Network analysis of depressive and anxiety symptoms in adolescents during the later stage of the COVID-19 pandemic

• Type of Material: Article
• Authors: Hong Cai, University of Macau; Wei Bai, University of Macau; Huanzhong Liu, Anhui Medical University; Xu Chen, Capital Medical University; Han Qi, Capital Medical University; Rui Liu, Capital Medical University; Teris Cheung, Hong Kong Polytechnic University; Zhaohui Su, UT Health San Antonio; Jingxia Lin, Hong Kong Polytechnic University; Yilang Tang, Emory University; Todd Jackson, University of Macau; Qinge Zhang, Capital Medical University; Yu-Ta Xiang, University of Macau
• Language: English
• Date: 2022-03-10
• Publisher: SPRINGERNATURE
• Publication Version: Final Published Version
• Copyright Statement: © The Author(s) 2022
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1038/s41398-022-01838-9
• Title of Journal or Parent Work: TRANSLATIONAL PSYCHIATRY
• Volume: 12
• Issue: 1
• Start Page: 98
• End Page: 98
• Grant/Funding Information: The study was supported by the Beijing Municipal Science & Technology Commission (Grant No.: Z181100001718124), Beijing Talents Foundation (Grant No.: 2017000021469G222), and the University of Macau (MYRG2019-00066-FHS).
• Keywords: Life Sciences & Biomedicine; CENTRALITY; Science & Technology; CHILDREN; SUICIDAL IDEATION; MENTAL-HEALTH; MEDIATING ROLE; GLOBAL BURDEN; BEHAVIOR; IRRITABILITY; Psychiatry; MODEL SELECTION; DISORDER
• Research Categories: Health Sciences, Public Health; Health Sciences, Rehabilitation and Therapy; Health Sciences, Mental Health

Abstract

Network analysis is an effective approach for examining complex relationships between psychiatric symptoms. This study was designed to examine item-level relationships between depressive and anxiety symptoms using network analysis in an adolescent sample and identified the most central symptoms within the depressive-anxiety symptoms network model. Depressive and anxiety symptoms were assessed using the Patient Health Questionire-9 (PHQ-9) and Generalized Anxiety Disorder Screener (GAD-7), respectively. The structure of depressive and anxiety symptoms was characterized using “Strength” and “Bridge Strength” as centrality indices in the symptom network. Network stability was tested using a case-dropping bootstrap procedure. Finally, a Network Comparison Test (NCT) was conducted to examine whether network characteristics differed on the basis of gender, school grade and residence. Network analysis revealed that nodes PHQ2 (“Sad mood”), GAD6 (“Irritability”), GAD3 (“Worry too much”), and PHQ6 (“Guilty”) were central symptoms in the network model of adolescents. Additionally, bridge symptoms linking anxiety and depressive symptoms in this sample were nodes PHQ6 (“Guilty”), PHQ2 (“Sad mood”), and PHQ9 (“Suicide ideation”). Gender, school grade and residence did not significantly affect the network structure. Central symptoms (e.g., Sad mood, Irritability, Worry too much, and Guilty) and key bridge symptoms (e.g., Guilty, Sad mood, and Suicide ideation) in the depressive and anxiety symptoms network may be useful as potential targets for intervention among adolescents who are at risk for or suffer from depressive and anxiety symptoms.