Profile of tobacco users identified in primary care practice and predictors of readiness to quit: a cross-sectional survey
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to document the prevalence of tobacco use and describe the characteristics of tobacco users identified in primary care practices. METHODS: We conducted a cross-sectional survey in 49 primary care practices in the province of Ontario. Consecutive patients were screened for smoking status at the time of their clinic appointment. Patients reporting current tobacco use completed a survey, which documented sociodemographic and smoking-related characteristics. Multilevel modelling was used to examine predictors of readiness to quit smoking and the presence of anxiety and/or depression. RESULTS: A total of 56 592 patients were screened, and 5245 tobacco users participated in the survey. Prevalence of tobacco use was 18.2% and varied significantly across practices (range 12.4%-36.1%). Of the respondents, 46.3% reported current anxiety and/or depression, and 61.3% reported smoking within the first 30 minutes of waking. A total of 41.1% of respondents reported they were ready to quit smoking in the next 6 months, and 30.1% reported readiness to quit in the next 30 days. Readiness to quit was positively associated with higher self-efficacy, male sex, presence of chronic obstructive pulmonary disease and more years of tobacco use. The presence of anxiety and/or depression was associated with lower cessation self-efficacy and time to first cigarette within 30 minutes of waking, but did not predict readiness to quit. INTERPRETATION: Tobacco users identified in primary care practices reported high rates of nicotine dependence and anxiety and/or depression, but also high rates of readiness to quit. Study findings support the need to tailor interventions to address the needs of tobacco users identified in primary care settings.
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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 | 0.001 |
| 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".