Are costs optimized as scale-up of Choose to Move–an effective health-promoting intervention for older adults–proceeds?

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. 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. 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. 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 135 programs (1278 participants; $595/participant), a reduction of 63% and 37% 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 and mobility in all participants, and loneliness among those < 75 years, compared with Phase 3. 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. Retrospectively registered at ClinicalTrials.gov, NCT05678985 (CTM Phase 4) and NCT05497648 (CTM Phase 3).

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Publication Details

Journal
International Journal of Behavioral Nutrition and Physical Activity
Published
2025-11-13
DOI
https://doi.org/10.1186/s12966-025-01826-4
Citations
1
Primary Topic
Health Policy Implementation Science
Type
article
Field-Weighted Citation Impact
2.82

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article

Are costs optimized as scale-up of Choose to Move–an effective health-promoting intervention for older adults–proceeds?

Marina B. Pinheiro, Lindsay Nettlefold, Heather McKay, Zoë Szewczyk et al.
1 citations
International Journal of Behavioral Nutrition and Physical Activity
Health Policy Implementation Science
2.82
article

Are costs optimized as scale-up of Choose to Move–an effective health-promoting intervention for older adults–proceeds?

Marina B. Pinheiro, Lindsay Nettlefold, Heather McKay, Zoë Szewczyk, Joanie Sims‐Gould, Heather Macdonald
article en
1 citations

Abstract

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. 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. 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. 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 135 programs (1278 participants; $595/participant), a reduction of 63% and 37% 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 and mobility in all participants, and loneliness among those < 75 years, compared with Phase 3. 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. Retrospectively registered at ClinicalTrials.gov, NCT05678985 (CTM Phase 4) and NCT05497648 (CTM Phase 3).

International Journal of Behavioral Nutrition and Physical ActivityVol. 22(1)
The University of Sydney (AU), University of British Columbia (CA), Institute for Musculoskeletal Health (AU), Active Aging Canada (CA)
Ministry of Health, British Columbia, Canadian Institutes of Health Research
Openalex Percentile: Top 7%
Health Policy Implementation Science
2.82
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