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. 2022 Aug 29;8(8):CD011677.
doi: 10.1002/14651858.CD011677.pub3.

Strategies for enhancing the implementation of school-based policies or practices targeting diet, physical activity, obesity, tobacco or alcohol use

Luke Wolfenden  1   2   3 , Sam McCrabb  1 , Courtney Barnes  1 , Kate M O'Brien  1 , Kwok W Ng  4   5 , Nicole K Nathan  1   2   3 , Rachel Sutherland  1   2   3 , Rebecca K Hodder  1   2   3 , Flora Tzelepis  1   2 , Erin Nolan  2 , Christopher M Williams  1   2   3   6 , Sze Lin Yoong  1   2   3
Affiliations

Strategies for enhancing the implementation of school-based policies or practices targeting diet, physical activity, obesity, tobacco or alcohol use

Luke Wolfenden et al. Cochrane Database Syst Rev. .

Update in

Abstract

Background: Several school-based interventions are effective in improving child diet and physical activity, and preventing excessive weight gain, and tobacco or harmful alcohol use. However, schools are frequently unsuccessful in implementing such evidence-based interventions.

Objectives: 1. To evaluate the benefits and harms of strategies aiming to improve school implementation of interventions to address student diet, physical activity, tobacco or alcohol use, and obesity. 2. To evaluate the benefits and harms of strategies to improve intervention implementation on measures of student diet, physical activity, obesity, tobacco use or alcohol use; describe their cost or cost-effectiveness; and any harms of strategies on schools, school staff or students.

Search methods: We used standard, extensive Cochrane search methods. The latest search was between 1 September 2016 and 30 April 2021 to identify any relevant trials published since the last published review.

Selection criteria: We defined 'Implementation' as the use of strategies to adopt and integrate evidence-based health interventions and to change practice patterns within specific settings. We included any trial (randomised controlled trial (RCT) or non-randomised controlled trial (non-RCT)) conducted at any scale, with a parallel control group that compared a strategy to implement policies or practices to address diet, physical activity, overweight or obesity, tobacco or alcohol use by students to 'no intervention', 'usual' practice or a different implementation strategy.

Data collection and analysis: We used standard Cochrane methods. Given the large number of outcomes reported, we selected and included the effects of a single outcome measure for each trial for the primary (implementation) and secondary (student health behaviour and obesity) outcomes using a decision hierarchy. Where possible, we calculated standardised mean differences (SMDs) to account for variable outcome measures with 95% confidence intervals (CI). For RCTs, we conducted meta-analyses of primary and secondary outcomes using a random-effects model, or in instances where there were between two and five studies, a fixed-effect model. The synthesis of the effects for non-randomised studies followed the 'Synthesis without meta-analysis' (SWiM) guidelines.

Main results: We included an additional 11 trials in this update bringing the total number of included studies in the review to 38. Of these, 22 were conducted in the USA. Twenty-six studies used RCT designs. Seventeen trials tested strategies to implement healthy eating, 12 physical activity and six a combination of risk factors. Just one trial sought to increase the implementation of interventions to delay initiation or reduce the consumption of alcohol. All trials used multiple implementation strategies, the most common being educational materials, educational outreach and educational meetings. The overall certainty of evidence was low and ranged from very low to moderate for secondary review outcomes. Pooled analyses of RCTs found, relative to a control, the use of implementation strategies may result in a large increase in the implementation of interventions in schools (SMD 1.04, 95% CI 0.74 to 1.34; 22 RCTs, 1917 participants; low-certainty evidence). For secondary outcomes we found, relative to control, the use of implementation strategies to support intervention implementation may result in a slight improvement on measures of student diet (SMD 0.08, 95% CI 0.02 to 0.15; 11 RCTs, 16,649 participants; low-certainty evidence) and physical activity (SMD 0.09, 95% CI -0.02 to 0.19; 9 RCTs, 16,389 participants; low-certainty evidence). The effects on obesity probably suggest little to no difference (SMD -0.02, 95% CI -0.05 to 0.02; 8 RCTs, 18,618 participants; moderate-certainty evidence). The effects on tobacco use are very uncertain (SMD -0.03, 95% CIs -0.23 to 0.18; 3 RCTs, 3635 participants; very low-certainty evidence). One RCT assessed measures of student alcohol use and found strategies to support implementation may result in a slight increase in use (odds ratio 1.10, 95% CI 0.77 to 1.56; P = 0.60; 2105 participants). Few trials reported the economic evaluations of implementation strategies, the methods of which were heterogeneous and evidence graded as very uncertain. A lack of consistent terminology describing implementation strategies was an important limitation of the review.

