Time to Make Sense: Doctors’ and Students’ Experiences of Difficult Feedback
Bibliographic record
Abstract
Introduction: Learners' experiences of feedback conversations, and their longitudinal impact, are largely invisible to educators. While we know more about what makes for an effective feedback conversation, we are yet to fully understand how learners make sense of these encounters over time. This has implications for understanding the potency of feedback on practice and for how best to support learners, particularly when the experience is challenging. Our research aimed to explore the characteristics of difficult feedback and the temporal aspects of feedback sensemaking. Methods: We collected written narratives from 32 doctors and 49 medical students via an online questionnaire about a time when they received difficult feedback in a clinical setting. Open- ended prompts facilitated participants to describe their experience, the evaluation of it over time, and the learning that arose from it. We undertook reflexive thematic analysis of the data, informed by constructivist sensemaking perspectives. Results: Difficult feedback conversations were characterized by unpredictable and complex interactions between emotions, sensemaking and learning. Despite some feedback perceived as personal, inappropriate, or threatening, feedback information was seldom disregarded. Participants engaged in feedback sharing and reflection, which often extended over years, contributing to identity work and to development of their clinical practice. Discussion: Our findings highlighted the temporal nature of sensemaking of difficult feedback and challenge expectations for learners to respond and commit to progress in the moment. Providing learners with time for reflection on feedback and opportunities to connect with personal and professional networks may facilitate the longitudinal sensemaking processes.
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How this classification was reachedexpand
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 | 0.000 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".