Can smartphone apps increase physical activity? Systematic review and meta-analysis
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Abstract
BACKGROUND: Smartphone apps are a promising tool for delivering accessible and appealing physical activity interventions. Given the large growth of research in this field, there are now enough studies using the "gold standard" of experimental design-the randomized controlled trial design-and employing objective measurements of physical activity, to support a meta-analysis of these scientifically rigorous studies. OBJECTIVE: This systematic review and meta-analysis aimed to determine the effectiveness of smartphone apps for increasing objectively measured physical activity in adults. METHODS: A total of 7 electronic databases (EMBASE, EmCare, MEDLINE, Scopus, Sport Discus, The Cochrane Library, and Web of Science) were searched from 2007 to January 2018. Following the Population, Intervention, Comparator, Outcome and Study Design format, studies were eligible if they were randomized controlled trials involving adults, used a smartphone app as the primary or sole component of the physical activity intervention, used a no- or minimal-intervention control condition, and measured objective physical activity either in the form of moderate-to-vigorous physical activity minutes or steps. Study quality was assessed using a 25-item tool based on the Consolidated Standards of Reporting Trials checklist. A meta-analysis of study effects was conducted using a random effects model approach. Sensitivity analyses were conducted to examine whether intervention effectiveness differed on the basis of intervention length, target behavior (physical activity alone vs physical activity in combination with other health behaviors), or target population (general adult population vs specific health populations). RESULTS: Following removal of duplicates, a total of 6170 studies were identified from the original database searches. Of these, 9 studies, involving a total of 1740 participants, met eligibility criteria. Of these, 6 studies could be included in a meta-analysis of the effects of physical activity apps on steps per day. In comparison with the control conditions, smartphone apps produced a nonsignificant (P=.19) increase in participants' average steps per day, with a mean difference of 476.75 steps per day (95% CI -229.57 to 1183.07) between groups. Sensitivity analyses suggested that physical activity programs with a duration of less than 3 months were more effective than apps evaluated across more than 3 months (P=.01), and that physical activity apps that targeted physical activity in isolation were more effective than apps that targeted physical activity in combination with diet (P=.04). Physical activity app effectiveness did not appear to differ on the basis of target population. CONCLUSIONS: This meta-analysis provides modest evidence supporting the effectiveness of smartphone apps to increase physical activity. To date, apps have been most effective in the short term (eg, up to 3 months). Future research is needed to understand the time course of intervention effects and to investigate strategies to sustain intervention effects over time.
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Several meta-analyses found that digital health interventions' effects on physical activity were not statistically significant.
“Yet several meta-analyses found these effects were not statistically significant (23, 24).”
Recent meta-analyses of randomized controlled trials reported only small effects for stand-alone physical activity apps.
“Unfortunately, recent meta-analyses of randomized controlled trials reported only small effects for these types of interventions (6, 7).”
From Which Components of a Smartphone Walking App Help Users to Reach Personalized Step Goals? Results From an Optimization Trial (2020) · cites this paper as [7]
The summary effect of stand-alone physical activity apps was estimated at 477 steps per day (95% CI −230 to 1,183).
“For example, the summary effect of stand-alone physical activity apps was estimated at 477 steps per day, 95% confidence interval (CI): [−230, 1,183] (7).”
From Which Components of a Smartphone Walking App Help Users to Reach Personalized Step Goals? Results From an Optimization Trial (2020) · cites this paper as [7]
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- Authors
- Romeo, A., Edney, S., Plotnikoff, R., Curtis, R., Ryan, J., Sanders, I., Crozier, A., & Maher, C.
- Affiliations
- University of South Australia (AU)
- University of Newcastle Australia (AU)
- Corresponding author
- Maher, Carol
- ORCID
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2019-03-19
- Volume
- 21
- Issue
- 3
- Pages
- e12053
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC6444212
- OpenAlex
- W2904460099
- Cited by
- 487
- References
- 38
- Citations by year
- 2026: 35 · 2025: 57 · 2024: 69 · 2023: 52 · 2022: 82 · 2021: 108 · 2020: 64 · 2019: 19
- FWCI
- 8.63
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UniSA Research Outputs Repository (University of South Australia) (acceptedVersion, other-oa)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion, cc-by)
- National University of Singapore (submittedVersion)
- Figshare (submittedVersion, cc-by)
- NOVA (University of Newcastle Australia) (submittedVersion, other-oa)
- NOVA (University of Newcastle Australia) (submittedVersion, cc-by)
- Funders
- Australian Government
- Medical Research Council
- National Health and Medical Research Council (1080186, 1125913)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- mobile application, physical activity interventions, step count, moderate-to-vigorous physical activity, objective physical activity measurement, adults, intervention duration, health behavior change, mobile health
- MeSH terms
- Smartphone, Adult, Humans, Health Behavior, Exercise, Mobile Applications
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