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Examining how gamers connect with their avatars to assess their anxiety: A novel artificial intelligence approach
Journal article   Open access   Peer reviewed

Examining how gamers connect with their avatars to assess their anxiety: A novel artificial intelligence approach

Kaiden Hein, Connor Conkey-Morrison, Tyrone L. Burleigh, Dylan Poulus and Vasileios Stavropoulos
Acta psychologica, Vol.246, 104298
06/2024
DOI: https://doi.org/10.1016/j.actpsy.2024.104298
PMID: 38701623
Appears in  Recent Faculty of Health Publications
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Published (Version of record)CC BY V4.0,  Open Access
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Abstract

Anxiety Artificial intelligence Avatar Internet gaming Machine learning Sport and exercise psychology Clinical psychology Expanding knowledge in psychology
Research has supported that a gamer's attachment to their avatar can offer significant insights about their mental health, including anxiety. To assess this hypothesis, longitudinal data from 565 adult and adolescent participants (Mage = 29.3 years, SD = 10.6) was analyzed at two points, six months apart. Respondents were assessed using the User-Avatar Bond (UAB) scale and the Depression Anxiety Stress Scale (DASS) to measure their connection with their avatar and their risk for anxiety. The records were processed using both untuned and tuned artificial intelligence [AI] classifiers to evaluate present and future anxiety. The findings indicated that AI models are capable of accurately and autonomously discerning cases of anxiety risk based on the gamers' self-reported UAB, age, and duration of gaming, both at present and after six months. Notably, random forest algorithms surpassed other AI models in effectiveness, with avatar compensation emerging as the most significant factor in model training for prospective anxiety. The implications for assessment, prevention, and clinical practice are discussed.

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