Smoking cessation for hospitalized smokers: An evaluation of the “Ottawa Model”
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Interventions for hospitalized smokers can increase long-term smoking cessation rates. The Ottawa Model for Smoking Cessation (the "Ottawa Model") is an application of the "5 A's" approach to cessation, customized to the hospital setting. This study evaluated the impact of implementing the Ottawa Model in 9 hospitals in eastern Ontario. METHODS: The RE-AIM (Reach, Efficacy, Adoption, Implementation, and Maintenance) framework was used to evaluate the intervention. Trained outreach facilitators assisted 9 hospitals to implement the Ottawa Model; program delivery was then monitored over a 1-year period using administrative data and data from a follow-up database. A before-and-after study was conducted to gauge the effect of the Ottawa Model program on cessation rates 6 months after hospitalization. Self-reports of smoking cessation were biochemically confirmed in a random sample of patients, and all cessation rates were corrected for potential misreporting. RESULTS: Sixty-nine percent of the expected number of smokers received the Ottawa Model intervention. Controlling for hospital, the confirmed 6-month continuous abstinence rate was higher after, than before, introduction of the Ottawa Model (29.4% vs. 18.3%; odds ratio = 1.71, 95% CI = 1.11-2.64; Z = 2.43; I(2) = 0%; p = .02). The intervention was more likely to accomplish counseling for smokers than delivery of medications or postdischarge follow-up. Attitudinal, managerial, and environmental challenges to program implementation were identified. DISCUSSION: Trained outreach facilitators successfully implemented the Ottawa Model in 9 hospitals leading to significantly higher long-term cessation rates. The public health implications of systematic cessation programs for hospitalized smokers are profound.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it