E‐&mHealth interventions targeting nutrition, physical activity, sedentary behavior, and/or obesity among children: A scoping review of systematic reviews and meta‐analyses
Open accessAbstract
Childhood obesity is a public health concern. Electronic and mobile health (e-&mHealth) approaches can facilitate the delivery of interventions for obesity prevention and treatment. Synthesizing reviews of e-&mHealth interventions to improve weight and weight-related behaviors (physical activity, sedentary behavior, and diet) is useful to characterize the current scope of the literature and identify opportunities for future reviews and studies. Using a scoping review methodology, we aimed to evaluate the breadth and methodological quality of systematic reviews and meta-analyses of e-&mHealth interventions targeting weight and weight-related behaviors in children and adolescents aged <19 years. A systematic search of seven databases was conducted, including reviews published between 2000 and 2019. Review characteristics were extracted, and methodological quality was assessed using the AMSTAR 2 tool. Forty-five systematic reviews and meta-analyses were included. All reviews evaluated intervention efficacy (100%), but few assessed other aspects (20% in total) such as cost-effectiveness. Smartphone applications (47%), text messages (44%), and websites (35%) were the main modalities. Weight (60%), physical activity (51%), and diet (44%) were frequently assessed, unlike sedentary behavior (8%). Most reviews were rated as having critically low or low methodological quality (97%). Reviews that identify the effective active ingredients of interventions and explore metrics beyond efficacy are recommended.
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Data were extracted by pairs of eight independent reviewers using a data-extraction form.
“Data were extracted by pairs of eight independent reviewers using a data-extraction form (appendix pp 3-16) developed for the Review based on a template used in previous reviews of systematic reviews.29,30”
From Effectiveness of wearable activity trackers to increase physical activity and improve health: a systematic review of systematic reviews and meta-analyses. (2022) · cites this paper as [30]
The Methods section (Data Extraction and Critical Appraisal) says one reviewer extracted data and a second checked them using a predetermined form. This supports use of a form and two-person involvement, but not extraction by pairs of eight independent reviewers; the described roles were extractor and checker. (LLM, conf=0.86)
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Ferrer, D. A., & Ellis, R. (2017) · Journal of Physical Activity and Health · doi:10.1123/jpah.2016-0534 · Cited by 33 · see citing works
Antwi, F. A., Fazylova, N., Garcon, M.-C., López, L. R., Rubiano, R., & Slyer, J. T. (2013) · The JBI Database of Systematic Reviews and Implementation Reports · doi:10.11124/jbisrir-2013-459 · Cited by 31 · see citing works
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The Impact of Active Video Gaming on Weight in Youth
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The use of web-based interventions to prevent excessive weight gain
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Flagged first, then by citations
Research works printed but not linked: 2
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- [18]Nand K, Baghaei N, Casey J, Barmada B, Mehdipour F, Liang H-N. Engaging children with educational content via Gamification. Smart Learning Environments. 2019; 6(1): 6.
Cited by
Sorted by citations
Singh, B., Olds, T., Curtis, R., Dumuid, D., Virgara, R., Watson, A., Szeto, K., O'Connor, E., Ferguson, T., Eglitis, E., et al. (2023) · British Journal of Sports Medicine · doi:10.1136/bjsports-2022-106195 · Cited by 1,049 · see citing works
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Self-citation
- Authors
- Kracht, C. L., Hutchesson, M., Ahmed, M., Müller, A. M., Ashton, L. M., Brown, H. M., DeSmet, A., Maher, C. A., Mauch, C. E., Vandelanotte, C., Yin, Z., Whatnall, M., Short, C. E., & Staiano, A. E.
- Affiliations
- Pennington Biomedical Research Center (US)
- University of Newcastle Australia (AU)
- University of Toronto (CA)
- National University of Singapore (SG)
- Hunter New England Local Health District (AU)
- Université Libre de Bruxelles (BE)
- University of South Australia (AU)
- Flinders University (AU)
- Central Queensland University (AU)
- The University of Texas at San Antonio (US)
- The University of Melbourne (AU)
- Corresponding author
- Staiano, Amanda E.
- ORCID
- Venue
- Obesity Reviews
- Publisher
- Wiley
- Published
- 2021-09-02
- Volume
- 22
- Issue
- 12
- Pages
- e13331-e13331
- ISSN
- 1467-7881 (ISSN-L)
- 1467-789X
- PMC
- PMC8865754
- OpenAlex
- W3197405589
- Cited by
- 37
- References
- 109
- Citations by year
- 2026: 6 · 2025: 10 · 2024: 9 · 2023: 9 · 2022: 3
- FWCI
- 1.08
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Obesity Reviews (publishedVersion, other-oa)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- UniSA Research Outputs Repository (University of South Australia) (submittedVersion)
- Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) (submittedVersion, other-oa)
- Minerva Access (University of Melbourne) (submittedVersion)
- Funders
- Mitacs
- Government of Canada
- National Institute of Diabetes and Digestive and Kidney Diseases (T32DK064584)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- e-health, mobile health, childhood obesity, obesity prevention, children and adolescents, physical activity, sedentary behavior, nutrition, diet, weight-related behaviors, mobile application, text messaging, websites, methodological quality of systematic reviews, cost-effectiveness
- MeSH terms
- Systematic Reviews as Topic, Adolescent, Child, Humans, Exercise, Telemedicine, Sedentary Behavior, Pediatric Obesity
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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