Misperceptions about “light” cigarettes among smokers in Zambia: Findings from the International Tobacco Control (ITC) Zambia Survey
Bibliographic record
Abstract
INTRODUCTIONLittle is known about beliefs about "light" cigarettes ("lights") in African countries where both tobacco industry activity and tobacco control efforts are intensifying.This study in Zambia is the first to examine the prevalence and beliefs about "lights" among smokers in Africa.METHODS Data are from 1,214 smokers participating in the International Tobacco Control (ITC) Zambia Wave 1 Survey (2012), a multi-stage clustered sampling design, face-to-face nationally representative probability sample of tobacco users and non-users aged 15 years and older.RESULTS 17.0% of respondents' usual brand of cigarettes was "lights".36.5% of smokers believed that "lights" are less harmful; beliefs differed by brand type (42.1% "lights" vs. 38.2%"non-lights").42.0% of smokers believed that "lights" are smoother on the throat and chest than regular cigarettes with beliefs differing by brand type.Among smokers who believed that "lights" are smoother, 81.0% believed that these cigarettes are less harmful, much higher than the 4.1% of smokers who did not believe that "lights" are smoother.Smoothness beliefs about "lights" was the strongest predictor of the belief that "lights" are less harmful (p<0.001,OR=131.13,95% CI 59.4 to 289.5).CONCLUSIONS Zambian smokers incorrectly believe that "lights" are less harmful.The highly strong association between the belief that "lights" are smoother and the belief that "lights" are less harmful suggests that tobacco control policies need to use a multi-pronged approach including product regulation, banning misleading descriptors and menthol, and implementing sustained longterm public education campaigns to combat sensory beliefs and misperceptions about "lights".
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".