Do graphic health warning labels on cigarette packages deter purchases at point-of-sale? An experiment with adult smokers
Bibliographic record
Abstract
This experiment tested whether the presence of graphic health warning labels on cigarette packages deterred adult smokers from purchasing cigarettes at retail point-of-sale (POS), and whether individual difference variables moderated this relationship. The study was conducted in the RAND StoreLab (RSL), a life-sized replica of a convenience store that was developed to evaluate how changing POS tobacco advertising influences tobacco use outcomes during simulated shopping experiences. Adult smokers (n = 294; 65% female; 59% African-American; 35% White) were assigned randomly to shop in the RSL under one of two experimental conditions: graphic health warning labels present on cigarette packages versus absent on cigarette packages. Cigarette packages in both conditions were displayed on a tobacco power wall, which was located behind the RSL cashier counter. Results revealed that the presence of graphic health warning labels did not influence participants' purchase of cigarettes as a main effect. However, nicotine dependence acted as a significant moderator of experimental condition. Graphic health warning labels reduced the chances of cigarette purchases for smokers lower in nicotine dependence but had no effect on smokers higher in dependence.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".