Smokers' use of nicotine replacement therapy for reasons other than stopping smoking: findings from the ITC Four Country Survey
Bibliographic record
Abstract
AIMS: To measure the prevalence and correlates of nicotine replacement therapy (NRT) use for reasons other than quitting smoking among smokers in four countries. DESIGN AND SETTING: Population-based, cross-sectional telephone survey with nationally representative samples of adult smokers in Canada, the United States, the United Kingdom and Australia, conducted in 2005. PARTICIPANTS: A total of 6532 adult daily smokers in Canada (n = 1660), the United States (n = 1664), the United Kingdom (n = 1617) and Australia (n = 1591). MEASUREMENTS: Survey questions included demographics, smoking behaviour, use of NRT and reasons for NRT use, as well as access and availability of NRT. FINDINGS: Approximately 17% of smokers surveyed had used NRT in the past year. Among NRT users, approximately one-third used NRT for a reason other than quitting smoking, including temporary abstinence or reducing the number of cigarettes smoked. The prevalence of non-standard NRT use was remarkably consistent across countries. Using NRT for reasons other than quitting was associated with higher education level, heavier smoking, having no quit intentions, having no past-year quit attempts, the type of NRT product used and accessing NRT without a prescription. CONCLUSIONS: The use of NRT for purposes other than quitting smoking is fairly common and may help to explain the difficulty in detecting significant quitting benefits associated with NRT use in population studies. Tobacco control policies, including the accessibility of NRT, may have important implications for patterns of NRT use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".