https://orcid.org/0000-0003-4440-4798
Figures
Abstract
Introduction
This paper presents the protocol for the effectiveness-implementation trial: Systems Thinking with Active Implementation Research (STAIR) for childhood obesity prevention. STAIR’s objective is to protect primary school children in Victoria, Australia from unhealthy weight and test implementation strategies for sustaining healthy school environments. STAIR is a 3-year cluster-randomised controlled trial with repeat-cross-sectional child-level data collection utilising an effectiveness-implementation type-1 hybrid design. Schools will be recruited from non-metropolitan government primary schools in Southwest Victoria, Australia, with consenting schools (target = 28) randomly assigned (1:1) to intervention or control, and students in grades 1–6 (n = 3000–6000) recruited using an opt-out approach.
Intervention
The intervention, co-designed by each school community, will involve multi-step group model building and action formulation process using community-based systems dynamics and baseline data (i.e., child weight status, HRQoL, health behaviours, and school environment characteristics). Implementation strategies will be guided by an active implementation framework, and coordinated by a leadership team of school representatives, community partners, and researchers.
Primary and secondary outcome measures
Primary outcomes are to measure (1) change in standardised body mass index (z-BMI) between intervention and control groups after three year and (2) change in acceptance and adoption of STAIR interventions and support. Secondary outcomes include differences in obesity prevalence, health behaviour measures and HRQoL, between intervention and control groups after three years. Implementation outcomes will focus on strategy effectiveness, acceptability, and utilisation. Secondary data will be collected from schools and partner organisations. An economic evaluation will assess the cost-effectiveness of intervention and implementation support.
Conclusion
STAIR aims to create lasting changes in schools to prevent childhood obesity by supporting healthy environments and providing insights into interventions’ cost-effectiveness and feasibility. The findings will guide policymakers and educational institutions in adopting sustainable health promotion strategies.
Citation: Jackson M, Whelan J, Allender S, Wolfenden L, Nichols M, Brown V, et al. (2025) Systems thinking with active implementation research (STAIR): Protocol for a school-based randomised control trial for childhood obesity prevention. PLoS One 20(6): e0325853. https://doi.org/10.1371/journal.pone.0325853
Editor: Jennifer Tucker, PLOS: Public Library of Science, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
Received: April 29, 2025; Accepted: May 6, 2025; Published: June 24, 2025
Copyright: © 2025 Jackson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: DATA AVAILABILITY In line with the National Statement on Ethical Conduct in Human Research 2023, deidentified data from STAIR will be shared with other potential users (those conducting epidemiological studies in the general area of research) at the unit record level (where numbers are sufficient) and school level with information on condition (intervention or control), when the study is completed and published.
Funding: National Health and Medical Research Council (NHMRC) Partnership Grant - Australia. Please refer to the attached letter.
Competing interests: The authors have declared that no competing interests exist.
Provenance: Not commissioned; externally peer reviewed.
Introduction
The case for action to prevent childhood obesity is compelling [1]. One in 4 children in Australia experience overweight or obesity. Prevalence has steadily increased from the 1980s to the 2000s and is unequally distributed socio-economically and geographically [2]. Children with obesity are stigmatised because of their weight, have a lower quality of life [1,3], have lower mastery of movement skills, and have more physical and psychosocial disability than their healthy-weight peers [4–6]. Unhealthy diets and insufficient physical activity are risk factors for child obesity, and obesity itself, endures into adulthood, putting children with obesity at risk of chronic diseases, such as type 2 diabetes, later in life [7,8]. Furthermore, adults living with obesity experience higher medical expenses, discrimination, and worse jobs [9]. Living with obesity is the leading contributor to the burden of disease in Australia, and the total cost was estimated at $1280 (US$940) per capita in 2019 [10]. Reviews of strategies for managing and treating obesity in childhood indicate they have limited effectiveness and can be costly and invasive [11–13].
The UN Convention on the Rights of the Child indicates that ‘children have the right to the best health care possible, clean water to drink, healthy food and a clean and safe environment to live in’ [14]. Interventions have been implemented in different settings including schools to create a healthy and safe environment. The most recent Cochrane review on childhood obesity prevention found changing diet and activity levels, particularly in school settings, can be effective in reducing standardised BMI scores in children aged 6–12 years [15]. The review acknowledged that the complex and dynamic determinants of childhood obesity require a systems approach involving interventions targeted at different parts of the system, leading to coordinated policy initiatives across various government departments [16].
In Australia, the national obesity prevention strategy has adopted such an approach [17], and our group has contributed to evidence of effectiveness. The research team’s latest trials (WHO STOPS, 2015–2019) [18] and (RESPOND 2019–2024) [19], drew on community-based systems dynamics to co-develop intervention actions, in line with recommendations from the Lancet Commission on the Global Syndemic of Obesity, Undernutrition, and Climate Change [20]. Community-based systems dynamics offers significant advantages over earlier approaches to intervention design by providing a communal and visualised understanding of local causes of childhood obesity and the complex interactions between them, and by achieving community proprietorship of and engagement in, prevention strategies [21]. It enhances rather than replaces existing activities and communities can identify and intervene in elements of the system where they can have the most impact. The WHO STOPS study achieved a 4% reduction in overweight and obesity prevalence and improved health-related quality of life (HRQoL) in intervention communities compared to no change in controls in the first two years of the trial [22]. However, while HRQoL and dietary changes were sustained after 4-years, weight status changes, which were similar in magnitude to other studies [15] were not. Other community-based interventions have also seen intervention effects on weight dissipate over time [23], and we think the reason is waning implementation support.
