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Social adjustment is critical to educational and occupational attainment. Yet little research has considered how the school's socioeconomic context is associated with social adjustment. In a longitudinal sample of Australian 4- to 8-year-olds (

Multimedia is ubiquitous in 21st-century education. Cognitive load theory and the cognitive theory of multimedia learning both postulate that the quality of multimedia design heavily influences learning. We sought to identify how to best design multimedia and review how well those learning theories held up to meta-analyses. We conducted an overview of systematic reviews that tested the effects of multimedia design on learning or cognitive load. We found 29 reviews including 1,189 studies and 78,177 participants. We found 11 design principles that demonstrated significant, positive, meta-analytic effects on learning and five that significantly improved management of cognitive load. The largest benefits were for captioning second-language videos, temporal/spatial contiguity, and signaling. We also found robust evidence for modality, animation, coherence/removing seductive details, anthropomorphics, segmentation, personalization, pedagogical agents, and verbal redundancy effects. Good design was more important for more complex materials, and in system-paced environments (e.g., lectures) than self-paced ones (e.g., websites). Results supported many tenets of both theories. We highlight a range of evidence-based strategies that could be implemented by educators.

Children’s engagement in screen time is a complex issue. While some forms of screen time have consistently been associated with harm, others have been associated with gains, making it difficult to weigh the risks and benefits of use. In this umbrella review, we systematically collate and synthesise meta-analyses examining the effects of screen use on children and youth. We converted results onto a common metric to make comparisons simple, and where possible we reanalysed study-level data to standardise the approach across meta-analyses. We identified 116 meta-analyses, and extracted 165 unique exposure/outcome combinations. These effects represent the findings of 2,171 primary studies comprised of 1,652,944 participants. When focusing on the meta-analyses with the most statistically robust evidence, we found that general screen use (when content was not indicated), was associated with potentially harmful impacts on learning, literacy, body composition, and depression. Like-wise, social media was consistently associated with risks to health, with no identified benefits. However, we also found that these harms could often be mitigated by certain kinds of content (e.g., educational), or by modifying the context (e.g., co-viewing with a parent). In summary, our findings point to the need for careful and nuanced guidelines that support parents to make the best decisions for their children.

Individuals’ subjective well-being (SWB) is an important marker of development and social progress. As psychological health issues often begin during adolescence, understanding the factors that enhance SWB among adolescents is critical to devising preventive interventions. However, little is known about how institutional contexts contribute to adolescent SWB. Using Programme for International Student Assessment (PISA) 2015 and 2018 data from 78 countries ( N = 941,475), we find that gender gaps in adolescents’ SWB (life satisfaction, positive and negative affect) are larger in more gender-equal countries. Results paradoxically indicated that gender equality enhances boys’ but not girls’ SWB, suggesting that greater gender equality may facilitate social comparisons across genders. This may lead to an increased awareness of discrimination against females and consequently lower girls’ SWB, diluting the overall benefits of gender equality. These findings underscore the need for researchers and policy-makers to better understand macro-level factors, beyond objective gender equality, that support girls’ SWB.

Background Reliable estimates of habitual sleep, physical activity, and sedentary time are essential to investigate the associations between these behaviours and health outcomes. While the number of days needed and hours/day for estimates of physical activity and sedentary time are generally known, the criteria for sleep estimates are more uncertain. The objective of this study was to identify the number of nights needed to obtain reliable estimates of habitual sleep behaviour using the GENEActiv wrist worn accelerometer. The number of days to obtain reliable estimate of physical activity was also examined. Methods Data was used from a two-year longitudinal study. Children wore an accelerometer for up to 8 days 24 h/day across three timepoints. The sample included 2,745 children (51 % girls) between the ages of 7-12-years-old (mean = 9.8 years, SD = 1.1 year) with valid accelerometer data from any timepoint. Reliability estimates were calculated for sleep duration, sleep efficiency, sleep onset, wake time, time in bed, light physical activity, moderate physical activity, moderate-to-vigorous physical activity, vigorous physical activity, and sedentary time. Results Intraclass correlations and the Spearman Brown prophecy formula were used to determine the nights and days needed for reliable estimates. We found that between 3 and 5 nights were needed to achieve acceptable reliability (ICC = 0.7) in sleep outcomes, while physical activity and sedentary time outcomes required between 3 and 4 days. Conclusions To obtain reliable estimates, researchers should consider these minimum criteria when designing their studies and prepare strategies to ensure sufficient wear time compliance.

