Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: May 14, 2020
Date Accepted: Aug 3, 2020
A systematic review and meta-analysis of rates of attrition and dropout in app-based interventions for chronic disease
ABSTRACT
Background:
Chronic disease represents a large and growing burden to the healthcare system worldwide. One method of managing this burden is app-based interventions, however attrition, defined as lack of patient use of the intervention, is an issue for these interventions. While many apps have been developed, there is some evidence that they have significant issues with sustained use, with up to 98% of people only using the application for a short time before dropping out and/or dropping use down to the point where the app is no longer effective at helping to manage disease.
Objective:
To systematically review and meta-analyze the rate and causes of dropout in mHealth interventions for diabetes and other chronic health issues.
Methods:
Medline, Pubmed, Cochrane CENTRAL, and Embase were searched from 2003 to the present, looking at mHealth and attrition or dropout. Studies – either randomized or observational - looking at chronic disease with measures of dropout were included. Meta-analysis of attrition rates was conducted in Stata 15.1. Included studies were also qualitatively synthesized to examine reasons for dropouts and avenues for future research.
Results:
Of 833 studies identified in the literature search, 17 were included in the review and meta-analysis. Meta-analysis results are presented below. Chronic disease management apps had an overall dropout rate of 47%. Apps specifically targeting metabolic disease had a lower rate of 32%. The studies were extremely varied, which is represented statistically in the high degree of heterogeneity (I2>99%). Qualitative synthesis revealed a range of reasons relating to attrition from apps, including social, demographic, and behavioural factors that could be addressed.
Conclusions:
Dropout rates in mHealth interventions are high, but possible areas to minimize attrition exist. Reducing dropout rates will make these apps more effective for disease management in the long term. Clinical Trial: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=128737
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