Authors' conclusions: The use of implementation strategies may result in large increases in implementation of interventions, and slight improvements in measures of student diet, and physical activity. Further research is required to assess the impact of implementation strategies on such behavioural- and obesity-related outcomes, including on measures of alcohol use, where the findings of one trial suggest it may slightly increase student risk. Given the low certainty of the available evidence for most measures further research is required to guide efforts to facilitate the translation of evidence into practice in this setting.

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Conflict of interest statement

Some members of the review team are currently undertaking a series of randomised trials aiming to facilitate the implementation of healthy eating and physical activity policies and practices by schools (LW, CB, KO, NN, RS, RH, CW, SLY). Authors LW, NN, RS, SLY, RH, and CMW are authors on one or more of the trials conducted in Australia. For such trials, eligibility, data extraction, risk of bias assessment and GRADE assessment were carried out by review authors who were not directly involved in these studies, this is in line with the Cochrane Conflict of Interests Policy. The authors have not received any benefit, in cash or kind, any hospitality, or any subsidy derived from any source perceived to have an interest in the outcome of the review. All authors have contributed to the development of evaluation of trials examining the impact of implementation strategies in community settings, including those conducted in schools. LW is Co‐ordinating Editor, SMc is Assistant Managing Editor and Method Editor, and KO is a Method Editor for Cochrane Public Health. LW, SMc and KO were not involved in any stage of the editorial management or assessment of this review.

LW: no other conflicts of interest.

SMc: no other conflicts of interest.

CB: no other conflicts of interest.

KO: no other conflicts of interest.

KN: no other conflicts of interest.

NN: no other conflicts of interest.

RS: no other conflicts of interest.

RH: no other conflicts of interest.

FT: no other conflicts of interest.

EN: no other conflicts of interest.

CMW: no other conflicts of interest.

SLY: no other conflicts of interest.

Figures

1
1
Study flow diagram.
2
2
Risk of bias summary: review authors' judgements about each risk of bias item for each included study.
3
3
Risk of bias graph: review authors' judgements about each risk of bias item presented as percentages across all included studies.
4
4
Forest plot of primary outcome (implementation).
5
5
Funnel plot for primary outcome (implementation).
6
6
Sensitivity analysis – standardised mean difference between implementation and control groups in implementation trials, excluding trials with a high risk of bias.
7
7
Sensitivity analysis – standardised mean difference between implementation and control groups in implementation trials, with effective sample size calculated using an intracluster correlation coefficient of 0.01.
8
8
Sensitivity analysis – Standardised mean difference between implementation and control groups in implementation trials, with effective sample size calculated using an intracluster correlation coefficient of 0.05.
9
9
Standardised mean difference between intervention and control groups in implementation trials.
10
10
Funnel plot – Standardised mean difference between intervention and treatment groups in implementation trials by standard error.
11
11
Standardised mean difference between intervention and treatment groups in implementation trials, grouped by target behaviour.
12
12
Funnel plot for secondary outcome (nutrition).
1.1
1.1. Analysis
Comparison 1: Primary outcome, Outcome 1: Implementation
2.1
2.1. Analysis
Comparison 2: Secondary outcomes, Outcome 1: Nutrition
2.2
2.2. Analysis
Comparison 2: Secondary outcomes, Outcome 2: Physical activity
2.3
2.3. Analysis
Comparison 2: Secondary outcomes, Outcome 3: Obesity
2.4
2.4. Analysis
Comparison 2: Secondary outcomes, Outcome 4: Tobacco
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References