This study aims to explore associations between physical activity intensity and well-being (i.e., positive and negative affect) in adolescents. A secondary aim was to determine if associations were moderated by sex. Grade 8 students from 14 government-funded secondary schools in low socio-economic areas of Western Sydney (Australia) were assessed. Data from three timepoints (baseline, 7–8 months, and 14–15 months) were combined to increase the sample size. Physical activity was objectively assessed for 1-week at each timepoint using Actigraph accelerometers. Time (minutes/day) in light, moderate and vigorous physical activity was estimated. The short form Positive and Negative Affect Scale for Children was used to measure well-being. Quantile regression was used to analyse the data. A total of 3140 observations were collected from 1223 students (mean age at baseline: 12.9(0.54); 55.1% male). Light and moderate physical activity was not associated with well-being. Higher levels of vigorous physical activity were associated with more positive affect [β(SE) = 0.307 (0.06), p < 0.001], to an estimated vigorous physical activity turning point [Point(95%CI) = 36.48 min/day (31.39–41.59)]. Similarly, higher levels of vigorous physical activity were associated with less negative affect [β(SE) = −0.250 (0.06), p < 0.001] up to the estimated vigorous physical activity turning point [Point(95%CI) = 37.35 min/day (31.27–43.44)]. The negative association between vigorous physical activity and negative affect was more pronounced in females than in males. Our findings highlight the importance of adolescents engaging in vigorous physical activity to improve positive affect and reduce negative affect.

Background Understanding the early roots of physical activity and sedentary behaviors is critical to developing intervention programs that promote healthy lifestyle habits in infants and children. There is, however, no evidence on how these behaviors cluster and develop together during early childhood. The aim of this study was to identify single and joint longitudinal trajectories in physical activity and screen time amongst children aged 0 to 9 years, their social-demographic predictors and their prospective health-related quality-of-life and socio-emotional outcomes. Methods Three waves of data from The Longitudinal Study of Australian Children, a national study tracking two cohorts every 2 years (B-cohort, 0–5 years, n = 4,164; K-cohort, 4–9 years, n = 3,974) were analysed. Growth mixture modelling was applied to longitudinal time-use diary data to identify joint trajectories in children’s physical activity and screen time over Waves 1–3. Key socio-demographic variables measured at Wave 1 were used to predict membership in different trajectories. The prospective consequences (at Wave 3) of time-use trajectories on health-related quality-of-life and socio-emotional outcomes were assessed. Results Three physical-activity/screen-time trajectories were identified for both cohorts: Cluster-A—children who maintained low levels of physical activity and screen time (∽50% of the sample), Cluster-B—children who progressively increased physical activity and maintained low screen-time levels (∽25%), and Cluster-C—children who maintained low physical-activity levels and increased screen time (∽25%). Children in Cluster-B experienced the best health-related quality-of-life and socio-emotional outcomes, while those in Cluster-C experienced the worst. Children who were female, Indigenous, from non-English-speaking backgrounds, not living with two biological parents, in more affluent households and neighbourhoods, without siblings and with parents with poor mental health were at greater risk of falling into Cluster-A or Cluster-C. Conclusion Our findings identified which children are most at-risk of falling into time-use trajectories that lead to poor health-related quality-of-life and socio-emotional outcomes later in life, increasing our ability to monitor, detect and prevent these suboptimal behaviours prior to their onset. Electronic supplementary material The online version of this article (10.1186/s12966-019-0816-3) contains supplementary material, which is available to authorized users.

