The importance of the belief that “light” cigarettes are smoother in misperceptions of the harmfulness of “light” cigarettes in the Republic of Korea: a nationally representative cohort study
Bibliographic record
Abstract
BACKGROUND: A number of countries have banned misleading cigarette descriptors such as "light" and "low-tar" as called for by the WHO Framework Convention on Tobacco Control. These laws, however, do not address the underlying cigarette design elements that contribute to misperceptions about harm. This is the first study to examine beliefs about "light" cigarettes among Korean smokers, and the first to identify factors related to cigarette design that are associated with the belief that "light" cigarettes are less harmful. METHODS: We analysed data from Wave 3 of the ITC Korea Survey, a telephone survey of a nationally representative sample of 1,753 adult smokers, conducted October - December 2010. A multinomial logistic regression was used to examine which factors were associated with the belief that "light" cigarettes are less harmful than regular cigarettes. RESULTS: One quarter (25.0 %) of smokers believed that "light" cigarettes are less harmful than regular cigarettes, 25.8 % believed that smokers of "light" brands take in less tar, and 15.5 % held both of these beliefs. By far the strongest predictor of the erroneous belief that "light" cigarettes are less harmful was the belief that "light" cigarettes are smoother on the throat and chest (p < 0.001, OR = 44.8, 95 % CI 23.6-84.9). CONCLUSIONS: The strong association between the belief that "light" cigarettes are smoother on the throat and chest and the belief that "light" cigarettes are less harmful, which is consistent with previous research, provides further evidence of the need to not only ban "light" descriptors, but also prohibit cigarette design and packaging features that contribute to the perception of smoothness.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".