Scaling Up a Diabetes Prevention Program in Geographically and Ethnoculturally Diverse Urban Regions of Canada: Protocol for a Hybrid Type 2 Implementation-Effectiveness Study (Preprint)
Bibliographic record
Abstract
BACKGROUND It is estimated that type 2 diabetes (T2D) impacts an estimated 5.3 million Canadians, despite the condition being largely preventable. Laboratory-based diabetes prevention programs (DPPs) have limited effectiveness when translated into community settings due to their low-quality delivery and inability to reach people in the community most in need. To date, no community-based DPPs have been implemented nationwide across Canada. Small Steps for Big Changes (SSBC) is a diet and physical activity counseling intervention that significantly reduces the risk of developing T2D and has been designed for feasible delivery by community-dwelling peers. To ensure maximum public health impact, SSBC must be optimally implemented, demonstrate effectiveness for diverse groups, and be sustainable over time. OBJECTIVE This project aims to adapt SSBC and evaluate the implementation, effectiveness, and sustainability of SSBC in diverse urban communities across Canada. METHODS A hybrid type 2 implementation-effectiveness study design using multiple and mixed methods will be used to evaluate the implementation and effectiveness of SSBC over 6 years in partnership with 11 regional Young Men’s Christian Associations across 8 provinces in Canada. Beginning in 2024, we will (1) adapt and implement SSBC in diverse urban cities across Canada; (2) examine the implementation (including implementation strategies), effectiveness, and cost-effectiveness of SSBC (2024-2028); and (3) determine the sustainability of SSBC at each delivery location (2028-2029). Data will be collected from SSBC clients, coaches, site leads, and senior leadership municipality partners. The project will be overseen by an advisory group and 3 committees focused on sex, gender, and inclusivity; program evaluation; and diabetes prevention engagement. This study has received ethical approval from the University of British Columbia Clinical Research Ethics Board (H23-01930). RESULTS Funding for this project began in October 2022, and Institutional Review Board approval was obtained in October 2023. Program implementation within each region is occurring in a phased approach, with partners beginning program delivery in one site (2024-2025) before expanding to any additional locations (2025-2027). Program enrollment occurs continuously during the implementation phase across all sites. From 2024-2025, a total of 13 delivery sites began program delivery, 722 participants have enrolled in the program, and 406 have begun the program (153/342, 44.7% non-Western or Eastern European; 80/345, 23.2% men or 82/347, 23.6% male). An additional 13 sites have confirmed they will launch the program in 2026. CONCLUSIONS This study will demonstrate that SSBC can be scaled up nationwide to effectively and equitably reduce the Canadian population-level risk of T2D. This work will determine best practice implementation determinants, outcomes, and strategies critical for sustaining DPP implementation across Canada and beyond. Project findings will be shared with municipality partners and will be copresented with partners and SSBC clients to community organizations, local interested parties, and academics. CLINICALTRIAL ClinicalTrials.gov NCT06440395; https://clinicaltrials.gov/study/NCT06440395 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/80276
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.064 | 0.043 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.085 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".