Importance Cardiorespiratory fitness is an important marker of childhood health and low fitness levels are a risk factor for disease later in life. Levels of children's fitness have declined in recent decades. Whether school-based physical activity interventions can increase fitness at the population level remains unclear. Objective To evaluate the effect of an internet-based intervention on children’s cardiorespiratory fitness across a large number of schools. Design, Setting, and Participants In this cluster randomized clinical trial, 22 government-funded elementary schools (from 137 providing consent) including 1188 students stratified from grades 3 and 4 in New South Wales, Australia, were randomized. The other schools received the intervention but were not included in the analysis. Eleven schools received the internet-based intervention and 11 received the control intervention. Recruitment and baseline testing began in 2016 and ended in 2017. Research assistants, blinded to treatment allocation, completed follow-up outcome assessments at 12 and 24 months. Data were analyzed from July to August 2020. Interventions The internet-based intervention included standardized online learning for teachers and minimal in-person support from a project mentor (9-10 months). Main Outcomes and Measures Multistage 20-m shuttle run test for cardiorespiratory fitness. Results Of 1219 participants (49% girls; mean [SD] age, 8.85 [0.71] years) from 22 schools, 1188 students provided baseline primary outcome data. At 12 months, the number of 20-m shuttle runs increased by 3.32 laps (95% CI, 2.44-4.20 laps) in the intervention schools and 2.11 laps (95% CI, 1.38-2.85 laps) in the control schools (adjusted difference = 1.20 laps; 95% CI, 0.17-2.24 laps). By 24 months, the adjusted difference was 2.22 laps (95% CI, 0.89-3.55 laps). The cost per student was AUD33 (USD26). Conclusions and Relevance In this study, a school-based intervention improved children's cardiorespiratory fitness when delivered in a large number of schools. The low cost and sustained effect over 24 months of the intervention suggests that it may have potential to be scaled at the population level. Trial Registration http://anzctr.org.au Identifier: ACTRN12616000731493

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.

Based on the Information Distortion Model (IDM), we hypothesized higher academic interest among low socioeconomic (SES) Australian children compared to equally able high SES Australian children. We extend the IDM in two ways. First, the IDM is a model of school selection and thus empirical evidence of its effect needs to come from a model that controls for achievement prior to school selection. Second, the mechanism of the IDM is presumed to be the big-fish-little-pond-effect (BFLPE), which has not been tested. We used a longitudinal representative sample of first-year high-school students (age ~12, N = 2507). We linked student high-school survey data to the whole of school and individual student administrative records of achievement from high-stakes national standardized tests in elementary and high-school. Our results were consistent with IDM for math interest but more mixed for reading interest, suggesting that additional processes may be in operation.

Objectives To determine the impact of bushfires on children’s physical activity. Design Natural experiment comparing device-measured physical activity and air quality index data for schools exposed and not exposed to the Australian bushfires. Methods Participants were drawn from 22 schools participating in a cluster randomised controlled trial of a school-based physical activity intervention that coincided with the 2019 Australian bushfires. Students in Years 3 and 4 (8–10 years old) provided data. We used propensity score matching to match 245 exposed and 344 control participants. Main outcome measures Minutes of moderate and vigorous physical activity. Results The bushfires had minimal effect on children’s average weekly physical activity. Analysis of acute effects showed children maintained their levels of physical activity up to an estimated turning point of air quality index of 737.08 (95% CI = 638.63, 835.53), beyond which daily physical activity levels dropped sharply. Similar results were found for girls and boys and for children from low-to-average and higher socio-economic backgrounds. Conclusions Children’s physical activity was not strongly influenced by the presence of smoke and targeted public health advice during the bushfires might not have had the intended effect of reducing children’s outdoor physical activity. Only when air quality deteriorated to approximately 3.5 times the Air Quality index threshold (>200) deemed ‘hazardous’ by the Australian Department of Health did children’s physical activity decline. Public health agencies should re-evaluate the effectiveness of health messages during bushfires and develop strategies to mitigate risks to children’s health.

Universities around the world are incorporating online learning, often relying on videos (asynchronous multimedia). We systematically reviewed the effects of video on learning in higher education. We searched five databases using 27 keywords to find randomized 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 multilevel random-effects meta-analysis. Searches retrieved 9,677 unique records. After screening 329 full texts, 105 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.

The authors thank the study participants and collaborators on the individual studies that provided data for this pooled IPD analysis., 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% confidence interval 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.

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.

Study Objectives To determine the day-to-day and longer-term longitudinal associations between daytime physical activity and night-time sleep. Methods We used data from a 2-year longitudinal study which included three time points (i.e. baseline, year 1, and year 2). Participants were recruited from primary schools and included 1059 children (50% girls) with a mean age of 8.81-years-old (SD = 0.72) at baseline. Sleep variables included sleep duration, sleep efficiency, time in bed, sleep onset, and wake time. Physical activity variables included light, moderate, moderate-to-vigorous, and vigorous physical activity as well as sedentary time. We objectively assessed physical activity and sleep behaviors using the GENEActiv wrist-worn accelerometer over an 8-day period at each timepoint for a potential 21 190 observed days. Results We used fixed-effects multilevel models and parallel latent growth curve modeling to examine day-to-day and longer-term associations, respectively. Day-to-day, physical activity, and sleep variables were significantly, positively, and bidirectionally associated, except for sleep efficiency, which showed little association with physical activity. Longer-term, we found little association between physical activity and sleep variables. Conclusions Overall, our findings indicate that there is a day-to-day association between the amount of time spent being physically active and improved sleep. The lack of a longer-term association indicates that a focus on children’s daily behavior may be most appropriate to help children improve sleep and increase physical activity.

