the initial wave of the COVID-19 pandemic in Macao
Zhao, Yan Jie1,2,3; Bai, Wei1,2,3; Cai, Hong1,2,3; Sha, Sha4; Zhang, Qinge4; Lei, Si Man5; Lok, Ka In6; Chow, Ines Hang Iao1,2,3; Cheung, Teris7; Su, Zhaohui8; Balbuena, Lloyd9; Xiang, Yu Tao1,2,3
2022-09-15
Source PublicationPeerJ
ISSN2167-8359
Volume10
Abstract

Background: The coronavirus disease 2019 (COVID-19) pandemic disrupted the working lives of Macau residents, possibly leading to mental health issues such as depression. The pandemic served as the context for this investigation of the network structure of depressive symptoms in a community sample. This study aimed to identify the backbone symptoms of depression and to propose an intervention target. Methods: This study recruited a convenience sample of 975 Macao residents between 20th August and 9th November 2020. In an electronic survey, depressive symptoms were assessed with the Patient Health Questionnaire-9 (PHQ-9). Symptom relationships and centrality indices were identified using directed and undirected network estimation methods. The undirected network was constructed using the extended Bayesian information criterion (EBIC) model, and the directed network was constructed using the Triangulated Maximally Filtered Graph (TMFG) method. The stability of the centrality indices was evaluated by a case-dropping bootstrap procedure. Wilcoxon signed rank tests of the centrality indices were used to assess whether the network structure was invariant between age and gender groups. Results: Loss of energy, psychomotor problems, and guilt feelings were the symptoms with the highest centrality indices, indicating that these three symptoms were backbone symptoms of depression. The directed graph showed that loss of energy had the highest number of outward projections to other symptoms. The network structure remained stable after randomly dropping 50% of the study sample, and the network structure was invariant by age and gender groups. Conclusion: Loss of energy, psychomotor problems and guilt feelings constituted the three backbone symptoms during the pandemic. Based on centrality and relative influence, loss of energy could be targeted by increasing opportunities for physical activity.

KeywordCovid-19 Depression Macao Network Analysis Survey
DOI10.7717/peerj.13840
URLView the original
Language英語English
Scopus ID2-s2.0-85138186353
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Document TypeJournal article
CollectionFaculty of Education
Faculty of Health Sciences
Affiliation1.Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao, Macao
2.Centre for Cognitive and Brain Sciences, University of Macau, Macao, Macao
3.Institute of Advanced Studies in Humanities and Social Sciences, University of Macau, Macao, Macao
4.The National Clinical Research Center for Mental Disorders, Beijing Key Laboratory of Mental Disorders, Beijing An Ding Hospital, Beijing, China
5.Faculty of Education, University of Macau, Macau, Macao
6.Kiang Wu Nursing College of Macau, Macau, Macao
7.School of Nursing, Hong Kong Polytechnic University, Hong Kong
8.Center on Smart and Connected Health Technologies, Mays Cancer Center, School of Nursing, UT Health San Antonio, San Antonio, United States
9.Department of Psychiatry, University of Saskatchewan, Saskatoon, Canada
First Author AffilicationFaculty of Health Sciences;  University of Macau
Recommended Citation
GB/T 7714
Zhao, Yan Jie,Bai, Wei,Cai, Hong,et al. The backbone symptoms of depression: a network analysis after the initial wave of the COVID-19 pandemic in Macao[J]. PeerJ,2022,10.
APA Zhao, Yan Jie,Bai, Wei,Cai, Hong,Sha, Sha,Zhang, Qinge,Lei, Si Man,Lok, Ka In,Chow, Ines Hang Iao,Cheung, Teris,Su, Zhaohui,Balbuena, Lloyd,&Xiang, Yu Tao.(2022).The backbone symptoms of depression: a network analysis after the initial wave of the COVID-19 pandemic in Macao.PeerJ,10.
MLA Zhao, Yan Jie,et al."The backbone symptoms of depression: a network analysis after the initial wave of the COVID-19 pandemic in Macao".PeerJ 10(2022).
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