Individual-level predictors of cessation behaviours among participants in the International Tobacco Control (ITC) Four Country Survey
Bibliographic record
Abstract
BACKGROUND: The International Tobacco Control (ITC) Four Country Survey (ITC-4) is a prospective cohort study designed to evaluate the psychosocial and behavioural impact of national-level tobacco control policies enacted in the Australia, Canada, the UK, and the USA. Wave 1 of ITC-4 survey was conducted between October 2002 and December 2002. Wave 2 survey was conducted between May 2003 and August 2003. OBJECTIVE: To test for individual-level predictors of smoking cessation behaviours (that is, quit attempts and smoking cessation) among cigarette smokers in the ITC Four Country Study measured between Wave 1 and Wave 2. This set of predictors will serve as the base for evaluating the added effect of tobacco control policies and other factors. METHODS: Respondents included in this study are 6682 adult current smokers in the Wave 1 main survey who completed the Wave 2 follow-up (1665 were in Canada, 1329 were in the USA, 1837 were in the UK and 1851 were in Australia). RESULTS: Factors predictive of making a quit attempt included intention to quit, making a quit attempt in the previous year, longer duration of past quit attempts, less nicotine dependence, more negative attitudes about smoking, and younger age. Lower levels of nicotine dependence were the main factor that predicted future cessation among those that made a quit attempt. CONCLUSION: Intention to quit and other cognitive variables were associated with quit attempts, but not cessation. Behavioural variables related to task difficulty, including measures of dependence, predicted both making attempts and their success. Predictors of making quit attempts and cessation were similar for each of the four countries, but there were some differences in predictors of success.
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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 | 0.005 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".