Purpose In this study, we tested the effectiveness of a multicomponent sports-based program aimed at promoting early intervention, help seeking, and resilience among a sample of adolescent male sport participants. Methods The Ahead of the Game program comprised four intervention components and a messaging campaign. Two components targeted mental health literacy, intentions to seek and provide help, and resilience among adolescent boys. A mental health literacy program for parents and a coach education program to assist in the support of athletes’ psychological needs were also included. We evaluated the program using a nonrandomized controlled trial matching two regional communities. In total, 350 sport participants (mean, 14.53 yr) were included in an intervention group, whereas 466 (mean, 14.66 yr) received usual practice in a matched control community. One hundred and eighty parents or caregivers and eight coaches also participated in the intervention components. Between-group mean differences on the primary and secondary outcomes were analyzed using linear mixed models, adjusted for clustering at club level, participant age, and socioeconomic status. Results Significant positive group–time interactions were found for the primary outcomes of depression and anxiety literacy, intentions to seek help from formal sources, confidence to seek mental health information, and resilience. We also found a significant positive group–time interaction for the secondary outcome of well-being. There were no group–time interactions for social distance (stigma), intentions to seek help from informal sources, implicit beliefs about adversity, perceived familial support, or psychological distress. Conclusions Given the high rates of sport participation worldwide and the increasing focus on mental health in this domain, translation and dissemination of the program may be warranted after replication.

Objective:Schools have been recognised as a potential setting for improving young peoples’ food and beverage choices; however, many schools fail to adhere to healthy food and beverage policy standards. The current study aimed to explore the enablers and barriers to effective implementation of and compliance with school-based food and beverage policies.Design:Systematic review and meta-synthesis. Eight electronic databases were searched for articles in June 2019. Studies were eligible for inclusion if they reported on implementation and/or compliance of school-based food and/or beverage policies with outcomes relating to enablers and/or barriers. This review had no restrictions on study design, year of publication or language. Seventy-two full-text articles were assessed for eligibility, of which twenty-eight were included in this review.Setting:Studies conducted globally that focused on schools.Participants:School-based healthy food and beverage policies.Results:Financial (cost of policy-compliant foods, decreased profit and revenue), physical (availability of policy-compliant foods, close geographical proximity to unhealthy food outlets) and social (poor knowledge, understanding, and negative stakeholders’ attitudes towards policy) factors were the most frequently reported barriers for policy implementation. Sufficient funding, effective policy communication and management, and positive stakeholders’ attitudes were the most frequently reported enablers for policy implementation.Conclusions:There is a need for better communication strategies, financial and social support prior to school-based food policy implementation. Findings of this review contribute to a thorough understanding of factors that underpin best practice recommendations for the implementation of school-based food policy, and inform those responsible for improving public health nutrition.

Background In this study we aimed to provide a global perspective of the association between different lifestyle behaviors and bullying in school adolescents and to ascertain whether or not the Human Development Index moderated those associations. Methods Data from the Global school-based Student Health Survey were analyzed in 273 121 from 82 countries. Logistic regression was applied to determine country-specific bullying victimization probability from meeting the recommended guidelines for physical activity, excessive sitting time, physical education attendance and active transport. Meta-analysis was then undertaken to ascertain pooled global effect estimates of the relationship between these behaviors and bullying victimization. Linear regression was used to study the relationship between odds of bullying from meeting the lifestyle guidelines and the Human Development Index. Results Our estimates indicate that excessive sitting time [1.38 (1.34,1.41)], attendance to physical education [0.87 (0.85,0.89)], and active transport [0.94 (0.91,0.97)] but not overall physical activity [1.01 (0.99,1.04)] were associated with bullying in the study sample. Limitations The present study is limited by its cross-sectional nature. Also, only two countries were surveyed from the European region Conclusions Active commuting and attendance to physical education play a protective role for bullying, while physical activity does not.

