Considering the interdependence of clinical performance: implications for assessment and entrustment
Bibliographic record
Abstract
INTRODUCTION: Our ability to assess independent trainee performance is a key element of competency-based medical education (CBME). In workplace-based clinical settings, however, the performance of a trainee can be deeply entangled with others on the team. This presents a fundamental challenge, given the need to assess and entrust trainees based on the evolution of their independent clinical performance. The purpose of this study, therefore, was to understand what faculty members and senior postgraduate trainees believe constitutes independent performance in a variety of clinical specialty contexts. METHODS: Following constructivist grounded theory, and using both purposive and theoretical sampling, we conducted individual interviews with 11 clinical teaching faculty members and 10 senior trainees (postgraduate year 4/5) across 12 postgraduate specialties. Constant comparative inductive analysis was conducted. Return of findings was also carried out using one-to-one sessions with key informants and public presentations. RESULTS: Although some independent performances were described, participants spoke mostly about the exceptions to and disclaimers about these, elaborating their sense of the interdependence of trainee performances. Our analysis of these interdependence patterns identified multiple configurations of coupling, with the dominant being coupling of trainee and supervisor performance. We consider how the concept of coupling could advance workplace-based assessment efforts by supporting models that account for the collective dimensions of clinical performance. CONCLUSION: These findings call into question the assumption of independent performance, and offer an important step toward measuring coupled performance. An understanding of coupling can help both to better distinguish independent and interdependent performances, and to consider revising workplace-based assessment approaches for CBME.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".