When Feedback is Not Perceived as Feedback: Challenges for Regulatory Body–Mandated Peer Review
Bibliographic record
Abstract
PURPOSE: Safe and competent patient care depends on physicians recognizing and correcting performance deficiencies. Generating effective insight depends on feedback from credible sources. Unfortunately, physicians often have limited access to meaningful guidance. To facilitate quality improvement, many regulatory authorities have designed peer-facilitated practice enhancement programs. Their mandate to ensure practice quality, however, can create tension between formative intentions and risk (perceived or otherwise) of summative repercussions. This study explored how physicians engage with feedback when required to undergo review. METHOD: Between October 2018 and May 2020, 30 physicians representing various specialties and career stages were interviewed about their experiences with peer review in the context of regulatory body-mandated programs. Twenty had been reviewees and reviewers and, hence, spoke from both vantage points. Interview transcripts were analyzed using a 3-stage coding process informed by constructivist grounded theory. RESULTS: Perceptions about the learning value of mandated peer review were mixed. Most saw value but felt anxiety about being selected due to being wary of regulatory bodies. Recognizing barriers such perceptions could create, reviewers described techniques for optimizing the value of interactions with reviewees. Their strategies aligned well with the R2C2 feedback and coaching model with which they had been trained but did not always overcome reviewees' concerns. Reasons included that most feedback was "validating," aimed at "tweaks" rather than substantial change. CONCLUSIONS: This study establishes an intriguing and challenging paradox: feedback appears often to not be recognized as feedback when it poses no threat, yet feedback that carries such threat is known to be suboptimal for inducing performance improvement. In efforts to reconcile that tension, the authors suggest that peer review for individuals with a high likelihood of strong performance may be more effective if expectations are managed through feedforward rather than feedback.
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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 | 0.339 | 0.622 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.021 |
| Scholarly communication | 0.020 | 0.015 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".