Summary Physical activity is considered an effective method to improve sleep quality in adolescents and adults. However, there is mixed evidence among children. Our objectives were to investigate this association in children and to examine potential moderating variables. Eight databases were systematically searched, and we included all study designs with a sample of healthy children ages 3-13 years-old. We identified 47 studies for meta-analysis. Overall, we found little association between physical activity and sleep (r = 0.02, 95% confidence interval = −0.03 to 0.07). There was a high amount of heterogeneity in the overall model (I2 = 93%). However, none of the examined variables significantly moderated the overall effect, including age, gender, risk of bias, study quality, measurement methodology, study direction, and publication year. Exploratory analyses showed some weak, but statistically significant associations for vigorous physical activity with sleep (r = 0.09, 95% CI = 0.01 to 0.17, I2 = 66.3%), specifically sleep duration (r = 0.07, 95% CI = 0.00 to 0.14, I2 = 41.1%). High heterogeneity and the lack of experimental research suggest our findings should be interpreted with caution. The current evidence, however, shows little support for an association between physical activity and sleep in children.

Additional file 6: Figure S3. Interactions and Quadratics.

This chapter provides an overview of (a) the Australian education system (including a historical overview from 1970 to today); (b) an exploration of socioeconomic inequality in IQ, academic achievement in high-stakes tests, and critical non-cognitive factors from the start of school to near the end of middle school; (c) an exploration of socioeconomic inequality in achievement in adolescent birth cohorts from the 1960s to 2000; and (d) a reflection on how education policy has influenced inequality and what may need to be done to redress it in the future. We find that inequalities present at the beginning of school tend to get larger as children age and that historical inequalities have also tended to increase over time. While Australia has had a large number of private schools since the 1970s, we argue that recent cultural changes have resulted in schools being seen as a market and that this has driven up ability stratification between schools and may account for increased inequality over time.

Table S1. Allocation of pre-determined LSAC time-use categories to physical activity and screen time. (DOCX 24 kb)

School‐based physical education (PE) provides opportunities to accumulate moderate‐to‐vigorous physical activity (MVPA), but many students are insufficiently active during PE lessons. Providing teachers with feedback regarding their students’ physical activity may increase the effectiveness of PE for achieving MVPA goals, but existing physical activity monitoring technologies have limitations in class environments. Therefore, the purpose of this study was to develop and validate a system capable of providing feedback on PE lesson MVPA. Equations for translating step counts to %MVPA were derived from measures in 492 students who concurrently wore an ActiGraph GT3X+ (ActiGraph) and Yamax pedometer (Yamax) during a PE lesson. To enhance feedback availability during PE lessons, we then developed a bespoke monitoring system using wireless tri‐axial pedometers (HMM) and a smart device app. After developing and testing the monitoring system, we assessed its validity and reliability in 100 students during a PE lesson. There was a strong correlation of 0.896 between step counts and accelerometer‐determined %MVPA and quantile regression equations showed good validity for translating step counts to %MVPA with a mean absolute difference of 5.3 (95% CI, 4.4‐6.2). The physical activity monitoring system was effective at providing %MVPA during PE lessons with a mean difference of 1.6 ± 7.1 compared with accelerometer‐determined %MVPA (7% difference between the two measurement methods). Teachers and students can use a smart device app and wireless pedometers to conveniently obtain feedback during PE lessons. Future studies should determine whether such technologies help teachers to increase physical activity during PE lessons.

Table S4. Average marginal effects for multinomial regression models presented in Table 2. (DOCX 16 kb)

Background Excessive engagement with digital screens is harmful to children’s health. However, new evidence suggests that exposure at moderate levels may not be harmful and may even provide benefit. Therefore, our objective was to determine if there are curvilinear relationships between different types of screen time and a diverse set of outcomes, including health and education. Methods We address our objective using a repeated measures design. Children (N = 4013), initially aged 10–11 were assessed every 2 years between 2010 and 2014. Children’s screen time behavior was measured using time-use diaries, and categorized into five types: social, passive, interactive, educational, or other. We used measures of children’s physical health, health-related quality of life, socio-emotional outcomes, and school achievement. The analysis plan was pre-registered. Models were adjusted for gender, socio-economic status, ethnicity, number of siblings, and housing factors. Results There were linear associations between total screen time and all outcomes, such that more screen time was associated with worse outcomes. However, there was variability when examined by screen time type. Passive screen time (e.g., TV) was associated with worse outcomes, educational screen time (e.g., computer for homework) was associated with positive educational outcomes and had no negative relations with other outcomes. Interactive screen time (e.g., video games) had positive associations with educational outcomes but negative associations with other outcomes. In all instances, these significant associations were small or very small, with standardised effects Conclusions The small effects of screen time on children’s outcomes appear to be moderated by the type of screen time. Policy makers, educators, and parents should consider the type of screen time when considering the benefits and harms of use.

