ArticleJournal of behavioral addictions2023
Deep learning(s) in gaming disorder through the user-avatar bond: A longitudinal study using machine learning.
Article in Journal of behavioral addictions, 2023. 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 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 15 citations in OpenAlex.
- Language of change in online narratives of recovery from disordered gaming.Scientific reports · 2026Article
- From monitoring to intervention: a closed-loop digital health framework for gaming disorder.Frontiers in public health · 2026Review
- The Relationship Between Smartphone and Game Addiction, Leisure Time Management, and the Enjoyment of Physical Activity: A Comparison of Regression Analysis and Machine Learning Models.Healthcare (Basel, Switzerland) · 2025Article
- Flowing in the net of disordered gaming: A network analysis approach.Addictive behaviors reports · 2025Article
- Machine Learning(s) in gaming disorder through the user-avatar bond: A step towards conceptual and methodological clarity.Journal of behavioral addictions · 2024Article
- User-avatar bond as diagnostic indicator for gaming disorder: A word on the side of caution.Journal of behavioral addictions · 2024Article
- Proteus effect avatar profiles: Associations with disordered gaming and activity levels.Addictive behaviors reports · 2024Article
- Gaming Disorder: The role of a gamers flow profile.Addictive behaviors reports · 2024Article
- Transdiagnostic study of dynamic brain activity and connectivity among people with gambling and internet gaming disorders: DYNAMIC BRAIN ACTIVITY IN GD AND IGD.International journal of clinical and health psychology : IJCHPArticle
Corrections and comments
- Erratum issued
Authors and funding
9 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and aims: Gaming disorder [GD] risk has been associated with the way gamers bond with their visual representation (i.e., avatar) in the game-world. More specifically, a gamer's relationship with their avatar has been shown to provide reliable mental health information about the user in their offline life, such as their current and prospective GD risk, if appropriately decoded. Methods: To contribute to the paucity of knowledge in this area, 565 gamers (Mage = 29.3 years; SD =10.6) were assessed twice, six months apart, using the User-Avatar-Bond Scale (UABS) and the Gaming Disorder Test. A series of tuned and untuned artificial intelligence [AI] classifiers analysed concurrently and prospectively their responses. Results: Findings showed that AI models learned to accurately and automatically identify GD risk cases, based on gamers' reported UABS score, age, and length of gaming involvement, both concurrently and longitudinally (i.e., six months later). Random forests outperformed all other AIs, while avatar immersion was shown to be the strongest training predictor. Conclusion: Study outcomes demonstrated that the user-avatar bond can be translated into accurate, concurrent and future GD risk predictions using trained AI classifiers. Assessment, prevention, and practice implications are discussed in the light of these findings.
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Registered trials
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.