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Wearable cameras have been demonstrated as a feasible method for capturing children’s health behaviours; however, there is limited research on the validity and reliability of wearable cameras in youth populations. The purpose of this systematic review will be to provide an overview of the current evidence on the use of wearable cameras to measure health-related behaviours in youth.

This study aims to answer 3 questions. Q1. What are the different time-use profiles regarding the overall quantity of physical activity, sedentary behaviour, and sleep among children? Q2. What time-use profiles can be identified, regarding different domains of physical activity, sedentary behaviour, and sleep that children do? Q3. Does the socioeconomic status of a child’s family predict profile membership in time-use profiles regarding overall physical activity, sedentary behaviour, or sleep and domain-specific time-use profiles?

Background: Children���s health is at risk because of declines in cardiorespiratory fitness. Meta-analyses of efficacy studies show that school-based physical activity interventions can improve children���s cardiorespiratory fitness. These interventions, however, are rarely disseminated at scale, meaning they typically have little public health impact. iPLAY is a primary school intervention designed to build schools��� capacity to promote physical activity without relying on external providers delivering programs to students. To enhance scalability and sustainability, iPLAY is delivered to teachers via an online learning platform, with mentoring support from experienced physical education teachers. Purpose: To determine whether iPLAY, when deployed across a large number of schools, could improve children���s cardiorespiratory fitness. Methods: We did a cluster randomized controlled trial (RCT) with allocation at the school level (1:1 allocation). We completed assessments at baseline, post-intervention (12 months after baseline), and maintenance (24 months after baseline). The primary outcome was students��� cardiorespiratory fitness, as measured by a 20m shuttle run test. We tested for between-arm differences in changes in student outcomes using linear mixed models. Results: We recruited 132 primary schools in New South Wales, Australia. We assigned a representative sample of 22 schools to the cluster RCT. The remaining 110 schools entered an implementation study in which teachers received iPLAY but students did not complete primary outcome assessments. In the 22 schools involved in the cluster RCT, we recruited 1,217 students from Grades 3 and 4 who completed baseline assessments of their cardiorespiratory fitness. At 12-months (post-intervention), there was a significant between-arm difference in students��� change in fitness favouring the iPLAY intervention condition (1.2 laps [95%CI=0.1,2.0]). This effect continued to grow, as at 24 months the between arm difference was 2.2 laps [95%CI=0.9, 3.6). Conclusions: iPLAY is a scalable model to deliver a school-based physical activity intervention that improves children���s cardiorespiratory fitness. iPLAY also builds capacity in schools such that benefits are sustained or continue to grow after the intervention ends. Funding: Study funded by the National Health and Medical Research Council (GNT1114281) and the New South Wales Department of Education. Trial registration: ACTRN12616000731493., The Health & Fitness Journal of Canada, Vol. 14 No. 3 (2021): Proceedings from the 8th International Society for Physical Activity and Health Congress

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. Purpose: 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 those images contained multiple screens. Most screen exposure involved television sets (36.3% of screen-based 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. Funding: This research was supported by the Research Training Program ��� International Stipend and Tuition Fees Scholarship., The Health & Fitness Journal of Canada, Vol. 14 No. 3 (2021): Proceedings from the 8th International Society for Physical Activity and Health Congress

Supplemental material, sj-docx-1-psp-10.1177_01461672221125619 for The Equality Paradox: Gender Equality Intensifies Male Advantages in Adolescent Subjective Well-Being by Jiesi Guo, Geetanjali Basarkod, Francisco Perales, Philip D. Parker, Herbert W. Marsh, James Donald, Theresa Dicke, Baljinder K. Sahdra, Joseph Ciarrochi, Xiang Hu, Chris Lonsdale, Taren Sanders and Borja del Pozo Cruz in Personality and Social Psychology Bulletin

Objectives To determine if subpopulations of students benefit equally from school-based physical activity interventions in terms of cardiorespiratory fitness and physical activity. To examine if physical activity intensity mediates improvements in cardiorespiratory fitness. Design Pooled analysis of individual participant data from controlled trials that assessed the impact of school-based physical activity interventions on cardiorespiratory fitness and device-measured physical activity. Participants Data for 6621 children and adolescents aged 4–18 years from 20 trials were included. Main outcome measures Peak oxygen consumption (VO2Peak mL/kg/min) and minutes of moderate and vigorous physical activity. Results Interventions modestly improved students’ cardiorespiratory fitness by 0.47 mL/kg/min (95% CI 0.33 to 0.61), but the effects were not distributed equally across subpopulations. Girls and older students benefited less than boys and younger students, respectively. Students with lower levels of initial fitness, and those with higher levels of baseline physical activity benefitted more than those who were initially fitter and less active, respectively. Interventions had a modest positive effect on physical activity with approximately one additional minute per day of both moderate and vigorous physical activity. Changes in vigorous, but not moderate intensity, physical activity explained a small amount (~5%) of the intervention effect on cardiorespiratory fitness. Conclusions Future interventions should include targeted strategies to address the needs of girls and older students. Interventions may also be improved by promoting more vigorous intensity physical activity. Interventions could mitigate declining youth cardiorespiratory fitness, increase physical activity and promote cardiovascular health if they can be delivered equitably and their effects sustained at the population level.

Additional file 1: Supplementary Figure S1. Distributions of sleep and physical activity variables.

Universities around the world are incorporating online learning, often relying upon videos (asynchronous multimedia). We systematically reviewed the effects of video on learning in higher education. We searched five databases using 27 keywords to find randomised trials that measured the learning effects of video among college students. We conducted full-text screening, data-extraction, and risk of bias in duplicate. We calculated pooled effect-sizes using multi-level random-effects meta-analysis. Searches retrieved 9,677 unique records. After screening 329 full-texts, 103 met inclusion criteria, with a pooled sample of 7,776 students. Swapping video for existing teaching methods led to small improvements in student learning (g = 0.28). Adding video to existing teaching led to strong learning benefits (g = 0.80). Although results may be subject to some experimental and publication biases, they suggest that videos are unlikely to be detrimental and usually improve student learning.