A recent systematic review identified ten characteristics for sustained implementation of community-based interventions, including leadership, workforce development, community engagement, partnerships, communication, policy, adaption, evaluation, resourcing, and governance. In WHO STOPS, the two-year time point coincided with a reduction in support from the research team (removal of trained staff available to support implementation) [18]. We hypothesised that this reduction in implementation support was the primary reason the intervention effect was not sustained as community capacity was low (e.g., too few staff, competing priorities). An unpublished audit conducted by the research team among rural-based communities, including WHO STOPS [24] and RESPOND [25] communities, revealed that rural prevention services were understaffed in Victoria, with only 1.4 full-time equivalents for every 10,000 people. For comparison, Australia has 37 doctors for every 10,000 people. Further, support available to schools in Victoria is largely online. Wolfenden et al identified that the complexity of the environment the community-based health service partners operate in is not well understood (size and diversity of the workforce, types and levels of training; mix of public and private organisations involved; mix of local, state and federal governance and funding structures) [26]. These implementation factors are also poorly measured, in part because researchers haven’t known what to measure. Collectively these observations reveal a tension between the expectations of researchers and policymakers on communities and their capacity to implement interventions, coupled with a scarcity of data on implementation [27].
In the face of low implementation capacity and competing priorities (such as responding to COVID-19) and increasingly obesogenic environments (such as advertising of unhealthy food) [28,29] we contend that communities, and particularly schools, need implementation support to sustain healthy environments. Working with school communities rather than whole communities may help focus implementation support and minimise competing priorities. Also, the Lancet Commission encourages greater application of expert-facilitated (not owned) implementation [20]. Our research has demonstrated it is possible to create environments that protect children from obesity and others have shown that healthy weight can persist after children have participated in school-based interventions [30,31]. However, there is a paucity of research exploring whether system-wide changes to school environments can be sustained so that successive cohorts of children are protected from unhealthy weight gain.
The primary objective of this study is to protect primary school children in rural Victoria, Australia, from unhealthy weight and test implementation strategies for sustaining school environments that promote health and wellbeing. The research questions being addressed in this study are: (1) can Victorian school communities be supported to prevent unhealthy weight gain for 3 years and; (2) what are the optimal implementation strategies to support delivery and maintenance of the intervention in schools? It is hypothesised: (1) a reduction of 0.13 units in z-BMI will be achieved in intervention schools relative to controls after 3 years of intervention and; (2) that implementation strategies will be cost-effective, acceptable, utilised, appropriate, feasible, delivered as intended and maintained in intervention schools.
Methods and analysis
Conceptual framework
Obesity prevention research is at the point where substantial knowledge about how to prevent childhood obesity is available but where that knowledge is not applied in practice [32]. The Interactive Systems Framework (ISF) was designed to facilitate the dissemination and implementation of such prevention knowledge. Given the gaps identified in implementation support for previous interventions, we used ISF to conceptualise a prevention support system (Fig 1). Obesity prevention will be the innovation we intend to disseminate and implement, school communities will be the prevention delivery system, and the research team will be the prevention synthesis and translation system (Fig 1). Trial partners, named below, are key stakeholders in this system. STAIR intends to strengthen prevention support and delivery systems (capacity in schools and among partners). Researchers in the field of applied implementation science have recognised the need to help communities translate prevention into practice and have developed frameworks and strategies to support this [33,34]. STAIR will use the Active Implementation Framework developed by Fixsen [35] to support schools so intended prevention outcomes (healthy weight, HRQoL) will be achieved and sustained. This framework was chosen as it emphasises system-wide change, active problem-solving, and on-going learning. It defines for the trial an executive and sponsorship function, a cross-system leadership team to coordinate and build overweight/obesity prevention capacity and quality, and outcome monitoring functions to ensure delivery of intended outcomes [36]. To complete the conceptual framework, we will place group model building (GMB), the co-design process from community-based systems dynamics [37], at the centre. Students, staff, and partners, will map the causes of childhood overweight/obesity and identify solutions and implementation strategies using GMB.
Ethics and dissemination
Approval has been obtained from the Deakin University Human Research Ethics Committee (ID: 2024_051) and the Victorian Government Department of Education and Training (ID: 24-02-254). We had intended to recruit from Government and Catholic schools, but the Diocese of Ballarat Catholic Education Office did not approve the project, citing that the project did not align with the Diocese’s priorities, so we are continuing this study using Government schools.
Partnerships and funding
STAIR is funded by the Australian National Health and Medical Research Council’s (NHMRC) Partnership Project Research Grant scheme (GNT2023737), supplemented by additional financial and in-kind contributions from four partner organisations who are signatories to the grant. Partners include Deakin University (sponsor), the Victorian Government Department of Education, the Royal Flying Doctor Service, VicHealth and the Victorian Government Department of Health.
Trial design and status
The STAIR project, conducted over five years with three intervention years, will comprise a cluster randomised controlled trial with repeat-cross sectional data collection, utilising an effectiveness-implementation type-1 hybrid design. Fig 2 shows the Standard Protocol Items: Recommendations for Intervention Trial (SPIRIT) schedule of enrolment, interventions, and assessments along with timelines (S1 Fig).
Participant recruitment and data collection have not begun. School recruitment for this study is planned to commence on 28/04/2025.
