How to adapt existing evidence-based clinical practice guidelines: a case example with smoking cessation guidelines in Canada
Bibliographic record
Abstract
OBJECTIVE: To develop and encourage the adoption of clinical practice guidelines (CPGs) for smoking cessation in Canada by engaging stakeholders in the adaptation of existing high-quality CPGs using principles of the ADAPTE framework. METHODS: An independent expert body in guideline review conducted a review and identified six existing CPGs, which met a priori criteria for quality and potential applicability to the local context. Summary statements were extracted and assigned a grade of recommendation and level of evidence by a second expert panel. Regional knowledge exchange brokers recruited additional stakeholders to build a multidisciplinary network of over 800 clinicians, researchers and decision-makers from across Canada. This interprofessional network and other stakeholders were offered various opportunities to provide input on the guideline both online and in person. We actively encouraged end-user input into the development and adaptation of the guidelines to ensure applicability to various practice settings and to promote adoption. RESULTS: The final guideline contained 24 summary statements along with supporting clinical considerations, across six topic area sections. The guideline was adopted by various provincial/territorial and national government and non-governmental organisations. CONCLUSIONS: This method can be applied in other jurisdictions to adapt existing high-quality smoking cessation CPGs to the local context and to facilitate subsequent adoption by various stakeholders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.411 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| 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 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".