Impact of Female-Oriented Cigarette Packaging in the United States
Bibliographic record
Abstract
INTRODUCTION: Cigarette packaging is among the most prominent forms of tobacco marketing. This study examined the impact of cigarette pack design among young women in the United States. METHOD: A national sample of 18- to 19-year-old females in the United States completed an online survey in February 2010. Participants were randomized to view eight cigarette packs designed according to one of four experimental conditions: fully branded female packs, same packs without descriptors (e.g., "slims"), same packs without brand imagery or descriptors ("plain" packs), and branded non-female brands. Participants rated packs on measures of appeal and health risk and completed a behavioral pack selection task. RESULTS: Fully branded female packs were rated significantly more appealing than the same packs without descriptors, "plain" packs, and non-female-branded packs. Female-branded packs were associated with a greater number of positive attributes including glamour, slimness, and attractiveness and were more likely to be perceived as less harmful. Approximately 40% of smokers and nonsmokers requested a pack at the end of the study; female-branded packs were 3 times more likely to be selected than plain packs. CONCLUSION: Plain packaging and removing descriptors such as "slims" from cigarette packs may reduce smoking susceptibility among young women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".