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Yoong 2016 {published data only}
    1. Reilly KL, Reeves P, Deeming S, Yoong SL, Wolfenden L, Nathan N, et al. Economic analysis of three interventions of different intensity in improving school implementation of a government healthy canteen policy in Australia: costs, incremental and relative cost effectiveness. BMC Public Health 2018;18:378. - PMC - PubMed
    1. Williams CM, Nathan N, Delaney T, Yoong SL, Wiggers J, Preece S. CAFÉ: a multicomponent audit and feedback intervention to improve implementation of healthy food policy in primary school canteens: protocol of a randomised controlled trial. BMJ Open 2015;5(6):e006969. - PMC - PubMed
    1. Yoong SL, Nathan N, Wolfenden L, Wiggers J, Reilly K, Oldmeadow C. CAFÉ: a multicomponent audit and feedback intervention to improve implementation of healthy food policy in primary school canteens: a randomised controlled trial. International Journal of Behavioral Nutrition and Physical Activity 2016;13(1):126. - PMC - PubMed
Young 2008 {published data only}
    1. Elder JP, Lytle L, Sallis JF, Young DR, Steckler A, Simons-Morton D. A description of the social–ecological framework used in the Trial of Activity for Adolescent Girls (TAAG). Health Education Research 2007;22(2):155-65. - PMC - PubMed
    1. Elder JP, Shuler L, Moe SG, Grieser M, Pratt C, Cameron S. Recruiting a diverse group of middle school girls into the trial of activity for adolescent girls. Journal of School Health 2008;78(10):523-31. - PMC - PubMed
    1. Stevens J, Murray DM, Catellier DJ, Hannan PJ, Lytle LA, Elder JP, et al. Design of the Trial of Activity in Adolescent Girls (TAAG). Contemporary Clinical Trials 2005;26(2):223-33. - PMC - PubMed
    1. Webber LS, Catellier DJ, Lytle LA, Murray DM, Pratt CA, Young DR, et al. Promoting physical activity in middle school girls: Trial of Activity for Adolescent Girls. American Journal of Preventive Medicine 2008;34(3):173-84. - PMC - PubMed
    1. Young DR, Steckler A, Cohen S, Pratt C, Felton G, Moe SG. Process evaluation results from a school-and community-linked intervention: the Trial of Activity for Adolescent Girls (TAAG). Health Education Research 2008;23(6):976-86. - PMC - PubMed