Setting and recruitment
All government primary schools in southwest education region of Victoria excluding schools in the Brimbank, Melton and Western Melbourne education areas, schools participating in other overweight/obesity prevention interventions (as advised by Victorian Government Department of Education and Training), schools with fewer than 120 children and schools exclusively educating children with special needs will be eligible to participate in the trial. A randomly sorted list of all eligible Government schools (n = 97) will be generated using a random selection without replacement. Starting at the top of the list, school principals will be contacted by the research team, provided with information about the study and invited to provide written informed consent. Up to three follow-up phone calls and/or in-person visits will made to gain consent before moving on to the next school on the list. Recruitment will continue until 28 schools have consented (assuming a 33% recruitment rate). Previous studies in the region suggest school participation rates of 70% and student participation >80% [18].
Randomisation and blinding procedure
After the full sample of schools is recruited schools will be randomly allocated (1:1), to intervention or control groups within strata defined by size (student enrolment ≥120). The study statistician will produce the random sequences and allocation will occur simultaneously for all schools. Given the nature of the intervention, it will be impossible to conceal the allocation from the school communities. However, data analysts will be blind to intervention allocation by removing school identification data.
Children
The research team will visit all participating schools to give a brief presentation about the study to students in grades 1–6 (ages 6–12). They will distribute a plain language statement and an opt-out form for students to take home to their parents/guardians. Students will be included in data collection unless they or their parent/guardian actively opt-out. Surveys will be conducted at the start (baseline), and after the first, second, and third years of the intervention. All children present on the day of data collection who have not opted out will be eligible. Consequently, the composition of children included in each time point of data collection will vary, with some children being followed longitudinally, while others will not.
Intervention
Before the commencement of the intervention, the research team will collect data on child weight status (using anthropometry), HRQoL, dietary behaviours, physical activity and sedentary behaviours, oral health (due to common risk factors with overweight/obesity [38]), sleep, and the school environment. The intervention process (Table 1) will comprise a series of facilitated GMB workshops (1–3 hours each) where this baseline data, along with evidence of best practice [33], will be provided to intervention school stakeholders (student leaders, teachers, parents, community leaders (including health promotion officers, general practitioners, journalists, food retailers) and partners). Student leaders will be children in grades 5 and 6 (aged approximately 10–12 years) as the Australian curriculum expects children by the end of grade 4 to use problem-solving skills to select and demonstrate strategies that help them stay safe, healthy, and active. Together, stakeholders will describe and visualise the causes of childhood overweight/obesity for the whole school community using causal loop diagrams employing Systems Thinking in Community Knowledge Exchange (STICKE) software [39]. Workshops will culminate in the formulation of specific actions the school community will take to create a healthier environment [40]. Communities find these methods engaging, effective and they translated to action faster than traditional approaches [18]. In previous trials, actions such as walking to school programs and improving the taste of the local water supply have been implemented to improve physical activity, healthy eating, children’s knowledge, and broader social determinants [41].
Control
Control schools will receive the usual support available to Victorian schools including the Vic Kids Eat Well initiative introduced by the Victorian state health department [42] in 2022, aimed at establishing healthier food environments for children, along with the Victorian Healthy Schools Achievement Program [43]. This program is designed to aid schools in defining and attaining benchmarks related to healthy eating, physical activity, and mental well-being and may include health promotion support. Control schools will be provided with a written report summarising overweight/obesity prevalence, HRQoL, dietary behaviours, physical activity and sedentary behaviours, oral health, sleep, and the school environment at baseline, after each time-point of data collection, and at the end of the trial. At the end of the trial, they will also receive a report on the overall results of the STAIR trial and, should they wish to design their own intervention actions, access to the STICKE training modules and STICKE software.
Implementation
After formulating intervention actions in the third GMB workshop, the STAIR implementation process comprises further GMB workshops at each school that will map intervention actions to existing, and in the pipeline, community infrastructure and resources and Active Implementation Framework functions (Table 2). These functions include a cross-system leadership team (self-nominated school representatives, researchers, and executive leaders/sponsors), a school implementation team and strengthening practitioner competence/confidence as well as quality and outcome monitoring. This implementation process is designed to overcome low implementation capacity and competing priorities for schools. It will identify how intervention actions will be implemented (implementation strategies), who will be involved in managing and completing actions and, where resourcing and accountability for various functions sit. Strategy definitions will be guided by the ERIC taxonomy (Expert Recommendations for Implementing Change) [33], MS teams will be used for communication and to foster collective learning within and between intervention schools. GMB workshops will be used to facilitate active problem-solving and adaptive intervention/implementation strategies [44].
Outcomes
Primary intervention effectiveness outcomes.
The primary measure of intervention effectiveness will be the between-group difference in change over time from baseline to year 3 in childhood z-BMI score in repeat cross-sections of grade 1–6 children in intervention and control schools. Cross-sections will be used because we are measuring the effectiveness of the intervention on the school population and not on individual children. Anthropometric data will be collected at each school by trained members of the research team at baseline (pre GMB1), and after 1, 2 and 3 years (primary endpoint). Height (cm) will be measured using a Charder HM-200P stadiometer and weight (kg) using A&D UC-321 digital scales and BMI (kg/m2) will be calculated and compared to the WHO reference population [45].
Secondary intervention effectiveness outcomes.
Secondary outcomes include overweight/obesity prevalence of grade 1–6 children, captured at the same four time points, and health behaviours of children in grades 4–6 collected via a self-completed questionnaire on electronic tablets [Samsung Galaxy A9+]. Questionnaires will be completed by classes of children in one school period (~ 45 minutes). The questionnaire will ask about physical activity (self-reported time in moderate to vigorous physical activity, use of active transport to and from school), sedentary behaviour (self-reported screen time for entertainment), diet (intake of vegetables, fruit, water, takeaway foods, sweet snacks, savoury snack and sugar-sweetened beverages), oral health (brushing frequency, oral health, dental care access), sleep (self-reported usual sleep and wake times) and HRQoL (global, physical and psychosocial domains) using validated tools (Table 3) [22,25]. Demographic data will include age, gender, country of birth, and ethnicity. The Index of Community Socio-Educational Advantage (ICSEA) [46] will be used to describe children’s socioeconomic position.
