Is it possible to optimize costs as scale-up of Choose to Move--an effective health-promoting intervention for older adults--proceeds?

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Zoe Szewczyk, Heather M Macdonald, Marina De Barros Pinheiro, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6331081/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Nov, 2025 Read the published version in International Journal of Behavioral Nutrition and Physical Activity → Version 1 posted 9 You are reading this latest preprint version Abstract Background Few studies have examined costs of implementing evidence-based interventions (EBIs) as scale-up proceeds. Across four phases, we co-adapted and scaled up an effective EBI designed to promote older adults’ health (Choose to Move; CTM). Following formative evaluation (2015), Phases 1–2 (2016-17) comprised the CTM pilot and early scale-up. For Phase 3 (2018-20), we adapted CTM to establish “best fit” and support broad scale-up. In response to COVID-19 (2020), we adapted CTM for virtual delivery. For Phase 4 (2020-22), we adapted CTM to reduce resource use. Objectives We aimed to 1) identify, measure, and value costs of implementing CTM across four phases (7 years) of scale-up; and 2) analyze change in implementation costs alongside changes in intervention effect sizes to assess cost-consequence trends from Phases 1–2 through Phase 4. Methods We conducted a trial-based cost and cost-consequence analysis of CTM Phases 1–2 through Phase 4 from a program provider perspective. Program costs were identified, measured, and valued using micro-costing techniques; variation in program cost was explored using scenario analyses. We compared Phase 4 intervention effects against those of Phases 1–2 and Phase 3 to examine how changes in implementation costs corresponded with changes in effect size. Results For Phases 1–2, total cost ( $ CDN, 2024) of CTM implementation was $ 863,559 for 55 programs (534 participants; $ 1,617/participant). Phase 3 costs were $ 1,564,446 for 165 programs (1668 participants; $ 938/participant). Phase 4 costs were $ 760,983 for 136 programs (1270 participants; $ 599/participant), a reduction of 63% and 36% compared with Phases 1–2 and Phase 3, respectively. Compared with Phases 1–2, Phase 4 had a greater positive effect on social isolation but effect sizes for physical activity, mobility and loneliness were reduced. Phase 4 had a greater positive effect on physical activity, mobility, social isolation, and loneliness (for those < 75 years), compared with Phase 3. Conclusion Costs associated with broad scale-up of EBIs are rarely investigated. We sought innovative ways to maximize impact of a health-promoting EBI, while minimizing costs. Our analysis highlights how strategic adaptations can enhance cost efficiency while improving intervention outcomes; this represents an emergent application of economic analysis within scale-up science. cost cost analysis cost consequence healthy aging implementation scale-up INTRODUCTION Optimization is the act of making the best or most effective use of a situation or resource. In public health, optimization is defined as “a deliberate, iterative, and data-driven process to improve a health intervention and/or its implementation to meet stakeholder-defined public health impacts within resource constraints” ( 1 ). The Dynamic Sustainability Framework ( 2 ) suggests that “interventions should not be considered optimized until they have been implemented, tested, and refined in settings where they will be ultimately delivered”. To improve population health, it is important to design evidence-based interventions (EBIs) that are scalable, monitor scale-up as it progresses, and seek ways to optimize implementation as scale-up proceeds. We define scale-up as “the process by which health interventions shown to be efficacious on a small scale and/or under controlled conditions are expanded under real-world conditions to reach a greater proportion of the eligible population, while retaining effectiveness” ( 3 ). Sustained effectiveness and costs associated with scaling-up EBIs are rarely investigated ( 2 , 4 ). That oversight needs to be addressed. Thus, researchers are encouraged to identify and justify costs associated with the implementation process and the intervention itself ( 2 ). Among the factors that influence scale-up and sustainment of public health and health-promoting EBIs, funding looms large ( 5 , 6 ). Healthcare decision-makers seek to improve health without increasing healthcare budgets. When comparing alternative courses of action, funding partners (often government agencies) increasingly scrutinize investments and consider costs along with other factors such as effectiveness, acceptability in context, scalability, and reach ( 7 ). Health economic evaluation provides a framework to compare the costs and benefits of different alternatives over various time horizons—outcomes of the evaluation inform decision making ( 8 ). Despite its value to decision makers, few studies examined the costs of implementing effective health-promoting EBIs across a long period of scale-up; nor have they studied the economic consequences associated with optimization ( 4 ). We sought to fill this information gap drawing upon our decade of experience implementing and scaling up Choose to Move (CTM). CTM (detailed below) is a scalable, health-promoting EBI for older adults. CTM was co-designed and scaled up across British Columbia, Canada with community and government partners using a phased approach. Elsewhere, we describe our formal, systematic, and data-driven co-adaptation process prior to implementing CTM across each phase of (horizontal ( 9 )) scale-up ( 10 – 12 ). We aimed to retain fidelity to the ‘core functions’ of CTM across phases (defined as behavior change techniques that theoretically drive positive health outcomes (e.g., goal setting) ( 13 )). Briefly, we began with a formative evaluation (2015). Phases 1 and 2 comprised the pilot and early scale-up of CTM (2016-17). For Phase 3 (2018-20), CTM was adapted with feedback from older adults and delivery partners to establish “best fit” and to support broad scale-up ( 10 ). In response to COVID-19 public health restrictions (2020), CTM was adapted with delivery partners for delivery in the virtual environment ( 11 ). For Phase 4 (2020-22), CTM was adapted to selectively reduce resource use (program delivery hours by activity coaches); virtual delivery remained an option ( 12 ). We demonstrated that CTM could be implemented with fidelity at increasingly larger scale ( 14 ), in different communities, and after adapting for virtual delivery ( 11 ) with reduced resource use ( 12 ). Adaptations did not compromise the effectiveness of CTM (i.e., health benefits for older adult participants were retained). Our current costing study has two objectives: 1) identify, measure, and value the costs of implementing the CTM intervention across four phases (7 years) of scale-up; and 2) analyze change in implementation costs alongside changes in intervention effect sizes to assess cost-consequence trends from Phases 1–2 through Phase 4. METHODS Choose to Move Choose to Move comprises the program ( https://choosetomove.ca ) and a suite of implementation strategies used to support implementation and scale-up. The CTM program is choice-based, coach- and peer-supported, and designed for low active (< 150 min/week moderate-to-vigorous physical activity (PA)) community-dwelling older adults. Participants are supported by an activity coach to choose physical activities that align with their personal preferences, health status, and available resources ( 14 – 16 ). The current 3-month CTM (Phase 4) program comprises a 30 min one-on-one consultation with a trained activity coach, and 8 group meetings with other participants, facilitated by the activity coach. We provide an overview of CTM Phases 1–4 in Supplementary Table 1. Phase 4 continues to be scaled up across British Columbia; to date (March 2025) > 7,000 older adults have participated in CTM. Implementation ( 17 , 18 ) and scale-up ( 19 ) frameworks and principles (e.g., community partnerships) guided implementation and scale-up of CTM. Community-based delivery partner organizations offer the CTM program in recreation centres or virtually (e.g., on Zoom™). We initially partnered with two large community organizations (i.e., YMCA and British Columbia Recreation and Parks Association (BCRPA)) that have broad geographic reach through recreation facilities across British Columbia ( 14 , 15 ). In 2018 we recruited small partner organizations (e.g., neighborhood houses and seniors’ centres) whose reach was more local. With government funding, the Active Aging Society (AAS; https://www.activeagingsociety.org ) provides broad functional and financial support to delivery partner organizations who hire activity coaches to deliver CTM under the umbrella of their organizations. The Central Support Unit ( 20 ), housed within the AAS, uses a suite of implementation strategies ( 21 ) to build capacity (e.g., provides tools, training and ongoing support) among community organizations that serve as delivery partners. Evaluating CTM Previous studies Elsewhere, we describe outcomes of the CTM evaluation across all phases of implementation ( 12 , 14 , 15 , 22 ). Briefly, we used a hybrid type 2 effectiveness-implementation study design ( 23 ) to evaluate CTM. For the implementation evaluation we were guided by a proposed minimum data set of implementation indicators ( 24 ). For the effectiveness (outcomes) evaluation, participants were > 60 years, able to read and understand English, reported low levels of PA (less than 150 minutes/week), and had no contraindications to participating in PA. Participants were recruited via local promotions, Facebook, the CTM website, media advertisements and word of mouth. The primary outcome across all phases of CTM was self-reported PA (number of days in the previous week with 30 minutes or more of moderate-to-vigorous PA) using a validated single-item PA measure ( 25 – 27 ). Secondary outcomes were mobility, social isolation and loneliness, and health related quality of life. Generally, CTM enhanced participants’ engagement in PA, increased mobility and decreased social isolation and loneliness across all phases ( 12 , 14 , 15 ). We observed a small voltage drop ( 2 ) in the magnitude of positive change in health outcomes (PA, mobility, loneliness) between Phases 1–2 and Phase 3. However, there was no further ‘scale-up penalty’ ( 28 ) for these outcomes between Phases 3 and 4 (except for loneliness in participants aged 75 years and older). In fact, we noted a voltage ‘surge’ in the positive effects of CTM on PA, mobility and social isolation between Phases 3 and 4 ( 12 ). Outcomes did not differ between CTM delivery modes (in-person or virtual); many health benefits were maintained one year after the end of formal participation in CTM Phases 1–2 and Phase 3 ( 14 , 29 ). Current study : For the current study, we used data from our two large delivery partners to compare effectiveness across 7 years of CTM scale-up (2016–2022). Specifically, we compared CTM Phase 4 effect sizes (change from baseline with 95% confidence interval, CI) for primary outcomes to those of Phases 1–2 and Phase 3 effect sizes. We used the approach of McCrabb et al. ( 28 ) to determine the proportion of the effect size retained in Phase 4 as compared with Phase 3 as: (Phase 4 effect size / Phases 3 effect size) * 100. We describe percent change narratively. Values greater than 100% indicate a greater benefit of the intervention in Phase 4 as compared with Phase 3; values of 50% indicate that Phase 4 was half as effective as Phase 3; and values less than 0% (negative values) indicate that the direction of the effect in Phase 4 was opposite that of Phase 3. We used the same approach to determine the proportion of effect size retained in Phase 4 as compared with Phases 1–2. Cost and cost-consequence analysis We identified, measured, and valued the costs and