References to studies excluded from this review

ACTRN12619000431123 {published data only}
    1. ACTRN12619000431123. A technology-based program to promote healthy lifestyles among secondary school students. trialsearch.who.int/Trial2.aspx?TrialID=ACTRN12619000431123 (first received 18 March 2019). [ACTRN ID: 12619000431123]
Cunningham‐Sabo 2016 {published data only}
    1. Cunningham-Sabo L, Lohse B, Smith S, Browning R, Strutz E, Nigg C, et al. Fuel for Fun: a cluster-randomized controlled study of cooking skills, eating behaviors, and physical activity of 4th graders. BMC Public Health 2016;16:444. - PMC - PubMed
Hodder 2012 {published data only}
    1. Hodder RK, Freund M, Bowman J, Wolfenden L, Campbell E, Wye P, et al. A cluster randomised trial of a school-based resilience intervention to decrease tobacco, alcohol and illicit drug use in secondary school students: study protocol. BMC Public Health 2012;12:1009. - PMC - PubMed
Hoelscher 2001 {published data only}
    1. Hoelscher DM, Kelder SH, Murray N, Cribb PW, Conroy J, Parcel GS. Dissemination and adoption of the Child and Adolescent Trial for Cardiovascular Health (CATCH): a case study in Texas. Journal of Public Health Management & Practice 2001;7(2):90-100. - PubMed
Hoelscher 2003 {published data only}
    1. Hoelscher DM, Mitchell P, Dwyer J, Elder J, Clesi A, Snyder P. How the CATCH Eat Smart Program helps implement the USDA regulations in school cafeterias. Health Education & Behavior 2003;30(4):434-46. - PubMed
Hoelscher 2004 {published data only}
    1. Hoelscher DM, Feldman HA, Johnson CC, Lytle LA, Osganian SK, Parcel GS, et al. School-based health education programs can be maintained over time: results from the CATCH Institutionalization study. Preventive Medicine Reports 2004;38(5):594-606. - PubMed
Hoelscher 2016 {published data only}
    1. Hoelscher D, Ory M, Dowdy D, Miao J, Atteberry H, Nichols D, et al. Effects of funding allocation for Safe Routes to School programs on active commuting to school and related behavioral, knowledge, and psychosocial outcomes: results from the Texas Childhood Obesity Prevention Policy Evaluation (T-COPPE) study. Environment and Behavior 2016;48(1):210-29.
ISRCTN11867516 {published data only}
    1. ISRCTN11867516. Chinese primary school children physical activity and dietary behaviour changes intervention (CHIRPY DRAGON Study). trialsearch.who.int/Trial2.aspx?TrialID=ISRCTN11867516 (first received 25 August 2015).
ISRCTN61188203 {published data only}
    1. ISRCTN61188203. Active Programme Promoting Lifestyle Education. trialsearch.who.int/Trial2.aspx?TrialID=ISRCTN61188203 (first received 23 January 2004).
Kajons 2018 {published data only}
    1. Kajons N, David M, Gowland-Ella J, Lewis P, Batchelor S. Thirsty? Choose Water! Behavioural interventions and water stations in secondary schools a two-by-two factorial. BMC Public Health 2018;18(788):1-7. - PMC - PubMed
Kelder 2003 {published data only}
    1. Kelder SH, Mitchell PD, McKenzie TL, Derby C, Strikmiller PK, Luepker RV, et al. Long-term implementation of the Catch Physical Education Program. Health Education & Behavior 2003;30(4):463-75. - PubMed
Kim 2012 {published data only}
    1. Kim K, Hong SA, Yun SH, Ryou HJ, Lee SS, Kim MK. The effect of a healthy school tuck shop program on the access of students to healthy foods. Nutrition Research & Practice 2012;6(2):138-45. - PMC - PubMed
Li 2010 {published data only}
    1. Li Y, Hu X, Zhang Q, Liu A, Fang H, Hao L, et al. The nutrition-based comprehensive intervention study on childhood obesity in China (NISCOC): a randomised cluster controlled trial. BMC Public Health 2010;10:229. - PMC - PubMed
Li 2014 {published data only}
    1. Li XH, Lin S, Guo H, Huang Y, Wu L, Zhang Z, et al. Effectiveness of a school-based physical activity intervention on obesity in school children: a nonrandomized controlled trial. BMC Public Health 2014;14:1282. - PMC - PubMed
Lubans 2005 {published data only}
    1. Lubans DR. Promoting Physical Activity in the Secondary School Setting: Evaluation of the Lifetime Activity Programme [Doctoral thesis]. Ann Arbor: University of Oxford (UK), 2005.
