Smoking Cessation by Phone Counselling in a Lung Cancer Screening Program: A Retrospective Comparative Cohort Study
Bibliographic record
Abstract
Introduction: Smoking cessation integration within lung cancer screening programs is challenging. Currently, phone counselling is available across Canada for individuals referred by healthcare workers and by self-referral. We compared quit rates after phone counselling interventions between participants who self-refer, those referred by healthcare workers, and those referred by a lung cancer screening program. Methods: This is a retrospective cohort study of participants referred to provincial smoking cessation quit line in contemporaneous cohorts: self-referred participants, healthcare worker referred, and those referred by a lung cancer screening program if they were still actively smoking at the time of first contact. Baseline, covariates (sociodemographic information, smoking history, and history of mental health disorder) and quit intentions (stage of change, readiness for change, previous use of quit programs, and previous quit attempts) were compared among the three cohorts. Our primary outcome was defined as self-reported 30-day abstinence rates at 6 months. Multivariable logistic regression was used to identify whether group assignment was associated with higher quit rates. Results: Participants referred by a lung cancer screening program had low quit rates (12%, 95% CI: 5-19) at six months despite the use of phone counselling. Compared to patients who were self-referred to the smoking cessation phone helpline, individuals referred by a lung cancer screening program were much less likely to quit (adjusted OR 0.37; 95% CI: 0.17-0.8), whereas those referred by healthcare workers were twice as likely to quit (adjusted OR 2.16 (1.3-3.58)) even after adjustment for differences in smoking intensity and quit intentions. Conclusions: Phone counselling alone has very limited benefit in a lung cancer screening program. Participants differ significantly from those who are otherwise referred by healthcare workers. This study underlines the importance of a dedicated and personalized tobacco treatment program within every lung cancer screening program. The program should incorporate best practices and encourage treatment regardless of readiness to quit.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".