outcomes of CTM Phases 1–4, against a ‘do nothing’ alternative. We chose this approach because health promotion activities for older adults are not routinely delivered in Canada. Thus, CTM does not displace usual practice activities or investments in these activities. We adopted a program provider perspective to reflect the real-world implementation of CTM, over a trial time horizon (3 months). We identified, measured, and valued financial costs and opportunity costs associated with implementation of CTM Phases 1–4. We define implementation costs as all costs associated with delivering CTM and the provision of ongoing implementation support to partner organizations throughout the lifecycle of program delivery (e.g., activity coach hours, equipment and resources, support staff). Financial costs included the costs of goods and services directly purchased to implement CTM which hold a market value. We define opportunity cost as the value of opportunities forgone. That is, any non-financial investment of resources, labor time, or products associated with implementing CTM. We used trial administrative records kept by the Central Support Unit to retrospectively identify resource use associated with implementation of Phases 1–2 across our delivery partners ( 30 ). Delivery partners used a cost-capture tool developed in Microsoft Excel (2013) to prospectively collect cost data for Phase 3 and Phase 4 using a time-driven activity-based costing approach ( 31 ). The cost capture tool included the following categories: ( 1 ) labor (staff, including overhead to allow for additional costs of employment), ( 2 ) materials such as non-labor cost items (e.g., stationary, education materials, electronic hardware or software), ( 3 ) joint costs such as those incurred in connection with multiple projects (e.g., maintenance costs of a website portal supporting different interventions); capital costs such as those for one-off investments (e.g., purchase of computers), and ( 4 ) miscellaneous costs (i.e., costs not easily classified into the other categories such as venue hire and travel). Our activity-based costing approach involved three parameters: ( 1 ) frequency of activity, (e.g., training session, phone call with support staff) ( 2 ) resources required to perform one single event of the activity, and ( 3 ) price or value of the resources used to perform the activity ( 31 ). Cost data were treated as counts of resource use, weighted by unit costs. The cost for each phase was determined by summing the costs relevant to and coded for that phase. The cost per participant was calculated as the cost of implementing CTM divided by the number of participants. Development, research and evaluation costs were excluded from cost and cost-consequence analyses as we focus on the costs of implementing CTM. The program provider perspective for this evaluation meant costs to participants and private care providers (including opportunity costs) were not included. Costs incurred after 12-months were not discounted as the trial time horizon was three months and was a function of the study design and not the expected timeline for real world expenses. All costs were adjusted for inflation using annual consumer price index ( 32 ) and reported in 2024 Canadian dollars ( $ CDN). We conducted a series of trial-based cost and cost-consequence analyses of health outcomes common across CTM Phases 1 through 4. Effectiveness is a prerequisite for economic evaluation; therefore, we included only outcomes that demonstrated a statistically significant effect size ( 14 , 15 ). Analyses were performed in R version 4.3.3 using the tidyverse package for data analysis ( 33 ). Results of the cost consequence analysis are presented as a scorecard comprising the total cost of CTM alongside the range of outcomes reflected in the primary and secondary trial outcomes (consequences). We conducted the economic evaluation and report findings in accordance with the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) publication guidelines and good reporting practices ( 8 ) (Supplementary Table 2). In practice, there is expected variation around estimates of cost, particularly when programs are implemented in diverse settings, with different program providers, and at scale. To explore the impact of variation on CTM program costs we conducted four scenario analyses to estimate a plausible upper and lower range and demonstrate the impact of uncertainty in key parameters on program delivery costs. Specifically, we calculated the average cost per program and per participant for each program provider (delivery partner). We estimated the range (low and high) of costs by: ( 1 ) calculating the range of material costs (years with the least and most number of facilities grants; funds provided to each delivery site (BCRPA sites only) to support program implementation) and ( 2 ) calculating the labor costs if Central Support Unit staff time was increased or decreased by 20% (equivalent to 0.2 FTE). We used these estimates to calculate the range of costs per participant and per program in a ‘best case scenario’ (lowest number of facilities grants provided and a 20% reduction in central support staff time) and ‘worst case scenario’ (highest number of facilities grants provided and a 20% increase in central support staff time). We excluded retrospective cost data (Phases 1–2) from the scenario analyses because they provided less detail than did the prospective Phase 3 and Phase 4 data. RESULTS Table 1 describes the number of programs and participants across Phases 1–2, Phase 3 and Phase 4. Table 1 also summarizes the total cost of implementing CTM across all phases and per participant. The cost per participant of implementing CTM Phase 4 was slightly more than one third (37%) of the cost per participant at Phases 1–2. We note a reduction of $803,463 in total costs and $339 in cost per participant between Phase 3 and Phase 4. Variation from differences in delivery partner provided the greatest individual impact on program costs (Range $894 - $1,017). The scenario that included variation in both facility grants, and staff time had the greatest overall impact on program costs (Range $866 - $1,014). Table 1. The total cost of implementing Choose to Move across all phases and per participant (Canadian 2024 dollars, CDN$), including scenario analyses. Category Phase 1-2 Phase 3 Phase 4 Participants (n) 534 1668 1270 Programs (n) 55 165 136 Phase 1-2 Phase 3 Phase 4 Δ (Phase 1–2 to 4) Total cost (CDN$) 863,559 1,564,446 760,983 102,576 Average cost per participant 1,617 938 599 1,018 Average cost per program 15,701 9,481 5,595 10,106 Scenario Analyses Phase 3 Phase 4 Low ($) High ($) Low ($) High ($) Delivery Partner Average cost per participant 894 1,017 585 630 Average cost per program 8,712 11,020 5,531 5,731 Facility Grants Average cost per participant 919 963 590 608 Average cost per program 9,289 9,740 5,513 5,681 Staff Time Average cost per participant 908 968 574 625 Average cost per program 9,177 9,786 5,359 5,832 Facilities and Staff Time Average cost per participant 866 1,014 565 634 Average cost per program 8,757 10,254 5,277 5,917 The evidence-based optimization and reduction in activity coach hours required to deliver Phase 4 resulted in a decrease in total labor costs between Phases 3 and 4 ($992 per program). Cost of materials decreased between Phase 3 and Phase 4, whereas the cost of miscellaneous items increased by 8% ($52,169) as a proportion of the total budget (Table 2). Across all three phases, labor accounted for 63% - 80% of total CTM implementation costs. Table 2 Proportion of Choose to Move implementation costs associated with each resource use (labor, materials, miscellaneous) category. Costs are in Canadian dollars (2024). Labor Materials Miscellaneous Cost ($) % Cost ($) % Cost ($) % Total cost ($) Phases 1–2 693,270 80% 119,816 14% 50,473 6% 863,559 Phase 3 981,086 63% 559,614 36% 23,746 2% 1,564,446 Phase 4 565,171 74% 119,897 16% 75,915 10% 760,983 The effectiveness of CTM Phases 1–2, Phase 3 and Phase 4 for each statistically significant outcome and age group is published elsewhere (12, 14, 15). We compared effect sizes of CTM Phase 4 outcomes to those of Phases 1–2 and Phase 3 (Table 3). When comparing CTM effect sizes (95% CI) for primary outcomes between Phase 3 and Phase 4, there was no voltage drop in effect size for PA, mobility, and social isolation for the full cohort, or in loneliness for those aged 75 years was small (6%); for loneliness the voltage drop was 70%. Between Phases 1–2 and Phase 4, social isolation improved across the full cohort and both age groups. The magnitude of improvement in PA, mobility, and loneliness decreased across CTM Phases 1–2 to Phase 4, suggesting a voltage drop in effectiveness as CTM was scaled up. Table 3 Comparison of Choose to Move intervention effect sizes (95% CI) for primary outcomes between Phase 3 and Phase 4 and between Phase 1–2 and Phase 4. Costs are in Canadian dollars (2024). Phase 4 Effect Size a Phase 3 to 4: Proportion (%) of CTM effect achieved post-optimization b Phases 1–2 to 4: Proportion (%) of CTM effect achieved with optimization b Full cohort < 75 yrs ≥ 75 yrs Full cohort < 75 yrs ≥ 75 yrs Full cohort < 75 yrs ≥ 75 yrs Physical activity 1.32 1.5 1 147 150 111 94 94 100 (1.2, 1.5) (1.3, 1.6) (0.7, 1.2) Mobility -0.053 -0.061 -0.034 113 105 131 37 43 24 (-9.7, -0.01) (-11.2, -0.01) (-11.8, 5.1) Social isolation 0.79 0.92 0.47 113 115 94 198 153 522 (0.58, 1.0) (0.67, 1.17) (0.08, 0.86) Loneliness -0.15 -0.23 0.03 75 115 30 38 58 6 (-0.24, -0.07) (-0.33, -0.12) (-0.14, 0.19) a As per McCrabb et al. (28) effect size was calculated as change from baseline. CTM Phase 4 effect sizes are also reported elsewhere (12). b (Phase 4 effect size / Phase 3 effect size) * 100. Values greater than 100% indicate a greater benefit of the intervention in Phase 4 than in Phase 3; values of 50% indicate that Phase 4 was half as effective as Phase 3; and values less than 0% (negative values) indicate that the direction of the effect in Phase 4 was opposite that in Phase 3. The same approach was used to compare Phase 4 with Phases 1–2. DISCUSSION As governments and health care decision makers grapple with escalating healthcare costs associated with aging populations, upstream investment in health promotion may provide one solution. To guide decision making, it is imperative that those who fund scaled-up health-promoting EBIs have evidence (data) to support effectiveness, scalability and implementation costs of the intervention. These data are essential to review and prioritize investment decisions. However, very few studies described the cost, cost consequences and effectiveness of health-promoting EBIs as they proceed along the scale-up continuum ( 34 ). Therefore, our study fills this gap. Specifically, we extend our previous work ( 12 ) and report costs and cost consequences of an effective health-promoting EBI across 7 years of scale-up. The Choose to Move context is unique—as we are unaware of any other health-promoting EBIs for older adults that were effectively scaled up with government support over the longer term. This is key, as health-promoting EBIs must be scaled up ( 35 ) and sustained ( 36 ) to improve health at the population level. Optimizing CTM to reduce cost in Phase 4 while maintaining effectiveness is also a novel aspect of our study. We also extend the literature and our previous work ( 12 ) by identifying, measuring and valuing the financial and opportunity costs associated with implementation of CTM across 7 years of scale-up. Our key finding was that total implementation costs for CTM between Phase 3 and Phase 4 decreased by 36%. Although CTM implementation costs were reduced (due primarily to a 40% reduction in activity coach hours ( 12 ), participant-level benefits (PA, mobility and social isolation in all participants; loneliness in those < 75 years) in Phase 4 were comparable to, or greater than those observed in Phase 3. Scaled-up, optimized (to reduce cost) health-promoting EBIs should not