Investing in a healthy lifestyle strategy: is it worth it?
Bibliographic record
Abstract
OBJECTIVES: In Quebec, various actors fund activities aimed at increasing physical activity, improving eating habits and reducing smoking. The objective was to evaluate how effective does the healthy lifestyle habits promotion (HLHP) strategy need to be to make to offset its costs. METHODS: First, we built the logic model of the HLHP strategy. We then assessed the strategy's total cost as well as the direct health care expenditures associated with lifestyle-related risk factors (smoking, physical inactivity, insufficient intake of fruits and vegetables, obesity and overweight). Finally, we estimated the break-even point beyond which the economic benefits of the HLHP strategy would outweigh its costs. RESULTS: The HLHP strategy cost for 2010-2011 was estimated at $110 million. Direct healthcare expenditures associated with lifestyle-related risk factors were estimated at $4.161 billion. We estimated that 47 % of these expenditures were attributable to these risk factors. CONCLUSIONS: We concluded that the HLHP strategy cost corresponded to 5.6 % of the annual healthcare expenditures attributable to these risk factors. This study compared the economic value of HLHP activities against healthcare expenditures associated with targeted risk factors.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".