A Pilot Randomized Controlled Trial of Smoking Cessation in an Outpatient Respirology Clinic
Bibliographic record
Abstract
OBJECTIVE: To assess the feasibility and potential effectiveness of a modified version of the Ottawa Model for Smoking Cessation in an outpatient respirology clinic. METHODS: Adult tobacco smokers attending the respirology clinic and willing to choose a quit date within one month of enrollment were randomly assigned to receive standard care or the intervention. Standard care participants received smoking cessation advice, a brochure and a prescription for smoking cessation medication if requested. Intervention participants received a $110 voucher to purchase smoking cessation pharmacotherapy and were registered to an automated calling system. Answers to automated calls determined which participants required nurse telephone counselling. Feasibility indicators included recruitment and retention rates, and intervention adherence. The effectiveness indicator was self-reported smoking status at 26 to 52 weeks. RESULTS: Forty-nine (54.4%) of 90 eligible smokers were randomly assigned to the intervention (n=23) or control (n=26) group. Self-reported smoking status at 26 to 52 weeks was available for 32 (65.3%) participants. The quit rate for intervention participants was 18.2% compared with 7.7% for controls (OR2.36 [95% CI 0.39 to 14.15]). CONCLUSION: It would be feasible to evaluate this intervention in a larger trial. Alternatives to face-to-face follow-up at the clinic are recommended.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".