compromise effectiveness. We reported a small voltage drop between CTM Phases 1–2 and Phase 3 ( 14 ). However, as we continued to scale and optimize CTM in Phase 4 to reduce resource use, effect sizes for outcomes (except loneliness) were similar or greater than those in Phase 3. This finding counters the voltage drop theory, which suggests that as community-based PA ( 37 ) and obesity ( 28 ) interventions go to scale, the magnitude of their effect diminishes by 50–60%, on average. Despite this, positive changes in most health outcomes remained significant ( 14 ). The difference in these findings across phases may be due, to slightly lower baseline PA in our Phase 4 cohort (2.0 days/week; 95% CI: 1.8, 2.1) who joined CTM during the COVID-19 pandemic, as compared with Phase 3 participants (2.3 days/week; 95% CI: 2.1, 2.6) ( 12 ). The substantial decrease in social isolation (voltage surge) between Phases 1–2 and Phase 3 ( 14 ), and between Phases 3 and 4 may reflect how CTM was adapted to create more opportunities for participants to socially connect in group sessions ( 12 , 14 ). We demonstrated that a health-promoting EBI can be optimized for cost while retaining core functions and program effectiveness. Using economic evidence to inform how best to develop and scale-up an intervention is of great value ( 38 ). Yet little is known about how to evaluate economic aspects of scaling up programs and strategies that comprise health-promoting EBIs ( 39 ). Nor is there much evidence to support how best to use economic data to optimize effective, scalable health-promoting EBIs. Findings from our study in an implementation, health promotion research context, highlight an emergent application of economic analysis. As cost savings were realized for CTM delivery without compromising health benefits, we also urge greater investment in this area of research. All areas of health and medical research focus on the rigorous measurement of health, program, and (less so) implementation outcomes. However, methods for measuring costs are neither systematic nor comprehensive ( 2 ). Additionally, economic evaluation in public health or health promotion is not routine, and cost data for these interventions are of mixed quality ( 40 ). Poor quality cost data are detrimental, as reliable data form the foundation of economic evaluations. Without reliable estimates, evaluation results could mislead decision makers and have significant implications for healthcare providers and patients ( 2 – 4 ). Economic evaluation of effectively scaled-up population health EBIs have encountered challenges. First, methods used to evaluate value for money vary ( 41 ). Second, there is little agreement on how best to determine ongoing investment in implementation or scale-up of EBIs ( 42 ). This could be because of different time horizons between conducting public health or health-promoting EBIs and realizing participant-level health benefits. Benefits may also occur outside the healthcare system, which precludes reliably measuring an EBI’s value (or return on investment) to the health system. A third challenge is that differences in healthcare financing and populations assessed limits transferability of cost data to different settings. Activities that drove successful implementation of CTM were related to building capacity within two larger community organizations that served as delivery partners (i.e., to implement CTM among their older adult constituents). Readiness-building activities ( 43 ) were embedded within the essential role of the Central Support Unit. We consider the role of the Central Support Unit as the foundation upon which EBIs are effectively implemented, scaled up, and sustained. This team provided training, tools and ongoing support directly to delivery partners and activity coaches while (indirectly) supporting participants. Thus, it comes as no surprise that as a proportion of the total cost of CTM, labor (including activities of the Central Support Unit) was the largest cost category across all CTM Phases. The Central Support Unit’s role in building capacity, trust, and a sense of community among community partner organizations, activity coaches and participants takes time, often with uncertain outcomes. We have begun to experience that Central Support Unit costs escalate further in smaller more poorly resourced community organizations that are less ‘ready’ ( 43 ). Our study has several strengths. First, we contribute to the scant literature that has determined costs and consequences of health-promoting EBIs across scale-up. We use a rare real-world example of a scaled-up health-promoting EBI (CTM) to derive our data. Second, we specify the cost of resource use within the total cost of implementing CTM. Third, we highlight that CTM can be optimized for cost while not compromising health outcomes; this finding can be applied to other health-promoting EBIs. We also acknowledge several limitations of our study. First, to minimize the likelihood of missing data in the retrospective costing, all items included in the cost analysis were identified from trial records. Where possible we triangulated data against a second data point or source and confirmed it by the Central Support Unit. Second, we did not impute missing outcomes data. Third, CTM retrospective data (Phases 1–2) did not provide sufficient detail to delineate material costs for research from material costs associated with development. Thus, these data are missing from Table 2 and the scenario analyses. Conclusion and future research Identifying costs associated with scale-up and value for money of health-promoting and public health EBIs is of high priority ( 44 ). We demonstrated an emergent application of economic analysis within scale-up science and contend that investments in advancing this type of research are worthwhile. Researchers might further explore ways to maximize the public health impact of EBIs while minimizing costs. Importantly, future studies should investigate whether a positive intervention effect (at lower cost) can be sustained over time, and the economic cost of implementation strategies (specifically) used in public health interventions ( 40 ). Although links between scaling up and sustaining EBIs have cost implications, factors and processes that influence both are not well understood. Finally, we urge researchers (including implementation scientists) to identify ways to prospectively weave economic evaluation into implementation, scale-up and sustainment science as part of standard practice. By providing cost and outcomes data, decision makers are better positioned to make informed investments in innovative public health and health-promoting EBIs. Declarations Ethics approval and consent to participateEthics approval was obtained from the University of British Columbia Research Ethics Board (H15-02522; H20-00780). All study participants provided informed consent. Consent for publication Not applicable. Availability of data and materials The datasets analyzed during the current study are not publicly available as consent was not obtained for this. However, data are available from the corresponding author on reasonable request. Competing interests None to declare Funding The British Columbia Ministry of Health provided funds to the Active Aging Society to support delivery of Choose to Move. The Canadian Institutes of Health Research (PJT-169159) funded the evaluation of Choose to Move. The funders had no role in study design, data collection, analysis or interpretation, or in writing the manuscript. Authors' contributions Conceptualization, Z.S., H.Mc, H.Mac, M.B.P, and L. N.; methodology, Z.S., M.B.P, H.Mc, H.Mac, L. N; formal analysis, Z.S. and H.Mac; writing — original draft preparation, Z.S., H.Mc; writing — review and editing, Z.S., H.Mc, H.Mac, M.B.P, and L.N.; and project administration, Z.S., H.Mc, H.Mac and L.N. All authors have read and agreed to the published version of the manuscript. Acknowledgements We are grateful for the ongoing support of Choose to Move from the BC Ministry of Health, the Active Aging Society and delivery partner organizations across BC. We thank all the older adults from across the province who participated in Choose to Move. Finally, we are grateful for the dedication of staff and trainees from the Active Aging Research Team who are the engine that powers operations and evaluation of CTM. In particular, we acknowledge the contributions of Christa Hoy, Program and Evaluation Manager, who assisted with data collection for this study. References Wolfenden L, Bolsewicz K, Grady A, McCrabb S, Kingsland M, Wiggers J, et al. Optimisation: defining and exploring a concept to enhance the impact of public health initiatives. Health research policy and systems. 2019;17(1):108. https://doi.org/10.1186/s12961-019-0502-6. Chambers DA, Glasgow RE, Stange KC. The dynamic sustainability framework: addressing the paradox of sustainment amid ongoing change. Implement Sci. 2013;8:117. https://doi.org/10.1186/1748-5908-8-117. Milat AJ, Bauman A, Redman S. Narrative review of models and success factors for scaling up public health interventions. Implement Sci. 2015;10:113. https://doi.org/10.1186/s13012-015-0301-6. Roberts SLE, Healey A, Sevdalis N. Use of health economic evaluation in the implementation and improvement science fields-a systematic literature review. Implement Sci. 2019;14(1):72. https://doi.org/10.1186/s13012-019-0901-7. Hailemariam M, Bustos T, Montgomery B, Barajas R, Evans LB, Drahota A. Evidence-based intervention sustainability strategies: a systematic review. Implement Sci. 2019;14(1):57. https://doi.org/10.1186/s13012-019-0910-6. Lee K, van Nassau F, Grunseit A, Conte K, Milat A, Wolfenden L, et al. Scaling up population health interventions from decision to sustainability - a window of opportunity? 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Prev Sci. 2020;21(3):355-65. https://doi.org/10.1007/s11121-019-01085-3. Gray SM, Franke T, Sims-Gould J, McKay HA. Rapidly adapting an effective health promoting intervention for older adults-choose to move-for virtual delivery during the COVID-19 pandemic. BMC Public Health. 2022;22(1):1172. https://doi.org/10.1186/s12889-022-13547-5. Nettlefold L, Macdonald HM, Sims Gould J, Bauman A, Szewczyk Z, McKay HA. Does optimizing Choose to Move - a health-promoting program for older adults - enhance scalability, program implementation and effectiveness? Int J Behav Nutr Phys Act. 2024;21(1):140. https://doi.org/10.1186/s12966-024-01649-9. Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, et al. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013;46(1):81-95. https://doi.org/10.1007/s12160-013-9486-6. McKay HA, Macdonald HM, Nettlefold L, Weatherson K, Gray SM, Bauman A, et al. What is the 'voltage drop' when an effective health promoting intervention for older adults-Choose to Move (Phase 3)-Is implemented at broad scale? PLoS ONE. 2023;18(5):e0268164. https://doi.org/10.1371/journal.pone.0268164. McKay H, Nettlefold L, Bauman A, Hoy C, Gray SM, Lau E, et al. Implementation of a co-designed physical activity program for older adults: positive impact when delivered at scale. BMC Public Health. 2018;18(1):1289. https://doi.org/10.1186/s12889-018-6210-2. Sims-Gould J, McKay HA, Hoy CL, Nettlefold L, Gray SM, Lau EY, et al. Factors that influence implementation at scale of a community-based health promotion intervention for older adults. BMC Public Health. 2019;19(1):1619. https://doi.org/10.1186/s12889-019-7984-6. Durlak JA, DuPre EP. Implementation matters: a review of research on the influence of implementation on program outcomes and the factors affecting implementation. Am J Community Psychol. 2008;41(3-4):327-50. https://doi.org/10.1007/s10464-008-9165-0. 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. https://doi.org/10.1007/s10464-008-9174-z. Yamey G. Scaling up global health interventions: a proposed framework for success. PLoS Med. 2011;8(6):e1001049. https://doi.org/10.1371/journal.pmed.1001049. Sims-Gould J, McKay HA, Franke T. How central support built capacity to deliver a health-promoting intervention for older adults in Canada. Health Soc Care Community. 