Lubans 2010 {published data only}
    1. Lubans D, Morgan P, Aguiar E, Callister R. Randomised controlled trial of the Physical Activity Leaders (PALs) program for low-active adolescent boys from disadvantaged secondary schools. Journal of Science and Medicine in Sport 2010;13:12. - PubMed
Lubans 2014 {published data only}
    1. Lubans D, Cohen K, Plotnikoff R, Callister R, Morgan P. The SCORES physical activity intervention for children attending schools in low-income communities: a cluster RCT. Journal of Science and Medicine in Sport 2014;18:121.
Lubans 2015 {published data only}
    1. Lubans D, Smith J, Morgan P, Beauchamp M, Miller A, Lonsdale C, et al. Improving muscular fitness enhances psychological well-being in low-income adolescent boys: findings from the ATLAS cluster RCT. Journal of Science and Medicine in Sport 2015;19:75.
NCT00061165 {published data only}
    1. NCT00061165. Obesity prevention in African American school children. clinicaltrials.gov/ct2/show/nct00061165 (first received 23 May 2003).
Osganian 2003a {published data only}
    1. Osganian SK, Parcel GS, Stone EJ. Introduction. Institutionalization of a school health promotion program: background and rationale of the CATCH-ON study. Health Education & Behavior 2003;30(4):410-7. - PubMed
Prell 2005 {published data only}
    1. Prell HC, Berg MC, Jonsson LM, Lissner L. A school-based intervention to promote dietary change. Journal of Adolescent Health 2005;36(6):529-30. - PubMed
Rissel 2012 {published data only}
    1. Rissel C, Laws R, St George A, Hector D, Milat AJ, Baur LA. Research to practice: application of an evidence building framework to a childhood obesity prevention initiative in New South Wales. Health Promotion Journal of Australia 2012;23(1):16-24. - PubMed
Rosario 2013 {published data only}
    1. Rosario R, Araujo A, Oliveira B, Padrao P, Lopes O, Teixeira V, et al. Impact of an intervention through teachers to prevent consumption of low nutrition, energy-dense foods and beverages: a randomized trial. Preventive Medicine 2013;57(1):20-5. - PubMed
Rosario 2016 {published data only}
    1. Rosário R, Araújo A, Padrão P, Lopes O, Moreira A, Abreu S. Impact of a school-based intervention to promote fruit intake: a cluster randomized controlled trial. Public Health 2016;136:94-100. - PubMed
Rosenbaum 2007 {published data only}
    1. Rosenbaum M, Nonas C, Weil R, Horlick M, Fennoy I, Vargas I, et al. School-based intervention acutely improves insulin sensitivity and decreases inflammatory markers and body fatness in junior high school students. Journal of Clinical Endocrinology & Metabolism 2007;92(2):504-8. - PubMed
Rosenkranz 2012 {published data only}
    1. Rosenkranz RR, Lubans DR, Peralta LR, Bennie A, Sanders T, Lonsdale C. A cluster-randomized controlled trial of strategies to increase adolescents' physical activity and motivation during physical education lessons: the Motivating Active Learning in Physical Education (MALP) trial. BMC Public Health 2012;12:834. - PMC - PubMed
Rothwell 2011 {published data only}
    1. Rothwell H, Segrott J. Preventing alcohol misuse in young people aged 9-11 years through promoting family communication: an exploratory evaluation of the Kids, Adults Together (KAT) Programme. BMC Public Health 2011;11:810. - PMC - PubMed
Rowlands 2008 {published data only}
    1. Rowlands A, Esliger DW, Pilgrim EL, Middlebrooke AR, Eston RG. Physical activity content of Motive8 PE compared to primary school PE lessons in the context of children's overall daily activity levels. Journal of Obesity 2008;6:1-8.
Rozi 2019 {published data only}
    1. Rozi S, Zahid N, Roome T, Lakhdir MP, Sawani S, Razzak A, et al. Effectiveness of a school based smokeless tobacco intervention: a cluster randomized trial. Journal of Community Health 2019;44(6):1098-110. - PubMed
Ruzita 2007 {published data only}
    1. Ruzita AT, Wan Azdie M, Ismail M. The effectiveness of nutrition education programme for primary school children. Malaysian Journal of Nutrition 2007;13(1):45-54. - PubMed
Sallis 2003 {published data only}
