Prototyping the implementation of a suicide prevention protocol in primary care settings using PDSA cycles: a mixed method study
Bibliographic record
Abstract
Introduction In Canada, approximately 4,500 individuals die by suicide annually. Approximately 45% of suicide decedents had contact with their primary care provider within the month prior to their death. Current versus never smokers have an 81% increased risk of death by suicide. Those who smoke have additional risks for suicide such as depression, chronic pain, alcohol, and other substance use. They are more likely to experience adverse social determinants of health. Taken together, this suggests that smoking cessation programs in primary care could be facilitators of suicide prevention, but this has not been studied. Study objectives The objectives of the study are to understand barriers/facilitators to implementing a suicide prevention protocol within a smoking cessation program (STOP program), which is deployed by an academic mental health and addiction treatment hospital in primary care clinics and to develop and test implementation strategies to facilitate the uptake of suicide screening and assessment in primary care clinics across Ontario. Methods The study employed a three-phase sequential mixed-method design. Phase 1: Conducted interviews guided by the Consolidated Framework for Implementation Research exploring barriers to implementing a suicide prevention protocol. Phase 2: Performed consensus discussions to map barriers to implementation strategies using the Expert Recommendations for Implementing Change tool and rank barriers by relevance. Phase 3: Evaluated the feasibility and acceptability of implementation strategies using Plan Do Study Act cycles. Results Eleven healthcare providers and four research assistants identified lack of training and the need of better educational materials as implementation barriers. Participants endorsed and tested the top three ranked implementation strategies, namely, a webinar, adding a preamble before depression survey questions, and an infographic. After participating in the webinar and reviewing the educational materials, all participants endorsed the three strategies as acceptable/very acceptable and feasible/very feasible. Conclusion Although there are barriers to implementing a suicide prevention protocol within primary care, it is possible to overcome them with strategies deemed both acceptable and feasible. These results offer promising practice solutions to implement a suicide prevention protocol in smoking cessation programs delivered in primary care settings. Future efforts should track implementation of these strategies and measure outcomes, including provider confidence, self-efficacy, and knowledge, and patient outcomes.
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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 | 0.107 | 0.124 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".