School-level implementation outcomes.
Each year of the study, the school principal (or nominee) will be invited to complete a school environment audit questionnaire in Qualtrics about their school’s physical activity, healthy eating and well-being policies, practices (i.e., minutes/week devoted to formal physical education/organised sport, canteen menu) (Table 3). In addition, the questionnaire will be used to assess change in frequency, length and attendance numbers of committee meetings providing guidance on the development of policies and practices concerning physical activity, healthy eating, wellbeing and/or mobile phone use (Table 3).
Intervention cost-effectiveness.
An economic evaluation will be undertaken to determine whether the STAIR intervention represents ‘value for money’ as compared to usual practice [59]. Intervention costs (financial resources, human resources and equipment) will be estimated using action registers completed by school champions in MS Teams and published sources (including meeting minutes). A within-trial cost-consequence analysis will allow the assessment of intervention costs from the perspective of different stakeholders (schools, partners, limited societal) alongside effectiveness outcomes (primary and secondary outcomes). A modelled cost-utility analysis will extend the costs and effects of the trial over a longer time horizon and across a broader target population and decision context. The ACE-Obesity policy model, a multi-state life table Markov model will then be used to estimate the health benefits (HALYs) and healthcare cost-savings of diseases averted through reduced exposure to BMI because of the intervention [60]. Modelling results will include an assessment of cost-effectiveness using a return-on-investment ratio and costs saved based on healthcare cost-savings of diseases averted over the lifetime of the intervention population. Uncertainty will be incorporated using Monte Carlo simulation using the Ersatz software package [61], and sensitivity analyses will explore the impacts of varying key input parameters on overall cost-effectiveness results. The economic evaluation will follow the recommendations of the Second Panel on Cost-Effectiveness in Health and Medicine [62] and will be reported according to published guidance [63].
Implementation outcomes.
As schools will have varying implementation needs, the research team will use a multiple embedded case study design with the intervention school community (n = 14) as the unit of analysis to evaluate the implementation process [64]. Using indicators based on Proctor’s taxonomy of implementation outcomes [65], data will be gathered at baseline (after GMB3 and before GMB4) and after 1, 2, and 3 years (primary endpoint). Participants will be a convenience sample of representatives from the prevention system organisations in the intervention school communities (e.g., school champions, local government, health service, project partners, and researchers). For some outcomes, children will be the unit of analysis. Within group analysis of Implementation outcomes will determine if intervention school communities consider the STAIR implementation support to be effective (acceptable, adopted, appropriate, feasible) [65,66]. Table 4 summarises how and when these implementation outcomes will be measured. Indicators will be finalised with school communities using pragmatic decisions to determine which aspects of implementation will be evaluated and when [67]. Collectively, these outcomes, and a cost-consequence analysis that will disaggregate implementation costs and outcomes, will evaluate the effectiveness of the STAIR implementation process [65–67]. Implementation survey data will be gathered online (Qualtrics) [68] and from meeting minutes, causal loop diagrams and action registers. These will be complemented by key informant interviews analysed thematically in NVIVO.
Sample size calculations
Victorian Government Department of Education summary statistics compiled in 2023 indicate that, in the 21 regional and remote LGAs of the Southwestern Department of Education region (excluding schools on the geographical fringe of Melbourne in Brimbank, Melton, and Western Melbourne education areas), there were 57,828 children in primary schools. A total of 47,087 (81.4%) children attended the 147 eligible schools with an average of 320 students per school. By recruiting 28 schools and accounting for a 20% school dropout rate, it is anticipated that data will be collected across all time points (baseline, year 1, year 2 and year 3) in 22 schools. A sample of 22 schools, with approximately 200 participating students per school, will provide 83% power to detect a difference of 0.13 units in the primary outcome (z-BMI) between study groups; assuming z-BMI standard deviation 1.1 and intra-cluster correlation coefficient 0.02, as found in the WHO STOPS trial in a comparable population [22,70]. An effect size of 0.13 units in z-BMI it was shown to be achievable, using similar intervention methods, after 2 years in the WHO STOPS trial. Power was estimated using Shiny CRT calculator based on a cluster randomised parallel design with baseline measure, cross-sectional samples, and exchangeable correlation structure (α = 0.05) [71].
Statistical analysis
Students will be the unit of observation for effectiveness analyses and analyses will be conducted under the intention-to-treat principle. The effect of the STAIR intervention on the z-BMI will be assessed using a linear mixed model with study group, time (baseline, year 1, year 2, year 3), and the interaction group × time as fixed effects. School and student will be included as random effects to account for clustering of students within schools and repeated measures in students measured more than once). Secondary outcomes will be analysed by fitting a generalised linear mixed model with link and distribution selected according to the outcome distribution. Whether age modifies the intervention effect will be explored using the same modelling approach including additional interaction terms. The environmental audit, and implementation outcomes will be analysed at the school level using descriptive statistics and thematic analyses.
Data management
Data custodianship arrangements and rights of access, rights to analyse, use and re-use the data by Deakin University and the collaborating institutions is covered by the Multi-Institutional Agreement between participating institutions. Information obtained in connection with this research that can identify participants will remain confidential. All information provided will be used for research purposes only, it will be collected and kept in confidence and will not be released to anyone outside the study team. Hardcopies of data will be kept in locked facilities at Deakin University in accordance with government guidelines. Digital copies of data will be kept in a secure Deakin University server. Data will be added to a mediated access repository on a secure DEAKIN server until such time as it is requested by other potential users, at which point de-identified data will be transferred to the other researchers via Deakin University approved software.
