Children living with disability have poorer health outcomes than their typically developing peers. They are less physically active and at increased risk of chronic disease. Teacher-led, whole-of-school physical activity interventions are promising levers for population-level change, but are seldom tested among children with disability. We aimed to evaluate the effect of a blended teacher-professional learning program (online and in-person) on fundamental movement skills (FMS) and physical activity among children with intellectual disability. In this cluster randomized clinical trial, we randomized 20 government-funded primary schools, including 238 consenting students (Grades 2–5; aged 8–11 years at baseline). Ten schools received the blended teacher-professional learning intervention and 10 were assigned as waitlist controls. The professional learning was designed to support teachers as they implemented a whole-of-school intervention designed to enhance FMS and increase physical activity levels. The school-based intervention was mostly online learning, followed by lesson observations and site visits from project staff. Blinded assessors measured FMS competency using the Test of Gross Motor Development-3. Secondary outcomes were self-concept, enjoyment, wellbeing, 300-yard run time, and accelerometer-measured physical activity. We found no significant group-by-time effects for the primary outcome (FMS competency: b = 1.07 [95

We conducted a systematic review to evaluate combinations of physical activity, sedentary behavior, and sleep duration (defined as "movement behaviors") and their associations with physical, psychological, and educational outcomes in children and adolescents. MEDLINE, CINAHL, PsychInfo, SPORTDiscus, PubMed, EMBASE, and ERIC were searched in June 2020. Included studies needed to 1) quantitatively analyze the association of 2 or more movement behaviors with an outcome, 2) analyze a population between 5 and 17 years of age, and 3) include at least an English abstract. We included 141 studies. Most studies included the combination of physical activity and sedentary behavior in their analyses. Sleep was studied less frequently. In combination, a high level of physical activity and a low level of sedentary behavior were associated with the best physical health, psychological health, and education-related outcomes. Sleep was often included in the combination that was associated with the most favorable outcomes. Sedentary behavior had a stronger influence in adolescents than in children and tended to be associated more negatively with outcomes when it was defined as screen time than when defined as overall time spent being sedentary. More initiatives and guidelines combining all 3 movement behaviors will provide benefit with regard to adiposity, cardiometabolic risk factors, cardiorespiratory fitness, muscular physical fitness, well-being, health-related quality of life, mental health, academic performance, and cognitive/executive function.

Background: Automated wearable cameras present a new opportunity to accurately assess human behavior. However, this technology is seldom used in the study of adolescent's screen exposure, and the field is reliant on poor-quality self-report data. Objective: This study aimed to examine adolescents' screen exposure by categorizing the type and context of behaviors using automated wearable cameras. Methods: Adolescents (mean age 15.4 years, SD 1.6 years; n=10) wore a camera for 3 school evenings and 1 weekend day. The camera captured an image every 10 seconds. Fieldwork was completed between February and March 2020, and data were analyzed in August 2020. Images were date and time stamped, and coded for screen type, content, and context. Results: Data representing 71,396 images were analyzed. Overall, 74.0% (52,842/71,396) of images contained screens and 16.8% (11,976/71,396) of images contained multiple screens. Most screen exposures involved television sets (25,950/71,396, 36.3%), smartphones (20,851/71,396, 29.2%), and laptop computers (15,309/71,396, 21.4%). The context of screen use differed by device type, although most screen exposures occurred at home (62,455/64,856, 96.3%) and with solitary engagement (54,430/64,856, 83.9%). The immediate after-school period saw high laptop computer use (4785/15,950, 30.0%), while smartphone use (2059/5320, 38.7%) peaked during prebedtime hours. Weekend screen exposure was high, with smartphone use (1070/1927, 55.5%) peaking in the early morning period and fluctuating throughout the day. Conclusions: There was evidence for high screen use during the after-school and weekend period, mostly through solitary engagement, and within the home environment. The findings may inform the basis of larger studies aimed at examining screen exposure in free-living conditions.

INTRODUCTION:Physical activity can improve academic performance; however, much less is known about the specific association between sport participation and academic performance, and this evidence has not been synthesized. Our aim was to systematically review and combine via meta-analyses evidence of the association between sport participation and academic performance in children and adolescents. METHODS:We conducted searches of five electronic databases using sport and academic performance related terms. We combined evidence from eligible studies using a structural equation modeling approach to multilevel meta-analysis. RESULTS:From 115 eligible studies, most of which had a high risk of bias (k = 87), we meta-analyzed 298 effect sizes. Overall, sport participation had a small positive effect on academic performance (d = 0.26, 95% confidence interval = 0.09, 0.42). Moderator analyses indicated that sports participation was most beneficial for academic performance when it was at a moderate dose (i.e., 1-2 h·wk-1), compared with no sport or a high dose of sport (3+ h·wk-1). CONCLUSIONS:Sports participation during school hours was more beneficial for academic performance compared with sport participation outside school hours. Based on mostly low-quality studies, we found some evidence that sport could positively affect academic performance in children and adolescents. It appears that sport participation of a moderate dose and at school could be used to promote academic performance. However, if this field were to inform policy, high-quality studies are needed that provide insight into the effect of dose and sport characteristics on academic performance.

BACKGROUND Automated wearable cameras present a new opportunity to accurately assess human behaviour. However, this technology is seldom used in the study of adolescent’s screen exposure and the field is reliant on poor quality, self-report data. OBJECTIVE To examine adolescents’ screen exposure by categorising the type and context of behaviours using automated wearable cameras. METHODS Adolescents (15.4 ± 1.6 years; n=10) wore a camera for three school evenings and one weekend day. The camera captured an image every 10 seconds. Fieldwork was completed between February and March 2020, and data analysed in August 2020. Images were date and time-stamped and coded for screen type, content, and context. RESULTS Data representing 71,396 images were analysed. Overall, 74% of images contained screens and 16.8% of total images contained multiple screens. Most screen exposure involved television sets (36.3% of images), smartphones (29.2%), and laptop computers (21.4%). The context of screen use differed by device type, although most screen exposure occurred at home (96.3%) and with solitary engagement (83.9%). The immediate after-school period saw high laptop computer use (30%), while smartphone use (38.7%) peaked in the middle evening and pre-bedtime hours, respectively. Weekend screen exposure was high, with smartphone use (55.5%) peaking in the early morning period and fluctuating throughout the day. CONCLUSIONS There was evidence for high screen use during the after-school and weekend period, mostly through solitary engagement, and within the home environment. Findings may inform the basis of larger studies aimed at examining screen exposure in free-living conditions.