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Background: Excessive screen time (≥ 2 h per day) is associated with childhood overweight and obesity, physical inactivity, increased sedentary time, unfavorable dietary behaviors, and disrupted sleep. Previous reviews suggest intervening on screen time is associated with reductions in screen time and improvements in other obesogenic behaviors. However, it is unclear what study characteristics and behavior change techniques are potential mechanisms underlying the effectiveness of behavioral interventions. The purpose of this meta-analysis was to identify the behavior change techniques and study characteristics associated with effectiveness in behavioral interventions to reduce children's (0–18 years) screen time. Methods: A literature search of four databases (Ebscohost, Web of Science, EMBASE, and PubMed) was executed between January and February 2020 and updated during July 2021. Behavioral interventions targeting reductions in children's (0–18 years) screen time were included. Information on study characteristics (e.g., sample size, duration) and behavior change techniques (e.g., information, goal-setting) were extracted. Data on randomization, allocation concealment, and blinding was extracted and used to assess risk of bias. Meta-regressions were used to explore whether intervention effectiveness was associated with the presence of behavior change techniques and study characteristics. Results: The search identified 15,529 articles, of which 10,714 were screened for relevancy and 680 were retained for full-text screening. Of these, 204 studies provided quantitative data in the meta-analysis. The overall summary of random effects showed a small, beneficial impact of screen time interventions compared to controls (SDM = 0.116, 95CI 0.08 to 0.15). Inclusion of the Goals, Feedback, and Planning behavioral techniques were associated with a positive impact on intervention effectiveness (SDM = 0.145, 95CI 0.11 to 0.18). Interventions with smaller sample sizes (n < 95) delivered over short durations (< 52 weeks) were associated with larger effects compared to studies with larger sample sizes delivered over longer durations. In the presence of the Goals, Feedback, and Planning behavioral techniques, intervention effectiveness diminished as sample size increased. Conclusions: Both intervention content and context are important to consider when designing interventions to reduce children's screen time. As interventions are scaled, determining the active ingredients to optimize interventions along the translational continuum will be crucial to maximize reductions in children's screen time. [ABSTRACT FROM AUTHOR]

Summary: Background: Population‐specific accelerometer cut‐points are required to accurately determine the accumulation of physical activity of various intensities. Objectives: A calibration study was conducted (i) to determine the cut‐points for the ActiGraph GT3X+, non‐dominant, wrist‐mounted accelerometer in children aged 8–12 years and (ii) to compare classification accuracies among the accelerometer's three axes and vector magnitude (VM) values. Methods: Forty‐five children aged 8–12 years performed up to seven activities while wearing accelerometers on their non‐dominant wrist. Activities were performed in a summer day camp setting, represented free‐living activities, and lasted for 10 min with minutes 5–8.5 used for analysis. Direct observation and percentage of heart rate reserve were used to determine activity intensity. Results: Receiver operator characteristic (ROC) analyses resulted in area under the curve values of all three axes and VM ranging 0.82–0.89, 0.80–0.83, 0.62–0.67 and 0.86–0.89 for light, moderate, vigorous and moderate‐to‐vigorous activity intensities. Additionally, regression analyses resulted in prediction equations with R2 values ranging from 0.70 to 0.77. Conclusion: Results found comparable activity intensity classification accuracies from the ActiGraph GT3X+ wrist‐worn accelerometer to previously published studies. Based on ROC and regression analyses, activity intensities can be distilled from this accelerometer using axis 1, axis 2 or VM values with similar classification accuracy. [ABSTRACT FROM AUTHOR]

Objective:To determine if time spent in objectively measured sedentary behavior is associated with a change in body mass index (BMI) between ages 9 and 15 years, adjusting for moderate-to-vigorous physical activity (MVPA).Design:Prospective observational study of children at ages 9 (2000), 11 (2002), 12 (2003) and 15 years (2006). Longitudinal quantile regression was used to model the influence of predictors on changes at the 10th, 25th, 50th, 75th and 90th BMI percentiles over time.Subjects:Participants were enrolled in the National Institute of Child Health and Human Development (NICHD) Study of Early Child Care and Youth Development and include both boys and girls (n=789).Measurements:Objectively measured BMI (kg m-2) was the outcome variable and objectively measured sedentary behavior was the main predictor. Adjustment was also made for MVPA, gender, race, maternal education, hours of sleep and healthy eating index.Results:Increases in BMI were observed at all percentiles, with the greatest increase observed at the 90th BMI percentile. Spending more time in sedentary behavior (h per day) was associated with additional increases in BMI at the 90th, 75th and 50th BMI percentiles, independent of MVPA and the other covariates (90th percentile=0.59, 95% confidence interval (95% CI): 0.19-0.98 kg m-2; 75th percentile=0.48, 95% CI: 0.25-0.72 kg m-2; and 50th percentile=0.19, 95% CI: 0.05-0.33 kg m-2). No associations were observed between sedentary behavior and changes at the 25th and 10th BMI percentiles.Conclusion:Sedentary behavior was associated with greater increases in BMI at the 90th, 75th and 50th BMI percentiles between ages 9 and 15 years, independent of MVPA. Preventing an increase in sedentary behavior from childhood to adolescence may contribute to reducing the number of children classified as obese. [ABSTRACT FROM AUTHOR]

The article focuses on the promotion of school-based physical activity (PA) for youth in the U.S. It describes the schools' leadership role in improving the health and PA levels of youth and the several legislations that require the schools to receive federal grants. It discusses the role of physical educators in the promotion of school-based PA and describes the quality physical education (QPE). It also discusses the school day's segments that show the potential for improving school-based PA.