Push & Pull: Social determinants of the use of smoking cessation support in Ontario
Bibliographic record
Abstract
Tobacco use continues to undermine the health of the Ontarian population. In addition, socio-economic disparities in smoking rates persist in Ontario, despite public health care and universal tobacco control policies. Public health strategies require a detailed understanding of how people are actually quitting smoking in order to develop appropriate interventions and strategies. This thesis used existing evidence and data from the Ontario Tobacco Survey (OTS) to explore unassisted and assisted quitting. The first manuscript estimated the proportion of adult smokers who report attempting to quit unassisted, without the use of pharmacological and/or behavioural assistance, by systematically reviewing population-based studies. A majority of quit attempts were unassisted; however, across and within countries over time, a trend toward lower prevalence of unassisted quit attempts was identified. The second manuscript estimated the prevalence of unassisted quitting and the reach and pattern of use of assisted methods in Ontario. Unassisted quitting was the dominant method reported (58.8%, 95% CI: 56.0-61.6). For assisted methods, pharmaceutical support was the most common (92.9%, 95% CI: 91.1-94.6). Use of behavioural support either alone (2.5%, 95% CI: 1.5-3.6) or in combination with pharmaceutical support (4.6%, 95% CI: 3.3-5.9) was rare. The third manuscript examined the associations between socioeconomic status (SES) and access to care measures and use of cessation strategies using multinomial regression models. Smokers living in areas with the lowest ethnic concentration were more likely to make an assisted quit attempt compared to unassisted quitting (RR=1.67; 95% CI=1.08-2.60) or making no quit attempt (RR=1.65; 95% CI=1.14-2.41). Smokers who reported visiting a doctor in the previous 6 months were more likely to quit with assistance versus unassisted, whether they were advised (RR=1.96, 95% CI=1.49-2.59) or not advised to quit (OR=1.37, 95% CI=1.04-1.82). Together, these studies make a substantial contribution to understanding how smokers are choosing to quit smoking.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".