Cigarette packaging, warnings, prices, and contraband: A discrete choice experiment among smokers in Ontario, Canada
Bibliographic record
Abstract
In Canada, despite substantial decline, tobacco use remains the leading risk factor responsible for mortality and morbidity. There is overwhelming evidence that higher tobacco taxes reduce tobacco use, even if high taxes create an incentive to avoid or evade tobacco taxes. Recently, in addition to taxes, plain and standardized packaging and printing a warning on each cigarette have been lauded to reduce tobacco use. In November 2019, Canada became the country with the most comprehensive cigarette packaging regulations; and in June 2022, Canada proposed to print health warnings on individual cigarettes, the first jurisdiction to ever do so. The regulations came into force on August 1, 2023, and are being implemented through a stepwise approach. Our objective was to examine the effects of plain and standardized packaging, warning on cigarettes, price, and the availability of illicit cigarettes on intention to purchase and risk perceptions. We conducted a discrete choice experiment, and examined heterogeneity in preferences using latent class models among smokers in Ontario, Canada. We found that using latent class analyses was essential in quantifying preferences for attributes of cigarettes and cigarette packs. First, nearly half of smokers stated a preference for cheaper illicit cigarettes in a branded pack without any health warnings, regardless of the licit cigarette alternatives. For about 20% of respondents, plain packaging and especially warning on cigarette sticks decreased the probability of stating a purchasing preference for these alternatives. Third, about a third of respondents chose competing alternatives with mostly one attribute in mind, price. Lastly, none of the products and attributes seem to have significantly influenced risk perception. Our findings attest to the importance of prices and taxes, to the potential of warnings on cigarette sticks to control tobacco use, and indicate that efforts to restrict the availability of illicit cigarettes may yield substantial benefits.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".