A Social Return on Investment Analysis of the Healthy Weights Initiative: 12-month Results for 1,401 Participants
Bibliographic record
Abstract
The Healthy Weights Initiative (HWI) is a free, comprehensive obesity-reduction program within two cities in the province of Saskatchewan, Canada. The objective of the study was to conduct a Social Return On Investment (SROI) analysis on the HWI, which estimates the overall economic, social, and environmental value of an intervention. There are six stages to an SROI: 1) identify stakeholders; 2) map intervention changes including inputs, outputs, and outcomes; 3) give outcomes a financial proxy; 4) account for other factors that can explain the outcome and adjust for drop-off; 5) calculate the SROI; and 6) report the results to a wide population. From June 1, 2015 to January 31, 2018, 2,000 participants completed the initial 24-week HWI program. As of December 31, 2018, 1,401 HWI participants (70.0%) agreed to one-year follow-up and the SROI survey. The survey was also completed by 121 of 132 referring physicians (91.7%). Overall, 99.9% of HWI participants believed the observed outcomes were acceptable, 7.1% believed the results were possibly due to another program in the city, 99.8% felt the program was worth the cost, 71.3% indicated they would be willing to pay for such a program themselves, and 99% believed some level of government should finance the program. Among referring physicians, 98.3% believed the observed outcomes were acceptable, 10.7% believed the results were possibly due to another program in the city, 96.7% felt the program was worth the cost, 53.7% indicated they would be willing to pay for such a program themselves, and 82.6% believed some level of government should finance the program. With a value of $2,984,916 Canadian dollars, and a total program cost of $1,000,314 Canadian dollars, the oneyear SROI was 2.99. For every $1.00 Canadian dollar invested in the HWI, a social return of investment of $2.99 Canadian dollars was obtained
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".