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Cited by 257Physical Activity and HealthMobile Health and mHealth ApplicationsContext-Aware Activity Recognition Systems

The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.

The Effect of Physical Activity Interventions Comprising Wearables and Smartphone Applications on Physical Activity: a Systematic Review and Meta-analysis

Open access
Gal, Roxanne, May, Anne M., van Overmeeren, Elon J., Simons, Monique, Monninkhof, Evelyn M.·2018·Sports Medicine - Open
DOI 10.1186/s40798-018-0157-9PMC PMC6120856
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Abstract

BACKGROUND: Worldwide physical activity levels of adults are declining, which is associated with increased chronic disease risk. Wearables and smartphone applications offer new opportunities to change physical activity behaviour. This systematic review summarizes the evidence regarding the effect of wearables and smartphone applications on promoting physical activity. METHODS: PubMed, EMBASE and Cochrane databases were searched for RCTs, published since January 2008, on wearables and smartphone applications to promote physical activity. Studies were excluded when the study population consisted of children or adolescents, the intervention did not promote physical activity or comprised a minor part of the intervention, or the intervention was Internet-based and not accessible by smartphone. Risk of bias was assessed by the Cochrane collaboration tool. The primary outcome was changed in physical activity level. Meta-analyses were performed to assess the pooled effect on (moderate-to-vigorous) physical activity in minutes per day and daily step count. RESULTS: = 90%). When removing studies with an unclear or high risk of bias, intervention effects improved and statistical heterogeneity was removed. CONCLUSIONS: This meta-analysis showed a small to moderate effect of physical activity interventions comprising wearables and smartphone applications on physical activity. Hence, wearables and smartphone applications are likely to bring new opportunities in delivering tailored interventions to increase levels of physical activity.

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Crossref · 10.1186/s40798-018-0157-9

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Figures

Fig. 1 Flow diagram of trial selection, adapted from PRISMA. PA physical activity, RCT randomized controlled trial
Fig. 1 Flow diagram of trial selection, adapted from PRISMA. PA physical activity, RCT randomized controlled trialCC BY · PubMed Central
Fig. 2 Risk of bias graph: review authors’ judgements about each risk of bias item presented as percentages across all included studies
Fig. 2 Risk of bias graph: review authors’ judgements about each risk of bias item presented as percentages across all included studiesCC BY · PubMed Central
Fig. 3 Risk of bias summary: review authors’ judgements about each risk of bias item for each included study. Green symbols represent a low risk of bias, yellow symbols represent an unclear risk of bias and the red symbols indicate a high risk of bias
Fig. 3 Risk of bias summary: review authors’ judgements about each risk of bias item for each included study. Green symbols represent a low risk of bias, yellow symbols represent an unclear risk of bias and the red symbols indicate a high risk of biasCC BY · PubMed Central
Fig. 4 Forest plot of the effect of wearables and smartphone applications versus control on moderate-to-vigorous physical activity (MVPA) in minutes per day. CI confidence interval, IV inverse variance, RoB risk of bias, SD standard deviation, Std standardized
Fig. 4 Forest plot of the effect of wearables and smartphone applications versus control on moderate-to-vigorous physical activity (MVPA) in minutes per day. CI confidence interval, IV inverse variance, RoB risk of bias, SD standard deviation, Std standardizedCC BY · PubMed Central
Fig. 5 Forest plot of the effect of wearables and smartphone applications versus control on daily step count. CI confidence interval, IV inverse variance, RoB risk of bias, SD standard deviation, Std standardized
Fig. 5 Forest plot of the effect of wearables and smartphone applications versus control on daily step count. CI confidence interval, IV inverse variance, RoB risk of bias, SD standard deviation, Std standardizedCC BY · PubMed Central
Fig. 6 Forest plot of the effect of wearables and smartphone applications versus control on other outcomes. CI confidence interval, IV inverse variance, MET metabolic equivalent of task, SD standard deviation, Std standardized
Fig. 6 Forest plot of the effect of wearables and smartphone applications versus control on other outcomes. CI confidence interval, IV inverse variance, MET metabolic equivalent of task, SD standard deviation, Std standardizedCC BY · PubMed Central

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  1. Review Manager (RevMan) [Computer program]. Version 5.3. Copenhagen: The Nordic Cochrane Centre The Cochrane Collaboration; 2014. https://community.cochrane.org/help/tools-and-software/revman-5 .

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Metadata

Authors
Gal, R., May, A. M., van Overmeeren, E. J., Simons, M., & Monninkhof, E. M.
Affiliations
Utrecht University (NL)
Corresponding author
Gal, Roxanne
ORCID
Venue
Sports Medicine - Open
Publisher
Springer Science and Business Media LLC
Published
2018-09-03
Volume
4
Issue
1
Pages
42-42
ISSN
  • 2198-9761 (ISSN-L)
  • 2199-1170
DOI
10.1186/s40798-018-0157-9
PMC
PMC6120856
OpenAlex
W2889406366
Cited by
257
References
62
Citations by year
2026: 23 · 2025: 18 · 2024: 30 · 2023: 34 · 2022: 56 · 2021: 44 · 2020: 33 · 2019: 16 · 2018: 2
FWCI
3.12
Type
journal article
Language
en
Open access
Licence
Locations
  • Sports Medicine - Open (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Socio-Environmental Systems Modeling (acceptedVersion, cc-by)
  • Leiden Repository (Leiden University) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
  • Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
Funders
  • Sport & Society, Utrecht University, The Netherlands
  • ZonMw (016.156.050)
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
Keywords
physical activity interventions, wearable devices, mobile application, physical activity promotion, moderate-to-vigorous physical activity, daily step count, behavior change, risk of bias

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