Measuring success of patients’ continuous use of mobile health services for self-management of chronic conditions: Model development and validation

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Abstract

Background: Mobile health services are gradually being introduced to support patients’ self-management of chronic conditions. The success of these services is contingent upon patients’ continuous use of them. Objective: This study aims to develop a model to measure the success of patients’ continuous use of mobile health services for the self-management of chronic conditions. Methods: The proposed model was derived from the information systems continuance model and the information systems success model. This model contains 7 theoretical constructs: information quality, system quality, service quality, perceived usefulness, user satisfaction, perceived health status, and continuous use intention. A web-based questionnaire survey instrument was developed to test the model. The survey was conducted to collect data from 129 patients who used a mobile health app for hypertension management from 2017 to 2019. The questionnaire items were derived from validated instruments and were measured using a 5-point Likert scale. The partial least squares modelling method was used to test the theoretical model. Results: The model accounted for 58.5% of the variance in perceived usefulness (R2=0.585), 52.3% of the variance in user satisfaction (R2=0.523), and 41.4% of the variance in patients’ intention to make continuous use of mobile health services (R2=0.414). The continuous use intention was significantly influenced by their perceived health status (β=.195, P=.03), perceived usefulness (β=.307, P=.004), and user satisfaction (β=.254, P=.04) with the mobile health service. Information quality (β=.235, P=.005), system quality (β=.192, P=.02), and service quality (β=.494, P

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Song, T., Deng, N., Cui, T., Qian, S., Liu, F., Guan, Y., & Yu, P. (2021). Measuring success of patients’ continuous use of mobile health services for self-management of chronic conditions: Model development and validation. Journal of Medical Internet Research, 23(7). https://doi.org/10.2196/26670

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