The Impact of AI-Based Emotion Regulation on Adolescent Internalizing Problems: Parallel Mediation Effects of Psychological Capital and Deviant Peer Association

This study aims to investigate the impact of emotion regulation strategies on adolescent internalizing problems, incorporating artificial intelligence (AI) techniques for data preprocessing to explore the parallel mediating roles of psychological capital and deviant peer association. Methods: Using a questionnaire-based survey, this study measured emotion regulation strategies, positive psychological capital, deviant peer association, and adolescent internalizing problems among students from seven middle schools in Beijing, China. AI techniques were applied to preprocess data, including outlier detection and data cleaning, to enhance the accuracy of the analysis. Results: The data analysis revealed that emotion regulation strategies are significantly positively correlated with both adolescent psychological capital and internalizing problems, while showing a significant negative correlation with deviant peer association. Additionally, adolescent internalizing problems are significantly negatively correlated with psychological capital and significantly positively correlated with deviant peer association. A significant negative correlation was also observed between psychological capital and deviant peer association. Furthermore, emotion regulation strategies were found to influence adolescent internalizing problems through the parallel mediating effects of psychological capital and deviant peer association. Conclusion: By employing AI-driven data preprocessing, this study elucidated the complex relationships among emotion regulation strategies, adolescent internalizing problems, psychological capital, and deviant peer association. The findings offer a new perspective on adolescent mental health and provide a theoretical foundation for developing effective intervention strategies.