All data collected from children will be disposed of after a minimum period of 15 years after the child reaches 18 years of age and all other data after a minimum period of 7 years from the last publication. Only members of the study team will have access to the data/records and the computer records will be password protected, to strict security standards. In any publication, presentation, or discussion the information will be provided in such a way that any child cannot be identified. The research team will not report individual child measurements. Results are reported at an aggregate level so no individual child can be identified. In reports back to schools and partners, the results are presented at an aggregate (e.g., Year 4 girls, All Year 6 children). The research team will not share individual-level data with any individual or agency other than the listed researchers on this paper (e.g., No individual-level data will be shared with a Partner Organisation, only summary reports at an aggregate level).
Safety considerations
It is recognised that participating in research may impact children’s safety, psychological security and wellbeing. The research team will take the following precautions to protect children’s safety, emotional and psychological health and wellbeing:
- Height and weight measurements will be taken in private measuring booths, so students cannot see one another, and their privacy is protected.
- All measurements will be taken in silence, the weight scale will be physically blocked from students’ view. Students are only told their height/weight measurements if they ask.
- All measurements are voluntary, and students can participate as much or as little as they like. Students are told on data collection days that overall participation and each component is voluntary even if an opt-out form has not been received. They can participate as much as they like (e.g., just do the questionnaire, just have their height measured). Prior to anthropometric measurements assent is sought with the student “Is it okay if I measure your height?”, “Is it okay that I measure your weight?”
- Researchers will look out for students that look uneasy, anxious or embarrassed and make rational decisions whether to measure the height and weight of these students. When such instances occur, data collectors either complete the measurement they are taking and skip the next one (e.g., finish measuring height and skip measuring weight) or direct the child to the next activity (e.g., questionnaire) or back to class.
- Each school is required to provide a registered teacher (typically the classroom teacher) to oversee measurements whilst researchers are present. School teachers will also look out for distressed students and notify the researchers if they think that participation would not be in the best interest of the child. If a schoolteacher thinks a child should not participate, the research team will not measure weight and height or complete the questionnaire.
- The research team will provide the number for support resources in the PLS
- All data collectors will have a current Victorian Working with Children’s Check or equivalent (e.g., Registered Teacher).
- All staff will be aware of obligations under the Victorian Child Safe Standards regarding mandatory reporting.
Timeline
Fig 2 shows the proposed timeline for the project. Due to delays in obtaining approval from the Department of Education, the project has been delayed and as such no data has been collected. It is anticipated data collection will begin in April 2025 and final data will be available in 2029.
Reporting and dissemination
This protocol and results will be reported following the CONSORT statement for reporting cluster randomised controlled trials, the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist for reporting the economic evaluation and, the Standards for Reporting Implementation Studies (StaRI) statement.
After each round of data collection, schools and partners will be provided with co-designed presentations and reports to keep them informed of progress and outcomes. The results of STAIR will also be disseminated via academic publications, conference presentations, and publications linked to postgraduate research projects.
Discussion
Ending childhood obesity is a global and national priority [2]. STAIR will be the first real-world study to combine systems thinking concepts for co-designing intervention strategies with active implementation strategies to help schools sustain them. It aligns with children’s right to health and is based on the best available evidence for effective obesity prevention [15]. Furthermore, by measuring the impact of intervention strategies on a range of health outcomes of relevance to Australian children (such as HRQoL, physical activity and oral health), we are recognizing that interventions can and should perform multiple duties [72]. As such, outcomes will add to existing knowledge on what intervention actions work, by providing evidence on how to implement overweight/obesity prevention strategies, who is responsible for the implementation strategies, where accountability for implementation sits and how much the anticipated health gains will cost [73]. Collectively these outcomes will provide school communities, partners and government with direct insight into how to prevent childhood overweight/obesity in school communities, how much it will cost and how best to support communities with ongoing efforts. As findings become available during the trial, STAIR’s research partners will ensure they are translated into local and state-level policy and practice.
Strengths and limitations of this study
- We will leverage current knowledge, use a co-design intervention process and will apply a cost-effective type-2 hybrid design to provide evidence on whether, and how intervention impact can be sustained in the longer term.
- STAIR will be the first real-world study to combine systems thinking with active implementation to help schools create and sustain healthy environments. The study will provide evidence on what intervention actions work, how to implement these actions, who is responsible for the implementation strategies, where accountability for implementation sits and how much the anticipated health gains will cost.
- Participating schools may be comparable to schools in other rural and regional areas but will not be representative of all Victorian schools.
- Schools and researchers will not be blinded to intervention allocation
References
- 1.
Chan M. WHO director-general opens a meeting of the childhood obesity commission. Geneva: World Health Organization; 2014. 1 p.
- 2.
Australian Institute of Health and Welfare. Overweight and obesity among Australian children and adolescents. Canberra, Australia: AIHW; 2020.
