Identifying coaching skills to improve feedback use in postgraduate medical education
Bibliographic record
Abstract
OBJECTIVES: Coaching in medical education has recently gained prominence, but minimal attention has been given to key skills and determining how they work to effectively ensure residents are progressing and developing self-assessment skills. This study examined process-oriented and content-oriented coaching skills used in coaching sessions, with particular attention to how supervisors use them to enhance resident acceptance of feedback to enhance learning. METHODS: This qualitative study analysed secondary audiotaped data from 15 supervisors: resident dyads during two feedback sessions, 4 months apart. The R2C2 model was used to engage the resident, build a relationship, explore reactions to feedback, explore resident perceptions of content, and coach for change. Framework analysis was used, including familiarisation with the data, identifying the thematic framework, indexing and charting the data and mapping and interpretation. RESULTS: Process skills included preparation, relationship development, using micro communication skills and techniques to promote reflection and self-assessment by the resident and supervisor flexibility. Content skills related to the specific feedback content included engaging the resident in discussion, ensuring the discussion was collaborative and focused on goal setting, co-developing a Learning Change Plan, ensuring resident commitment and following up on the plan. Together, these skills foster agency in the resident learner. Three overarching themes emerged from the analysis: the interconnectedness of process and content; tensions between encouraging self-direction and ensuring progress and competence; and balancing a coaching dialogue and a teaching monologue. CONCLUSIONS: Effective coaching by supervisors requires a combination of specific process and content skills that are chosen depending on the needs of the individual resident. Mastering these skills helps residents engage and develop agency in their own professional development. These outcomes depend on faculty maintaining a balance between coaching and teaching, encouraging resident self-direction and ensuring progression to competence.
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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 | 0.002 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads 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".