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Implementing Resistance Training in Secondary Schools

A Cluster Randomized Controlled Trial


Author Information
Medicine & Science in Sports & Exercise: January 2018 - Volume 50 - Issue 1 - p 62-72
doi: 10.1249/MSS.0000000000001410


Physical inactivity has been described as a global pandemic because of its prevalence, global reach and social, economic and health consequences (1). Physical activity levels decline dramatically during adolescence (2), and only 20% of adolescents globally are sufficiently active (3). Of additional concern, evidence suggests that there have been global secular declines in young people’s cardiorespiratory (4) and muscular fitness (5), both of which are important predictors of health status. The World Health Organization recommend children and adolescents participate in at least 60 min of (predominantly aerobic) moderate-to-vigorous physical activity (MVPA) every day (6) and engage in muscle-strengthening activities (e.g., resistance training (RT)) on at least 3 d·wk−1 (6). It is therefore important to identify scalable approaches for promoting regular participation in both aerobic and resistance-based activities for adolescents.

Schools are considered ideal settings for physical activity promotion as they provide an environment within which children and adolescents can regularly engage in physical activity. Moreover, schools have the potential to help youth develop the skills, knowledge, and confidence needed to sustain an active lifestyle beyond schooling years (7). Physical education (PE) is considered to be the cornerstone of a Comprehensive School Physical Activity Program (CSPAP), but has historically focused largely on traditional competitive team games and sports (8). Such activities, although enjoyable for some, are unlikely to prepare most young people for a lifetime of physical activity and may not engage the least active and least skilled youth (8).

Young people have identified a desire to try a variety of nontraditional “lifelong” physical activities (e.g., RT, yoga, cycling, etc.) (9), with global data suggesting that these activities become more popular with increasing age (10). However, absolute prevalence data suggest that participation is still quite low, with reports that only 21.9% of adults in the United States meet the muscle-strengthening guidelines (11). Schools are ideally placed to introduce young people to a range of lifelong physical activities, including RT. The introduction to RT within the school setting might provide youth with the skills and confidence needed to participate in this important form of physical activity across the life-span. However, most school-based physical activity interventions have promoted aerobic physical activity, with very few focusing on RT (12). It may be that teachers are unsure of how to integrate RT into their PE/school sport programs. Alternatively, teachers may subscribe to enduring misconceptions regarding the safety and feasibility of RT for youth (i.e., RT can stunt growth, requires specialized equipment and gym access) (13). Given the recognized importance of muscle-strengthening activities for health, there is a need to test feasible and scalable school-based interventions that include RT.

The Nutrition and Enjoyable Activity for Teen (NEAT) Girls (14) and Active Teen Leaders Avoiding Screen-Time (ATLAS) (15) programs were originally designed as school-based obesity prevention interventions and focused on the promotion of lifelong physical activities including RT. On the basis of process evaluation data (15) and feedback from the New South Wales (NSW) Department of Education (DoE), the NEAT and ATLAS programs were refined, placing a greater emphasis on muscular fitness (13) and introducing strategies to improve scalability. The aim of the current study was to evaluate the effects of the revised NEAT and ATLAS programs (known collectively as “Resistance Training for Teens”) using a cluster randomized controlled trial (RCT). The 10-wk programs (NEAT for girls and ATLAS for boys) were designed to improve muscular fitness and provide adolescents with the knowledge, motivation, and skills to engage in RT. This study reports the postprogram (6-month; study’s primary end point) and follow-up (12-month) intervention effects.


Study Design and Participants

Ethics approval for this study was obtained from the human research ethics committees of the University of Newcastle, Australia, and NSW DoE. School principals, teachers, parents, and study participants all provided written informed consent. The design and methods have been reported in detail previously (16). In summary, Resistance Training for Teens was evaluated using a cluster RCT, which adhered to the Standard Protocol Items: Recommendations for Interventional Trials and Consolidated Standards of Reporting Trials guidelines. The intervention was delivered over a 10-wk school term, with pretest and posttest data collection occurring in the preceding and ensuing school terms to the intervention, respectively (i.e., pretests occurred in term 2 (April–June), the intervention was delivered in term 3 (July–September), and posttest occurred during term 4 (October–December)). This resulted in an approximate period of 6 months between pretest and posttest measurements. Government-funded secondary schools located within the Hunter, Central Coast, and Sydney regions of NSW, Australia, were considered eligible for inclusion. The NSW DoE “Services Locator” Web site was used to identify government secondary schools within approximately 50 km of the University of Newcastle and the University of Sydney, and 16 coeducational secondary schools were recruited. Participants were adolescents in year 9 (N = 607; 50.1% female; mean age, 14.1 ± 0.5 yr) who did not have an injury or illness that would preclude participation in a physical activity program.

