Key points are not available for this paper at this time.
BACKGROUND: Mobile health (mHealth) services can not give full play to their value if only it is used in the short term, and their continuous usage can achieve better effects in health management. This study aims to explore the factors that affect continuous usage intentions of mHealth services and their mechanism of action. METHODS: First, considering the uniqueness of health services and social environmental factors, this study constructed an extended Expectation Confirmation Model of Information System Continuance (ECM-ISC) to investigate factors that may influence the intention of continuous usage of mHealth services based on three dimensions, namely individual characteristics, technology and environment. Second, the survey method was used to validate the research model. The questionnaire items were derived from validated instruments and discussed by experts and data were collected both online and offline. The structural equation model was used for data analysis. RESULTS: There were 334 avidity questionnaires through cross-sectional data and these participants had used mHealth services ever. The reliability and validity of the test model were good, in which Cronbach's Alpha values of 9 variables exceeded 0.9, composite reliability 0.8, the average variance extracted value 0.5, and the factor loading 0.8. The modified model had a good fitting effect and strong explanatory power. It accounted for 89% of the variance in expectation confirmation, 74% of the variance in perceived usefulness, 92% of the variance in customer satisfaction, and 84% of the variance in continuous usage intention. Compared with the initial model hypotheses, perceived system quality was deleted according to the heterotrait-monotrait ratio, so paths related to it were deleted; perceived usefulness wasn't positively associated with customer satisfaction, and its path was also deleted. Other paths were consistent with the initial hypothesis. The two new added paths were that subjective norm was positively associated with perceived service quality (β = 0.704, P < 0.001), and perceived information quality (β = 0.606, P < 0.001). Electronic health literacy (E-health literacy) was positively associated with perceived usefulness (β = 0.379, P < 0.001), perceived service quality (β = 0.200, P < 0.001), and perceived information quality (β = 0.320, P < 0.001). Continuous usage intention was influenced by perceived usefulness (β = 0.191, P < 0.001), customer satisfaction (β = 0.453, P < 0.001), and subjective norm (β = 0.372, P < 0.001). CONCLUSIONS: The study constructed a new theoretical model including E-health literacy, subjective norm and technology qualities to clarify continuous usage intention of mHealth services, and empirically validated the model. Attention should be paid to E-health literacy, subjective norm, perceived information quality, and perceived service quality to improve continuous usage intention of users and self-management by mHealth Apps managers and governments. This research provides solid evidence for the validity of the expanded model of ECM-ISC in the mHealth field, which can be a theoretical and practical basis for mHealth operators' product research and development.
Nie et al. (Thu,) studied this question.