2022;30(5):e3063-e74. https://doi.org/10.1111/hsc.13751. Proctor EK, Powell BJ, McMillen JC. Implementation strategies: recommendations for specifying and reporting. Implement Sci. 2013;8:139. https://doi.org/10.1186/1748-5908-8-139. Nettlefold L, Gray SM, Sims-Gould J, McKay HA. From Start-Up to Scale-Up of a Health-Promoting Intervention for Older Adults: The Choose to Move Story. Kinesiol Rev. 2023;12(1):76-86. https://doi.org/10.1123/kr.2022-0034. Curran GM, Bauer M, Mittman B, Pyne JM, Stetler C. Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact. Med Care. 2012;50(3):217-26. https://doi.org/10.1097/MLR.0b013e3182408812. McKay H, Naylor PJ, Lau E, Gray SM, Wolfenden L, Milat A, et al. Implementation and scale-up of physical activity and behavioural nutrition interventions: an evaluation roadmap. Int J Behav Nutr Phys Act. 2019;16(1):102. https://doi.org/10.1186/s12966-019-0868-4. Milton K, Bull FC, Bauman A. Reliability and validity testing of a single-item physical activity measure. Brit J Sport Med. 2011;45(3):203-8. https://doi.org/10.1136/bjsm.2009.068395. Milton K, Clemes S, Bull F. Can a single question provide an accurate measure of physical activity? Brit J Sport Med. 2013;47(1):44-8. https://doi.org/10.1136/bjsports-2011-090899. Macdonald HM, Nettlefold L, Bauman A, Sims-Gould J, McKay HA. Pragmatic Evaluation of Older Adults' Physical Activity in Scale-Up Studies: Is the Single-Item Measure a Reasonable Option? J Aging Phys Act. 2022;30(1):25-32. https://doi.org/10.1123/japa.2020-0412. McCrabb S, Lane C, Hall A, Milat A, Bauman A, Sutherland R, et al. Scaling-up evidence-based obesity interventions: A systematic review assessing intervention adaptations and effectiveness and quantifying the scale-up penalty. Obes Rev. 2019;20(7):964-82. https://doi.org/10.1111/obr.12845. McKay HA, Nettlefold L, Sims-Gould J, Macdonald HM, Khan KM, Bauman A. Status Quo or Drop-Off: Do Older Adults Maintain Benefits From Choose to Move-A Scaled-Up Physical Activity Program-12 Months After Withdrawing the Intervention? J Phys Act Health. 2021;18(10):1236-44. https://doi.org/10.1123/jpah.2020-0850. Reeves P, Szewczyk Z, Kingsland M, Doherty E, Elliott E, Dunlop A, et al. Protocol for an economic evaluation and budget impact assessment of a randomised, stepped-wedge controlled trial for practice change support to increase routine provision of antenatal care for maternal alcohol consumption. Implement Sci Commun. 2020;1(1):91. https://doi.org/10.1186/s43058-020-00079-5. Cidav Z, Mandell D, Pyne J, Beidas R, Curran G, Marcus S. A pragmatic method for costing implementation strategies using time-driven activity-based costing. Implement Sci. 2020;15(1):28. https://doi.org/10.1186/s13012-020-00993-1. Statistics Canada. Consumer price index portal Online: Government of Canada 2022 [Available from: https://www.statcan.gc.ca/en/subjects-start/prices_and_price_indexes/consumer_price_indexes. Wickham et al. Welcome to the Tidyverse. Journal of Open Source Software. 2019;4(43):1686. https://doi.org/https://doi.org/10.21105/joss.01686. Brown V, Tran H, Williams J, Laws R, Moodie M. Exploring the economics of public health intervention scale-up: a case study of the Supporting Healthy Image, Nutrition and Exercise (SHINE) cluster randomised controlled trial. BMC Public Health. 2022;22(1):1338. https://doi.org/10.1186/s12889-022-13754-0. Milat AJ, Newson R, King L, Rissel C, Wolfenden L, Bauman A, et al. A guide to scaling up population health interventions. Public Health Res Pract. 2016;26(1):e2611604. https://doi.org/10.17061/phrp2611604. Shelton RC, Cooper BR, Stirman SW. The Sustainability of Evidence-Based Interventions and Practices in Public Health and Health Care. Annu Rev Public Health. 2018;39:55-76. https://doi.org/10.1146/annurev-publhealth-040617-014731. Lane C, McCrabb S, Nathan N, Naylor PJ, Bauman A, Milat A, et al. How effective are physical activity interventions when they are scaled-up: a systematic review. Int J Behav Nutr Phys Act. 2021;18(1):16. https://doi.org/10.1186/s12966-021-01080-4. Milat AJ, King L, Bauman AE, Redman S. The concept of scalability: increasing the scale and potential adoption of health promotion interventions into policy and practice. Health Promot Int. 2013;28(3):285-98. https://doi.org/10.1093/heapro/dar097. Brundisini F, Zomahoun HTV, Légaré F, Rhéault N, Bernard-Uwizeye C, Massougbodji J, et al. Economic evaluations of scaling up strategies of evidence-based health interventions: a systematic review protocol. BMJ Open. 2021;11(9):e050838. https://doi.org/10.1136/bmjopen-2021-050838. Reeves P, Edmunds K, Searles A, Wiggers J. Economic evaluations of public health implementation-interventions: a systematic review and guideline for practice. Public Health. 2019;169:101-13. https://doi.org/10.1016/j.puhe.2019.01.012. Turner HC, Hori Y, Revill P, Rattanavipapong W, Arai K, Nonvignon J, et al. Analyses of the return on investment of public health interventions: a scoping review and recommendations for future studies. BMJ Glob Health. 2023;8(8). https://doi.org/10.1136/bmjgh-2023-012798. Milat AJ, King L, Rissel C, Bauman A, Redman S. The case for funding more intervention research in public health--policy maker and researcher perspectives. Aust N Z J Public Health. 2012;36(6):582-3. https://doi.org/10.1111/j.1753-6405.2012.00937.x. Scaccia JP, Cook BS, Lamont A, Wandersman A, Castellow J, Katz J, et al. A practical implementation science heuristic for organizational readiness: R = MC(2). J Community Psychol. 2015;43(4):484-501. https://doi.org/10.1002/jcop.21698. Proctor E, Luke D, Calhoun A, McMillen C, Brownson R, McCrary S, et al. Sustainability of evidence-based healthcare: research agenda, methodological advances, and infrastructure support. Implement Sci. 2015;10:88. https://doi.org/10.1186/s13012-015-0274-5. Additional Declarations No competing interests reported. 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In public health, optimization is defined as \u0026ldquo;a deliberate, iterative, and data-driven process to improve a health intervention and/or its implementation to meet stakeholder-defined public health impacts within resource constraints\u0026rdquo; (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The Dynamic Sustainability Framework (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) suggests that \u0026ldquo;interventions should not be considered optimized until they have been implemented, tested, and refined in settings where they will be ultimately delivered\u0026rdquo;. To improve population health, it is important to design evidence-based interventions (EBIs) that are scalable, monitor scale-up as it progresses, and seek ways to optimize implementation as scale-up proceeds. We define scale-up as \u0026ldquo;the process by which health interventions shown to be efficacious on a small scale and/or under controlled conditions are expanded under real-world conditions to reach a greater proportion of the eligible population, while retaining effectiveness\u0026rdquo; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Sustained effectiveness and costs associated with scaling-up EBIs are rarely investigated (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). That oversight needs to be addressed. Thus, researchers are encouraged to identify and justify costs associated with the implementation process and the intervention itself (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the factors that influence scale-up and sustainment of public health and health-promoting EBIs, funding looms large (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Healthcare decision-makers seek to improve health without increasing healthcare budgets. When comparing alternative courses of action, funding partners (often government agencies) increasingly scrutinize investments and consider costs along with other factors such as effectiveness, acceptability in context, scalability, and reach (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Health economic evaluation provides a framework to compare the costs and benefits of different alternatives over various time horizons\u0026mdash;outcomes of the evaluation inform decision making (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Despite its value to decision makers, few studies examined the costs of implementing effective health-promoting EBIs across a long period of scale-up; nor have they studied the economic consequences associated with optimization (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). We sought to fill this information gap drawing upon our decade of experience implementing and scaling up Choose to Move (CTM).\u003c/p\u003e \u003cp\u003eCTM (detailed below) is a scalable, health-promoting EBI for older adults. CTM was co-designed and scaled up across British Columbia, Canada with community and government partners using a phased approach. Elsewhere, we describe our formal, systematic, and data-driven co-adaptation process prior to implementing CTM across each phase of (horizontal (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)) scale-up (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). We aimed to retain fidelity to the \u0026lsquo;core functions\u0026rsquo; of CTM across phases (defined as behavior change techniques that theoretically drive positive health outcomes (e.g., goal setting) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)). Briefly, we began with a formative evaluation (2015). Phases 1 and 2 comprised the pilot and early scale-up of CTM (2016-17). For Phase 3 (2018-20), CTM was adapted with feedback from older adults and delivery partners to establish \u0026ldquo;best fit\u0026rdquo; and to support broad scale-up (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). In response to COVID-19 public health restrictions (2020), CTM was adapted with delivery partners for delivery in the virtual environment (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). For Phase 4 (2020-22), CTM was adapted to selectively reduce resource use (program delivery hours by activity coaches); virtual delivery remained an option (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). We demonstrated that CTM could be implemented with fidelity at increasingly larger scale (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), in different communities, and after adapting for virtual delivery (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) with reduced resource use (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Adaptations did not compromise the effectiveness of CTM (i.e., health benefits for older adult participants were retained).\u003c/p\u003e \u003cp\u003eOur current costing study has two objectives: 1) identify, measure, and value the costs of implementing the CTM intervention across four phases (7 years) of scale-up; and 2) analyze change in implementation costs alongside changes in intervention effect sizes to assess cost-consequence trends from Phases 1\u0026ndash;2 through Phase 4.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eChoose to Move\u003c/h2\u003e \u003cp\u003eChoose to Move comprises the program (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://choosetomove.ca\u003c/span\u003e\u003cspan address=\"https://choosetomove.ca\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and a suite of implementation strategies used to support implementation and scale-up. The CTM program is choice-based, coach- and peer-supported, and designed for low active (\u0026lt;\u0026thinsp;150 min/week moderate-to-vigorous physical activity (PA)) community-dwelling older adults. Participants are supported by an activity coach to choose physical activities that align with their personal preferences, health status, and available resources (\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The current 3-month CTM (Phase 4) program comprises a 30 min one-on-one consultation with a trained activity coach, and 8 group meetings with other participants, facilitated by the activity coach. We provide an overview of CTM Phases 1\u0026ndash;4 in Supplementary Table\u0026nbsp;1. Phase 4 continues to be scaled up across British Columbia; to date (March 2025)\u0026thinsp;\u0026gt;\u0026thinsp;7,000 older adults have participated in CTM.