Trends in beliefs about the harmfulness and use of stop-smoking medications and smokeless tobacco products among cigarettes smokers: Findings from the ITC four-country survey
Bibliographic record
Abstract
BACKGROUND: Evidence shows that smokers are generally misinformed about the relative harmfulness of nicotine, and smokeless forms of nicotine delivery in relation to smoked tobacco. This study explores changing trends in the beliefs about the harmfulness and use of stop smoking medications and smokeless tobacco in adult smokers in four countries where public education and access to alternative forms of nicotine is varied (Canada, the US, the UK and Australia). METHODS: Data are from seven waves of the ITC-4 country study conducted between 2002 and 2009 with adult smokers from Canada, the US, the UK and Australia. For the purposes of this study, data were collected from 21,207 current smokers. Using generalised estimating equations to control for multiple response sets, multivariate models were tested to look for main effects of country, and trends across time, controlling for demographic variables. RESULTS: Knowledge remained low in all countries, although UK smokers tended to be better informed. There was a small but significant improvement across time in the UK, but mixed effects in the other three countries. At the final wave, between 37.5% (US) and 61.4% (UK) reported that NRT is a lot less harmful than cigarettes. In Canada and the US, where smokeless tobacco is marketed, only around one in six believed some smokeless tobacco products could be less harmful than cigarettes. CONCLUSIONS: Many smokers continue to be misinformed about the relative safety of nicotine and alternatives to smoked tobacco, especially in the US and Canada. Concerted efforts to educate UK smokers have probably improved their knowledge. Further research is required to assess whether misinformation deters smokers from appropriate use of alternative forms of nicotine.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".