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

Abstract

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.

The effectiveness of e‐health interventions for the treatment of overweight or obesity in children and adolescents: A systematic review and meta‐analysis

“…Similar to our findings, the previous meta-analyses on the treatment of childhood obesity have not found a difference in treatment effect according to intervention duration. 97,100 However, a previous meta-analysis targeting technology-based interventions for prevention and treatment of obesity, 52 found that shorter duration interventions were associated with significant effect, which the authors argue that could be related to the issues of engagement and long-term adherence of digital interventions. 101 In our meta-analysis, none of the included studies recorded follow-up measurements after the end of the intervention.…”

“…44 Systematic reviews have examined the effectiveness of e-health interventions, combining prevention and treatment of obesity in children. [48][49][50][51][52][53] However, just a few specifically focused on the treatment of obesity, defined as interventions which target only children with overweight and obesity rather than mixed weight. 54 The meta-analyses on e-health intervention for the treatment of overweight and obesity so far published do not limit the duration of the intervention delivery.…”

“…However, there is evidence that although interventions appeared to be effective in the short-term, they may not be in the long term (> 6 months), 58 in particular e-health interventions seem to have a greater effect on shorter intervention duration. 52 Therefore, this narrative systematic review and meta-analysis aimed to examine the effectiveness of e-health interventions for the treatment of overweight or obesity in children (0 to 17 years old). The secondary aim was to explore subgroup differences according to age, weight status, duration, behaviours targeted, income and study quality on intervention outcomes and provide a narrative synthesis to gather knowledge of the components of e-health interventions to guide future research and implementation.…”

Effectiveness of digital primary prevention interventions targeting physical activity, motor skills and nutrition in children aged 3–10 years in the setting of day care and primary school: protocol for a systematic review

“…However, little seems to be known about the impact of digital technologies on healthy eating/drinking, PA and the variety of movement in children, especially when being applied in the relevant settings of (early) childhood education. 30 45 50 51 An evidence-based and responsible implementation of digital primary prevention interventions in these settings may lead to an increased acceptance of educational staff and ultimately lay the foundations of digital interventions being also seen as facilitators of healthy lifestyles for children. 35 It is of vital importance to find out how settings like day-care facilities and primary schools can be adequately equipped, qualified and empowered to effectively and responsibly use digital interventions to support healthy behaviours of children.…”

Translating Family-Based Behavioral Treatment for Childhood Obesity into a User-Friendly Digital Package for Delivery to Low-Income Families through Primary Care Partnerships: The MO-CORD Study

“…Importantly, technology adjuncts to FBT have been shown to be feasible in children from low-income households, 20 and a recent meta-analysis suggests that technology-based/assisted treatment approaches for childhood obesity are effective. 21 Although possession and knowledge of use of technology to facilitate health information are not universal, households that have limited access to health care, for example, lowincome households, are more likely to rely solely on mobile devices for communication and Internet access, 22,23 suggesting the potential for mobile devices to be a viable method for service delivery, particularly when that service does not rely heavily on data usage. A digital treatment platform that can be accessed through any mobile or Internet-enabled device and provides easy access to digitized treatment materials and resources to support families in FBT (e.g., having mobile access to daily behavior tracking logs can reduce barriers to tracking and improve adherence) can also facilitate a continuous relationship between the provider delivering the treatment and the family outside of in-person treatment sessions, improving adherence to and sustained engagement with treatment.…”