\u003c/p\u003e \u003cp\u003eImplementation (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) and scale-up (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) frameworks and principles (e.g., community partnerships) guided implementation and scale-up of CTM. Community-based delivery partner organizations offer the CTM program in recreation centres or virtually (e.g., on Zoom\u0026trade;). We initially partnered with two large community organizations (i.e., YMCA and British Columbia Recreation and Parks Association (BCRPA)) that have broad geographic reach through recreation facilities across British Columbia (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). In 2018 we recruited small partner organizations (e.g., neighborhood houses and seniors\u0026rsquo; centres) whose reach was more local. With government funding, the Active Aging Society (AAS; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.activeagingsociety.org\u003c/span\u003e\u003cspan address=\"https://www.activeagingsociety.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) provides broad functional and financial support to delivery partner organizations who hire activity coaches to deliver CTM under the umbrella of their organizations. The Central Support Unit (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), housed within the AAS, uses a suite of implementation strategies (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) to build capacity (e.g., provides tools, training and ongoing support) among community organizations that serve as delivery partners.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEvaluating CTM\u003c/h3\u003e\n\u003cp\u003ePrevious studies Elsewhere, we describe outcomes of the CTM evaluation across all phases of implementation (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Briefly, we used a hybrid type 2 effectiveness-implementation study design (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) to evaluate CTM. For the implementation evaluation we were guided by a proposed minimum data set of implementation indicators (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). For the effectiveness (outcomes) evaluation, participants were \u0026gt;\u0026thinsp;60 years, able to read and understand English, reported low levels of PA (less than 150 minutes/week), and had no contraindications to participating in PA. Participants were recruited via local promotions, Facebook, the CTM website, media advertisements and word of mouth. The primary outcome across all phases of CTM was self-reported PA (number of days in the previous week with 30 minutes or more of moderate-to-vigorous PA) using a validated single-item PA measure (\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Secondary outcomes were mobility, social isolation and loneliness, and health related quality of life.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eGenerally, CTM enhanced participants\u0026rsquo; engagement in PA, increased mobility and decreased social isolation and loneliness across all phases (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). We observed a small \u003cem\u003evoltage drop\u003c/em\u003e (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) in the magnitude of positive change in health outcomes (PA, mobility, loneliness) between Phases 1\u0026ndash;2 and Phase 3. However, there was no further \u0026lsquo;scale-up penalty\u0026rsquo; (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) for these outcomes between Phases 3 and 4 (except for loneliness in participants aged 75 years and older). In fact, we noted a voltage \u0026lsquo;surge\u0026rsquo; in the positive effects of CTM on PA, mobility and social isolation between Phases 3 and 4 (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Outcomes did not differ between CTM delivery modes (in-person or virtual); many health benefits were maintained one year after the end of formal participation in CTM Phases 1\u0026ndash;2 and Phase 3 (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eCurrent study\u003c/em\u003e: For the current study, we used data from our two large delivery partners to compare effectiveness across 7 years of CTM scale-up (2016\u0026ndash;2022). Specifically, we compared CTM Phase 4 effect sizes (change from baseline with 95% confidence interval, CI) for primary outcomes to those of Phases 1\u0026ndash;2 and Phase 3 effect sizes. We used the approach of McCrabb et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) to determine the proportion of the effect size retained in Phase 4 as compared with Phase 3 as: (Phase 4 effect size / Phases 3 effect size) * 100. We describe percent change narratively. Values greater than 100% indicate a greater benefit of the intervention in Phase 4 as compared with Phase 3; values of 50% indicate that Phase 4 was half as effective as Phase 3; and values less than 0% (negative values) indicate that the direction of the effect in Phase 4 was opposite that of Phase 3. We used the same approach to determine the proportion of effect size retained in Phase 4 as compared with Phases 1\u0026ndash;2.\u003c/p\u003e\n\u003ch3\u003eCost and cost-consequence analysis\u003c/h3\u003e\n\u003cp\u003eWe identified, measured, and valued the costs and outcomes of CTM Phases 1\u0026ndash;4, against a \u0026lsquo;do nothing\u0026rsquo; alternative. We chose this approach because health promotion activities for older adults are not routinely delivered in Canada. Thus, CTM does not displace usual practice activities or investments in these activities. We adopted a program provider perspective to reflect the real-world implementation of CTM, over a trial time horizon (3 months).\u003c/p\u003e \u003cp\u003eWe identified, measured, and valued financial costs and opportunity costs associated with implementation of CTM Phases 1\u0026ndash;4. We define implementation costs as all costs associated with delivering CTM and the provision of ongoing implementation support to partner organizations throughout the lifecycle of program delivery (e.g., activity coach hours, equipment and resources, support staff). Financial costs included the costs of goods and services directly purchased to implement CTM which hold a market value. We define opportunity cost as the value of opportunities forgone. That is, any non-financial investment of resources, labor time, or products associated with implementing CTM. We used trial administrative records kept by the Central Support Unit to retrospectively identify resource use associated with implementation of Phases 1\u0026ndash;2 across our delivery partners (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Delivery partners used a cost-capture tool developed in Microsoft Excel (2013) to prospectively collect cost data for Phase 3 and Phase 4 using a time-driven activity-based costing approach (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). The cost capture tool included the following categories: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) labor (staff, including overhead to allow for additional costs of employment), (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) materials such as non-labor cost items (e.g., stationary, education materials, electronic hardware or software), (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) joint costs such as those incurred in connection with multiple projects (e.g., maintenance costs of a website portal supporting different interventions); capital costs such as those for one-off investments (e.g., purchase of computers), and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) miscellaneous costs (i.e., costs not easily classified into the other categories such as venue hire and travel). Our activity-based costing approach involved three parameters: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) frequency of activity, (e.g., training session, phone call with support staff) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) resources required to perform one single event of the activity, and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) price or value of the resources used to perform the activity (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Cost data were treated as counts of resource use, weighted by unit costs. The cost for each phase was determined by summing the costs relevant to and coded for that phase. The cost per participant was calculated as the cost of implementing CTM divided by the number of participants. Development, research and evaluation costs were excluded from cost and cost-consequence analyses as we focus on the costs of implementing CTM.\u003c/p\u003e \u003cp\u003eThe program provider perspective for this evaluation meant costs to participants and private care providers (including opportunity costs) were not included. Costs incurred after 12-months were not discounted as the trial time horizon was three months and was a function of the study design and not the expected timeline for real world expenses. All costs were adjusted for inflation using annual consumer price index (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) and reported in 2024 Canadian dollars (\u003cspan\u003e$\u003c/span\u003eCDN).\u003c/p\u003e \u003cp\u003eWe conducted a series of trial-based cost and cost-consequence analyses of health outcomes common across CTM Phases 1 through 4. Effectiveness is a prerequisite for economic evaluation; therefore, we included only outcomes that demonstrated a statistically significant effect size (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Analyses were performed in R version 4.3.3 using the tidyverse package for data analysis (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Results of the cost consequence analysis are presented as a scorecard comprising the total cost of CTM alongside the range of outcomes reflected in the primary and secondary trial outcomes (consequences). We conducted the economic evaluation and report findings in accordance with the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) publication guidelines and good reporting practices (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) (Supplementary Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eIn practice, there is expected variation around estimates of cost, particularly when programs are implemented in diverse settings, with different program providers, and at scale. To explore the impact of variation on CTM program costs we conducted four scenario analyses to estimate a plausible upper and lower range and demonstrate the impact of uncertainty in key parameters on program delivery costs. Specifically, we calculated the average cost per program and per participant for each program provider (delivery partner). We estimated the range (low and high) of costs by: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) calculating the range of material costs (years with the least and most number of facilities grants; funds provided to each delivery site (BCRPA sites only) to support program implementation) and (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) calculating the labor costs if Central Support Unit staff time was increased or decreased by 20% (equivalent to 0.2 FTE). We used these estimates to calculate the range of costs per participant and per program in a \u0026lsquo;best case scenario\u0026rsquo; (lowest number of facilities grants provided and a 20% reduction in central support staff time) and \u0026lsquo;worst case scenario\u0026rsquo; (highest number of facilities grants provided and a 20% increase in central support staff time). We excluded retrospective cost data (Phases 1\u0026ndash;2) from the scenario analyses because they provided less detail than did the prospective Phase 3 and Phase 4 data.