Supporting cancer patients quit smoking: the initial evaluation of our tobacco cessation intervention program
Bibliographic record
Abstract
Abstract Background: Tobacco is a known addictive consumer product and its use has been reported to be associated with several health problems as well as the leading cause of premature, preventable mortality worldwide. For patients undergoing cancer treatment, tobacco smoking can potentially compromise treatment effectiveness; however, there is sufficient evidence suggesting numerous health benefits of smoking cessation interventions for cancer patients. Methods: The Grand River Regional Cancer Centre (GRRCC) smoking cessation program began in October 2013 to provide evidence-based intensive tobacco intervention to patients. All new patients are screened for tobacco use and those identified as active smokers are advised of the benefits of cessation and offered referral to the program where a cessation nurse offers counseling. Patients’ disease site, initial cessation goal, quit date, number of quit attempts and mode of contact are collected by the cessation nurse. This study reports on the initial evaluation of the smoking cessation program activities at GRRCC. Results: There are 1,210 patients who were screened, accepted a referral and counseled in the program. The referral pattern shows a modest increase every year and most of the patients (58%) indicated readiness to quit smoking. Overall, 29 and 26% of patients either quit or cut-back smoking, respectively. Among 348 patients who quit smoking, 300 (86%) were able to quit at the first attempt. The data indicated that 309 (44%) out of the 698 patients who indicated their initial intent to quit smoking were able to quit, whereas about 242 (35%) were able to cutback. A total of 15 patients out of 32 who indicated initial readiness to ‘cutback’ smoking were able to reduce tobacco use and three patients actually ended up quitting, although their initial goal was ‘ready-to-cut-back’. Conclusions: GRRCC smoking cessation program started in October 2013 to provide evidence-based intensive smoking cessation interventions for patients with cancer. Most patients referred to the program indicated a readiness to quit smoking affirming that if patients become aware of the various risks associated with continual smoking or if they are informed of the benefits associated with cessation with regard to their treatment, they will be more likely to decide to quit. Therefore, it is essential that patients, their partners and families are counseled on the health and treatment benefits of smoking cessation and sustainable programs should be available to support them to quit smoking. It is imperative then, that oncology programs should consistently identify and document the smoking status of cancer patients and support those who use tobacco at the time of diagnosis to quit. Evidence-based smoking cessation intervention should be sustainably integrated into the cancer care continuum in all oncology programs from prevention of cancer through diagnosis, treatment, survivorship and palliative care.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".