Currently submitted to: Journal of Medical Internet Research
Date Submitted: Jun 13, 2019
Open Peer Review Period: Jun 13, 2019 - Jun 21, 2019
(currently open for review)
Exploring Factors Influencing Patients’ Intention to Use Diabetes Management Mobile Apps Based on an Integrated Theoretical Model—a Web-Based Survey in China
Diabetes poses heavy social and economic burdens on the world. Diabetes management mobile apps show great potential for diabetes self-management. However, the uptake of diabetes apps among diabetes patients is poor. The factors influencing patients’ intention to use these apps are unclear. Understanding patients’ behavioral intention is necessary to support the development and promotion of diabetes app use.
To identify the determinants of patients’ intention to use diabetes apps based on an integrated theoretical model.
The hypotheses of our research model were developed based on the Unified Theory of Acceptance and Use of Technology (UTAUT) integrated with context-related hypotheses. From 20 April to 20 May 2019, adult diabetes patients across China who were familiar with diabetes management mobile apps were surveyed using the web-based survey tool Sojump (Changsha ran Xing InfoTech Ltd). Structural equation modeling was used to analyze the data.
A total of 746 qualified questionnaires were collected. The fitness indices suggested that the collected data fit well with the research model. The model explained 62.6% of the variance in performance expectancy and 57.1% of the variance in behavioral intention. Performance expectancy and social influence had the strongest total effects on behavioral intention (β=.482 p=0.001). Performance expectancy (β=.482 P=.001), social influence (β=.223 P=.003), facilitating conditions (β=.17 P=.006), perceived disease threat (β=.073 P=.005) and perceived privacy risk (β=-.073 P=.012) had direct effects on behavioral intention. Additionally, social influence, effort expectancy and facilitating conditions had indirect effects on behavioral intention that were mediated by performance expectancy. Social influence had the highest indirect effects among the three constructs (β=.259 P=.001).
Performance expectancy and social influence are the most important determinants of the intention to use diabetes apps. Healthcare technology companies must improve the usefulness of apps and carry out research to provide clinical evidence for the apps’ effectiveness, which will benefit the promotion of these apps. Facilitating conditions and perceived privacy risk also have an impact on behavioral intention. Therefore, it is necessary to improve facilitating conditions and provide solid privacy protection. Our study supports the use of UTAUT in explaining patients’ intention to use diabetes management mobile apps. Context-related determinants should also be taken into consideration.
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