Mapping Network Connectivity Between Internet Addiction and Residual Depressive Symptoms in Patients with Depression

Overview

Journal Front Psychiatry

Specialty Psychiatry

Date 2022 Nov 10

PMID 36353572

Authors

Hong Cai

Wei Bai

Yan Yue

Ling Zhang

Wen-Fang Mi

Yu-Chen Li

Huan-Zhong Liu

Xiangdong Du

Zhen-Tao Zeng

Chang-Mou Lu

Lan Zhang

Ke-Xin Feng

Yan-Hong Ding

Juan-Juan Yang

Todd Jackson

Teris Cheung

Feng-Rong An

Yu-Tao Xiang

Affiliations

Soon will be listed here.

Abstract

Background And Aims: Depression often triggers addictive behaviors such as Internet addiction. In this network analysis study, we assessed the association between Internet addiction and residual depressive symptoms in patients suffering from clinically stable recurrent depressive disorder (depression hereafter).

Materials And Methods: In total, 1,267 depressed patients were included. Internet addiction and residual depressive symptoms were measured using the Internet Addiction Test (IAT) and the two-item Patient Health Questionnaire (PHQ-2), respectively. Central symptoms and bridge symptoms were identified via centrality indices. Network stability was examined using the case-dropping procedure.

Results: The prevalence of IA within this sample was 27.2% (95% CI: 24.7-29.6%) based on the IAT cutoff of 50. IAT15 ("Preoccupation with the Internet"), IAT13 ("Snap or act annoyed if bothered without being online") and IAT2 ("Neglect chores to spend more time online") were the most central nodes in the network model. Additionally, bridge symptoms included the node PHQ1 ("Anhedonia"), followed by PHQ2 ("Sad mood") and IAT3 ("Prefer the excitement online to the time with others"). There was no gender difference in the network structure.

Conclusion: Both key central and bridge symptoms found in the network analysis could be potentially targeted in prevention and treatment for depressed patients with comorbid Internet addiction and residual depressive symptoms.

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