Future Intentions Regarding Quitting and Reducing Cigarette Use in a Representative Sample of Canadian Daily Smokers: Implications for Public Health Initiatives
Bibliographic record
Abstract
Pre-cessation reduction is associated with quitting smoking. However, many smokers reduce the amount consumed but may not quit altogether. Using a representative sample of adult current daily smokers, this project explored future intentions of smokers regarding cigarette consumption. This information is important because it can provide a framework within which to plan tobacco cessation initiatives. A random digit dialing telephone survey was conducted of 889 Canadian current daily smokers, 18 years and older. The response rate was 65% (of households with a smoker in residence, 65% agreed to participate). Analyses focused on the 825 respondents who smoked at least 10 cigarettes per day at some point in their lives. As part of this survey, respondents were asked their future plans about their smoking (maintain, increase, reduce, quit). Of these 825 respondents, the majority of respondents had plans to change their cigarette use, with 55% planning to quit, 18.8% to reduce and 22.5% to maintain the amount they smoked (3.4% did not know and 2 respondents planned to increase). Most smokers who planned to reduce their smoking saw it as a step towards quitting smoking completely. These results present a picture of smokers, the majority of whom appear to be in some form of transition. Many smokers planned to reduce, of which the overwhelming majority saw their reduction as a step towards quitting. Opportunities exist to capitalize on these intentions to change in efforts to promote tobacco cessation.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".