Assessing Physician Awareness of the Choosing Wisely Canada Recommendations
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
Background: Choosing Wisely Canada (CWC), an initiative to reduce low-value care, launched in April 2014. However, it remains unclear to what extent physicians are aware of the initiative and specific recommendations. The objective of this study was to assess physician awareness of the CWC campaign and recommendations, in addition to assessment of attitudes and perspectives on low-value medical care. Methods: This study was conducted as a survey of faculty physicians and residents of McMaster University. Electronic surveys were sent to all faculty physicians and residents within specialties with CWC recommendations. Responses were analyzed to determine awareness of CWC recommendations, defined as awareness of ≥3 recommendations targeted to a respondent’s respective specialty. Results: A total of 361 respondents were included in the analysis (response rate = 33%). Eighty-eight percent of respondents were aware of the CWC campaign. Only 30.1% (95% CI 23.5–36.7%) of respondents were able to correctly describe ≥3 of the recommendations targeted to their respective specialty, with a mean of 1.6 (95% CI 1.4–1.9) recommendations correctly identified per respondent. Most recommendations (70.9%) were reported as already being part of a respondents’ practice prior to release of the CWC recommendations. Interpretation: Despite general awareness of the CWC campaign, more than two thirds of physicians cannot describe most recommendations targeted to their own specialty. Nonetheless, many of these physicians report already practicing in compliance with these recommendations. Future studies are required to identify methods to improve communication, to track compliance with current CWC recommendations, and to determine areas of care that would most benefit from additional recommendations.
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.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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