%0 Journal Article
%@ 2291-5222
%I JMIR Publications
%V 5
%N 12
%P e195
%T Chinese Cardiovascular Disease Mobile Apps’ Information Types, Information Quality, and Interactive Functions for Self-Management: Systematic Review
%A Xie,Bo
%A Su,Zhaohui
%A Zhang,Wenhui
%A Cai,Run
%+ Chongqing Cancer Institute, 181 Hanyu Road, Shapingba District, Chongqing, 400030, China, 86 23 6507 5628, cairun0519@163.com
%K mobile health
%K mHealth
%K cardiovascular disease
%K CVD
%K patient preferences
%K information quality
%K self-management
%K mobile applications
%K mobile apps
%K China
%D 2017
%7 14.12.2017
%9 Review
%J JMIR Mhealth Uhealth
%G English
%X 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. 
%M 29242176
%R 10.2196/mhealth.8549
%U http://mhealth.jmir.org/2017/12/e195/
%U https://doi.org/10.2196/mhealth.8549
%U http://www.ncbi.nlm.nih.gov/pubmed/29242176