    1. Sallis JF, McKenzie TL, Conway TL, Elder JP, Prochaska JJ, Brown M, et al. Environmental interventions for eating and physical activity: a randomized controlled trial in middle schools. American Journal of Preventive Medicine 2003;24(3):209-17. - PubMed
Salmon 2005 {published data only}
    1. Salmon J, Ball K, Crawford D, Booth M, Telford A, Hume C, et al. Reducing sedentary behaviour and increasing physical activity among 10-year-old children: overview and process evaluation of the 'Switch-Play' intervention. Health Promotion International 2005;20(1):7-17. - PubMed
Singhal 2010 {published data only}
    1. Singhal N, Misra A, Shah P, Gulati S. Effects of controlled school-based multi-component model of nutrition and lifestyle interventions on behavior modification, anthropometry and metabolic risk profile of urban Asian Indian adolescents in North India. European Journal of Clinical Nutrition 2010;64(4):364-73. - PubMed
Sirikulchayanonta 2011 {published data only}
    1. Sirikulchayanonta C, Pavadhgul P, Chongsuwat R, Klaewkla J. Participatory action project in reducing childhood obesity in Thai primary schools. Asia-Pacific Journal of Public Health 2011;23(6):917-27. - PubMed
Smith 2001 {published data only}
    1. Smith KW, Hoelscher DM, Lytle LA, Dwyer JT, Nicklas TA, Zive MM, et al. Reliability and validity of the Child and Adolescent Trial for Cardiovascular Health (CATCH) Food Checklist: a self-report instrument to measure fat and sodium intake by middle school students. Journal of the American Dietetic Association 2001;101(6):635-47. - PubMed
Smith 2015 {published data only}
    1. Smith NJ, Monnat SM, Lounsbery MA. Physical activity in physical education: are longer lessons better? Journal of School Health 2015;85(3):141-8. - PMC - PubMed
Somsri 2016 {published data only}
    1. Somsri P, Satheannoppakao W, Tipayamongkholgul M, Vatanasomboon P, Kasemsup R. A cosmetic content-based nutrition education program improves fruit and vegetable consumption among grade 11 Thai students. Journal of Nutrition Education & Behavior 2016;48(3):190-8. - PubMed
Sutherland 2016 {published data only}
    1. Sutherland R, Campbell E, Lubans DR, Morgan PJ, Okely AD, Nathan N. 'Physical Activity 4 Everyone' school-based intervention to prevent decline in adolescent physical activity levels: 12 month (mid-intervention) report on a cluster randomised trial. British Journal of Sports Medicine 2016;50(8):488-95. - PMC - PubMed
Uys 2016 {published data only}
    1. Uys M, Draper CE, Hendricks S, Villiers A, Fourie J, Steyn NP, et al. Impact of a South African school-based intervention, HealthKick, on fitness correlates. American Journal of Health Behavior 2016;40(1):55-66. - PubMed
Velicer 2007 {published data only}
    1. Velicer WF, Redding CA, Anatchkova MD, Fava JL, Prochaska JO. Identifying cluster subtypes for the prevention of adolescent smoking acquisition. Addictive Behaviors 2007;32(2):228-47. - PubMed
Vetter, 2015 {published data only}
    1. Vetter, O'Connor H, O'Dwyer N, Orr R. Active learning: effectiveness of learning a numeracy skill with physical activity, reducing sedentary time in school children. Journal of Science and Medicine in Sport 2015;19:12.
Veugelers 2005 {published data only}
    1. Veugelers PJ, Fitzgerald AL. Effectiveness of school programs in preventing childhood obesity: a multilevel comparison. American Journal of Public Health 2005;95(3):432-5. - PMC - PubMed
Viggiano 2015 {published data only}
    1. Viggiano A, Viggiano E, Di Costanzo A, Viggiano A, Andreozzi E, Romano V, et al. Kaledo, a board game for nutrition education of children and adolescents at school: cluster randomized controlled trial of healthy lifestyle promotion. European Journal of Pediatrics 2015;174(2):217-28. - PubMed
Volpe 2013 {published data only}
    1. Volpe SL, Hall WJ, Steckler A, Schneider M, Thompson D, Mobley C, et al. Process evaluation results from the HEALTHY nutrition intervention to modify the total school food environment. Health Education Research 2013;28(6):970-8. - PMC - PubMed
Wang 2015 {published data only}
    1. Wang D, Stewart D, Yuan Y, Chang C. Do health-promoting schools improve nutrition in China? Health Promotion International 2015;30(2):359-68. - PubMed