Sample Size Calculation and Randomization

The sample size calculation was based on detecting changes in the primary outcome of muscular fitness (i.e., assessed using the 90°-push-up and standing long jump tests). The calculation assumed 80% power, an α level of 0.05, an expected 20% dropout rate over the study period (10% at each of 6 (primary end point) and 12 months), and an anticipated effect size for muscular fitness of d = 0.40. We adjusted for clustering at the class level using a correction factor of [1 + (m − 1) × ICC], where m represents the number of participants per class and ICC refers to the intraclass correlation coefficient for muscular fitness. On the basis of our previous research, we assumed an ICC of 0.09 (15). Assuming 20 students per class (and two classes per school), the final required sample size was estimated to be 640 students from 16 schools. After baseline assessments, schools were match paired on the basis of their size, geographical location, and socioeconomic status (SES). An independent researcher then randomized each pair to either the intervention group or the wait-list control group (regularly scheduled PE and cocurricular school sport) using a computer-based random number producing algorithm.


Like many previous school-based interventions, the original NEAT (for girls) and ATLAS (for boys) programs included a large number of intervention strategies, making them difficult to implement more broadly. Because of this, a number of modifications were made to the original NEAT and ATLAS interventions, which are described in detail elsewhere (16). In recognition of the unique contextual differences between schools (i.e., lesson duration, number of students and sex distribution within the individual classes, student behavioral issues), a flexible delivery mode was considered an important feature of the scalable model (17). The programs were designed to be delivered over one school term (10 wk), for approximately 90 min·wk−1. The intervention was delivered through either: (i) compulsory PE, (ii) cocurricular school sport, or (iii) an elective course known as Physical Activity and Sports Studies.

The intervention was guided by social cognitive theory (18) and self-determination theory (19) and included the following sex-targeted components: an interactive student seminar; a structured physical activity program, which focused on RT; lunchtime fitness sessions; and a Web-based smartphone app. The NEAT and ATLAS interventions had the same structure and format. However, various sociocultural targeting strategies were applied to the interventions to increase their relevance and appeal to adolescent girls and boys. For example, the program resources, including the circuit cards, interactive seminars, and smartphone apps, included images of same-sex role models. In addition, separate interactive seminars, focusing on health behaviors common to each sex, were designed for girls and boys (see Table 1 for further details of these strategies). Although teachers were advised to deliver the program separately to girls and boys, the flexible delivery mode allowed sessions to be conducted with mixed-sex groups. This was an important aspect of intervention scalability because it accounted for potential barriers such as staff availability and timetabling. The structured physical activity program followed a specified session format, including the following: (i) movement-based games and dynamic stretching warm-up; (ii) RT skill development; (iii) high-intensity RT (HIRT) workout; (iv) modified game involving fitness infusion, boxing, or core strength activity; (v) static stretching; and (vi) reinforcement of key behavioral messages (see Table, Supplemental Digital Content 1, proposed RT for teens physical activity session structure, The level of intensity for each session component was guided by Borg’s rating of perceived exertion scale. Choice and variety were included in each of the session components to fit with the individual school needs. The following implementation components were also used: school champions, professional learning workshop for teachers, teacher handbook, session resources, fitness equipment, and physical activity session observation and feedback (i.e., a member of the research team observing and providing feedback to the teacher). The professional learning workshop for teachers introduced the “Supportive, Active, Autonomous, Fair, and Enjoyable” (SAAFE) teaching principles (20), which served as the framework for the design and delivery of the physical activity sessions, as well as the session observations. Teachers were educated about the importance of, and provided with strategies for, integrating SAAFE principles within their lessons. The Resistance Training for Teens intervention was designed to be scalable. In particular, the following features reflect the scalability of the program: (i) partnership with the NSW DoE, including their commitment to support program delivery beyond the research study; (ii) flexibility of the program and adaptability for delivery within PE, school sport, or Physical Activity and Sports Studies; (iii) accredited teacher-training workshop and teacher-led delivery of the program; (iv) smartphone apps to support intervention delivery within and beyond schools; and (v) capability of the program to be delivered without elaborate equipment or access to a gym. More details regarding the intervention components and implementation strategies are provided in Table 1. The control group participated in usual practice (regularly scheduled PE and cocurricular school sport) for the duration of the intervention and received the intervention after the 12-month assessments.