- 3. Jansen PW, Mensah FK, Clifford S, Nicholson JM, Wake M. Bidirectional associations between overweight and health-related quality of life from 4-11 years: Longitudinal Study of Australian Children. Int J Obes (Lond). 2013;37(10):1307–13. pmid:23736370
- 4. Rees RW, Caird J, Dickson K, Vigurs C, Thomas J. “It’s on your conscience all the time”: a systematic review of qualitative studies examining views on obesity among young people aged 12-18 years in the UK. BMJ Open. 2014;4(4):e004404. pmid:24785398
- 5. Cliff DP, Okely AD, Morgan PJ, Jones RA, Steele JR, Baur LA. Proficiency deficiency: mastery of fundamental movement skills and skill components in overweight and obese children. Obesity (Silver Spring). 2012;20(5):1024–33. pmid:21799480
- 6. Sanders RH, Han A, Baker JS, Cobley S. Childhood obesity and its physical and psychological co-morbidities: a systematic review of Australian children and adolescents. Eur J Pediatr. 2015;174(6):715–46. pmid:25922141
- 7. Singh AS, Mulder C, Twisk JWR, van Mechelen W, Chinapaw MJM. Tracking of childhood overweight into adulthood: a systematic review of the literature. Obes Rev. 2008;9(5):474–88. pmid:18331423
- 8. GBD 2015 Obesity Collaborators, Afshin A, Forouzanfar MH, Reitsma MB, Sur P, Estep K, et al. Health effects of overweight and obesity in 195 countries over 25 years. N Engl J Med. 2017;377(1):13–27. pmid:28604169
- 9. Puhl RM, King KM. Weight discrimination and bullying. Best Pract Res Clin Endocrinol Metab. 2013;27(2):117–27. pmid:23731874
- 10. Okunogbe A, Nugent R, Spencer G, Ralston J, Wilding J. Economic impacts of overweight and obesity: current and future estimates for eight countries. BMJ Glob Health. 2021;6(10):e006351. pmid:34737167
- 11. Ells LJ, Mead E, Atkinson G, Corpeleijn E, Roberts K, Viner R, et al. Surgery for the treatment of obesity in children and adolescents. Cochrane Database Syst Rev. 2015;(6):CD011740. pmid:26104326
- 12. Mead E, Atkinson G, Richter B, Metzendorf M-I, Baur L, Finer N, et al. Drug interventions for the treatment of obesity in children and adolescents. Cochrane Database Syst Rev. 2016;11(11):CD012436. pmid:27899001
- 13. Mead E, Brown T, Rees K, Azevedo LB, Whittaker V, Jones D, et al. Diet, physical activity and behavioural interventions for the treatment of overweight or obese children from the age of 6 to 11 years. Cochrane Database Syst Rev. 2017;6(6):CD012651. pmid:28639319
- 14.
United Nations. Convention on the rights of the child (1989) Treaty no. 27531. United Nations Treaty Series; 1989;(1577). p. 3–178.
- 15. Brown T, Moore TH, Hooper L, Gao Y, Zayegh A, Ijaz S, et al. Interventions for preventing obesity in children. Cochrane Database Syst Rev. 2019;7(7):CD001871. pmid:31332776
- 16. Rutter H, Savona N, Glonti K, Bibby J, Cummins S, Finegood DT, et al. The need for a complex systems model of evidence for public health. Lancet. 2017;390(10112):2602–4. pmid:28622953
- 17.
Commonwealth of Australia. The national obesity strategy 2022-2032. Australia; 2022.
- 18. Allender S, Brown AD, Bolton KA, Fraser P, Lowe J, Hovmand P. Translating systems thinking into practice for community action on childhood obesity. Obes Rev. 2019;20 Suppl 2(Suppl 2):179–84. pmid:31359617
- 19.
Strugnell C, Jackson M, Hayward J, Becker D, Hillenaar M, Bell C, et al. RESPOND regional childhood health behaviours and anthropometry report (2019-2022). Ovens Murray & Goulburn Valley Regional Report Victoria, Australia Deakin University; 2023.
- 20. Swinburn BA, Kraak VI, Allender S, Atkins VJ, Baker PI, Bogard JR, et al. The global syndemic of obesity, undernutrition, and climate change: the lancet commission report. Lancet. 2019;393(10173):791–846. pmid:30700377
- 21.
Hovmand P. Community based system dynamics. New York: Springer; 2014.
- 22. Allender S, Orellana L, Crooks N, Bolton KA, Fraser P, Brown AD, et al. Four-year behavioral, health-related quality of life, and BMI outcomes from a cluster randomized whole of systems trial of prevention strategies for childhood obesity. Obesity (Silver Spring). 2021;29(6):1022–35. pmid:33950583
- 23. Economos C, Hyatt RR, Must A. Prev Med. 2013;57:322–7.
- 24. Allender S, Millar L, Hovmand P, Bell C, Moodie M, Carter R, et al. Whole of systems trial of prevention strategies for childhood obesity: WHO STOPS childhood obesity. Int J Environ Res Public Health. 2016;13(11):1143. pmid:27854354
- 25. Whelan J, Hayward J, Nichols M, Brown AD, Orellana L, Brown V, et al. Reflexive Evidence and Systems interventions to Prevention Obesity and Non-communicable Disease (RESPOND): protocol and baseline outcomes for a stepped-wedge cluster-randomised prevention trial. BMJ Open. 2022;12(9):e057187. pmid:36581987
- 26. Wolfenden L, Reilly K, Kingsland M, Grady A, Williams CM, Nathan N, et al. Identifying opportunities to develop the science of implementation for community-based non-communicable disease prevention: a review of implementation trials. Prev Med. 2019;118:279–85. pmid:30468794
- 27. Whelan J, Love P, Millar L, Allender S, Morley C, Bell C. A rural community moves closer to sustainable obesity prevention - an exploration of community readiness pre and post a community-based participatory intervention. BMC Public Health. 2019;19(1):1420. pmid:31666042
- 28. Backholer K, Gupta A, Zorbas C, Bennett R, Huse O, Chung A, et al. Differential exposure to, and potential impact of, unhealthy advertising to children by socio‐economic and ethnic groups: a systematic review of the evidence. Obes Rev. 2020;22(3).