References to ongoing studies

Fernandez‐Jimenez 2019 {published data only}
    1. Fernandez-Jimenez R, Santos-Beneit G, Tresserra-Rimbau A, Bodega P, Miguel M, Cos-Gandoy A, et al. Rationale and design of the school-based SI! Program to face obesity and promote health among Spanish adolescents: a cluster-randomized controlled trial. American Heart Journal 2019;215:27-40. - PubMed
Haible 2019 {published data only}
    1. Haible S, Volk C, Demetriou Y, Honer O, Thiel A, Trautwein U, et al. Promotion of physical activity-related health competence in physical education: study protocol for the GEKOS cluster randomized controlled trial. BMC Public Health 2019;19(1):396. - PMC - PubMed
Liu 2019b {published data only}
    1. Liu Z, Wu Y, Niu WY, Feng X, Lin Y, Gao A, et al. A school-based, multi-faceted health promotion programme to prevent obesity among children: protocol of a cluster-randomised controlled trial (the DECIDE-Children study). BMJ Open 2019;9(11):e027902. - PMC - PubMed
Lonsdale 2016 {published data only}
    1. Lonsdale C, Sanders T, Cohen KE, Parker P, Noetel M, Hartwig T. Scaling-up an efficacious school-based physical activity intervention: study protocol for the 'Internet-based Professional Learning to help teachers support Activity in Youth' (iPLAY) cluster randomized controlled trial and scale-up implementation evaluation. BMC Public Health 2016;16(1):873. - PMC - PubMed
Nathan 2019a {published data only}
    1. ACTRN12617001265369. A randomised trial of an intervention to facilitate the implementation of scheduled physical activity in NSW primary schools. www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=373520 (first received 24 August 2017).
Nathan 2019b {published data only}
    1. ACTRN12619001229167. Preparing an effective school-based physical activity implementation strategy for scale-up: a randomized noninferiority trial. anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378086 (first received 31 July 2019).
Nathan 2020a {published data only}
    1. Nathan N. A randomised trial of an intervention to sustain primary schools’ implementation of a state-wide physical activity policy. www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378735 (first received 9 March 2020).
Randby 2019 {published data only}
    1. ISRCTN12683953. An implementation intervention to increase adherence to the Norwegian school food guideline. www.isrctn.com/ISRCTN12683953 (first received 7 July 2019).
Sutherland 2019 {published data only}
    1. Mclaughlin M, Duff J, Sutherland R, Campbell E, Wolfenden L, Wiggers J. Protocol for a mixed methods process evaluation of a hybrid implementation-effectiveness trial of a scaled-up whole-school physical activity program for adolescents: Physical Activity 4 Everyone (PA4E1). Trials 2020;21:268. - PMC - PubMed
    1. Sutherland R, Campbell E, Nathan N, Wolfenden L, Lubans DR, Morgan PJ, et al. A cluster randomised trial of an intervention to increase the implementation of physical activity practices in secondary schools: study protocol for scaling up the Physical Activity 4 Everyone (PA4E1) program. BMC Public Health 2019;19(1):883. - PMC - PubMed
Welk 2019 {published data only}
    1. NCT04045288. SWITCH Implementation Effectiveness Trial. clinicaltrials.gov/ct2/show/NCT04045288 (first received 5 August 2019).
Wyse 2019 {published data only}
    1. Leonard A, Delaney T, Seward K, Zoetemeyer R, Lamont H, Sutherland R, et al. Investigating differences between traditional (paper bag) ordering and online ordering from primary school canteens: a cross-sectional study comparing menu, usage and lunch order characteristics. Public Health Nutrition 2020;Oct:1-10. [DOI: doi: 10.1017/S1368980020003559] - PMC - PubMed
    1. Wyse R, Delaney T, Gibbins P, Ball K, Campbell K, Yoong SL, et al. Cluster randomised controlled trial of an online intervention to improve healthy food purchases from primary school canteens: a study protocol of the 'Click & Crunch' trial. BMJ Open 2019;9(9):e030538. - PMC - PubMed
Zoellner 2019 {published data only}
    1. Zoellner JM, Porter KJ, You W, Chow PI, Ritterband LM, Yuhas M, et al. Kids SIPsmartER, a cluster randomized controlled trial and multi-level intervention to improve sugar-sweetened beverages behaviors among Appalachian middle-school students: rationale, design & methods. Contemporary Clinical Trials 2019;83:64-80. - PMC - PubMed

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