Assessing the sustained impact of a school-based obesity prevention program for adolescent boys: the ATLAS cluster randomized controlled trial

Lubans, David R.; Smith, Jordan J.; Plotnikoff, Ronald C.; Dally, Kerry; Okely, Anthony D.; Salmon, Jo; Morgan, Philip J.

doi:10.1186/s12966-016-0420-8

Cited by 102 publications

(293 citation statements)

References 67 publications

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“…The main effect of group was also significant ( F =5.3, p = .01 ç =0.27). The individual group (1.89 m/s) was significantly faster than the control group (1.45 m/s; t =3.94, p = .003, d = 1.31), and faster than the social group (1.58 m/s; t =2.05, p = .08, d = .89), though the latter did not reach statistical significance. Study quality LowCONSORT score: 12Percentage of fulfilled criteria: 48.0%Smith et al 2014 [29], Lubans et al 2016 [30]Australia Study design 2-group cluster RCT Duration Intervention exposure: 20 weeks (Dec 2012 - June 2013)Measurement points: baseline, 8 months (post-intervention), 18 monthsAttrition rate: 19% Sample Children N = 36112.7 years/12–14 years100% (M)Random Behaviour change theory Self-determination theory, social cognitive theory App features Newly designed app:Goal setting for physical activity and screen time, self-monitoring (uploading pedometer measured steps), tailored motivational and informational messages via ‘push prompts’, assessment of resistance training skill competency, recording fitness challenge results, resistance training and aerobic exercises. Intervention group Goal setting, self-monitoring (steps through pedometer), fitness challenge during school sport sessions, teacher professional development, provision of fitness equipment to schools, face-to-face physical activity sessions led by teachers, lunchtime student mentoring sessions, researcher-led educational sessions for children, a smartphone application and website, parental education and tips for reducing screen time through newsletter Control group Usual practice (regular school sports and PE lessons) Multi-component versus stand-alone app intervention Multi-component Outcome Physical activity (moderate-to-vigorous, total; minutes/day)Sugar-sweetened beverages consumption (glasses/day) Other relevant outcomes FitnessWeight status (BMI, waist circumference, body fat) Measures Accelerometer (worn on 7 consecutive days including weekend) Diet Significant between-group decrease in mean glasses/day of sugar-sweetened beverage consumption in IG (−0.6 ± 0.26; p = 0.01) at 8-months follow-up. No significant intervention effects at 18-months follow-up. Physical activity No significant changes in daily MVPA or overall PA at 8-months and 18-months follow-ups. Sedentary behaviour Significant between-group difference in mean minutes/day screen-time in favour of IG at 8-months follow-up (−30.0 ± 10.08; p = 0.03) and 18-months follow-up (−32.2; 95% CI: −53.6- -10.8; p = 0.03). Fitness Significant between-group increase in muscular endurance in IG as measured by mean push-ups repetitions (0.9 ± 0.49; p =0.04) and resistance training skills (mean units 5.7 ± 0.67; p <0.001) at 8–months follow-up.…”

Section: Methodsmentioning

confidence: 99%

Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour: a systematic review

Schöeppe

Alley

Lippevelde

et al. 2016

Int J Behav Nutr Phys Act

814

710

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Background: Health and fitness applications (apps) have gained popularity in interventions to improve diet, physical activity and sedentary behaviours but their efficacy is unclear. This systematic review examined the efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour in children and adults. Methods: Systematic literature searches were conducted in five databases to identify papers published between 2006 and 2016. Studies were included if they used a smartphone app in an intervention to improve diet, physical activity and/or sedentary behaviour for prevention. Interventions could be stand-alone interventions using an app only, or multi-component interventions including an app as one of several intervention components. Outcomes measured were changes in the health behaviours and related health outcomes (i.e., fitness, body weight, blood pressure, glucose, cholesterol, quality of life). Study inclusion and methodological quality were independently assessed by two reviewers. Results: Twenty-seven studies were included, most were randomised controlled trials (n = 19; 70%). Twenty-three studies targeted adults (17 showed significant health improvements) and four studies targeted children (two demonstrated significant health improvements). Twenty-one studies targeted physical activity (14 showed significant health improvements), 13 studies targeted diet (seven showed significant health improvements) and five studies targeted sedentary behaviour (two showed significant health improvements). More studies (n = 12; 63%) of those reporting significant effects detected between-group improvements in the health behaviour or related health outcomes, whilst fewer studies (n = 8; 42%) reported significant within-group improvements. A larger proportion of multi-component interventions (8 out of 13; 62%) showed significant between-group improvements compared to stand-alone app interventions (5 out of 14; 36%). Eleven studies reported app usage statistics, and three of them demonstrated that higher app usage was associated with improved health outcomes. Conclusions: This review provided modest evidence that app-based interventions to improve diet, physical activity and sedentary behaviours can be effective. Multi-component interventions appear to be more effective than standalone app interventions, however, this remains to be confirmed in controlled trials. Future research is needed on the optimal number and combination of app features, behaviour change techniques, and level of participant contact needed to maximise user engagement and intervention efficacy.

