Influence Mechanisms and Guiding Strategies of College Students’ Intention and Behavior of Using Smartwatches for Health Management Based on UTAUT2

With the deep integration of AI and IoT technologies, smartwatches have become core terminals for health management. However, research on the use mechanisms among “digital native” college students remains limited. Extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and selected constructs from the Health Action Process Approach (HAPA), this study uncovers the drivers and barriers of youths’ smartwatch health function adoption to propose targeted design strategies. A mixed-methods approach was employed, collecting semi-structured questionnaire data from 226 Chinese college students. Quantitative analysis was conducted (n = 106) using Partial Least Squares Structural Equation Modeling (PLS-SEM), complemented by qualitative text mining of open-ended feedback from non-users and churned users. The model demonstrated robust predictive power, supporting five hypotheses. Habit and action planning emerged as core antecedents of use intention, which significantly promoted actual use behavior. Effort expectancy acted as a baseline hygiene factor positively influencing performance expectancy. Qualitative findings confirmed that insufficient sensor accuracy and “health data anxiety” are critical psychological barriers. Validating the integrated model’s effectiveness, we propose three strategic interventions: enhancing data precision to build trust, implementing tiered pricing, and designing anxiety-alleviating visual interfaces, offering theoretical and empirical foundations for optimizing smart health products.