An integrated approach to improving appropriate use of anti-inflammatory medication in the treatment of osteoarthritis in Québec (Canada): the CURATA model
Bibliographic record
Abstract
CURATA is a multifaceted continuing medical education (CME) intervention, developed with input from 12 healthcare organizations to address the gap between current and recommended osteoarthritis (OA) treatment of general practitioners in Québec, Canada. Focusing on appropriate prescription of non-steroidal anti-inflammatory drugs, including cyclooxygenase-2 selective inhibitors (coxibs), the intervention comprised small-group, case-based workshops modelled after the Script Concordance test, and a decision tool reflecting current evidence-based clinical practice guidelines. A self-reported questionnaire measured knowledge of recommended OA treatment on an eight-point scale. Participants (n = 381) showed a mean 10.1% improvement in questionnaire score immediately following the workshop (15.2% improvement relative to mean pre-workshop score). Knowledge was maintained for three months post-workshop.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".