To Choose or Not To Choose: Evaluating the Effect of a Choosing Wisely Knowledge Translation Initiative for Imaging in Low Back Pain by Emergency Physicians
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: We aimed to quantify the baseline familiarity of emergency medicine (EM) physicians with the Choosing Wisely Canada (CWC)-EM recommendations. We then assessed whether a structured knowledge translation (KT) initiative affected awareness, knowledge, and practice patterns for imaging in low back pain. METHODS: We completed a two-center, before and after practice evaluation study. Physicians working in two Canadian emergency departments (EDs) were asked to participate in a survey before a KT initiative, and were surveyed again at a six-month follow up period post-intervention. The primary outcome of physician practice was determined by analyzing the frequency of lumbar X-ray imaging for back pain. RESULTS: A total of 37 physicians were asked to complete the pre- and post-intervention survey. Awareness of the CWC-EM recommendations increased following the intervention (63%; 95%CI: 43-79 at baseline vs. 86%; 66-96 post-intervention). Knowledge increased with 58% (39-76) of physicians responding correctly initially, and 86% (66-96) after the intervention. Despite increases in awareness and knowledge of the guidelines, the lumbar X-ray imaging rate increased from a baseline of 12% (9.9-14.5) to 16.2% (13.6-19.2; p = 0.023) following the intervention. CONCLUSION: We demonstrated some improvements in physician awareness and knowledge of the CWC-EM recommendations following our intervention. Despite these improvements, our KT intervention was associated with an increased frequency of imaging for low back pain, contrary to our expectations.
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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 | 0.013 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it