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Section: Methodsmentioning

confidence: 99%

Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour: a systematic review

Schöeppe

Alley

Lippevelde

et al. 2016

Int J Behav Nutr Phys Act

814

710

View full text Add to dashboard Cite

show abstract

“…In another example of a school-based randomized controlled trial targeting obesity prevention, Lubans and colleagues (2016) integrated elements from SDT and SCT and targeted autonomy, competence, and self-efficacy for school-based leisure physical activity. Inactive adolescent boys (ages 12–14) who were at high-risk for becoming overweight were recruited.…”

Section: Summary Of Evidence-based Randomized Controlled Trialsmentioning

confidence: 99%

“…Primary care settings, especially those that involve multiple medical health care personnel (Resnicow et al, 2015) appear to be a critical environment for promoting positive behavioral and parenting skills. Relatedly, training teachers and staff to use autonomy supportive strategies offer rich opportunities for developing positive supportive environments for youth (Lubans et al, 2016); however, sustainable behavioral change may require positive support from both parents and teachers (Wilson et al, 2011). Taken together, these studies suggest that youth and parents are likely to benefit when they receive positive support from multiple sources and across different contexts.…”

Section: Recommendations For Future Researchmentioning

confidence: 99%

Promoting Social Nurturance and Positive Social Environments to Reduce Obesity in High-Risk Youth

Wilson

Sweeney

Kitzman-Ulrich

et al. 2017

Clin Child Fam Psychol Rev

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Nurturing environments within the context of families, schools, and communities all play an important role in enhancing youth’s behavioral choices and health outcomes. The increasing prevalence rates of obesity among youth, especially among low income and ethnic minorities, highlight the need to develop effective and innovative intervention approaches that promote positive supportive environments across different contexts for at risk youth. We propose that the integration of Social Cognitive Theory, Family Systems Theory, and Self-Determination Theory offers a useful framework for understanding how individual, family and social-environmental level factors contribute to the development of nurturing environments. In this paper, we summarize evidence-based randomized controlled trials that integrate positive parenting, motivational, and behavioral skills strategies in different contexts, including primary care, home, community, and school-based settings. Taken together, these studies suggest that youth and parents are most likely to benefit when youth receive individual-level behavioral skills, family-level support and communication, and autonomous motivational support from the broader social environment. Future investigators and health care providers should consider integrating these evidence-based approaches that support the effects of positive social climate-based interventions on promoting healthy eating, physical activity, and weight management in youth.

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“…This means that not only an increase of PA in the intervention group leads to intervention success, but also a decrease of PA in the control group. Secondly, four studies in our pool of 49 studies used clustered randomization methods (for example by school) [40,53,55,66]. We did not differentiate those studies from fully randomized controlled trials, because we did not expect an interaction between the intervention effect and the type of unit randomized (i.e.…”

Section: Limitationsmentioning

confidence: 99%

Key Elements of mHealth Interventions to Successfully Increase Physical Activity: Meta-Regression (Preprint)

Eckerstorfer¹,

Tanzer²,

Vogrincic-Haselbacher³

et al. 2018

Preprint

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Background: Mobile technology gives researchers unimagined opportunities to design new interventions to increase physical activity. Unfortunately, it is still unclear which elements are useful to initiate and maintain behavior change. Objective: In this meta-analysis, we investigated randomized controlled trials of physical activity interventions that were delivered via mobile phone. We analyzed which elements contributed to intervention success. Methods: After searching four databases and science networks for eligible studies, we entered k=49 studies with N=5764 participants into a random effects meta-analysis, controlling for baseline group differences. We also calculated a meta-regression with categories of intervention techniques for behavior change (education, goals, feedback/prompts, rewards, and social cues) as moderators. Results: We found a small overall effect of Hedges' g=.29, (95% CI: .20 to .37) which reduced to g=.22 after correcting for publication bias. None of the predefined elements (e.g., education) led to more intervention success by themselves, but a combination of goals and rewards showed that using goals and rewards simultaneously increased intervention efficacy by g=.31 compared to using none of the two elements. Conclusion: Overall, mHealth interventions to increase physical activity have a small to moderate effect. However, including functions related to goals and rewards led to greater intervention success. More research is needed to look at single behavior change techniques instead of categories. To achieve this, reporting interventions in trial registrations and articles should be more structured and more thorough.

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Assessing the sustained impact of a school-based obesity prevention program for adolescent boys: the ATLAS cluster randomized controlled trial

Cited by 102 publications

References 67 publications

Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour: a systematic review

Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour: a systematic review

Promoting Social Nurturance and Positive Social Environments to Reduce Obesity in High-Risk Youth

Key Elements of mHealth Interventions to Successfully Increase Physical Activity: Meta-Regression (Preprint)

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