ArticleJMIR mental health2024
Digital Phenotypes for Early Detection of Internet Gaming Disorder in Adolescent Students: Explorative Data-Driven Study.
Article in JMIR mental health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- AI-Enabled Digital Phenotyping for Personalized Risk Stratification in Internet Gaming Disorder: A Privacy-Preserving Simulation Study.Journal of personalized medicine · 2026Article
- Digital Phenotyping of High-Risk Gaming Behavior Using Wearable Devices.Alpha psychiatry · 2026Article
- From monitoring to intervention: a closed-loop digital health framework for gaming disorder.Frontiers in public health · 2026Review
- Gaming disorder in the ICD-11: the state of the game.BMC psychiatry · 2025Review
- Digital Phenotyping of Sensation Seeking: A Machine Learning Approach Using Gait Analysis.Behavioral sciences (Basel, Switzerland) · 2025Article
- Facial Emotional Expression in Reaction to Internet Gaming Videos Among Young Adults: A Preliminary and Exploratory Study.Neuropsychopharmacology reports · 2025Article
- Interaction Effects Between Low Self-Control and Meaning in Life on Internet Gaming Disorder Symptoms and Functioning in Chinese Adolescents: Cross-Sectional Latent Moderated Structural Equation Modeling Study.Journal of medical Internet research · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLimited awareness, social stigma, and access to mental health professionals hinder early detection and intervention of internet gaming disorder (IGD), which has emerged as a significant concern among young individuals. Prevalence estimates vary between 0.7% and 15.6%, and its recognition in the International Classification of Diseases, 11th Revision and Diagnostic and Statistical Manual of Mental Disorders, 5th Edition underscores its impact on academic functioning, social isolation, and mental health challenges.
objectiveThis study aimed to uncover digital phenotypes for the early detection of IGD among adolescents in learning settings. By leveraging sensor data collected from student tablets, the overarching objective is to incorporate these digital indicators into daily school activities to establish these markers as a mental health screening tool, facilitating the early identification and intervention for IGD cases.
methodsA total of 168 voluntary participants were engaged, consisting of 85 students with IGD and 83 students without IGD. There were 53% (89/168) female and 47% (79/168) male individuals, all within the age range of 13-14 years. The individual students learned their Korean literature and mathematics lessons on their personal tablets, with sensor data being automatically collected. Multiple regression with bootstrapping and multivariate ANOVA were used, prioritizing interpretability over predictability, for cross-validation purposes.
resultsA negative correlation between IGD Scale (IGDS) scores and learning outcomes emerged (r
conclusionsThe aggregated findings show a negative correlation between IGD and learning performance, highlighting the effectiveness of digital markers in detecting IGD. This underscores the importance of digital phenotyping in advancing mental health care within educational settings. As schools adopt a 1-device-per-student framework, digital phenotyping emerges as a promising early detection method for IGD. This shift could transform clinical approaches from reactive to proactive measures.
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