Public Health Policy in Support of Insurance Coverage for Smoking Cessation Treatment
Bibliographic record
Abstract
Insurance coverage for evidence-based smoking cessation treatments (SCTs) promotes uptake and reduces smoking rates. Published studies in this area are based in the US where employers are the primary source of health insurance. In Ontario, Canada, publicly funded healthcare does not cover SCTs, but it can be supplemented with employer-sponsored benefit plans. This study explores factors affecting the inclusion/exclusion of smoking cessation (SC) benefits. In total, 17 interviews were conducted with eight employers (auto, retail, banking, municipal and university industries), four health insurers, two government representatives and three advisors/consultants. Overall, SCT coverage varied among industries; it was inconsistently restrictive and SCT differed by coverage amount and length of use. Barriers impeding coverage included the lack of the following: Canadian-specific return on investment (ROI), SC cost information, employer demand, government regulations/incentives and employee awareness of and demand. A Canadian evidence-based calculation of ROI for SC coupled with government incentives and public education may be needed to promote uptake of SCT coverage by employers.
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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 | 0.015 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".