A smoking cessation program as a resource for bladder cancer patients
Bibliographic record
Abstract
Background: Continued tobacco use following a bladder cancer(CaB) diagnosis puts patients at risk for other tobacco-associateddiseases and has also been associated with heightened risks oftreatment-related complications, tumour recurrence, morbidity andmortality. Our aim was to determine if patients with CaB who continueto smoke warrant a smoking cessation program as a resourcefor improving their prognosis and long-term health.Methods: A cross-sectional quantitative questionnaire-based studywas performed between January and April 2009. We surveyedpatients with a pathologically confirmed diagnosis of CaB duringtheir cystoscopy appointments at a single cancer centre.Results: One hundred patients completed the survey with 72% ofthem admitting to smoking in their lifetime. A third of respondentssmoked at the time of their diagnosis; 76% of patients who hadbeen active smokers at the time of their diagnosis (n = 33) reportedsmoking at some point thereafter and 58% continued to smoke. Among continued smokers, they were classified in the following categories: 26% were in “precontemplation,” 5% in “contemplation,”16% in “preparation,” and 53% in “action;” 37% of patientswho continued to smoke were interested in a hospital-based smokingcessation program. Overall, 70% reported smoking as a risk factor for a poor CaB prognosis. The two most common barriersto quitting were “trouble managing stress and mood” and “fear ofgaining weight.”Conclusion: Based on the data from our centre, patients with CaBwho continue to smoke after their diagnosis warrant a smoking cessationprogram as a resource for improving prognosis and long-term health. Further research should focus on establishing an efficacious and cost-effective program that provides these patients with theresources they need 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".