Determinants of continuous use intention of smart healthcare services: Evidence from a commitment-trust theory perspective

Objective: While smart healthcare services have shown potential in improving healthcare efficiency and effectiveness, significant barriers remain for consumers' long-term engagement in such services. The study sought to propose and validate a theoretical framework to investigate the continuous use of smart healthcare services. Methods: The research model integrates commitment-trust theory with the information system success model, empirically validated through partial least squares structural equation modeling. Data were collected via a Chinese online survey platform, targeting 355 active users of smart health services. Results: The proposed model explained 61.4% of the variance in continuous usage intention. Affective commitment, trust, and satisfaction significantly affected continuous usage intention (p's < 0.01). Trust and satisfaction were found to significantly influence affective commitment (p's < 0.001). Satisfaction and perceived value were found to be significant determinants of trust (p's < 0.05). Perceived value also significantly influenced satisfaction (p < 0.001). The relationships were also moderated by age, gender, and AI literacy. Conclusion: This study represents rare attempts to explore continuous usage intention of smart healthcare services from the commitment-trust theory perspective. Practitioners should prioritize trust-building measures (e.g., transparent data usage policies) and personalized features (e.g., adaptive health recommendations) to enhance long-term engagement. Demographic characteristics should also be considered when designing such services.