Understanding Former Smokers in Canada: Examining Who They are and When, Why and How They Quit
Bibliographic record
Abstract
Abstract Objectives : Although the benefits of smoking cessation are well established, long-term abstinence from cigarettes is difficult for many smokers to achieve. We aimed to examine quit attempts, years since quitting and factors associated with long-term abstinence among former smokers. Methods : Data were from the 2006 Canadian Tobacco Use Monitoring Survey. Descriptive analyses were performed and logistic regression models were used to examine factors associated with long-term abstinence (more than 5 years) among former smokers. Results : In 2006, over one in four Canadians (27.1%, n = 7,200,000) aged 15 and older was a former smoker. The prevalence of former smoking was higher among men (30.9%) in comparison to women (23.4%). Former smokers who quit in the past 3 years or earlier were more likely to be older as well as have children younger than 15 in the household. Logistic regression analyses revealed that older age was a significant predictor of long-term abstinence from smoking. Conclusion : Our findings suggest that there are modifiable characteristics associated with long-term smoking abstinence that could be addressed by relapse prevention programming. Longitudinal data are warranted to further clarify the relationship between certain characteristic of former smokers and the duration of abstinence.
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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".