Evidence map›Paper›PMID 37957585›Full record

ArticleBMC psychiatry2023

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

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PubMed Full text at PMC Publisher
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Article in BMC psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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7citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Lina ZhangDepartment of Clinical Psychology, Tianjin Medical University General Hospital, Tianjin, China.
Mengqi LiuThe National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders and Beijing Institute for Brain Disorders Center of Schizophrenia, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Ming YuanDepartment of Applied Psychology, Hunan University of Chinese Medicine, Changsha, China.
Mutian HouPsychological Research and Counseling Center, Southwest Jiaotong University, Chengdu, China.
Cheng YangDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, the Second Xiangya Hospital of Central South University, Changsha, China.
Yingying WangSchool of Physical Education and Health, Hunan University of Technology and Business, Changsha, China.
Wei HaoDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, the Second Xiangya Hospital of Central South University, Changsha, China. weihao57@csu.edu.cn.
Yanhui LiaoDepartment of Psychiatry, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China. liaoyanhui@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGaming 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.

methodsTotally, 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.

resultsThe 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.

conclusionsThis 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.

Indexed as

Behavior, AddictiveVideo GamesAdolescentEast Asian PeopleFemaleHumansInternetMaleStudentsSurveys and QuestionnairesChinese adolescentsGaming disorderLatent profile analysis

Identifiers

PMID37957585
PMCPMC10644538

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.