Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Meta-Analysis
. 2025 Oct 17:27:e69065.
doi: 10.2196/69065.

Lifestyle eHealth and mHealth Interventions for Children and Adolescents: Systematic Umbrella Review and Meta-Meta-Analysis

Ben Singh  1 , Mavra Ahmed  2 , Amanda E Staiano  3 , Maria F Vasiloglou  4 , Claire Gough  5 , Jasmine M Petersen  1 , Zenong Yin  6 , Corneel Vandelanotte  7 , Chelsea Kracht  8 , Janis Fiedler  9 , Irina Timm  9 , Joan Dallinga  10 , Bridve Sivakumar  11 , Hannes Baumann  12 , Christopher Huong  6 , Kathrin Wunsch  9   13 , Mónica Suárez-Reyes  3   14 , Stephanie Schoeppe  7 , Alyssa M Button  15 , Katherine Spring  3 , Carol Maher  1
Affiliations
Meta-Analysis

Lifestyle eHealth and mHealth Interventions for Children and Adolescents: Systematic Umbrella Review and Meta-Meta-Analysis

Ben Singh et al. J Med Internet Res. .

Abstract

Background: eHealth and mobile health (mHealth) interventions are promising in promoting healthy behaviors among children and adolescents.

Objective: This systematic umbrella review and meta-meta-analysis aimed to evaluate the effectiveness of eHealth and mHealth interventions in promoting healthy behaviors among children and adolescents.

Methods: Nine databases were searched for systematic reviews and meta-analyses of randomized controlled trials of eHealth and mHealth interventions targeting physical activity, sedentary behavior, sleep, and dietary outcomes in children and adolescents aged below 18 years. Screening, data extraction, and all assessments were completed by 2 reviewers. Study quality was assessed using the AMSTAR-2 (A Measurement Tool to Assess Systematic Reviews-2) checklist, and meta-analyses were conducted to combine effect sizes using random effects models. Subgroup analyses examined participant and intervention characteristics.

Results: A total of 25 systematic reviews comprising 440 randomized controlled trials and 133,501 participants, mostly involving healthy children and adolescents (n=18, 72%) or those who were overweight or with obesity (n=4, 16%), were included. Interventions mostly included active video games or serious games (n=8, 32%), various mHealth interventions (n=6, 24%), various eHealth interventions (n=5, 20%), combined eHealth and mHealth interventions (n=4, 16%), wearables (n=1, 4%), and computer-based interventions (n=1, 4%). Most studies (n=18, 72%) had critically low AMSTAR-2 scores. Meta-analyses based on standardized mean difference (SMD) showed significant effects (all P<.05) for moderate to vigorous physical activity (SMD 0.18, 95% CI 0.09-0.27), total physical activity (SMD 0.24, 95% CI 0.13-0.35), fat intake (SMD 0.10, 95% CI 0.02-0.18), fruit and vegetable intake (SMD 0.11, 95% CI 0.00-0.22), BMI (SMD 0.19, 95% CI 0.11-0.27), and body weight (SMD 0.15, 95% CI 0.01-0.30). No effects were found for sedentary behavior (SMD 0.12, 95% CI -0.11 to 0.35) or sleep (SMD 0.27, 95% CI -0.09 to 0.63). Shorter interventions (lasting <8 weeks) had a greater effect on moderate to vigorous physical activity than longer interventions (lasting ≥8 weeks), while longer interventions (lasting ≥12 weeks) had a greater effect on BMI compared with shorter interventions.

Conclusions: eHealth and mHealth interventions offer modest but meaningful improvements in physical activity, diet, and weight management in children and adolescents, with important implications for integrating digital tools into health promotion strategies.

Trial registration: PROSPERO CRD42024537019; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024537019.

Keywords: diet; digital interventions; eHealth; health behaviors; health technologies; lifestyle; mHealth; mobile health; physical activity; sedentary behavior; sleep.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart.
Figure 2
Figure 2
Meta-analysis of effects of eHealth and mobile health interventions on physical activity outcomes in children and adolescents based on standardized mean difference. Positive effect sizes favor intervention.
Figure 3
Figure 3
Meta-analysis of effects of eHealth and mobile health interventions on dietary outcomes in children and adolescents based on standardized mean difference. Positive effect sizes favor intervention.
Figure 4
Figure 4
Meta-analysis of effects of eHealth and mobile health interventions on sedentary behavior in children and adolescents based on standardized mean difference. Positive effect sizes favor intervention.
Figure 5
Figure 5
Meta-analysis of effects of eHealth and mobile health interventions on BMI and body weight in children and adolescents based on standardized mean difference. Positive effect sizes favor intervention.
See this image and copyright information in PMC

References

    1. Davis A, Sweigart R, Ellis R. A systematic review of tailored mHealth interventions for physical activity promotion among adults. Transl Behav Med. 2020 Oct 12;10(5):1221–32. doi: 10.1093/tbm/ibz190.5921064 - DOI - PubMed
    1. Kohl 3rd HW, Craig CL, Lambert EV, Inoue S, Alkandari JR, Leetongin G, Kahlmeier S, Lancet Physical Activity Series Working Group The pandemic of physical inactivity: global action for public health. Lancet. 2012 Jul 21;380(9838):294–305. doi: 10.1016/S0140-6736(12)60898-8. https://doi.org/10.5167/uzh-69552 S0140-6736(12)60898-8 - DOI - PubMed
    1. Stamatakis E, Ekelund U, Ding D, Hamer M, Bauman AE, Lee IM. Is the time right for quantitative public health guidelines on sitting? A narrative review of sedentary behaviour research paradigms and findings. Br J Sports Med. 2019 Mar;53(6):377–82. doi: 10.1136/bjsports-2018-099131. http://bjsm.bmj.com/lookup/pmidlookup?view=long&pmid=29891615 bjsports-2018-099131 - DOI - PMC - PubMed
    1. Endalifer ML, Diress G. Epidemiology, predisposing factors, biomarkers, and prevention mechanism of obesity: a systematic review. J Obes. 2020 May 31;2020:6134362. doi: 10.1155/2020/6134362. https://europepmc.org/abstract/MED/32566274 - DOI - PMC - PubMed
    1. Rosenberger ME, Fulton JE, Buman MP, Troiano RP, Grandner MA, Buchner DM, Haskell WL. The 24-hour activity cycle: a new paradigm for physical activity. Med Sci Sports Exerc. 2019 Mar;51(3):454–64. doi: 10.1249/MSS.0000000000001811. https://europepmc.org/abstract/MED/30339658 - DOI - PMC - PubMed

LinkOut - more resources