Internet addiction and residual depressive symptoms among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic: a network analysis perspective

Hong Cai, Yan Jie Zhao, Fan He, Shu Ying Li, Zong Lei Li, Wu Yang Zhang, Yao Zhang, Teris Cheung, Chee H. Ng, Sha Sha, Yu Tao Xiang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)

Abstract

To assess the inter-relationships between residual depressive symptoms (RDS) and Internet addiction (IA) using network analysis among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic. RDS and IA were assessed using the Patient Health Questionnaire-9 (PHQ-9) and the Internet Addiction Test (IAT), respectively. Central symptoms and bridge symptoms in the network model were examined. A total of 1,454 adolescents met the study criteria and were included in the analyses. The prevalence of IA was 31.2% (95% CI: 28.8%-33.6%). In the network analysis, the nodes IAT15 (“Preoccupation with the Internet”), PHQ2 (“Sad mood”), and PHQ1 (“Anhedonia”) were the most central symptoms in the IA-RDS network model. Bridge symptoms included IAT10 (“Sooth disturbing about your Internet use”), PHQ9 (“Suicide ideation”), and IAT3 (“Prefer the excitement online to the time with others”). Additionally, PHQ2 (“Sad mood”) was the main node linking “Anhedonia” to other IA clusters. Internet addiction was common among clinically stable adolescents with major psychiatric disorders during the COVID-19 pandemic. Core and bridge symptoms identified in this study could be prioritized as targets for the prevention and treatment of IA in this population.

Original languageEnglish
Article number186
JournalTranslational Psychiatry
Volume13
Issue number1
DOIs
Publication statusPublished - Dec 2023

ASJC Scopus subject areas

  • Psychiatry and Mental health
  • Cellular and Molecular Neuroscience
  • Biological Psychiatry

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