Previously submitted to: JMIR Medical Informatics (no longer under consideration since Feb 08, 2022)
Date Submitted: Jan 28, 2022
Open Peer Review Period: Jan 28, 2022 - Feb 8, 2022
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Continuous Usage Intention of Mobile Health Services：Model Construction and Validation
ABSTRACT
Background:
Background:
Mobile health (mHealth) services are of positive significance for alleviating the unbalanced allocation of medical resources and reducing the time cost of users. But the sustainability of using mHealth services among users is still a problem.
Objective:
Objective:
Through the construction of models, questionnaire surveys, and empirical verification, the study aims to explore the factors that affect continuous usage intentions of mHealth services and the mechanism of action among these factors. Moreover, it may improve users’ self-management capabilities, and provides evidences for improving the quality of digital medical services.
Methods:
Methods:
Considering the uniqueness of health services and social environmental factors, this study constructed an Expectation Confirmation Model of Information System Continuance (ECM-ISC) to investigate factors that may influence the intention of continuance usage of mHealth services based on the three dimensions，which were individual, technology and environment. The questionnaires were collected by random sampling, the reliability and validity of the model were tested, the structural equation model was applied and full path analysis was performed.
Results:
Results:
Totally there were 334 participants completing the questionnaires through cross-sectional data. Reliability and validity of the test model were good, which Cronbach’s Alpha values of 9 variables all 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 79% of the variance in expectation confirmation, 67% of the variance in perceived usefulness, 97% of the variance in customer satisfaction, and 83% of the variance in continuance usage intention. Compared with the initial hypotheses, perceived system quality didn’t affect the continuous usage intention and was deleted. The added two paths were that subjective norm was positively associated with perceived service quality（β=0.675, P<0.001）and perceived information quality（β=0.579, P<0.001）. Electronic health (E-health) literacy was positively associated with perceived usefulness (β=0.415, P<0.001), perceived service quality (β=0.207, P<0.001), and perceived information quality (β=0.343, P<0.001). Continuance usage intention was influenced by perceived usefulness（β=0.216, P<0.001）, customer satisfaction（β=0.432, P<0.001） and subjective norm（β=0.36, P<0.001）.
Conclusions:
Conclusions:
The study constructed a theoretical model including E-health literacy, subjective norm and technology qualities to clarify continuous usage intention of mHealth services and empirically validated the model. E-health literacy, subjective norm, perceived service quality, and perceived service quality should be paid attention to improving continuance usage intention of users and self–management by mHealth Apps managers and government.
Citation
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