Patterns in and treatment of missing data. (DOCX 23 kb)

The internet has become the chosen medium for professional learning. Completing professional learning can improve work performance; however, many individuals who begin online courses do not complete them. It is not well understood which influences keep individuals engaged in online professional learning. We address these issues with a systematic review. Our review of 51 studies and 9,583 participants includes a narrative synthesis and a meta-analysis that examined influences on user engagement in online professional learning. We found that course design and employers’ provision of time to complete learning are key for engaging learners. Other important influences were learners’ reasons for learning (e.g., intrinsic value and perceived usefulness), access to learning support, and opportunities for interaction during the learning experience.

There is a recognised need for targeted community-wide mental health strategies and interventions aimed specifically at prevention and early intervention in promoting mental health. Young males are a high need group who hold particularly negative attitudes towards mental health services, and these views are detrimental for early intervention and help-seeking. Organised sports provide a promising context to deliver community-wide mental health strategies and interventions to adolescent males. The aim of the Ahead of the Game program is to test the effectiveness of a multi-component, community-sport based program targeting prevention, promotion and early intervention for mental health among adolescent males. The Ahead of the Game program will be implemented within a sample drawn from community sporting clubs and evaluated using a sample drawn from a matched control community. Four programs are proposed, including two targeting adolescents, one for parents, and one for sports coaches. One adolescent program aims to increase mental health literacy, intentions to seek and/or provide help for mental health, and to decrease stigmatising attitudes. The second adolescent program aims to increase resilience. The goal of the parent program is to increase parental mental health literacy and confidence to provide help. The coach program is intended to increase coaches’ supportive behaviours (e.g., autonomy supportive behaviours), and in turn facilitate high-quality motivation and wellbeing among adolescents. Programs will be complemented by a messaging campaign aimed at adolescents to enhance mental health literacy. The effects of the program on adolescent males’ psychological distress and wellbeing will also be explored. Organised sports represent a potentially engaging avenue to promote mental health and prevent the onset of mental health problems among adolescent males. The community-based design, with samples drawn from an intervention and a matched control community, enables evaluation of adolescent males’ incremental mental health literacy, help-seeking intentions, stigmatising attitudes, motivation, and resilience impacts from the multi-level, multi-component Ahead of the Game program. Notable risks to the study include self-selection bias, the non-randomised design, and the translational nature of the program. However, strengths include extensive community input, as well as the multi-level and multi-component design. Australian New Zealand Clinical Trials Registry ACTRN12617000709347 . Date registered 17 May 2017. Retrospectively registered.

Background Physically active occupations with high-energy expenditure may lead to lower motivation to exercise during leisure time, while the reverse can be hypothesized for sedentary occupations. The aim of this study was to investigate the impact of changing occupational activity level on exercise behavior. Methods Data on occupational physical activity and leisure time exercise were taken from a population-based cohort, with surveys completed in 2010 and 2014. Using data on those employed in both years, two trajectories were analyzed: (i) participants who changed from sedentary to active occupations and (ii) participants who changed from active to sedentary occupations. Exercise was reported in hours per week and changes from 2010 to 2014 were categorized as decreased, increased or stable. Associations were expressed as ORs and 95% CIs adjusting for age, gender and education. Results Data were available for 12 969 participants (57% women, aged 45 ± 9 years, 57% highly educated). Relative to participants whose occupational activity was stable, participants who changed to active occupations (n = 549) were more likely to decrease exercise (OR = 1.22, 95% CI = 1.02-1.47) and those who changed to sedentary occupations (n = 373) more likely to increase exercise levels (OR = 1.21, 95% CI = 0.97-1.52). Conclusion People changing from sedentary to active occupations compensate by exercising less, and those changing from physically active to sedentary occupations seem to compensate by exercising more in their leisure time. When developing and evaluating interventions to reduce occupational sedentary behavior or to promote exercise, mutual influences on physical activity of different contexts should be considered.

