Family physicians' reactions to performance assessment feedback.
Bibliographic record
Abstract
OBJECTIVE: To explore and describe family physicians' personal and professional responses to performance assessment feedback. DESIGN: Qualitative study using one-on-one semistructured interviews after feedback on performance. SETTING: Fee-for-service family practices in eastern Ontario. PARTICIPANTS: Eight physicians out of 25 physicians in the control group of a previous randomized controlled trial who received performance assessment feedback were purposefully selected using maximum variation sampling to represent various levels of performance. Five female physicians (2 part-time and 3 full-time) and 3 male physicians (all full-time) were interviewed. These physicians had practised family medicine for an average of 18.5 years (range 9 to 32 years). METHOD: Semistructured one-on-one interviews were conducted to determine what physicians thought and felt about their private feedback sessions and to solicit their opinions on performance assessment in general. Information was analyzed using an open coding style and a constant comparative method of analysis. MAIN FINDINGS: Two major findings were central to the core elements of medical professionalism and perceived accountability. Physicians indicated that the private feedback they received was a valuable and necessary part of medical professionalism; however, they were reluctant to share this feedback with patients. Physicians described various layers of accountability from the most important inner layer, patients, to the least important outer layer, those funding the system. CONCLUSION: Performance feedback was viewed as important to family physicians for maintaining medical professionalism and accountability.
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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 | 0.016 | 0.113 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".