Improving Smoking Cessation Services for Persons with Spinal Cord Injury: Insights from a World Café Approach
Bibliographic record
Abstract
Introduction: Persons with spinal cord injury (SCI) report high cigarette smoking rates and poor health outcomes related to tobacco use. Despite high motivation to quit smoking, those with SCI experience challenges to quitting due to a lack of SCI-specific support. Objective: Use an integrated knowledge translation (IKT) and world café approach to (1) identify strategies to improve the relevance and useability of smoking cessation services for persons with SCI and (2) identify meaningful outcomes to measure when testing a smoking cessation intervention for persons with SCI.Methods: Aligned with an IKT approach, an SCI organization was meaningfully engaged throughout the research process. An in-person world café was conducted with staff from an SCI organization who deliver peer support to people with SCI. Strategies to improve the delivery and receipt of a smoking cessation intervention for persons with SCI and meaningful outcomes were identified using a conventional content analysis.Results: Ten staff members who provided SCI peer support through an SCI organization participated in the World Café. Five overarching themes to improve the delivery and receipt of a smoking cessation intervention for persons with SCI were identified: Training for SCI peer health coaches; don’t need to be told smoking is bad for you; coming alongside as a tour guide; ease of use; and wanting to be well informed.Conclusion: Findings from this study provide important insight to improve the relevance, usefulness, and useability of smoking cessation services for persons with SCI and may ultimately help people with SCI stop smoking.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".