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Meta-Analysis
. 2021 Jan 11;9(1):e21563.
doi: 10.2196/21563.

Effectiveness of Mobile Apps to Promote Health and Manage Disease: Systematic Review and Meta-analysis of Randomized Controlled Trials

Sarah J Iribarren  1 , Tokunbo O Akande #  2 , Kendra J Kamp #  3 , Dwight Barry  4 , Yazan G Kader  1 , Elizabeth Suelzer  5
Affiliations
Meta-Analysis

Effectiveness of Mobile Apps to Promote Health and Manage Disease: Systematic Review and Meta-analysis of Randomized Controlled Trials

Sarah J Iribarren et al. JMIR Mhealth Uhealth. .

Abstract

Background: Interventions aimed at modifying behavior for promoting health and disease management are traditionally resource intensive and difficult to scale. Mobile health apps are being used for these purposes; however, their effects on health outcomes have been mixed.

Objective: This study aims to summarize the evidence of rigorously evaluated health-related apps on health outcomes and explore the effects of features present in studies that reported a statistically significant difference in health outcomes.

Methods: A literature search was conducted in 7 databases (MEDLINE, Scopus, PsycINFO, CINAHL, Global Index Medicus, Cochrane Central Register of Controlled Trials, and Cochrane Database of Systematic Reviews). A total of 5 reviewers independently screened and extracted the study characteristics. We used a random-effects model to calculate the pooled effect size estimates for meta-analysis. Sensitivity analysis was conducted based on follow-up time, stand-alone app interventions, level of personalization, and pilot studies. Logistic regression was used to examine the structure of app features.

Results: From the database searches, 8230 records were initially identified. Of these, 172 met the inclusion criteria. Studies were predominantly conducted in high-income countries (164/172, 94.3%). The majority had follow-up periods of 6 months or less (143/172, 83.1%). Over half of the interventions were delivered by a stand-alone app (106/172, 61.6%). Static/one-size-fits-all (97/172, 56.4%) was the most common level of personalization. Intervention frequency was daily or more frequent for the majority of the studies (123/172, 71.5%). A total of 156 studies involving 21,422 participants reported continuous health outcome data. The use of an app to modify behavior (either as a stand-alone or as part of a larger intervention) confers a slight/weak advantage over standard care in health interventions (standardized mean difference=0.38 [95% CI 0.31-0.45]; I2=80%), although heterogeneity was high.

Conclusions: The evidence in the literature demonstrates a steady increase in the rigorous evaluation of apps aimed at modifying behavior to promote health and manage disease. Although the literature is growing, the evidence that apps can improve health outcomes is weak. This finding may reflect the need for improved methodological and evaluative approaches to the development and assessment of health care improvement apps.

Trial registration: PROSPERO International Prospective Register of Systematic Reviews CRD42018106868; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=106868.

Keywords: mobile apps; mobile phone; systematic review.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram. RCT: randomized controlled trial.
Figure 2
Figure 2
Publication of included studies per year.
Figure 3
Figure 3
Number of studies with app features and frequency of app features.
Figure 4
Figure 4
Frequency of app features.
Figure 5
Figure 5
Risk of Bias.
Figure 6
Figure 6
Effect of studies with continuous outcomes.
Figure 7
Figure 7
Funnel plot.
Figure 8
Figure 8
Effect of studies with binary outcomes.
Figure 9
Figure 9
Effect of app features on outcome.
See this image and copyright information in PMC

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