Physical activity and diet are major modifiable risk factors for chronic disease and have been shown to be associated with neighborhood built environment. Systematic review evidence from longitudinal studies on the impact of changing the built environment on physical activity and diet is currently lacking. A systematic review of natural experiments of neighborhood built environment was conducted. The aims of this systematic review were to summarize study characteristics, study quality, and impact of changes in neighborhood built environment on physical activity and diet outcomes among residents. Natural experiments of neighborhood built environment change, exploring longitudinal impacts on physical activity and/or diet in residents, were included. From five electronic databases, 2084 references were identified. A narrative synthesis was conducted, considering results in relation to study quality. Nineteen papers, reporting on 15 different exposures met inclusion criteria. Four studies included a comparison group and 11 were pre-post/longitudinal studies without a comparison group. Studies reported on the impact of redeveloping or introducing cycle and/or walking trails (n = 5), rail stops/lines (n = 4), supermarkets and farmers’ markets (n = 4) and park and green space (n = 2). Eight/15 studies reported at least one beneficial change in physical activity, diet or another associated health outcome. Due to limitations in study design and reporting, as well as the wide array of outcome measures reported, drawing conclusions to inform policy was challenging. Future research should consider a consistent approach to measure the same outcomes (e.g., using measurement methods that collect comparable physical activity and diet outcome data), to allow for pooled analyses. Additionally, including comparison groups wherever possible and ensuring high quality reporting is essential. View Full-Text

Objectives Formative evaluation is critical in maximising the implementation strategies and processes of interventions. It is also critical to both providing contextual explanations for and maximising the success of such interventions. The purpose of this study was to undertake a comprehensive formative evaluation of the implementation process of a multi-component, sports-based mental health program for adolescent males (“Ahead of the Game”). Methods Primary outcomes included program reach, dose, fidelity and cost during initial piloting and two distinct implementation phases. The iterative formative evaluation process provided opportunities to adapt the program and its implementation strategy to optimise reach, dose and fidelity relative to implementation cost. Results Formative evaluation data showed that the program failed to achieve optimal reach in the initial pilot phase (Phase I), with low doses of the program received by stakeholders, and moderate fidelity. Bottom up implementation strategies improved dose and club ownership during Phase II but resulted in high costs and lower fidelity and was associated with implementation staff retention and management issues. Phase III with more streamlined staffing and club integrated implementation resulted in high reach, dose, fidelity and club ownership and an associated reduction in implementation cost per participant. Conclusion : Formative evaluation succeeded in maximising the Ahead of the Game program engagement over three distinct phases. Results are salient for informing cost-effective implementation strategies for sports-based health promotion.

Objective Physical education (PE) programs aim to promote physical activity (PA) and reach most school-aged youth. However, PA levels within PE lessons are often low. In this cluster-randomized controlled trial, we examined the effects of three self-determination theory-based motivational strategies on PA and sedentary behavior, as well as their hypothesized antecedents during PE lessons. Methods Data were collected in Sydney, Australia (October–December 2011). After baseline testing, teachers (n = 16) and their classes (n = 288 students; M = 13.6 years, 50.4% male) were randomly assigned to one of four teaching strategy conditions: (1) explaining relevance; (2) providing choice; (3) complete free choice; or (4) usual practice. Teachers then delivered the assigned strategy. Primary outcomes were accelerometer-assessed PA and student motivation during lessons. Secondary outcomes included sedentary behavior, perceptions of teachers' support and psychological needs satisfaction. Results The ‘free choice’ intervention increased PA (p < .05). ‘Providing choice’ and ‘free choice’ interventions decreased sedentary behavior (p < .05). The interventions did not influence motivation, but students' autonomy increased during both choice-based interventions (p < .05). Conclusions Promoting choice can produce short-term increases in PA and decreases in sedentary behavior, as well as increased perceived autonomy during PE lessons.

