Effectiveness, acceptability and usefulness of mobile applications for cardiovascular disease self-management: Systematic review with meta-synthesis of quantitative and qualitative data

Background: Mobile technologies are innovative, scalable approaches to reducing risk of cardiovascular disease (CVD) but evidence related to effectiveness and acceptability remains limited. We aimed to explore the effectiveness, acceptability and usefulness of mobile applications (apps) for CVD self-management and risk factor control.Design: Systematic review with meta-synthesis of quantitative and qualitative data.Methods: Comprehensive search of multiple databases (Medline, Embase, CINAHL, SCOPUS, and Cochrane CENTRAL) and grey literature. Studies were included if the intervention was primarily an app aimed at improving at least two lifestyle behaviours in adults with CVD. Meta-synthesis of quantitative and qualitative data was performed to review and evaluate findings.Results: Ten studies of varying designs including 607 patients from 5 countries were included. Interventions targeted hypertension, heart failure, stroke and cardiac rehabilitation populations. Factors that improved among app users were rehospitalisation rates, disease-specific knowledge, quality of life, psychosocial well-being, blood pressure, body mass index, waist circumference, cholesterol, and exercise capacity. Improved physical activity, medication adherence, and smoking cessation were also characteristic of app users. Appealing app features included tracking healthy behaviours, self-monitoring, , disease education, and personalised, customisable content. Small samples, short duration, and selection bias were noted limitations across some studies, as was the relatively low overall scientific quality of evidence. Conclusions: Multiple behaviours and CVD risk factors appear modifiable in the shorter term with use of mobile apps. Evidence for effectiveness requires larger, controlled studies of longer duration, with emphasis on process evaluation data to better understand important system- and patient-level characteristics