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

Background: Youth (age 15-24 years) with and without disability are not adequately represented enough in exercise research due to a lack of time and transportation. These barriers can be overcome by including accessible web-based assessments that eliminate the need for on-site visitations. There is no simple, low-cost, and psychometrically sound compilation of measures for physical fitness and function that can be applied to youth with and without mobility disabilities. Objective: The first purpose was to determine the statistical level of agreement of 4 web-modified clinical assessments with how they are typically conducted in person at a laboratory (convergent validity). The second purpose was to determine the level of agreement between a novice and an expert rater (interrater reliability). The third purpose was to explore the feasibility of implementing the assessments via 2 metrics: safety and duration. Methods: The study enrolled 19 ambulatory youth: 9 (47%) with cerebral palsy with various mobility disabilities from a children’s hospital and 10 (53%) without disabilities from a university student population. Participants performed a battery of tests via videoconferencing and in person. The test condition (teleassessment and in person) order was randomized. The battery consisted of the hand grip strength test with a dynamometer, the five times sit-to-stand test (FTST), the timed up-and-go (TUG) test, and the 6-minute walk test (6MWT) either around a standard circular track (in person) or around a smaller home-modified track (teleassessment version, home-modified 6-minute walk test [HM6MWT]). Statistical analyses included descriptive data, intraclass correlation coefficients (ICCs), and Bland-Altman plots. Results: The mean time to complete the in-person assessment was 16.9 (SD 4.8) minutes and the teleassessment was 21.1 (SD 5.9) minutes. No falls, injuries, or adverse events occurred. Excellent convergent validity was shown for telemeasured hand grip strength (right ICC=0.96, left ICC=0.98, P<.001) and the TUG test (ICC=0.92, P=.01). The FTST demonstrated good agreement (ICC=0.95, 95% CI 0.79-0.98; P=.01). The HM6MWT demonstrated poor absolute agreement with the 6MWT. However, further exploratory analysis revealed a strong positive correlation between the tests (r=0.83, P<.001). The interrater reliability was excellent for all tests (all ICCs>0.9, P<.05). Conclusions: This study suggests that videoconference assessments are convenient and useful measures of fitness and function among youth with and without disabilities. This paper presents operationalized teleassessment procedures that can be replicated by health professionals to produce valid and reliable measurements. This study is a first step toward developing teleassessments that can bypass the need for on-site data collection visitations for this age group. Further research is needed to identify psychometrically sound teleassessment procedures, particularly for measures of cardiorespiratory endurance or walking ability.

Background: Fundamental motor skills (FMS) are considered essential for sport participation and might be deficit in obese children. While evidence indicates that physical activity (PA) levels impact motor skill development, the relationship between body composition, PA, and motor competence, particularly in early childhood, is not thoroughly understood. We aimed to determine if PA, fat mass (FM), and fat-free mass (FFM) are predictors of FMS. Methods: Preschoolers (n = 47) from two preschools were assessed for FMS, PA, and body composition. Peabody Developmental Motor Scales (PDMS-2) subscale scores were used to assess FMS. PA was assessed with a wrist-worn accelerometer for five days during school. FM and FFM were measured with foot-to-foot bioelectrical impedance. Results: Linear regressions indicate significant models for stationary skills (SS) (F = 4.57, p = .004) and object manipulation skills (OMS) (F = 4.66, p = .003). FFM was the only significant predictor of SS (t = 3.98, p < .001) and OMS (t = 3.50, p = .001). FM and all intensities of PA were nonsignificant predictors in all models. Conclusions: These results indicate that interventions that target improving or maintaining FFM may improve FMS.

Background : Population-level physical activity surveillance is critical for informing research, practice, and policy efforts for supporting healthy development. The 2024 US Report Card on Physical Activity for Children and Youth synthesizes the most recent national data on physical activity levels and supports among US children and youth. Methods : A committee of experts evaluated 12 indicators related to physical activity in children and youth using the best available national data for each indicator. Based on established criteria from the Active Healthy Kids Global Alliance, letter grades (A–F) were assigned to the indicators to reflect how well the United States is succeeding at providing children and youth with opportunities for physical activity. Key metrics within select indicators were evaluated for differences among racial/ethnic and disability subgroups and trends over time since the first report card (2014) or earliest available data. Results : Sufficient data were available to assign grades for 8 indicators. The grades ranged from B− to D−, with Overall Physical Activity earning a D−. Racial/ethnic disparities were observed for the Overall Physical Activity, Organized Sport, Sedentary Behavior, Sleep, and Community and Built Environment indicators. Key metrics for Overall Physical Activity and Active Transportation metrics decreased slightly over the past decade, whereas larger decreases were observed for Organized Sport and Sedentary Behavior metrics. Conclusions : Findings highlight opportunities to improve physical activity levels and supports among US children and youth. The 2024 Report Card can be a tool for informing research and practice at the local and national levels.

Objective: Examine the effect of an 8-week teacher-guided active play intervention on preschoolers’ body composition and fundamental motor skills. Methods: Participants were from two local preschool centers randomly assigned to either the intervention (n = 25, 3.91 ± 0.53 years) or the control group (n = 25, 3.69 ± 0.81 years). All measures were assessed at baseline (week 0), post-intervention (weeks 9–11), and follow-up (weeks 30–33). Bioelectrical Impedance assessed body composition (fat mass (FM) and fat-free mass (FFM)). The Peabody Developmental Motor Scales, Second Edition (PDMS-2) assessed fundamental motor skills (gross motor quartile (GMQ)). Results: A significant Group × Time interaction for GMQ at post-intervention (p = 0.03), with the intervention group scoring significantly higher on GMQ. A significant main effect of Time (p < 0.001) indicated that GMQ increased in both groups across the 33-week period. For FM, a significant main effect of Time at both post-intervention (p < 0.05) and follow-up testing (p < 0.001) indicated that participants increased FM over the 33-week period. Lastly, there was a significant main effect of Time for FFM at post-intervention (p = 0.003) and follow-up (p < 0.001). Interestingly, there was a significant Group × Time interaction (p < 0.05) at follow-up testing showing that FFM increased over time but significantly more for the control group. Conclusions: Results indicate that active play interventions might be a successful pathway to improve gross motor skills in young children. Further research is needed to understand the effect that active play interventions have on body composition in preschoolers.