Investigating conditions for meaningful feedback in the context of an evidence‐based feedback programme
Bibliographic record
Abstract
CONTEXT: We developed, implemented and evaluated an evidence-based programme of feedback designed to address limitations identified in the current literature. OBJECTIVES: We sought to advance understanding about how and why feedback processes might be more effective in clinical education. METHODS: Three faculty members and nine first-year internal medicine residents participated in the pilot programme. To counter challenges identified in the literature, feedback was based on direct observation, grounded in longitudinal faculty-resident relationships, and devoid of summative assessment. We used a qualitative case study design to address three research questions: (i) What benefits did the participants describe? (ii) What elements of the programme facilitated these benefits? (iii) What were the limitations and challenges of the programme? Collected data included audiotapes of interactions between faculty members and residents, field notes written during observations, and semi-structured interviews and focus groups with resident participants. Data analysis moved cyclically and iteratively through inductive and deductive analysis. RESULTS: Residents described benefits relating to their ways of working (clinical skills), ways of learning (accountability for learning) and ways of feeling (emotional well-being). According to participants, specific elements of the programme that achieved these benefits included the direct observation of authentic clinical work, the longitudinal relationship with a faculty member and the emergence of feedback as a conversation between the faculty member and learner. CONCLUSIONS: We conclude that the conditions established within our pilot feedback programme influenced the learning culture for first-year internal medicine residents by grounding direct observation in authentic clinical work and setting the observations in the context of a longitudinal, non-assessment-based relationship between a faculty member and resident. These conditions appeared to influence residents' participation in the feedback process, their ways of approaching their daily clinical work, their emotional well-being and their engagement in their own learning.
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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 | 0.177 | 0.411 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".