Background Despite the health benefits of regular physical activity, most children are insufficiently active. Schools are ideally placed to promote physical activity; however, many do not provide children with sufficient in-school activity or ensure they have the skills and motivation to be active beyond the school setting. The aim of this project is to modify, scale up and evaluate the effectiveness of an intervention previously shown to be efficacious in improving children’s physical activity, fundamental movement skills and cardiorespiratory fitness. The ‘Internet-based Professional Learning to help teachers support Activity in Youth’ (iPLAY) study will focus largely on online delivery to enhance translational capacity. Methods/Design The intervention will be implemented at school and teacher levels, and will include six components: (i) quality physical education and school sport, (ii) classroom movement breaks, (iii) physically active homework, (iv) active playgrounds, (v) community physical activity links and (vi) parent/caregiver engagement. Experienced physical education teachers will deliver professional learning workshops and follow-up, individualized mentoring to primary teachers (i.e., Kindergarten – Year 6). These activities will be supported by online learning and resources. Teachers will then deliver the iPLAY intervention components in their schools. We will evaluate iPLAY in two complementary studies in primary schools across New South Wales (NSW), Australia. A cluster randomized controlled trial (RCT), involving a representative sample of 20 schools within NSW (1:1 allocation at the school level to intervention and attention control conditions), will assess effectiveness and cost-effectiveness at 12 and 24 months. Students’ cardiorespiratory fitness will be the primary outcome in this trial. Key secondary outcomes will include students’ moderate-to-vigorous physical activity (via accelerometers), fundamental movement skill proficiency, enjoyment of physical education and sport, cognitive control, performance on standardized tests of numeracy and literacy, and cost-effectiveness. A scale-up implementation study guided by the RE-AIM framework will evaluate the reach, effectiveness, adoption, implementation, and maintenance of the intervention when delivered in 160 primary schools in urban and regional areas of NSW. Discussion This project will provide the evidence and a framework for government to guide physical activity promotion throughout NSW primary schools and a potential model for adoption in other states and countries. Trial registration Australia and New Zealand Clinical Trials Registry ( ACTRN12616000731493 ). Date of registration: June 3, 2016.

There is a growing belief that green space (for example, parks) help prevent obesity. There is evidence of an inverse association between green space and childhood body mass index (BMI); however, the majority of these studies are cross-sectional. Longitudinal studies that track change in BMI across childhood in relation to levels of green space proximity would improve the quality of evidence available for decision making.Objectively measured BMI was obtained every 2 years between 2006 and 2012 for 4423 participants initially aged 6-7 years in the Longitudinal Study of Australian Children (LSAC). The LSAC is a nationally representative study on a range of health and socio-demographic measures. Using Australian Bureau of Statistics mesh block data, which classify small scale land areas based on the main usage, each participant was assigned an objective measure of green space availability within their Statistical Area (level 2) of residence. Gender-stratified multilevel linear regression was used to estimate BMI growth curves across childhood in relation to green space availability. Family income, Australian Indigenous status, mothers' education and language spoken were used to adjust for socio-economic confounding.Age was found to be an effect modifier of associations between green space and BMI for boys (P=0.005) and girls (P=0.048). As children grew older, an inverse patterning of BMI by green space availability emerged. These findings held after adjustment for socio-economic circumstances for boys (P=0.009), though were less robust for girls after this adjustment (P=0.056).A beneficial effect of green space on BMI emerges as children grow older. However, there was little additional benefit after a modest amount of green space was met. Further research is needed to understand whether the drivers of this effect are from age-specific mechanisms, or whether the benefit of living in a greener neighbourhood is accumulated through childhood.

ObjectivesAccurate, objective measurement is important for understanding adolescents' physical activity (PA) behaviour. When using accelerometry to objectively measure PA, a decision must be made regarding how frequently data is recorded (i.e., epoch length). The purpose of this study was to examine i) PA bout length, and ii) the effect of variations in accelerometer epoch length on PA estimates during physical education (PE) and leisure time in adolescent boys.DesignCross-sectional study.MethodsYear 9 boys (N = 133; mean age ±SD = 14.36±0.48 years) wore accelerometers during two PE lessons, and for a period of seven consecutive days. Data were reintegrated from 1s into longer periods of 2, 5, 10, 30, and 60 seconds. ANOVAs were used to test for differences in PA estimates between epochs in leisure time and PE.ResultsThe mean length of vigorous PA (VPA) bouts was 3.5±2.0 seconds for PE and 2.5±1.7 seconds for leisure time, and mean length of moderate PA (MPA) bouts was 2.3±0.5 seconds for PE and 2.9±0.5 seconds for leisure time. During PE, estimates of MVPA, MPA, and light PA (LPA) increased as epoch increased from 1 second to 60 seconds, while VPA and sedentary behaviour estimates decreased. During leisure time, estimates of all PA intensities decreased as epoch increased from 1 second to 60 seconds, with the exception of sedentary behaviour, which increased as epoch length increased.ConclusionThe context in which PA occurs can influence PA bout length measurement and the effect of variations in epoch length on PA estimates. Researchers measuring PA with accelerometry should be conscious of the possible influence of context on PA estimates.