The R2C2 Model in Residency Education: How Does It Foster Coaching and Promote Feedback Use?
Bibliographic record
Abstract
PURPOSE: The authors previously developed and tested a reflective model for facilitating performance feedback for practice improvement, the R2C2 model. It consists of four phases: relationship building, exploring reactions, exploring content, and coaching. This research studied the use and effectiveness of the model across different residency programs and the factors that influenced its effectiveness and use. METHOD: From July 2014-October 2016, case study methodology was used to study R2C2 model use and the influence of context on use within and across five cases. Five residency programs (family medicine, psychiatry, internal medicine, surgery, and anesthesia) from three countries (Canada, the United States, and the Netherlands) were recruited. Data collection included audiotaped site assessment interviews, feedback sessions, and debriefing interviews with residents and supervisors, and completed learning change plans (LCPs). Content, thematic, template, and cross-case analysis were conducted. RESULTS: An average of nine resident-supervisor dyads per site were recruited. The R2C2 feedback model, used with an LCP, was reported to be effective in engaging residents in a reflective, goal-oriented discussion about performance data, supporting coaching, and enabling collaborative development of a change plan. Use varied across cases, influenced by six general factors: supervisor characteristics, resident characteristics, qualities of the resident-supervisor relationship, assessment approaches, program culture and context, and supports provided by the authors. CONCLUSIONS: The R2C2 model was reported to be effective in fostering a productive, reflective feedback conversation focused on resident development and in facilitating collaborative development of a change plan. Factors contributing to successful use were identified.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".