Mitigating Public Anxiety and Depression toward AI in Sports and Health Governance: A Policy Framework for Government Citizen Collaboration
Hsiao-Hsien Lin, Chih-Cheng Lo, Po-Hsuan Wu, I-En Tsai, Yong-Zhan ZhengAbstract
Objective
This study aimed to examine the effects of a big data-driven sports health monitoring and control system (BSHMCS) on users’ exercise outcomes and their perceived levels of anxiety and depression. The system was jointly developed by government agencies and developers and based on the characteristics and mechanisms of an Artificial Intelligence Health Monitoring System (AISHMS).
Methods
This study employed a mixed-methods design informed by grounded theory. Purposive, snowball, and convenience sampling methods were used to recruit participants and collect data. Data were analyzed using statistical tests, confirmatory factor analysis (CFA), semi-structured interviews, and multivariate statistical analyses. The study empirically examined the role of artificial intelligence in the relationships among leisure, exercise, stress, health, and well-being.
Results
Significant relationships were found among the perceived value of facility experience, exercise motivation, leisure attitude, leisure satisfaction, and perceived well-being (p < 0.001). Specifically, the perceived value of facility experience had a significant positive effect on exercise motivation. Exercise motivation positively influenced leisure attitude, which in turn positively affected leisure satisfaction. Leisure satisfaction also had a significant positive effect on well-being. In contrast, academic stress also had a significant negative effect on well-being (p < 0.001).
Conclusions
Artificial intelligence can significantly influence individuals' leisure activities, physical activity, stress regulation, health, and subjective well-being. However, excessively strict monitoring or control measures may increase users’ stress and adversely affect their mental health. Therefore, reward-based strategies should be adopted in place of punitive measures to reduce user anxiety and contribute to the achievement of Sustainable Development Goals (SDGs).
Corresponding Author
Yong-Zhan Zheng, Tajen University, Pingtung 90741, Taiwan.