BMC Psychiatry (Nov 2023)

The latent profile analysis of Chinese adolescents’ gaming disorder: examination and validation

  • Lina Zhang,
  • Mengqi Liu,
  • Ming Yuan,
  • Mutian Hou,
  • Cheng Yang,
  • Yingying Wang,
  • Wei Hao,
  • Yanhui Liao

DOI
https://doi.org/10.1186/s12888-023-05320-8
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 9

Abstract

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Abstract Background Gaming disorder is a new disease, which is included in the disease unit of disorder caused by addiction in the 11th revision of the International Classification of Diseases. This study examined the symptom characteristics of gaming disorders in Chinese adolescents using the latent profile analysis. Methods Totally, 5988 students (including 3285 boys and 2703 girls; aged 12–18 years) from junior high schools and senior high schools were enrolled. The Gaming Disorder Symptom Questionnaire-21 (GDSQ-21) was used to screen gaming disorder. A latent profile analysis was used for classifying the subgroups based on the extent of gaming usage. The relationship between adolescent gamers and demographic variables was analyzed by logistic regression. Results The results of latent profile analysis supported the models of four latent profiles, which were defined as healthy gamers (Profile 1, 56.83%), impaired control gamers (Profile 2, 26.09%), impaired control-game priority gamers (Profile 3, 9.72%) and gamers with disorder (Profile 4, 7.36%), respectively. Logistic regression analysis found that, compared with girls, boys were more likely to be classified into the group dominated by the impaired gamers, the impaired control-game priority gamers, and the gamers with disorder. Conclusions This study highlighted that the latent profile analysis identified four different groups of adolescent gamers, showing a clearer conceptualization of heterogeneous gamers. Gender and average weekly gaming time can predict the latent profile of adolescents. Our findings may facilitate the design of individualized assessment and early intervention programs for adolescent gamer users based on different gaming usage symptoms.

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