Meta-Analysis of Internet Gaming Disorder Prevalence: Assessing the Impacts of DSM-5 and ICD-11 Diagnostic Criteria

Ruoyu Zhou, Nobuaki Morita, Yasukazu Ogai, Tamaki Saito, Xinyue Zhang, Wenjie Yang () and Fan Yang
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Ruoyu Zhou: Doctoral Program in Human Care Science, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tsukuba 305-8577, Japan
Nobuaki Morita: Department of Social Psychiatry and Mental Health, School of Medicine and Medical Sciences, University of Tsukuba, Tsukuba 305-8577, Japan
Yasukazu Ogai: Department of Social Psychiatry and Mental Health, School of Medicine and Medical Sciences, University of Tsukuba, Tsukuba 305-8577, Japan
Tamaki Saito: Department of Social Psychiatry and Mental Health, School of Medicine and Medical Sciences, University of Tsukuba, Tsukuba 305-8577, Japan
Xinyue Zhang: Public Health Degree Program, Faculty of Comprehensive Human Sciences, University of Tsukuba, Tsukuba 305-8577, Japan
Wenjie Yang: The Mental Health Center, Yunnan University, Kunming 650091, China
Fan Yang: Graduate School of Letters, Arts and Sciences, Waseda University, Tokyo 162-8644, Japan

IJERPH, 2024, vol. 21, issue 6, 1-14

Abstract: With the inclusion of Internet gaming disorder (IGD) in both the DSM-5 and ICD-11, understanding the prevalence and diagnostic discrepancies is crucial for developing appropriate interventions. This study presents a meta-analysis of the prevalence of IGD based on two diagnostic criteria. We systematically searched the PubMed and Web of Science databases. A total of 22 studies were included in the final analysis. The analysis incorporated studies employing the DSM-5 and ICD-11 criteria and focused on the impact of various factors, including study location, sample characteristics, sample size, and quality score, on the reported prevalence rates using a random-effects model. The pooled prevalence of IGD is 6.7% (95% CI: 5.7–7.7%). The subgroup analysis indicated significant differences in the prevalence rates of IGD (DSM-5 criteria) and GD (ICD-11 criteria) (Q b = 38.46, p < 0.01). There were also significant differences in IGD prevalence rates between different scales (Q b = 54.23, p < 0.001). Our findings indicate that different diagnostic criteria and different assessment scales have a significant impact on the prevalence of IGD. This underscores the importance of adopting standardized methodologies to guide public health interventions. However, given the limited research based on ICD-11 diagnostic criteria, further investigation is necessary to determine the variations in prevalence rates of IGD under different diagnostic standards.

Keywords: Internet gaming disorder; gaming disorder; DSM-5; ICD-11; prevalence; meta-analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2024
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