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eTable\u0026nbsp;1 describes the number of programs and participants across Phases 1–2, Phase 3 and Phase 4. Table\u0026nbsp;1 also summarizes the total cost of implementing CTM across all phases and per participant. The cost per participant of implementing CTM Phase 4 was slightly more than one third (37%) of the cost per participant at Phases 1–2. We note a reduction of $803,463 in total costs and $339 in cost per participant between Phase 3 and Phase 4. Variation from differences in delivery partner provided the greatest individual impact on program costs (Range $894 - $1,017). The scenario that included variation in both facility grants, and staff time had the greatest overall impact on program costs (Range $866 - $1,014).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e The total cost of implementing Choose to Move across all phases and per participant (Canadian 2024 dollars, CDN$), including scenario analyses.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"652\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePhase 1-2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Phase 3\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Phase 4\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eParticipants (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e534\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1668\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePrograms (n)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePhase 1-2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Phase 3\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Phase 4\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Δ (Phase 1–2 to 4)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal cost (CDN$)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e863,559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1,564,446\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e760,983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e102,576\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAverage cost per participant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1,617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1,018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAverage cost per program\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e15,701\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e9,481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e5,595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e10,106\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eScenario Analyses\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Phase 3\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Phase 4\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Low ($)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;High ($)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Low ($) \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;High ($)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelivery Partner\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAverage cost per participant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1,017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e585\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e630\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAverage cost per program\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e8,712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e11,020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e5,531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e5,731\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFacility Grants\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAverage cost per participant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e919\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e608\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAverage cost per program\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e9,289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e9,740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e5,513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e5,681\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eStaff Time\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAverage cost per participant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e908\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e574\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e625\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAverage cost per program\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e9,177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e9,786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e5,359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e5,832\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFacilities and Staff Time \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAverage cost per participant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1,014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e634\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAverage cost per program\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e8,757\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e10,254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e5,277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e5,917\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cdiv\u003e\n \u003cdiv align=\"left\"\u003eThe evidence-based optimization and reduction in activity coach hours required to deliver Phase 4 resulted in a decrease in total labor costs between Phases 3 and 4 ($992 per program). Cost of materials decreased between Phase 3 and Phase 4, whereas the cost of miscellaneous items increased by 8% ($52,169) as a proportion of the total budget (Table 2). Across all three phases, labor accounted for 63% - 80% of total CTM implementation costs.\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eProportion of Choose to Move implementation costs associated with each resource use (labor, materials, miscellaneous) category. Costs are in Canadian dollars (2024).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eLabor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eMaterials\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eMiscellaneous\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCost ($)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCost ($)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCost ($)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal cost ($)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhases 1–2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e693,270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e119,816\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50,473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e863,559\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhase 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e981,086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e559,614\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23,746\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1,564,446\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhase 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e565,171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e119,897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e75,915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e760,983\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe effectiveness of CTM Phases 1–2, Phase 3 and Phase 4 for each statistically significant outcome and age group is published elsewhere (12, 14, 15). We compared effect sizes of CTM Phase 4 outcomes to those of Phases 1–2 and Phase 3 (Table\u0026nbsp;3). When comparing CTM effect sizes (95% CI) for primary outcomes between Phase 3 and Phase 4, there was no voltage drop in effect size for PA, mobility, and social isolation for the full cohort, or in loneliness for those aged \u0026lt; 75 years. The voltage drop detected in social isolation for those aged \u0026gt; 75 years was small (6%); for loneliness the voltage drop was 70%. Between Phases 1–2 and Phase 4, social isolation improved across the full cohort and both age groups. The magnitude of improvement in PA, mobility, and loneliness decreased across CTM Phases 1–2 to Phase 4, suggesting a voltage drop in effectiveness as CTM was scaled up.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eComparison of Choose to Move intervention effect sizes (95% CI) for primary outcomes between Phase 3 and Phase 4 and between Phase 1–2 and Phase 4. Costs are in Canadian dollars (2024).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"10\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePhase 4 Effect Size\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePhase 3 to 4: Proportion (%) of CTM effect achieved post-optimization\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePhases 1–2 to 4: Proportion (%) of CTM effect achieved with optimization\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFull cohort\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026lt; 75 yrs\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e≥ 75 yrs\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFull cohort\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026lt; 75 yrs\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e≥ 75 yrs\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFull cohort\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026lt; 75 yrs\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e≥ 75 yrs\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysical activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(1.2, 1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(1.3, 1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.7, 1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMobility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(-9.7, -0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(-11.2, -0.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-11.8, 5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial isolation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e522\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(0.58, 1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(0.67, 1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.08, 0.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLoneliness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(-0.24, -0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(-0.33, -0.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(-0.14, 0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e As per McCrabb et al. (28) effect size was calculated as change from baseline. CTM Phase 4 effect sizes are also reported elsewhere (12).\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e (Phase 4 effect size / Phase 3 effect size) * 100. Values greater than 100% indicate a greater benefit of the intervention in Phase 4 than in Phase 3; values of 50% indicate that Phase 4 was half as effective as Phase 3; and values less than 0% (negative values) indicate that the direction of the effect in Phase 4 was opposite that in Phase 3. The same approach was used to compare Phase 4 with Phases 1–2.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eAs governments and health care decision makers grapple with escalating healthcare costs associated with aging populations, upstream investment in health promotion may provide one solution. To guide decision making, it is imperative that those who fund scaled-up health-promoting EBIs have evidence (data) to support effectiveness, scalability and implementation costs of the intervention. These data are essential to review and prioritize investment decisions. However, very few studies described the cost, cost consequences and effectiveness of health-promoting EBIs as they proceed along the scale-up continuum (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Therefore, our study fills this gap. Specifically, we extend our previous work (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) and report costs and cost consequences of an effective health-promoting EBI across 7 years of scale-up.