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Latent profile and transition analyses of internet gaming disorder among college students: A one-year longitudinal study

Jie Yang1,#, Wenhui Ma2,#, Yan Tang3,*, Bin Gao4,*
1 College of Philosophy, Law & Political Science, Shanghai Normal University, Shanghai, China
2 School of Marxism, Shanghai Normal University, Shanghai, China
3 School of Education, Shanghai Normal University, Shanghai, China
4 School of Teacher Education, Hubei Minzu University, Enshi, China
* Corresponding Author: Yan Tang. Email: email; Bin Gao. Email: email
# These authors contributed equally to this work and share co-first authorship

Journal of Psychology in Africa https://doi.org/10.32604/jpa.2026.078648

Received 05 January 2026; Accepted 03 April 2026; Published online 29 April 2026

Abstract

Previous research has indicated heterogeneity in Internet Gaming Disorder (IGD) profiles in college students. However, longitudinal evidence regarding the stability and transition patterns of IGD subgroups among college students remains limited. This two-wave longitudinal study, with a one-year interval, included 343 Chinese undergraduate students (57.7% female; mean age = 18.28 years, SD = 1.14) who participated in both surveys. Latent profile analysis identified three distinct IGD subgroups—High, Moderate, and Low IGD—which were consistent across both time points. Regression analyses indicated that male gender, greater gaming time, loneliness, and depression were associated with higher IGD severity. Self-control consistently served as a protective factor. Latent transition analysis revealed moderate stability but substantial fluidity in IGD profiles, particularly among Moderate and High IGD groups, suggesting that IGD is a dynamic condition that changes over time. These findings are consistent with self-regulation theory and compensatory internet use theory and underscore the importance of integrated self-regulatory interventions to address IGD in university settings.

Keywords

Internet gaming disorder; college students; latent profile analysis; latent transition analysis; risk and protective factors
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