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Chinese Cardiovascular Disease Mobile Apps' Information Types, Information Quality, and Interactive Functions for
Bo Xie1,2, Zhaohui Su3, Wenhui Zhang1,4
1School of Nursing, The University of Texas at Austin, Austin, TX, United States.
Background:
China has a large population with cardiovascular disease (CVD) that requires extensive self-management. Mobile health (mHealth) apps may be a useful tool for CVD self-management. Little is currently known about the types and quality of health information provided in Chinese CVD mobile apps and whether app functions are conducive to promoting CVD self-management.
Objective:
We undertook a systematic review to evaluate the types and quality of health information provided in Chinese CVD mobile apps and interactive app functions for promoting CVD self-management.
Methods:
Mobile apps targeting end users in China with CVD conditions were selected in February 2017 through a multi-stage process. Three frameworks were used to evaluate the selected apps: (1) types of health information offered were assessed using our Health Information Wants framework, which encompasses 7 types of information; (2) quality of information provided in the apps was assessed using the 11 guidelines recommended by the National Library of Medicine of the National Institutes of Health; and (3) types of interactive app functions for CVD self-management were assessed using a 15-item framework adapted from the literature, including our own prior work.
Results:
Of 578 apps identified, 82 were eligible for final review. Among these, information about self-care (67/82, 82%) and information specifically regarding CVD (63/82, 77%) were the most common types of information provided, while information about health care providers (22/82, 27%) and laboratory tests (5/82, 6%) were least common. The most common indicators of information quality were the revealing of apps' providers (82/82, 100%) and purpose (82/82, 100%), while the least common quality indicators were the revealing of how apps' information was selected (1/82, 1%) and app sponsorship (0/82, 0%). The most common interactive functions for CVD self-management were those that enabled user interaction with the app provider (57/82, 70%) and with health care providers (36/82, 44%), while the least common interactive functions were those that enabled lifestyle management (13/82, 16%) and psychological health management (6/82, 7%). None of the apps covered all 7 types of health information, all 11 indicators of information quality, or all 15 interactive functions for CVD self-management.
Conclusions:
Chinese CVD apps are insufficient in providing comprehensive health information, high-quality information, and interactive functions to facilitate CVD self-management. End users should exercise caution when using existing apps. Health care professionals and app developers should collaborate to better understand end users' preferences and follow evidence-based guidelines to develop mHealth apps conducive to CVD self-management.
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