A cross-lagged panel network model on internet gaming disorder and depressive symptoms concerning preferences for game genres.

J Affect Disord

Dept of Social Work & Social Administration, University of Hong Kong, Hong Kong; HKJC Centre for Suicide Research and Prevention, University of Hong Kong, Hong Kong. Electronic address:

Published: January 2025

Background: Internet gaming disorder (IGD) is a prevalent behavioral addiction that co-occurs with depression. Little is known about how IGD and depression intercorrelate longitudinally at a symptom level. This study aimed to explore the directional relationships between IGD and depressive symptoms and identify the key symptoms in their comorbidity using cross-lagged panel network (CLPN) modeling.

Methods: A sample of 601 young gamers (mean age = 23.76) in Hong Kong completed the Internet Gaming Disorder Scale - Short Form and Patient Health Questionnaire-9 semi-annually at two-time points. Autoregressive and cross-lagged effects between depressive and IGD symptoms were analyzed via CLPN while controlling gamers' preferences across five game genres in R.

Results: The comorbidity was mainly driven from depressive symptoms to IGD symptoms, with a few weaker associations from IGD to depressive symptoms. 'Anhedonia' (out-/bridge-expected influence = 2.88; 0.03) and 'Motor problems' (out-/bridge-expected influence = 1.24; 0.03) from depression were the central and bridge symptoms to trigger the development of IGD symptoms, whereas 'continue gaming despite harm' (in-expected influence = 1.29) was the most consequent symptom. 'Anhedonia' (r = 0.17) and 'suicidal risk' (r = 0.15) to 'continuation despite harm' were the strongest paths connecting depression and IGD. Gamers who preferred First-Person Shooter games and Massively Multiplayer Online Role-Playing games were more vulnerable to depressive and IGD symptoms.

Conclusions: Our findings provide empirical support for the comorbidity between IGD and depression and clarify their directional relationships at a symptom level. We identify antecedent bridge symptoms as targets for preventing escalation of co-occurring issues.

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Source
http://dx.doi.org/10.1016/j.jad.2025.01.006DOI Listing

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