Using Artificial Intelligence for Cognitive Rehabilitation in Gaming Addiction

Gaming addiction is recognized as a behavioral disorder of the digital age, with potentially detrimental effects on mental health, social functioning, and users’ quality of life. This study aimed to investigate the factors contributing to gaming addiction and to predict this behavior using artificial intelligence algorithms. A mixed-methods approach was employed, combining qualitative and quantitative analyses. In the qualitative phase, data were collected and analyzed through semi-structured interviews with ۱۲ heavy users of video games. In the quantitative phase, data from ۱۰۰ participants were gathered using standard questionnaires, including the Gaming Addiction Questionnaire developed by Poursalehi and Matinfar. Findings revealed that psychological factors such as anxiety, depression, and limited social interactions were significant predictors of gaming addiction. Artificial intelligence analyses, utilizing deep neural networks and random forest algorithms, demonstrated high accuracy (۹۲%) in predicting addictive behaviors. Furthermore, the qualitative analysis highlighted the critical role of multiplayer online games (MMORPGs) and reward systems in fostering user dependency. The results underscore the importance of integrating artificial intelligence technologies with cognitive interventions to manage this disorder effectively. It is recommended to develop AI-based prevention programs alongside psychological interventions to mitigate gaming addiction. By offering an innovative approach to predicting and managing addiction, this study contributes to improving users’ mental health.

کلیدواژه ها:

Gaming Addiction ، Artificial Intelligence ، Cognitive Rehabilitation ، Machine Learning ، Virtual Reality