From Acceptance to Dependence: Exploring Influences of Smart Healthcare on Continuous Use Intention of Mobile Health Services Among Older Adults with Chronic Illnesses in China.

With the acceleration of the aging process in China, chronic diseases have become one of the main health threats for older adults, creating significant pressure on society and the healthcare system. As information technology and artificial intelligence advance rapidly, smart health services have become readily accessible. However, utilization rates among the older adults, especially those with chronic illnesses, remain low, preventing them from fully benefiting from these advanced technologies. The value of mobile health (mHealth) services can only be realized through sustained use. Therefore, this study empirically investigates the continuous use intention of mHealth services from the perspective of older adults with chronic illnesses, integrating the Technology Acceptance Model (TAM) and Value-Based Adoption Model (VAM). A total of 372 questionnaires were collected from various cities in China, and data were analyzed using SPSS 24.0 and Partial Least Squares Structural Equation Modeling (PLS-SEM). Results indicate that perceived ease of use ( = 0.155, = 0.004; = 0.116, = 0.027) and perceived usefulness ( = 0.175, = 0.001; = 0.151, = 0.004) have a significant positive impact on attitude and perceived value. Perceived enjoyment significantly influences attitude ( = 0.147, = 0.010), while perceived risk ( = -0.189, < 0.001; = -0.281, < 0.001) and perceived cost ( = -0.155, = 0.003; = -0.130, = 0.022) have a significant negative impact on attitude and perceived value. Both attitude ( = 0.357, < 0.001) and perceived value ( = 0.314, < 0.001) positively impact continuous intention. In total, only one of the twelve hypotheses was not supported. This study not only provides strong evidence for the effectiveness of the integrated TAM and VAM model in the mHealth field but also offers theoretical insights and practical recommendations for product optimization and promotion to mHealth service providers and designers.