The DOI matches its Crossref record; 90 of the 91 references it cites were found in a registry or an index.
Do smartphone applications and activity trackers increase physical activity in adults? Systematic review, meta-analysis and metaregression
Open accessAbstract
Objective: To determine the effectiveness of physical activity interventions involving mobile applications (apps) or trackers with automated and continuous self-monitoring and feedback. Design: Systematic review and meta-analysis. Data sources: PubMed and seven additional databases, from 2007 to 2020. Study selection: Randomised controlled trials in adults (18–65 years old) without chronic illness, testing a mobile app or an activity tracker, with any comparison, where the main outcome was a physical activity measure. Independent screening was conducted. Data extraction and synthesis: We conducted random effects meta-analysis and all effect sizes were transformed into standardised difference in means (SDM). We conducted exploratory metaregression with continuous and discrete moderators identified as statistically significant in subgroup analyses. Main outcome measures: Physical activity: daily step counts, min/week of moderate-to-vigorous physical activity, weekly days exercised, min/week of total physical activity, metabolic equivalents. Results: Thirty-five studies met inclusion criteria and 28 were included in the meta-analysis (n=7454 participants, 28% women). The meta-analysis showed a small-to-moderate positive effect on physical activity measures (SDM 0.350, 95% CI 0.236 to 0.465, I 2 =69%, T 2 =0.051) corresponding to 1850 steps per day (95% CI 1247 to 2457). Interventions including text-messaging and personalisation features were significantly more effective in subgroup analyses and metaregression. Conclusion: Interventions using apps or trackers seem to be effective in promoting physical activity. Longer studies are needed to assess the impact of different intervention components on long-term engagement and effectiveness.
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“Several systematic reviews and meta-analyses [15–19] have shown that these digital technology-based programs resulted in increased PA and reduced body weight, at least for a short duration.”
From A systematic review of artificial intelligence chatbots for promoting physical activity, healthy diet, and weight loss (2021) · cites this paper as [19]
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Canali, S., Schiaffonati, V., & Aliverti, A. (2022) · PLOS Digital Health · doi:10.1371/journal.pdig.0000104 · Cited by 457
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Background
Metadata
- Authors
- Laranjo, L., Ding, D., Heleno, B., Kocaballi, B., Quiroz, J. C., Tong, H. L., Chahwan, B., Neves, A. L., Gabarron, E., Dao, K. P., Rodrigues, D., Neves, G. C., Antunes, M. L., Coiera, E., & Bates, D. W.
- Affiliations
- The University of Sydney (AU)
- Universidade Nova de Lisboa (PT)
- UNSW Sydney (AU)
- Macquarie University (AU)
- Brigham and Women's Hospital (US)
- Corresponding author
- Laranjo, Liliana
- ORCID
- Venue
- British Journal of Sports Medicine
- Publisher
- BMJ
- Published
- 2020-12-21
- Volume
- 55
- Issue
- 8
- Pages
- 422-432
- ISSN
- 0306-3674 (ISSN-L)
- 1473-0480
- OpenAlex
- W3113845499
- Cited by
- 400
- References
- 91
- Citations by year
- 2026: 55 · 2025: 80 · 2024: 102 · 2023: 54 · 2022: 75 · 2021: 34
- FWCI
- 7.77
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- British Journal of Sports Medicine (publishedVersion)
- PubMed (publishedVersion)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by-nc-nd)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, other-oa)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by)
- Repository of Digital Objects for Teaching Research and Culture (University of Valencia) (submittedVersion, other-oa)
- Zenodo (CERN European Organization for Nuclear Research) (cc-by)
- Funders
- National Health and Medical Research Council (APP1134919)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- mobile health apps, wearable activity trackers, physical activity promotion, self-monitoring, feedback, step count, moderate-to-vigorous physical activity, text messaging, personalization, adults
- MeSH terms
- Smartphone, Fitness Trackers, Adult, Feedback, Humans, Regression Analysis, Health Behavior, Exercise, Mobile Applications
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