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Harnessing technological solutions for childhood obesity prevention and treatment: a systematic review and meta-analysis of current applications

BACKGROUND: Technology holds promise for delivery of accessible, individualized, and destigmatized obesity prevention and treatment to youth. OBJECTIVES: This review examined the efficacy of recent technology-based interventions on weight outcomes. METHODS: Seven databases were searched in April 202...

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Detalles Bibliográficos
Autores principales: Fowler, Lauren A., Grammer, Anne Claire, Staiano, Amanda E., Fitzsimmons-Craft, Ellen E., Chen, Ling, Yaeger, Lauren H., Wilfley, Denise E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7904036/
https://www.ncbi.nlm.nih.gov/pubmed/33627775
http://dx.doi.org/10.1038/s41366-021-00765-x
Descripción
Sumario:BACKGROUND: Technology holds promise for delivery of accessible, individualized, and destigmatized obesity prevention and treatment to youth. OBJECTIVES: This review examined the efficacy of recent technology-based interventions on weight outcomes. METHODS: Seven databases were searched in April 2020 following PRISMA guidelines. Inclusion criteria were: participants aged 1–18 y, use of technology in a prevention/treatment intervention for overweight/obesity; weight outcome; randomized controlled trial (RCT); and published after January 2014. Random effects models with inverse variance weighting estimated pooled mean effect sizes separately for treatment and prevention interventions. Meta-regressions examined the effect of technology type (telemedicine or technology-based), technology purpose (stand-alone or adjunct), comparator (active or no-contact control), delivery (to parent, child, or both), study type (pilot or not), child age, and intervention duration. FINDINGS: In total, 3406 records were screened for inclusion; 55 studies representing 54 unique RCTs met inclusion criteria. Most (89%) included articles were of high or moderate quality. Thirty studies relied mostly or solely on technology for intervention delivery. Meta-analyses of the 20 prevention RCTs did not show a significant effect of prevention interventions on weight outcomes (d = 0.05, p = 0.52). The pooled mean effect size of n = 32 treatment RCTs showed a small, significant effect on weight outcomes (d = ‒0.13, p = 0.001), although 27 of 33 treatment studies (79%) did not find significant differences between treatment and comparators. There were significantly greater treatment effects on outcomes for pilot interventions, interventions delivered to the child compared to parent-delivered interventions, and as child age increased and intervention duration decreased. No other subgroup analyses were significant. CONCLUSIONS: Recent technology-based interventions for the treatment of pediatric obesity show small effects on weight; however, evidence is inconclusive on the efficacy of technology based prevention interventions. Research is needed to determine the comparative effectiveness of technology-based interventions to gold-standard interventions and elucidate the potential for mHealth/eHealth to increase scalability and reduce costs while maximizing impact.