Intervention and implementation description.


A study protocol manual, including specific instructions for conducting assessment tests and procedures, was developed and used by the research team to ensure accuracy and consistency. Trained research assistants collected data at baseline, postintervention (6 months from baseline; primary end point), and follow-up (12 months from baseline) assessments. Students completed a questionnaire to obtain demographic information, which included sex, age, ethnicity, indigenous (Aboriginal or Torres Strait Islander) descent, and language spoken at home. SES was determined using an index of relative socioeconomic disadvantage on the basis of participants’ residential postal codes.

Primary Outcome Measures

Muscular fitness

Upper body muscular endurance was assessed using the 90° push-up test (21) and lower body muscular strength was measured using the standing long jump test (22), which have excellent validity and reliability in the study population.

Secondary Outcome Measures

Height was recorded using a portable stadiometer (Model No. PE087; Mentone Educational Centre, Moorabbin, Australia), and weight was measured using a portable digital scale (Model No. UC-321PC; A&D Company Ltd., Tokyo Japan). Body mass index (BMI) was calculated using the standard equation (weight [kg]/height [m]2), with BMI z-scores calculated using the lambdamu–sigma method (International Obesity Task Force cutoffs). Physical activity was assessed using GENEActiv wrist-worn accelerometers (Model GAT04; Activinsights Ltd, Cambridgeshire, England, UK) in a random subsample of participants. This random sample was chosen by allocating accelerometers to 50% of the students present on the day of testing (i.e., students were stratified by sex and allocated ID numbers, with every odd numbered student receiving an accelerometer). Analyses for weekday MVPA included participants who wore their monitor for ≥600 min·d−1 on at least three weekdays (23). Mean weekday MVPA was determined using previously developed thresholds (24). Maximal aerobic capacity (i.e., V˙O2max) was estimated using a submaximal step test protocol. Flexibility was assessed using the FITNESSGRAM back-saver sit and reach test (21), and RT skill competency was assessed using video analysis of the Resistance Training Skills Battery (25). The intrinsic and identified regulation subscales from the Behavioral Regulations in Exercise Questionnaire-2 (26) were combined to assess autonomous motivation for physical activity. An adapted version of the complete Behavioral Regulations in Exercise Questionnaire-2 (26) was used to assess motivation for RT, and a four-item scale developed for use with adolescents (27) was used to evaluate self-efficacy for RT.

Process Evaluation

A detailed process evaluation was conducted and included the following: 1) intervention implementation (e.g., number of structured physical activity sessions that were delivered), 2) attendance (e.g., student participation in the structured physical activity sessions), 3) engagement (e.g., student engagement with the Web-based app), 4) satisfaction (overall student and teacher satisfaction), 5) fidelity (e.g., compliance with the proposed physical activity session structure; see Table, Supplemental Digital Content 1, proposed RT for teens physical activity session structure,, and 6) adherence to SAAFE teaching principles (i.e., the inclusion of Supportive, Active, Autonomous, Fair, and Enjoyable elements within lessons, which were explained to teachers during the Resistance Training for Teens Professional Learning workshop). Intervention fidelity and adherence to the SAAFE teaching principles was determined using two lesson observations during the intervention period (per class), one scheduled during weeks 3–5 of the school term and the second during weeks 7–9. Members of the research team, all of whom held a tertiary PE teaching qualification and had been involved in the adaptation of the SAAFE principles to RT, conducted the lesson observations using a structured observation checklist. Teachers were asked to record any injuries or adverse events that occurred during any of the sessions.

