112: Multi-Source Feedback: Everyone has a Say, But Who is Listening?
Bibliographic record
Abstract
Multi-source feedback (360-degree feedback) involves the collection of feedback from multiple groups of assessors, including those who do not traditionally have a hierarchal responsibility to evaluate physicians. Allied health care professionals, administrative staff, colleagues, patients and their families contribute to the formative assessment of physicians through the completion of standardized forms that are compiled and then reviewed by the individual being assessed. Theoretically, the feedback collectively provides a thorough view of physician performance in daily practice in the humanistic and relational competencies, which traditionally are particularly difficult to assess. To explore perceptions of multi-source feedback and prerequisites to an effective multi-source feedback program in postgraduate medical education from the perspectives of both paediatric residents and allied health care professionals. This exploratory case study utilized a paediatric inpatient unit where multi-source feedback has not yet been implemented as part of a needs assessment. Three focus groups were conducted with purposefully recruited participants from three distinct groups: junior paediatric residents, senior paediatric residents, and allied health care professionals. Discussions were audio recorded, subsequently transcribed and analyzed with thematic analysis. Both residents and allied health care professionals expressed a strong interest in the concept of multi-source feedback. However, more in depth discussions identified barriers to residents' acceptance of, and allied health care professionals' provision of feedback. Interpersonal dynamics, concerns about (mis)understanding of roles and responsibilities and power hierarchies were identified as barriers to both accepting and providing feedback. Interest in opportunities to engage in bidirectional feedback amongst allied health care providers and residents were expressed by all three focus groups. The barriers and prerequisites to providing and accepting multisource feedback identified suggest limits to the efficacy of the multi-source feedback process. Our findings suggest that these factors should be considered in the design and implementation of multi-source feedback programs.
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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 | 0.010 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".