Smartphone-Based Interventions for Physical Activity Promotion: Scoping Review of the Evidence Over the Last 10 Years
- PMID: 34287209
- PMCID: PMC8339983
- DOI: 10.2196/24308
Smartphone-Based Interventions for Physical Activity Promotion: Scoping Review of the Evidence Over the Last 10 Years
Abstract
Background: Several reviews of mobile health (mHealth) physical activity (PA) interventions suggest their beneficial effects on behavior change in adolescents and adults. Owing to the ubiquitous presence of smartphones, their use in mHealth PA interventions seems obvious; nevertheless, there are gaps in the literature on the evaluation reporting processes and best practices of such interventions.
Objective: The primary objective of this review is to analyze the development and evaluation trajectory of smartphone-based mHealth PA interventions and to review systematic theory- and evidence-based practices and methods that are implemented along this trajectory. The secondary objective is to identify the range of evidence (both quantitative and qualitative) available on smartphone-based mHealth PA interventions to provide a comprehensive tabular and narrative review of the available literature in terms of its nature, features, and volume.
Methods: We conducted a scoping review of qualitative and quantitative studies examining smartphone-based PA interventions published between 2008 and 2018. In line with scoping review guidelines, studies were not rejected based on their research design or quality. This review, therefore, includes experimental and descriptive studies, as well as reviews addressing smartphone-based mHealth interventions aimed at promoting PA in all age groups (with a subanalysis conducted for adolescents). Two groups of studies were additionally included: reviews or content analyses of PA trackers and meta-analyses exploring behavior change techniques and their efficacy.
Results: Included articles (N=148) were categorized into 10 groups: commercial smartphone app content analyses, smartphone-based intervention review studies, activity tracker content analyses, activity tracker review studies, meta-analyses of PA intervention studies, smartphone-based intervention studies, qualitative formative studies, app development descriptive studies, qualitative follow-up studies, and other related articles. Only 24 articles targeted children or adolescents (age range: 5-19 years). There is no agreed evaluation framework or taxonomy to code or report smartphone-based PA interventions. Researchers did not state the coding method, used various evaluation frameworks, or used different versions of behavior change technique taxonomies. In addition, there is no consensus on the best behavior change theory or model that should be used in smartphone-based interventions for PA promotion. Commonly reported systematic practices and methods have been successfully identified. They include PA recommendations, trial designs (randomized controlled trials, experimental trials, and rapid design trials), mixed methods data collection (surveys, questionnaires, interviews, and focus group discussions), scales to assess app quality, and industry-recognized reporting guidelines.
Conclusions: Smartphone-based mHealth interventions aimed at promoting PA showed promising results for behavior change. Although there is a plethora of published studies on the adult target group, the number of studies and consequently the evidence base for adolescents is limited. Overall, the efficacy of smartphone-based mHealth PA interventions can be considerably improved through a more systematic approach of developing, reporting, and coding of the interventions.
Keywords: BCT; adolescents; adults; behavior change; mHealth; mobile health; mobile phone; mobile phonescoping review; physical activity; research design; scoping review; smartphone application.
©Alex Domin, Donna Spruijt-Metz, Daniel Theisen, Yacine Ouzzahra, Claus Vögele. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 21.07.2021.
Conflict of interest statement
Conflicts of Interest: None declared.
Figures
Similar articles
-
Effects of Mobile Health Including Wearable Activity Trackers to Increase Physical Activity Outcomes Among Healthy Children and Adolescents: Systematic Review.JMIR Mhealth Uhealth. 2019 Apr 30;7(4):e8298. doi: 10.2196/mhealth.8298. JMIR Mhealth Uhealth. 2019. PMID: 31038460 Free PMC article.
-
Efficacy and Effectiveness of Mobile Health Technologies for Facilitating Physical Activity in Adolescents: Scoping Review.JMIR Mhealth Uhealth. 2019 Feb 12;7(2):e11847. doi: 10.2196/11847. JMIR Mhealth Uhealth. 2019. PMID: 30747716 Free PMC article.
-
Apps for IMproving FITness and Increasing Physical Activity Among Young People: The AIMFIT Pragmatic Randomized Controlled Trial.J Med Internet Res. 2015 Aug 27;17(8):e210. doi: 10.2196/jmir.4568. J Med Internet Res. 2015. PMID: 26316499 Free PMC article. Clinical Trial.
-
A Theory-Informed, Personalized mHealth Intervention for Adolescents (Mobile App for Physical Activity): Development and Pilot Study.JMIR Form Res. 2022 Jun 10;6(6):e35118. doi: 10.2196/35118. JMIR Form Res. 2022. PMID: 35687409 Free PMC article.
-
An mHealth Intervention Promoting Physical Activity and Healthy Eating in a Family Setting (SMARTFAMILY): Randomized Controlled Trial.JMIR Mhealth Uhealth. 2024 Apr 26;12:e51201. doi: 10.2196/51201. JMIR Mhealth Uhealth. 2024. PMID: 38669071 Free PMC article. Clinical Trial.
Cited by
-
Improving Predictability and Effectiveness in Preventive Digital Health Interventions: Scoping Review.Interact J Med Res. 2023 Jul 20;12:e40205. doi: 10.2196/40205. Interact J Med Res. 2023. PMID: 37471129 Free PMC article.
-
A scoping review of the feasibility, usability, and efficacy of digital interventions in older adults concerning physical activity and/or exercise.Front Aging. 2025 Apr 11;6:1516481. doi: 10.3389/fragi.2025.1516481. eCollection 2025. Front Aging. 2025. PMID: 40290578 Free PMC article.
-
A Smartphone App to Increase Immunizations in the Pediatric Solid Organ Transplant Population: Development and Initial Usability Study.JMIR Form Res. 2022 Jan 13;6(1):e32273. doi: 10.2196/32273. JMIR Form Res. 2022. PMID: 35023840 Free PMC article.
-
Effect of a Mobile App-Based Urinary Incontinence Self-Management Intervention Among Pregnant Women in China: Pragmatic Randomized Controlled Trial.J Med Internet Res. 2023 Jun 27;25:e43528. doi: 10.2196/43528. J Med Internet Res. 2023. PMID: 37368465 Free PMC article. Clinical Trial.
-
Utility of a high-intensity interval training app as a remote exercise support strategy in children with obesity: An exploratory study of adherence, effect, and perceptions of its use.Digit Health. 2024 Oct 18;10:20552076241291386. doi: 10.1177/20552076241291386. eCollection 2024 Jan-Dec. Digit Health. 2024. PMID: 39465221 Free PMC article.
References
-
- Lee I, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT, Lancet Physical Activity Series Working Group Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet. 2012 Jul 21;380(9838):219–29. doi: 10.1016/S0140-6736(12)61031-9. http://europepmc.org/abstract/MED/22818936 - DOI - PMC - PubMed
-
- Ding D, Lawson KD, Kolbe-Alexander TL, Finkelstein EA, Katzmarzyk PT, van Mechelen W, Pratt M, Lancet Physical Activity Series 2 Executive Committee The economic burden of physical inactivity: a global analysis of major non-communicable diseases. Lancet. 2016 Sep 24;388(10051):1311–24. doi: 10.1016/S0140-6736(16)30383-X. - DOI - PubMed
-
- WHO Director-general’s Opening Remarks at the Media Briefing on Covid-19. World Health Organization. [2020-05-26]. https://www.who.int/dg/speeches/detail/who-director-general-s-opening-re....
-
- COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) Johns Hopkins University. [2020-05-26]. https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594....
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Medical