Reporting of Differences in Taste Between Branded and Unbranded Cigarettes by Smokers Blinded to Cigarette Branding: Within-Person, Randomized Crossover Study
Bibliographic record
Abstract
BACKGROUND: Saudi Arabia implemented a plain tobacco packaging regulation, one of the World Health Organization's recommended initiatives to help reduce smoking rates, in August 2019. A few weeks after implementation, a large number of smokers complained via various media channels, especially social media (eg, Twitter), that an extreme change in cigarette taste had occurred, frequency of coughing had increased, and for some, shortness of breath had led to hospitalization. OBJECTIVE: The main objective is to determine whether smokers blinded to cigarette branding report differences in taste between branded and unbranded cigarettes. The secondary objective is to observe the frequency of immediate cough or shortness of breath. METHODS: This study employed a within-person, randomized crossover design that recruited current smokers 18 years and older who were cleared upon physical assessment before the experiment. Participants received 6 sequences of different random exposures (3 puffs) to 3 plain-packaged cigarettes (2 from their favorite brand and 1 from another brand as a control) and 3 branded cigarettes (2 from the favorite brand and 1 from another brand as a control). Participants wore virtual reality goggles accompanied by special software to alter visual reality and gloves to alter the touch sensation. RESULTS: =-0.63, mean 0.47, P=.53). In terms of immediate coughing, out of the 108 experiments, 1 episode of short coughing was observed, which was attributed to the branded cigarette, not the plain-packaged cigarette. CONCLUSIONS: After controlling the visual and touch sensations, participants were not able to differentiate between branded and plain-packaged cigarettes in terms of taste or inducing immediate shortness of breath or cough. Interestingly, participants were not able to identify their favorite brand.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".