Clinicians' evaluations of, endorsements of, and intentions to use practice guidelines change over time: a retrospective analysis from an organized guideline program
Bibliographic record
Abstract
PURPOSE: Clinical practice guidelines (CPGs) can improve clinical care but uptake and application are inconsistent. Objectives were: to examine temporal trends in clinicians' evaluations of, endorsements of, and intentions to use cancer CPGs developed by an established CPG program; and to evaluate how predictor variables (clinician characteristics, beliefs, and attitudes) are associated with these trends. DESIGN AND METHODS: Between 1999 and 2005, 756 clinicians evaluated 84 Cancer Care Ontario CPGs, yielding 4,091 surveys that targeted four CPG quality domains (rigour, applicability, acceptability, and comparative value), clinicians' endorsement levels, and clinicians' intentions to use CPGs in practice. RESULTS: Time: In contrast to the applicability and intention to use in practice scores, there were small but statistically significant annual net gains in ratings for rigour, acceptability, comparative value, and CPG endorsement measures (p < 0.05 for all rating categories). PREDICTORS: In 17 comparisons, ratings were significantly higher among clinicians having the most favourable beliefs and most positive attitudes and lowest for those having the least favourable beliefs and most negative attitudes (p < 0.05). Interactions Time x PREDICTORS: Over time, differences in outcomes among clinicians decreased due to positive net gains in scores by clinicians whose beliefs and attitudes were least favorable. CONCLUSION: Individual differences among clinicians largely explain variances in outcomes measured. Continued engagement of clinicians least receptive to CPGs may be worthwhile because they are the ones showing most significant gains in CPG quality ratings, endorsement ratings, and intentions to use in practice ratings.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".