Clinical supervision and learning opportunities during simulated acute care scenarios
Bibliographic record
Abstract
CONTEXT: Closer clinical supervision has been increasingly promoted to improve patient care. However, the continuous bedside presence of supervisors may threaten the model of progressive independence traditionally associated with effective clinical training. Studies have shown favourable effects of closer supervision on trainees' learning, but have not paid specific attention to the learning processes involved. METHODS: We conducted a simulation-based study to explore the learning opportunities created during simulated resuscitation scenarios under different levels of supervision. Fifty-three residents completed a supervised scenario. Residents were randomised to one of three levels of supervision: telephone (distant); in-person after telephone consultation (immediately available), and in-person from the beginning of the simulation (direct). These interactions were converted into 234 pages of transcripts for analysis. We performed an inductive thematic analysis followed by a deductive analysis using situated learning theory as a theoretical framework. RESULTS: Learning opportunities created during simulated scenarios were identified as belonging to either of two categories, incidental and engineered opportunities. The themes resulting from this framework contributed to our understanding of trainees' contributions to patient care, supervisors' influences on patient care, and trainee-supervisor interactions. All forms of supervision offered trainees incidental opportunities for practice, although the nature of these contributions could be affected by the bedside presence of supervisors. Supervisors' involvement in patient care by telephone and in person was associated with a shift of responsibility for patient care, but represented, respectively, engineered and incidental opportunities for observation. In-person supervisor-trainee interactions added value to observation and created additional opportunities for incidental feedback and engineered practice. CONCLUSIONS: The shift of responsibility for patient care occurred during both direct and distant supervision, and did not necessarily translate into a lack of opportunities for trainee participation and practice.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".