Statistical Analyses

Linear mixed models were used to analyze the primary and secondary outcomes using IBM SPSS Statistics for Windows, Version 20.0 (2010 SPSS Inc., IBM Company, Armonk, NY), with significance set at P < 0.05. Models assessed the effect of treatment (intervention or control), time (baseline, 6 months, and 12 months), and the group–time interaction. Time and treatment were included as fixed factors, with school class included as a random effect. Previous school-based studies have shown that school-level clustering is negligible after accounting for clustering at the class level (28). Mixed models are consistent with the intention-to-treat principle, assuming that data are missing at random. Three potential moderators were identified a priori (i.e., sex (male, female), household SES (low, medium, high), and initial weight status (not overweight, overweight/obese)) (29) and examined using linear mixed models with interaction terms. Subgroup analyses were conducted if P < 0.1 (see Table, Supplemental Digital Content 2, interaction tests for moderators (sex, SES and initial weight status), and are presented in Supplemental Digital Content 3 (see Table, Supplemental Digital Content 3, moderator analyses of primary and secondary outcomes, Two sensitivity analyses were conducted: (i) completers analysis (i.e., participants who provided useable data at baseline and at 12 months; see Table, Supplemental Digital Content 4, completer’s analysis of primary and secondary outcomes, and (ii) last observation carried forward analysis (see Table, Supplemental Digital Content 5, last observation carried forward analysis of primary and secondary outcomes, Differences between completers and those who dropped out of the study were examined using independent-samples t-tests.


Sixteen schools were recruited, with 607 students (50.1% female; mean age, 14.1 ± 0.5 yr) assessed at baseline (Fig. 1). Baseline characteristics of the study sample can be seen in Table 2. Most participants were born in Australia, spoke English at home, and recognized themselves as having an “Australian” cultural background, whereas 7.3% identified as indigenous. More than 70% of participants were from low- to medium-SES households, and almost a third were classified as overweight or obese. Postintervention (6-month) and follow-up (12-month) assessments were completed by 513 (84.5%) and 472 (77.8%) students, respectively. Within- and between-group changes in primary and secondary outcomes are presented in Table 3. Participants (both intervention and control) who did not complete 6- or 12-month assessments were more likely to have indigenous heritage (P = 0.019), lower SES (P = 0.005), poorer RT skill competency (P = 0.020), and lower motivation for RT (P = 0.013), compared with students providing data at all time points.

Flow of participants through the study.
Baseline characteristics of the study sample.
Intention-to-treat analysis of primary and secondary outcomes.

Muscular fitness

Significant intervention effects for push-ups were found at 6 months (2.0 repetitions; 95% confidence interval (CI), 0.8–3.2) and 12 months (1.5 repetitions; 95% CI, 0.4–2.7). There were no intervention effects for standing long jump at 6 or 12 months.

Health-related fitness and physical activity

There were no significant intervention effects for BMI or BMI z-scores at 6 or 12 months among the full sample. However, significant interaction effects were observed for weight status. At 12 months, intervention effects were found for BMI (−0.55 kg·m−2; 95% CI, −1.01 to −0.08) among students classified as overweight or obese at baseline.

Significant group–time interactions were found for estimated V˙O2max at 6 months (−1.3 mL·kg−1·min−1; 95% CI, −2.5 to −0.1) and for flexibility at 12 months (1.1 cm; 95% CI, 0.2–2.0). No significant intervention effects were observed for weekday MVPA at either time point.

RT skill competency

Significant group–time effects were observed for RT skill competency at 6 months (4.4 units; 95% CI, 3.2–5.5), which were sustained at 12 months (2.0 units; 95% CI, 0.8–3.3).

Self-efficacy and motivation

After 6 months, there was a significant group–time effect for RT self-efficacy (0.2 units; 95% CI, 0.1–0.3), which was not sustained at 12 months. A significant group–time effect was observed for autonomous motivation for physical activity at 12 months only (0.1 units; 95% CI, 0.0–0.3), favoring the intervention group.

Sensitivity analyses

Similar findings were observed in the completers’ (see Table, Supplemental Digital Content 4, completer’s analysis of primary and secondary outcomes, and last observation carried forward (see Table, Supplemental Digital Content 5, last observation carried forward analysis of primary and secondary outcomes, sensitivity analyses when compared with intention-to-treat. A difference of note, however, is that the completers’ analysis indicated a significant group–time effect for BMI among the overall study sample at 12 months (−0.20 kg·m−2; 95% CI, −0.39 to −0.01).

