Cigarette brands with flavour capsules in the filter: trends in use and brand perceptions among smokers in the USA, Mexico and Australia, 2012–2014
Bibliographic record
Abstract
OBJECTIVE: To describe trends, correlates of use and consumer perceptions related to the product design innovation of flavour capsules in cigarette filters. METHODS: Quarterly surveys from 2012 to 2014 were analysed from an online consumer panel of adult smokers aged 18-64, living in the USA (n=6865 observations; 4154 individuals); Mexico (n=5723 observations; 3366 individuals); and Australia (n=5864 observations; 2710 individuals). Preferred brand varieties were classified by price (ie, premium; discount) and flavour (ie, regular; flavoured without capsule; flavoured with capsule). Participants reported their preferred brand variety's appeal (ie, satisfaction; stylishness), taste (ie, smoothness, intensity), and harm relative to other brands and varieties. GEE models were used to determine time trends and correlates of flavour capsule use, as well as associations between preferred brand characteristics (ie, price stratum, flavour) and perceptions of relative appeal, taste and harm. RESULTS: Preference for flavour capsules increased significantly in Mexico (6% to 14%) and Australia (1% to 3%), but not in the USA (4% to 5%). 18-24 year olds were most likely to prefer capsules in the USA (10%) and Australia (4%), but not Mexico. When compared to smokers who preferred regular brands, smokers who preferred brands with capsules viewed their variety of cigarettes as having more positive appeal (all countries), better taste (all countries), and lesser risk (Mexico, USA) than other brand varieties. CONCLUSIONS: Results indicate that use of cigarettes with flavour capsules is growing, is associated with misperceptions of relative harm, and differentiates brands in ways that justify regulatory action.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".