Identification of central symptoms in Internet addictions and depression among adolescents in Macau: A network analysis

J Affect Disord. 2022 Apr 1:302:415-423. doi: 10.1016/j.jad.2022.01.068. Epub 2022 Jan 20.

Abstract

Background: Internet addiction (IA) and depression are common among adolescents and often are co-occurring. This study examined the network structures of IA and depressive symptoms (depression hereafter) in adolescents.

Methods: A total of 1,009 adolescents were recruited. IA and depression were measured using the Internet Addiction Test (IAT) and the 9 items-Patient Health Questionnaire (PHQ-9), respectively. A network analysis was conducted to identify central symptoms and bridge symptoms using centrality indices. Network stability was evaluated using the case-dropping procedure. The Network Comparison Test (NCT) was conducted to examine whether network characteristics differed by gender.

Results: Network analysis revealed that nodes IAT-15 ("Preoccupation with the Internet"), IAT-2 ("Neglect chores to spend more time online"), PHQ-6 ("Guilty"), and IAT-16 ("Request an extension for longer time spent online") were the most central symptoms within the model of coexisting IA and depression. The most important bridge symptom was node IAT-11 ("Anticipation for future online activities"), followed by IAT-12 ("Fear that life is boring and empty without the Internet") and IAT-19 ("Spend more time online over going out with others"). Gender did not significantly influence the network structure. The IA and depression network model showed a high degree of stability.

Conclusion: The central symptoms along with key bridge symptoms identified could be potentially targeted when treating and preventing IA and depression among adolescents.

Keywords: Adolescents; Depression; Internet addiction; Network analysis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Behavior, Addictive* / diagnosis
  • Behavior, Addictive* / epidemiology
  • Depression / diagnosis
  • Depression / epidemiology
  • Fear
  • Humans
  • Internet
  • Internet Addiction Disorder* / epidemiology
  • Macau
  • Surveys and Questionnaires