\u003c/p\u003e \u003cp\u003eThe Choose to Move context is unique—as we are unaware of any other health-promoting EBIs for older adults that were effectively scaled up with government support over the longer term. This is key, as health-promoting EBIs must be scaled up (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) and sustained (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) to improve health at the population level. Optimizing CTM to reduce cost in Phase 4 while maintaining effectiveness is also a novel aspect of our study.\u003c/p\u003e \u003cp\u003eWe also extend the literature and our previous work (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) by identifying, measuring and valuing the financial and opportunity costs associated with implementation of CTM across 7 years of scale-up. Our key finding was that total implementation costs for CTM between Phase 3 and Phase 4 decreased by 36%. Although CTM implementation costs were reduced (due primarily to a 40% reduction in activity coach hours (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), participant-level benefits (PA, mobility and social isolation in all participants; loneliness in those \u0026lt; 75 years) in Phase 4 were comparable to, or greater than those observed in Phase 3.\u003c/p\u003e \u003cp\u003eScaled-up, optimized (to reduce cost) health-promoting EBIs should not compromise effectiveness. We reported a small voltage drop between CTM Phases 1–2 and Phase 3 (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). However, as we continued to scale and optimize CTM in Phase 4 to reduce resource use, effect sizes for outcomes (except loneliness) were similar or greater than those in Phase 3. This finding counters the voltage drop theory, which suggests that as community-based PA (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) and obesity (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) interventions go to scale, the magnitude of their effect diminishes by 50–60%, on average. Despite this, positive changes in most health outcomes remained significant (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The difference in these findings across phases may be due, to slightly lower baseline PA in our Phase 4 cohort (2.0 days/week; 95% CI: 1.8, 2.1) who joined CTM during the COVID-19 pandemic, as compared with Phase 3 participants (2.3 days/week; 95% CI: 2.1, 2.6) (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). The substantial decrease in social isolation (voltage surge) between Phases 1–2 and Phase 3 (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), and between Phases 3 and 4 may reflect how CTM was adapted to create more opportunities for participants to socially connect in group sessions (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). We demonstrated that a health-promoting EBI can be optimized for cost while retaining core functions and program effectiveness.\u003c/p\u003e \u003cp\u003eUsing economic evidence to inform how best to develop and scale-up an intervention is of great value (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Yet little is known about how to evaluate economic aspects of scaling up programs and strategies that comprise health-promoting EBIs (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Nor is there much evidence to support how best to use economic data to optimize effective, scalable health-promoting EBIs. Findings from our study in an implementation, health promotion research context, highlight an emergent application of economic analysis. As cost savings were realized for CTM delivery without compromising health benefits, we also urge greater investment in this area of research.\u003c/p\u003e \u003cp\u003eAll areas of health and medical research focus on the rigorous measurement of health, program, and (less so) implementation outcomes. However, methods for measuring costs are neither systematic nor comprehensive (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Additionally, economic evaluation in public health or health promotion is not routine, and cost data for these interventions are of mixed quality (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Poor quality cost data are detrimental, as reliable data form the foundation of economic evaluations. Without reliable estimates, evaluation results could mislead decision makers and have significant implications for healthcare providers and patients (\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e–\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEconomic evaluation of effectively scaled-up population health EBIs have encountered challenges. First, methods used to evaluate value for money vary (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Second, there is little agreement on how best to determine ongoing investment in implementation or scale-up of EBIs (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). This could be because of different time horizons between conducting public health or health-promoting EBIs and realizing participant-level health benefits. Benefits may also occur outside the healthcare system, which precludes reliably measuring an EBI’s value (or return on investment) to the health system. A third challenge is that differences in healthcare financing and populations assessed limits transferability of cost data to different settings.\u003c/p\u003e \u003cp\u003eActivities that drove successful implementation of CTM were related to building capacity within two larger community organizations that served as delivery partners (i.e., to implement CTM among their older adult constituents). Readiness-building activities (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e) were embedded within the essential role of the Central Support Unit. We consider the role of the Central Support Unit as the foundation upon which EBIs are effectively implemented, scaled up, and sustained. This team provided training, tools and ongoing support directly to delivery partners and activity coaches while (indirectly) supporting participants. Thus, it comes as no surprise that as a proportion of the total cost of CTM, labor (including activities of the Central Support Unit) was the largest cost category across all CTM Phases. The Central Support Unit’s role in building capacity, trust, and a sense of community among community partner organizations, activity coaches and participants takes time, often with uncertain outcomes. We have begun to experience that Central Support Unit costs escalate further in smaller more poorly resourced community organizations that are less ‘ready’ (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur study has several strengths. First, we contribute to the scant literature that has determined costs and consequences of health-promoting EBIs across scale-up. We use a rare real-world example of a scaled-up health-promoting EBI (CTM) to derive our data. Second, we specify the cost of resource use within the total cost of implementing CTM. Third, we highlight that CTM can be optimized for cost while not compromising health outcomes; this finding can be applied to other health-promoting EBIs.\u003c/p\u003e \u003cp\u003eWe also acknowledge several limitations of our study. First, to minimize the likelihood of missing data in the retrospective costing, all items included in the cost analysis were identified from trial records. Where possible we triangulated data against a second data point or source and confirmed it by the Central Support Unit. Second, we did not impute missing outcomes data. Third, CTM retrospective data (Phases 1–2) did not provide sufficient detail to delineate material costs for research from material costs associated with development. Thus, these data are missing from Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and the scenario analyses.\u003c/p\u003e "},{"header":"Conclusion and future research","content":"\u003cp\u003eIdentifying costs associated with scale-up and value for money of health-promoting and public health EBIs is of high priority (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). We demonstrated an emergent application of economic analysis within scale-up science and contend that investments in advancing this type of research are worthwhile. Researchers might further explore ways to maximize the public health impact of EBIs while minimizing costs. Importantly, future studies should investigate whether a positive intervention effect (at lower cost) can be sustained over time, and the economic cost of implementation strategies (specifically) used in public health interventions (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Although links between scaling up and sustaining EBIs have cost implications, factors and processes that influence both are not well understood. Finally, we urge researchers (including implementation scientists) to identify ways to prospectively weave economic evaluation into implementation, scale-up and sustainment science as part of standard practice. By providing cost and outcomes data, decision makers are better positioned to make informed investments in innovative public health and health-promoting EBIs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participateEthics approval was obtained from the University of British Columbia Research Ethics Board (H15-02522; H20-00780). All study participants provided informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed during the current study are not publicly available as consent was not obtained for this. However, data are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eNone to declare\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe British Columbia Ministry of Health provided funds to the Active Aging Society to support delivery of Choose to Move. The Canadian Institutes of Health Research (PJT-169159) funded the evaluation of Choose to Move. The funders had no role in study design, data collection, analysis or interpretation, or in writing the manuscript.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions\u003c/p\u003e\n\u003cp\u003eConceptualization, Z.S., H.Mc, H.Mac, M.B.P, and L. N.; methodology, Z.S., M.B.P, H.Mc, H.Mac, L. N; formal analysis, Z.S. and H.Mac; writing \u0026mdash; original draft preparation, Z.S., H.Mc; writing \u0026mdash; review and editing, Z.S., H.Mc, H.Mac, M.B.P, \u0026nbsp;and L.N.; and project administration, Z.S., H.Mc, H.Mac and L.N. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful for the ongoing support of Choose to Move from the BC Ministry of Health, the Active Aging Society and delivery partner organizations across BC. We thank all the older adults from across the province who participated in Choose to Move. Finally, we are grateful for the dedication of staff and trainees from the Active Aging Research Team who are the engine that powers operations and evaluation of CTM. In particular, we acknowledge the contributions of Christa Hoy, Program and Evaluation Manager, who assisted with data collection for this study.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWolfenden L, Bolsewicz K, Grady A, McCrabb S, Kingsland M, Wiggers J, et al. Optimisation: defining and exploring a concept to enhance the impact of public health initiatives. Health research policy and systems. 2019;17(1):108. https://doi.org/10.1186/s12961-019-0502-6.\u003c/li\u003e\n\u003cli\u003eChambers DA, Glasgow RE, Stange KC. The dynamic sustainability framework: addressing the paradox of sustainment amid ongoing change. Implement Sci. 2013;8:117. https://doi.org/10.1186/1748-5908-8-117.\u003c/li\u003e\n\u003cli\u003eMilat AJ, Bauman A, Redman S. Narrative review of models and success factors for scaling up public health interventions. 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Factors that influence implementation at scale of a community-based health promotion intervention for older adults. BMC Public Health. 