- 29. Harris JL, Graff SK. Protecting children from harmful food marketing: options for local government to make a difference. Prev Chronic Dis. 2011;8(5):A92. pmid:21843422
- 30. Cao Z, Hua J, Zhang D, Thapa JR, Wang S. A cohort study assessing the sustainable long-term effectiveness of a childhood-obesity intervention in China. Int J Epidemiol. 2019;48(1):108–15. pmid:30357404
- 31. Llauradó E, Tarro L, Moriña D, Aceves-Martins M, Giralt M, Solà R. Follow-up of a healthy lifestyle education program (the EdAl study): four years after cessation of randomized controlled trial intervention. BMC Public Health. 2018;18(1):104. pmid:29304772
- 32. Wolfenden L, Reilly K, Kingsland M, Grady A, Williams CM, Nathan N, et al. Identifying opportunities to develop the science of implementation for community-based non-communicable disease prevention: a review of implementation trials. Prev Med. 2019;118:279–85. pmid:30468794
- 33. Powell BJ, Waltz TJ, Chinman MJ, Damschroder LJ, Smith JL, Matthieu MM, et al. A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project. Implement Sci. 2015;10:21. pmid:25889199
- 34. Wandersman A, Duffy J, Flaspohler P, Noonan R, Lubell K, Stillman L, et al. Bridging the gap between prevention research and practice: the interactive systems framework for dissemination and implementation. Am J Community Psychol. 2008;41(3–4):171–81. pmid:18302018
- 35. Fixsen D, Van Dyke M, Blase K. Science and implementation. AIRN. 2019;7:2021.
- 36. Aldridge WA 2nd, Boothroyd RI, Fleming WO, Lofts Jarboe K, Morrow J, Ritchie GF, et al. Transforming community prevention systems for sustained impact: embedding active implementation and scaling functions. Transl Behav Med. 2016;6(1):135–44. pmid:27012261
- 37. Allender S, Brown AD, Bolton KA, Fraser P, Lowe J, Hovmand P. Translating systems thinking into practice for community action on childhood obesity. Obes Rev. 2019;20(S2):179–84.
- 38. Dooley D, Moultrie NM, Sites E, Crawford PB. Primary care interventions to reduce childhood obesity and sugar-sweetened beverage consumption: food for thought for oral health professionals. J Public Health Dent. 2017;77 Suppl 1:S104–27. pmid:28621808
- 39. Hayward J, Morton S, Johnstone M, Creighton D, Allender S. Tools and analytic techniques to synthesise community knowledge in CBPR using computer-mediated participatory system modelling. NPJ Digit Med. 2020;3:22. pmid:32133423
- 40. Bolton KA, Whelan J, Fraser P, Bell C, Allender S, Brown AD. The Public Health 12 framework: interpreting the “Meadows 12 places to act in a system” for use in public health. Arch Public Health. 2022;80(1):72. pmid:35255970
- 41. Maitland N, Wardle K, Whelan J, Jalaludin B, Creighton D, Johnstone M, et al. Tracking implementation within a community-led whole of system approach to address childhood overweight and obesity in south west Sydney, Australia. BMC Public Health. 2021;21(1):1233. pmid:34174853
- 42. Victorian Government. Vic Kids Eat Well [online]; 2022 [cited 2024 Feb 1. ]. Available from: https://www.vickidseatwell.health.vic.gov.au/
- 43. Victorian Government. The achievment program [online]; 2018 [cited 2024 Feb 1. ]. Available from: https://www.achievementprogram.health.vic.gov.au/
- 44. Yoong SL, Brown AD, Leung GKW, Hillenaar M, David JL, Hayward J, et al. A protocol of a pilot randomised trial (Action-RESPOND) to support rural and regional communities with implementing community-based systems thinking obesity prevention initiatives. PLoS One. 2024;19(5):e0302047. pmid:38696541
- 45.
World Health Organisation. BMI-for-age (5-19 years). World Health Organisation; 2024 [cited 2024 Aug 4. ]. Available from: https://www.who.int/tools/growth-reference-data-for-5to19-years/indicators/bmi-for-age
- 46.
Australian Curriculum Assessment and Reporting Authority (ACARA). My school. Australian Curriculum Assessment and Reporting Authority (ACARA); 2024 [cited 2024 Aug 4. ]. Available from: https://www.myschool.edu.au/
- 47. de Onis M, Garza C, Onyango AW, Borghi E. Comparison of the WHO child growth standards and the CDC 2000 growth charts. J Nutr. 2007;137(1):144–8. pmid:17182816
- 48.
Commonwealth Department of Health and Aged Care. Australian 24-hour movement guidelines for children and young people (5-17) - an integration of physical activity, sedentary behaviour and sleep Canberra. Commonwealth of Australia; 2019 [cited 2024 Oct 23. ]. Available from: https://www.health.gov.au/topics/physical-activity-and-exercise/physical-activity-and-exercise-guidelines-for-all-australians/for-children-and-young-people-5-to-17-years
- 49.
Card A, Manske S, Mammen G, King M, Gleddie D, Schwartz M. Core indicators and measures of youth health physical activity & sedentary behaviour module: indicators and questions to use with youth respondents and/or school setting assessment. Newfoundland, Canada: Memorial University of Newfoundland; 2012.
- 50. Wong SL, Leatherdale ST, Manske SR. Reliability and validity of a school-based physical activity questionnaire. Med Sci Sports Exerc. 2006;38(9):1593–600. pmid:16960520
- 51.
National Health and Medical Research Council. Australian dietary guidelines. Canberra: Commonwealth of Australia; 2013.
