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Cited by 561Mobile Health and mHealth ApplicationsDigital Mental Health InterventionsHealth, Technology, Consumer Behavior

Rates of Attrition and Dropout in App-Based Interventions for Chronic Disease: Systematic Review and Meta-Analysis

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Meyerowitz-Katz, Gideon, Ravi, Sumathy, Arnolda, Leonard, Feng, Xiaoqi, Maberly, Glen, Astell-Burt, Thomas·2020·Journal of Medical Internet Research
DOI 10.2196/20283PMC PMC7556375

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Abstract

Background: Chronic disease represents a large and growing burden to the health care system worldwide. One method of managing this burden is the use of 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 app 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: Our objectives are to systematically appraise and perform a meta-analysis on dropout rates in apps for chronic disease and to qualitatively synthesize possible reasons for these dropout rates that could be addressed in future interventions. Methods: MEDLINE (Medical Literature Analysis and Retrieval System Online), PubMed, Cochrane CENTRAL (Central Register of Controlled Trials), and Embase were searched from 2003 to the present to look at mobile health (mHealth) and attrition or dropout. Studies, either randomized controlled trials (RCTs) or observational trials, looking at chronic disease with measures of dropout were included. Meta-analysis of attrition rates was conducted in Stata, version 15.1 (StataCorp LLC). Included studies were also qualitatively synthesized to examine reasons for dropout and avenues for future research. Results: Of 833 studies identified in the literature search, 17 were included in the review and meta-analysis. Out of 17 studies, 9 (53%) were RCTs and 8 (47%) were observational trials, with both types covering a range of chronic diseases. The pooled dropout rate was 43% (95% CI 29-57), with observational studies having a higher dropout rate (49%, 95% CI 27-70) than RCTs in more controlled scenarios, which only had a 40% dropout rate (95% CI 16-63). 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 app-based interventions, including social, demographic, and behavioral 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. Trial Registration: International Prospective Register of Systematic Reviews (PROSPERO) CRD42019128737; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019128737

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  • The sample size calculation required 69 participants per group (at least 138 total) to demonstrate a significant effect, assuming an effect size of 0.55, a one-sided significance level of 2.5%, a power of 0.8, and an expected attrition rate of 23%.

    “Assuming an effect size of 0.55, a significance level of 2.5% (1-sided test), and a power of 0.8, a sample size of 69 participants per group, that is, at least 138 participants in total, was required to demonstrate a significant effect. This included an expected attrition rate of 23% [37].”

    From Evaluation of the Impact of Mobile Health App Vitadio in Patients With Type 2 Diabetes: Randomized Controlled Trial (2025) · cites this paper as [37]

    The citation is attached to the expected 23% attrition rate, not the preceding sample-size calculation. The Results > Meta-Analysis passage reports 43% attrition overall and 40% in randomized trials, rather than 23%. The paper does not provide the cited 23% estimate. (LLM, conf=0.84)

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  • The threshold for trial retention to be feasible was judged against 57%, which was the pooled attrition rate of app-based interventions for chronic diseases.

    “The threshold for trial retention to be feasible was judged against 57 %, which was the pooled attrition rate of app-based interventions for chronic diseases (Meyerowitz-Katz et al., 2020).”

    From An online acceptance, commitment, and self-compassion based treatment to decrease psychological distress in people with type 2 diabetes: A feasibility randomised-controlled trial (2023) · cites this paper as Meyerowitz-Katz et al., 2020

    The Results > Meta-Analysis passage reports a pooled attrition rate of 43% (95% CI 29–57), not 57%. The cited 57% is the upper confidence-interval bound. The citing authors’ choice of a feasibility threshold is their own, but their description of the source’s pooled rate is incorrect. (LLM, conf=0.95)

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  • The comparatively higher attrition rate in pure online intervention studies was also evident in this review, where the blended group scored higher in the risk of bias assessment regarding withdrawals and dropouts compared to the online group.

    “Generally, the comparatively higher attrition rate in pure online intervention studies (84–88) was also evident in this review where the blended group scored higher in the risk of bias assessment regarding withdrawals and dropouts compared to the online group.”

    From Digital resilience interventions for healthcare workers: a systematic review (2025) · cites this paper as [84]

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  • The treatment completion rate of 47% was below the threshold of 57% suggested as the average completion in previous studies of online programmes for chronic disease.

    “The treatment completion rate of 47 % was below the threshold of 57 % suggested as the average completion in previous studies of online programmes for chronic disease (Meyerowitz-Katz et al., 2020).”

    From An online acceptance, commitment, and self-compassion based treatment to decrease psychological distress in people with type 2 diabetes: A feasibility randomised-controlled trial (2023) · cites this paper as Meyerowitz-Katz et al., 2020

    The Results (Meta-Analysis) report average attrition of 43% in app-based chronic-disease interventions, implying 57% retention. But the Results (Overview) say purely online interventions were excluded, and the paper reports attrition rather than a treatment-completion threshold. The cited paper therefore supports the numerical comparison only as an inference for app-based interventions. (LLM, conf=0.87)

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  • The proportion of treatment completion in online self-management programmes for chronic disease has varied widely (between 9 and 82%), with a pooled estimate of 43% treatment drop-outs, indicating 57% treatment completion across studies.

    “The proportion of treatment completion in online self-management programmes for chronic disease has varied widely (between 9 and 82 %), with a pooled estimate of 43 % treatment drop-outs, indicating 57 % treatment completion across studies (Meyerowitz-Katz et al., 2020).”

    From An online acceptance, commitment, and self-compassion based treatment to decrease psychological distress in people with type 2 diabetes: A feasibility randomised-controlled trial (2023) · cites this paper as Meyerowitz-Katz et al., 2020

    The Results > Meta-Analysis section reports a pooled attrition rate of 43%, from which 57% retention follows arithmetically. But Results > Characteristics of Included Studies identifies 9%–82% as the range of attrition, not completion. Results > Overview also says purely online interventions were excluded; the synthesis concerned app-based interventions for chronic disease. (LLM, conf=0.90)

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Authors
Meyerowitz-Katz, G., Ravi, S., Arnolda, L., Feng, X., Maberly, G., & Astell-Burt, T.
Affiliations
  • Western Sydney Local Health District (AU)
  • University of Wollongong (AU)
  • The University of Sydney (AU)
ORCID
Venue
Journal of Medical Internet Research
Publisher
JMIR Publications Inc.
Published
2020-09-29
Volume
22
Issue
9
Pages
e20283
ISSN
1438-8871 (ISSN-L)
DOI
10.2196/20283
PMC
PMC7556375
OpenAlex
W3047292084
Cited by
561
References
31
Citations by year
2026: 120 · 2025: 129 · 2024: 129 · 2023: 84 · 2022: 73 · 2021: 26
FWCI
8.72
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Journal of Medical Internet Research (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Figshare (publishedVersion)
  • Research Online (University of Wollongong) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
Keywords
attrition, dropout, mobile health apps, chronic disease management, smartphone-based intervention, causes of dropout, sociodemographic factors, behavioral factors, digital health interventions
MeSH terms
Internet-Based Intervention, Chronic Disease, Humans, Telemedicine, Mobile Applications

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