2019;19(1):1619. https://doi.org/10.1186/s12889-019-7984-6.\u003c/li\u003e\n\u003cli\u003eDurlak JA, DuPre EP. Implementation matters: a review of research on the influence of implementation on program outcomes and the factors affecting implementation. Am J Community Psychol. 2008;41(3-4):327-50. https://doi.org/10.1007/s10464-008-9165-0.\u003c/li\u003e\n\u003cli\u003eWandersman 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. https://doi.org/10.1007/s10464-008-9174-z.\u003c/li\u003e\n\u003cli\u003eYamey G. Scaling up global health interventions: a proposed framework for success. PLoS Med. 2011;8(6):e1001049. https://doi.org/10.1371/journal.pmed.1001049.\u003c/li\u003e\n\u003cli\u003eSims-Gould J, McKay HA, Franke T. How central support built capacity to deliver a health-promoting intervention for older adults in Canada. Health Soc Care Community. 2022;30(5):e3063-e74. https://doi.org/10.1111/hsc.13751.\u003c/li\u003e\n\u003cli\u003eProctor EK, Powell BJ, McMillen JC. Implementation strategies: recommendations for specifying and reporting. Implement Sci. 2013;8:139. https://doi.org/10.1186/1748-5908-8-139.\u003c/li\u003e\n\u003cli\u003eNettlefold L, Gray SM, Sims-Gould J, McKay HA. From Start-Up to Scale-Up of a Health-Promoting Intervention for Older Adults: The Choose to Move Story. Kinesiol Rev. 2023;12(1):76-86. https://doi.org/10.1123/kr.2022-0034.\u003c/li\u003e\n\u003cli\u003eCurran GM, Bauer M, Mittman B, Pyne JM, Stetler C. 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Brit J Sport Med. 2013;47(1):44-8. https://doi.org/10.1136/bjsports-2011-090899.\u003c/li\u003e\n\u003cli\u003eMacdonald HM, Nettlefold L, Bauman A, Sims-Gould J, McKay HA. Pragmatic Evaluation of Older Adults\u0026apos; Physical Activity in Scale-Up Studies: Is the Single-Item Measure a Reasonable Option? J Aging Phys Act. 2022;30(1):25-32. https://doi.org/10.1123/japa.2020-0412.\u003c/li\u003e\n\u003cli\u003eMcCrabb S, Lane C, Hall A, Milat A, Bauman A, Sutherland R, et al. Scaling-up evidence-based obesity interventions: A systematic review assessing intervention adaptations and effectiveness and quantifying the scale-up penalty. Obes Rev. 2019;20(7):964-82. https://doi.org/10.1111/obr.12845.\u003c/li\u003e\n\u003cli\u003eMcKay HA, Nettlefold L, Sims-Gould J, Macdonald HM, Khan KM, Bauman A. Status Quo or Drop-Off: Do Older Adults Maintain Benefits From Choose to Move-A Scaled-Up Physical Activity Program-12 Months After Withdrawing the Intervention? 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Consumer price index portal Online: Government of Canada 2022 [Available from: https://www.statcan.gc.ca/en/subjects-start/prices_and_price_indexes/consumer_price_indexes.\u003c/li\u003e\n\u003cli\u003eWickham et al. Welcome to the Tidyverse. Journal of Open Source Software. 2019;4(43):1686. https://doi.org/https://doi.org/10.21105/joss.01686.\u003c/li\u003e\n\u003cli\u003eBrown V, Tran H, Williams J, Laws R, Moodie M. Exploring the economics of public health intervention scale-up: a case study of the Supporting Healthy Image, Nutrition and Exercise (SHINE) cluster randomised controlled trial. BMC Public Health. 2022;22(1):1338. https://doi.org/10.1186/s12889-022-13754-0.\u003c/li\u003e\n\u003cli\u003eMilat AJ, Newson R, King L, Rissel C, Wolfenden L, Bauman A, et al. A guide to scaling up population health interventions. Public Health Res Pract. 2016;26(1):e2611604. https://doi.org/10.17061/phrp2611604.\u003c/li\u003e\n\u003cli\u003eShelton RC, Cooper BR, Stirman SW. The Sustainability of Evidence-Based Interventions and Practices in Public Health and Health Care. Annu Rev Public Health. 2018;39:55-76. https://doi.org/10.1146/annurev-publhealth-040617-014731.\u003c/li\u003e\n\u003cli\u003eLane C, McCrabb S, Nathan N, Naylor PJ, Bauman A, Milat A, et al. How effective are physical activity interventions when they are scaled-up: a systematic review. Int J Behav Nutr Phys Act. 2021;18(1):16. https://doi.org/10.1186/s12966-021-01080-4.\u003c/li\u003e\n\u003cli\u003eMilat AJ, King L, Bauman AE, Redman S. The concept of scalability: increasing the scale and potential adoption of health promotion interventions into policy and practice. Health Promot Int. 2013;28(3):285-98. https://doi.org/10.1093/heapro/dar097.\u003c/li\u003e\n\u003cli\u003eBrundisini F, Zomahoun HTV, L\u0026eacute;gar\u0026eacute; F, Rh\u0026eacute;ault N, Bernard-Uwizeye C, Massougbodji J, et al. Economic evaluations of scaling up strategies of evidence-based health interventions: a systematic review protocol. BMJ Open. 2021;11(9):e050838. https://doi.org/10.1136/bmjopen-2021-050838.\u003c/li\u003e\n\u003cli\u003eReeves P, Edmunds K, Searles A, Wiggers J. Economic evaluations of public health implementation-interventions: a systematic review and guideline for practice. Public Health. 2019;169:101-13. https://doi.org/10.1016/j.puhe.2019.01.012.\u003c/li\u003e\n\u003cli\u003eTurner HC, Hori Y, Revill P, Rattanavipapong W, Arai K, Nonvignon J, et al. Analyses of the return on investment of public health interventions: a scoping review and recommendations for future studies. BMJ Glob Health. 2023;8(8). https://doi.org/10.1136/bmjgh-2023-012798.\u003c/li\u003e\n\u003cli\u003eMilat AJ, King L, Rissel C, Bauman A, Redman S. The case for funding more intervention research in public health--policy maker and researcher perspectives. Aust N Z J Public Health. 2012;36(6):582-3. https://doi.org/10.1111/j.1753-6405.2012.00937.x.\u003c/li\u003e\n\u003cli\u003eScaccia JP, Cook BS, Lamont A, Wandersman A, Castellow J, Katz J, et al. A practical implementation science heuristic for organizational readiness: R = MC(2). J Community Psychol. 2015;43(4):484-501. https://doi.org/10.1002/jcop.21698.\u003c/li\u003e\n\u003cli\u003eProctor E, Luke D, Calhoun A, McMillen C, Brownson R, McCrary S, et al. Sustainability of evidence-based healthcare: research agenda, methodological advances, and infrastructure support. Implement Sci. 2015;10:88. https://doi.org/10.1186/s13012-015-0274-5.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-behavioral-nutrition-and-physical-activity","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijbn","sideBox":"Learn more about [International Journal of Behavioral Nutrition and Physical Activity](http://ijbnpa.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ijbn/default.aspx","title":"International Journal of Behavioral Nutrition and Physical Activity","twitterHandle":"@IJBNPA","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"cost, cost analysis, cost consequence, healthy aging, implementation, scale-up","lastPublishedDoi":"10.21203/rs.3.rs-6331081/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6331081/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eFew studies have examined costs of implementing evidence-based interventions (EBIs) as scale-up proceeds. Across four phases, we co-adapted and scaled up an effective EBI designed to promote older adults\u0026rsquo; health (Choose to Move; CTM). Following formative evaluation (2015), Phases 1\u0026ndash;2 (2016-17) comprised the CTM pilot and early scale-up. For Phase 3 (2018-20), we adapted CTM to establish \u0026ldquo;best fit\u0026rdquo; and support broad scale-up. In response to COVID-19 (2020), we adapted CTM for virtual delivery. For Phase 4 (2020-22), we adapted CTM to reduce resource use.\u003c/p\u003e\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eWe aimed to 1) identify, measure, and value costs of implementing CTM across four phases (7 years) of scale-up; and 2) analyze change in implementation costs alongside changes in intervention effect sizes to assess cost-consequence trends from Phases 1\u0026ndash;2 through Phase 4.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a trial-based cost and cost-consequence analysis of CTM Phases 1\u0026ndash;2 through Phase 4 from a program provider perspective. Program costs were identified, measured, and valued using micro-costing techniques; variation in program cost was explored using scenario analyses. We compared Phase 4 intervention effects against those of Phases 1\u0026ndash;2 and Phase 3 to examine how changes in implementation costs corresponded with changes in effect size.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e For Phases 1\u0026ndash;2, total cost (\u003cspan\u003e$\u003c/span\u003eCDN, 2024) of CTM implementation was \u003cspan\u003e$\u003c/span\u003e863,559 for 55 programs (534 participants; \u003cspan\u003e$\u003c/span\u003e1,617/participant). Phase 3 costs were \u003cspan\u003e$\u003c/span\u003e1,564,446 for 165 programs (1668 participants; \u003cspan\u003e$\u003c/span\u003e938/participant). Phase 4 costs were \u003cspan\u003e$\u003c/span\u003e760,983 for 136 programs (1270 participants; \u003cspan\u003e$\u003c/span\u003e599/participant), a reduction of 63% and 36% compared with Phases 1\u0026ndash;2 and Phase 3, respectively. Compared with Phases 1\u0026ndash;2, Phase 4 had a greater positive effect on social isolation but effect sizes for physical activity, mobility and loneliness were reduced. Phase 4 had a greater positive effect on physical activity, mobility, social isolation, and loneliness (for those\u0026thinsp;\u0026lt;\u0026thinsp;75 years), compared with Phase 3.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eCosts associated with broad scale-up of EBIs are rarely investigated. We sought innovative ways to maximize impact of a health-promoting EBI, while minimizing costs. Our analysis highlights how strategic adaptations can enhance cost efficiency while improving intervention outcomes; this represents an emergent application of economic analysis within scale-up science.\u003c/p\u003e","manuscriptTitle":"Is it possible to optimize costs as scale-up of Choose to Move--an effective health-promoting intervention for older adults--proceeds?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-07 07:52:24","doi":"10.21203/rs.3.rs-6331081/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-06T20:36:14+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-06T18:28:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"152366194503408835078544961739329554049","date":"2025-07-13T23:22:21+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-23T09:02:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"259823578463467081299994391506207344638","date":"2025-05-14T07:31:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-15T17:43:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-31T22:49:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-31T22:49:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Behavioral Nutrition and Physical Activity","date":"2025-03-28T23:07:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-behavioral-nutrition-and-physical-activity","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijbn","sideBox":"Learn more about [International Journal of Behavioral Nutrition and Physical Activity](http://ijbnpa.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ijbn/default.aspx","title":"International Journal of Behavioral Nutrition and Physical Activity","twitterHandle":"@IJBNPA","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7e34a49d-5543-4b35-9a55-6fff22963869","owner":[],"postedDate":"April 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T16:09:49+00:00","versionOfRecord":{"articleIdentity":"rs-6331081","link":"https://doi.org/10.1186/s12966-025-01826-4","journal":{"identity":"international-journal-of-behavioral-nutrition-and-physical-activity","isVorOnly":false,"title":"International Journal of Behavioral Nutrition and Physical Activity"},"publishedOn":"2025-11-13 15:57:49","publishedOnDateReadable":"November 13th, 2025"},"versionCreatedAt":"2025-04-07 07:52:24","video":"","vorDoi":"10.1186/s12966-025-01826-4","vorDoiUrl":"https://doi.org/10.1186/s12966-025-01826-4","workflowStages":[]},"version":"v1","identity":"rs-6331081","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6331081","identity":"rs-6331081","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}