Process evaluation

Process evaluation data are presented in Table 4. On average, schools delivered most scheduled physical activity sessions, with a mean attendance of greater than 80%. The smartphone app was used by almost 70% of students during the intervention period, with more than one-third of users entering their motivation for physical activity. Physical activity behavior was entered by almost one quarter of users, whereas more than 10% used the workouts function. Very few students used the RT technique section of the app (see Figure, Supplemental Digital Content 6, Web-based App components (NEAT and ATLAS), Overall satisfaction (1 being poor to 5 being excellent) with the program was moderate among students (3.8 ± 0.9) and high among teachers (4.8 ± 0.4). However, students did not enjoy the lunch time sessions (1.6 ± 0.9). In regard to intervention fidelity, resource usage was high, with more than 90% of observed lessons including the circuit cards, teacher handbook, resistance band training devices (Gymsticks), smartphone app, or a combination of the three. Of the session components, including movement-based games within the warm-up, an RT skill development circuit and an HIRT workout were the most commonly completed. Adherence to the SAAFE teaching principles was high among teachers, with all elements included in at least 80% of lessons. No injuries or adverse events were recorded by any of the teachers involved in the study.

Process evaluation summary.


The aim of this study was to evaluate the immediate and sustained effects of the Resistance Training for Teens intervention delivered by trained secondary school teachers. The intervention significantly improved adolescents’ upper body muscular fitness, with improvements maintained at 12 months (particularly for overweight/obese participants). However, no intervention effects were observed for lower body muscular fitness. RT skill competency also improved after the intervention and was maintained at follow-up. Significant group–time effects were also evident for flexibility, autonomous motivation for physical activity, and RT self-efficacy. To the authors’ knowledge, this is the first experimental evidence showing increases in muscular fitness, RT skill competency, and RT self-efficacy in a sample of adolescents.

These findings contribute to evidence that school-based physical activity interventions can increase muscular fitness (15). However, previous interventions involving RT have been delivered on a smaller scale, often within gym settings where there is access to free-standing and fixed equipment and trained exercise professionals (30). The Resistance Training for Teens intervention was delivered by PE teachers who attended a 1-d professional learning workshop and used minimal equipment (i.e., Gymstick™ resistance bands and body weight exercises only). The inclusion of teacher training and the provision of resources were important contributors to the program successes and maintenance of these findings. These inclusions not only allowed the teachers to deliver the Resistance Training for Teens intervention, which they evaluated as “excellent,” but also provided them with the skills, knowledge, and equipment to facilitate the program’s delivery into the future. Resistance Training for Teens is a sustainable intervention, which has been successfully up-scaled from its predecessors (the original NEAT [14] and ATLAS [15] programs), through its modified design, increased flexibility of delivery, and stakeholder consultation (the DoE) during these processes (17).

The intervention was not successful in increasing adolescents’ lower body muscular fitness. The null findings for lower body muscular fitness are likely due to the specificity of the exercise training involved in the intervention, which was more focused on muscular endurance, as well as core strength and stability. This finding is in line with the idea of muscle action and testing specificity, whereby greater increases are noticed when the muscle being trained matches that being tested (i.e., push-up repetitions during training and the maximal push-up test) (31). Conversely, the lower body exercises performed in the intervention (i.e., repetitions of squats, lunges, skipping) developed muscular endurance and were not specifically matched with the test used (i.e., standing long jump), which required explosive power, rather than muscular endurance.

Although overall intervention effects for BMI were not significant in the intention-to-treat analysis, a significant intervention effect was observed in the completers’ analysis (i.e., per protocol; −0.20 kg·m−2; 95% CI, −0.39 to −0.01) and among participants who were overweight/obese at baseline (−0.55 kg·m−2; 95% CI, −1.01 to −0.08). Importantly, the reduction in BMI seen in the overweight/obese group is sufficient to produce clinically meaningful effects for metabolic outcomes (32). The intervention effects for the current study compare favorably with previous school-based obesity prevention trials. In a recent review of 43 school-based obesity prevention interventions (33), the pooled effects for BMI were −0.35 kg·m−2 (95% CI, −0.12 to −0.58) and −0.17 kg·m−2 (95% CI, −0.29 to −0.06), for overweight/obese students and all students, respectively. Of note, it is possible that the effects observed in this trial underestimate the true effect of the intervention on body composition. The calculation of BMI, which takes into consideration only whole body mass, lacks the sensitivity to differentiate between fat and/or fat-free mass. Given that participation in muscle-strengthening exercises are generally associated with increases in fat-free (i.e., muscle) mass (34) and decreases in fat mass (35), it is possible that the intervention effect would have been stronger if a criterion measure, such as dual-energy x-ray absorptiometry or hydrostatic weighing, was used to measure body composition.

