Heterogeneity among smokers and non-smokers in attitudes and behaviour regarding smoking and smoking restrictions
Bibliographic record
Abstract
OBJECTIVE: To determine if smokers and non-smokers cluster into meaningful, discrete subgroups with distinguishable attitudes and behaviours regarding smoking and smoking restrictions. DESIGN: Qualitative research with 45 smokers guided development of questionnaire items applied in a population based telephone survey of 432 current smokers and 1332 non-smokers in Ontario, Canada. METHODS: Cluster analysis of questionnaire items used to categorise adult smokers and non-smokers; comparison of clusters on sociodemographic characteristics and composite knowledge and attitude scores. RESULTS: Smokers clustered in three groups. "Reluctant" smokers (16%) show more concern about other people discovering that they smoke, but parallel "easygoing" smokers (42%) in supporting restrictions on smoking and not smoking around others. "Adamant" smokers (42%) feel restrictions have gone too far, and are less likely to accommodate non-smokers. Significant gradients across categories in the expected direction were observed with respect to smoking status, stage of change, knowledge, and attitude scores, and predicted compliance with restrictions, validating the proposed typology. Non-smokers also clustered into three groups, of which the "adamant" non-smokers (45%) are the least favourably disposed to smoking. "Unempowered" non-smokers (34%) also oppose smoking, but tend not to act on it. "Laissez-faire" non-smokers (21%) are less opposed to smoking in both attitude and behaviour. A significant gradient across categories in the expected direction was observed with respect to composite scores regarding knowledge of the health effects of active and passive smoking and a composite score on support for restrictions on smoking in public places. CONCLUSION: Recognition and consideration of the types of smokers and non-smokers in the population and their distinguishing characteristics could inform the development of tobacco control policies and programmes and suggest strategies to assist implementation.
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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 | 0.000 | 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".