A Population-Based Evaluation of the Intention to Quit Smoking, Cervical Cancer Screening Behaviour, and Multiple Health Behaviours Among Female Canadian Smokers
Bibliographic record
Abstract
Abstract Introduction:Proschaska's transtheoretical model (TTM) of behaviour change suggests that a population of smokers varies along many dimensions, including readiness to quit and the presence of other risk factors. This study examines whether smokers contemplating quitting are more likely to be contemplating another change (e.g., Pap testing and physical activity).Methods:The study used self-reported cross-sectional data (n= 2,873) from the Canadian Community Health Survey (CCHS) Cycle 4.1 2007/2008. The association between the smoking stage of change (SOC) and Pap testing behaviour was assessed. Control variables included sociodemographic and behavioural characteristics (e.g. doctor visits and number of cigarettes smoked). The distribution of health behaviours (e.g., dietary changes and exercise) by smoking SOC among women with recent Pap tests was also examined.Results:Female smokers contemplating or preparing to quit smoking had higher odds of having a recent Pap test, OR = 1.40, 95% CI (1.19, 1.65), and OR = 1.82, 95% CI (1.47, 2.25) respectively, compared to smokers who had no intention of quitting. This association remained statistically significant after adjusting for confounders, AOR = 1.28, 95% CI (1.08, 1.52), and AOR = 1.63, 95% CI (1.31, 2.04) respectively. Fruit and vegetable consumption, physical activity, and recent dental visit were associated with advanced smoking SOC among women with recent Pap tests (P< .05).Conclusions:Advanced smoking SOC was associated with the increased likelihood of having a recent Pap test and engaging in other healthy behaviours. These findings show that targeting several health behaviours simultaneously may be an effective health promotion strategy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".