Likelihood of Change: A Study Assessing Surgeon Use of Multisource Feedback Data
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: Multisource feedback, using questionnaire-based data from patients, coworkers, and medical colleagues, is designed to provide broad-based information about clinical performance to facilitate change. PURPOSE: To determine and explain the likelihood that surgeons would implement change following receipt of performance data. METHODS: Surgeons were surveyed to determine the likelihood they would make changes based on specific feedback about their clinical practices. RESULTS: One hundred fifty-three surgeons (76.5%) responded to the follow-up survey. There was little correlation between performance ratings provided by self or medical colleagues and the likelihood of change. A linear regression analysis indicated that 19.2% of the variance in likelihood to change could be explained by age, time spent reviewing feedback, the gap between self- and other ratings, and surgical specialty. CONCLUSION: Surgeons made few changes in practice in response to feedback data. Attention needs to be paid to methods that might increase surgeon use of performance data
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 | 0.004 | 0.008 |
| 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 | 0.000 | 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