- 52. Wilson AM, Magarey AM, Mastersson N. Reliability and relative validity of a child nutrition questionnaire to simultaneously assess dietary patterns associated with positive energy balance and food behaviours, attitudes, knowledge and environments associated with healthy eating. Int J Behav Nutr Phys Act. 2008;5:5. pmid:18226268
- 53. Gray HL, Koch PA, Contento IR, Bandelli LN, Ang IYH, Di Noia J. Validity and reliability of behavior and theory-based psychosocial determinants measures, using audience response system technology in urban upper-elementary schoolchildren. J Nutr Educ Behav. 2016;48(7):437-452.e1. pmid:27142929
- 54.
Victorian Government. Victorian student health and wellbeing survey. Victorian Government; 2023 [cited 2023 Nov 21. ]. Available from: https://www.vic.gov.au/victorian-student-health-and-wellbeing-survey
- 55. Varni JW, Limbers CA, Burwinkle TM. How young can children reliably and validly self-report their health-related quality of life?: an analysis of 8,591 children across age subgroups with the PedsQL 4.0 Generic Core Scales. Health Qual Life Outcomes. 2007;5:1. pmid:17201920
- 56. Berentzen NE, Smit HA, Bekkers MBM, Brunekreef B, Koppelman GH, De Jongste JC, et al. Time in bed, sleep quality and associations with cardiometabolic markers in children: the Prevention and Incidence of Asthma and Mite Allergy birth cohort study. J Sleep Res. 2014;23(1):3–12. pmid:24118590
- 57. Bell AC, Simmons A, Sanigorski AM, Kremer PJ, Swinburn BA. Preventing childhood obesity: the sentinel site for obesity prevention in Victoria, Australia. Health Promot Int. 2008;23(4):328–36. pmid:18820261
- 58. Chote B, McKelvie-Sebileau P, Swinburn B, Tipene-Leach D, D’Souza E. Culture of healthy eating and food environments, policies, and practices in regional New Zealand schools. IJERPH. 2022;19(11):6729.
- 59. Sweeney R, Moodie M, Nguyen P, Fraser P, Bolton K, Brown A, et al. Protocol for an economic evaluation of WHO STOPS childhood obesity stepped-wedge cluster randomised controlled trial. BMJ Open. 2018;8(5):e020551. pmid:29764881
- 60. Ananthapavan J, Sacks G, Brown V, Moodie M, Nguyen P, Veerman L, et al. Priority-setting for obesity prevention-The Assessing Cost-Effectiveness of obesity prevention policies in Australia (ACE-Obesity Policy) study. PLoS One. 2020;15(6):e0234804. pmid:32559212
- 61.
Barendregt J. EratZ. Queensland, Australia: Epidgear International Pty Ltd; 2017.
- 62. Sanders GD, Neumann PJ, Basu A, Brock DW, Feeny D, Krahn M, et al. Recommendations for conduct, methodological practices, and reporting of cost-effectiveness analyses: second panel on cost-effectiveness in health and medicine. JAMA. 2016;316(10):1093–103. pmid:27623463
- 63. Husereau D, Drummond M, Augustovski F, de Bekker-Grob E, Briggs AH, Carswell C, et al. Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) statement: updated reporting guidance for health economic evaluations. BMC Med. 2022;20(1):23. pmid:35022047
- 64. Moullin JC, Dickson KS, Stadnick NA, Albers B, Nilsen P, Broder-Fingert S, et al. Ten recommendations for using implementation frameworks in research and practice. Implement Sci Commun. 2020;1:42. pmid:32885199
- 65. Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, et al. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health. 2011;38(2):65–76. pmid:20957426
- 66. Weiner BJ, Lewis CC, Stanick C, Powell BJ, Dorsey CN, Clary AS, et al. Psychometric assessment of three newly developed implementation outcome measures. Implement Sci. 2017;12(1):108. pmid:28851459
- 67. Sweet S, Martin Ginis K. Operationalizing the RE-AIM framework to evaluate the impact of multi-sector partnerships. Implement Sci. 2014.
- 68.
Qualtrics. Qualtrics. 02–2024 ed. Provo (UT): Qualtrics; 2022.
- 69. Bolton KA, Whelan J, Fraser P, Bell C, Allender S, Brown AD. The Public Health 12 framework: interpreting the “Meadows 12 places to act in a system” for use in public health. Arch Public Health. 2022;80(1):72. pmid:35255970
- 70. Strugnell C, Orellana L, Hayward J, Millar L, Swinburn B, Allender S. Active (opt-in) consent underestimates mean BMI-z and the prevalence of overweight and obesity compared to passive (opt-out) consent. Evidence from the healthy together Victoria and childhood obesity study. Int J Environ Res Public Health. 2018;15(4):747. pmid:29652831
- 71. Hemming K, Kasza J, Hooper R, Forbes A, Taljaard M. A tutorial on sample size calculation for multiple-period cluster randomized parallel, cross-over and stepped-wedge trials using the Shiny CRT Calculator. Int J Epidemiol. 2020;49(3):979–95. pmid:32087011
- 72. Venegas Hargous C, Strugnell C, Allender S, Orellana L, Corvalan C, Bell C. Double- and triple-duty actions in childhood for addressing the global syndemic of obesity, undernutrition, and climate change: a scoping review. Obes Rev. 2023;24(4):e13555. pmid:36754361
- 73. Sohn H, Tucker A, Ferguson O, Gomes I, Dowdy D. Costing the implementation of public health interventions in resource-limited settings: a conceptual framework. Implement Sci. 2020;15(1):86. pmid:32993713