The intervention effects among overweight and obese participants were stronger for a number of outcomes, including upper body muscular fitness, RT skill competency, and motivation for RT. These findings are promising because declines in physical activity during adolescence are greater among overweight/obese youth compared with their leaner peers (36). Overweight and obese adolescents often suffer “weight criticism” from others when engaging in physical activity, which may negatively influence their motivation to participate in physical activity (37). The focus on RT may explain the positive effects of the intervention in overweight and obese adolescents. In comparison to aerobic activities, RT may be a more appealing physical activity for overweight and obese adolescents, because this is one of the few activities in which they may outperform their leaner peers (owing to greater lean mass and superior absolute strength) (38). This greater lean mass and absolute strength may be attributed to the chronic overload that the overweight/obese adolescents’ muscles are placed under during day-to-day activities (i.e., walking) (39). The findings from this study provide support for the inclusion of RT in physical activity interventions for overweight/obese adolescents.

In addition to the improvements in muscular fitness, RT skill competency, and motivation to participate in RT, adolescents also significantly increased their RT self-efficacy. In social cognitive theory, self-efficacy is considered the central mechanism of behavior change and essential for continuing participation in physical activity (18). The increase in RT self-efficacy seen at 6 months, before a plateau at follow-up, may highlight the importance of positive role models in the delivery of adolescent physical activity programs. The motivational climate of the sessions and the support provided by the teachers delivering the intervention may explain the immediate improvements in self-efficacy.

There was a null finding for weekday MVPA, with both groups following the age-related decline in physical activity seen throughout adolescence (2). There is now compelling evidence that CSPAPs are needed to increase adolescents’ physical activity levels (40). CSPAPs should consist of evidence-based components, including the following: quality PE; physical activity before, during, and after school; staff involvement; and family and community engagement. Resistance Training for Teens is an evidence-based program that can be delivered in PE or school sport within a multicomponent CSPAP.

Strengths and limitations

Strengths of this study include the cluster RCT design, objective outcome measures, high participant retention, and extensive process evaluation. However, some limitations should be noted. First, incomplete process evaluation data limited our ability to evaluate attendance and delivery of lunchtime sessions. Data available indicated that this aspect of the intervention was poorly implemented. Available student data are consistent with previous school-based physical activity interventions (15), suggesting that students were unwilling to give up time that may be used for socialization and participation in alternate activities. Smartphone app usage was moderate, and this component of the intervention seemed to be less important than the face-to-face components. Of note, students reported a reluctance to use data from their own mobile phone plan when the school Wi-Fi was not functioning correctly. School policies surrounding the use of personal electronic devices during class-time was another barrier to app usage in some schools. This was a large-scale effectiveness trial involving field-based assessments, and we were unable to use gold standard measures of muscular fitness (i.e., one-repetition maximum) and body composition (i.e., dual-energy x-ray absorptiometry). Finally, the timing of collection of data in the terms before and after intervention delivery was not ideal, but could not be avoided because of the number of schools involved in the study and the realities of gaining access to schools in “real-world” trials. Sensitivity analyses, which included the time between baseline and follow-up assessments as a covariate, did not change the findings. However, it is possible that the intervention effects reported herein are not as large as they might have been, had assessments been conducted directly after the intervention concluded.


The Resistance Training for Teens intervention achieved immediate and sustained improvements in upper body muscular fitness and RT skill competency, as well as increases in RT self-efficacy, autonomous motivation for physical activity, and flexibility. In addition, effects were found for BMI and motivation for RT in overweight/obese individuals. These findings highlight the potential to train teachers to deliver a school-based RT intervention involving minimal equipment. This study has provided evidence of how to effectively modify existing interventions to maximize uptake in the school environment via flexible delivery options, scalable design, and novel approaches. Further investigation into the scalability of the Resistance Training for Teens intervention is warranted, with future directions for this research including a large-scale dissemination trial.

The authors thank the participating schools, students, and teachers for their support and cooperation throughout the project. The authors acknowledge Matthew Stemley for his assistance in data collection. The authors thank the Australian Research Council and the DoE School Sport Unit (with special thanks to Ross Morrison and Sue Meade) for providing funding. S. G. K. is supported by an Australian Government Research Training Program Scholarship. D. R. L. is supported by an ARC Future Fellowship. The results of this study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation. The results of the present study do not constitute endorsement by the American College of Sports Medicine.

There are no conflicts of interest.


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