Insight into team competence in medical, nursing and respiratory therapy students
Bibliographic record
Abstract
This study provides information for educators about levels of competence in teams comprised of medical, nursing and respiratory therapy students after receiving a simulation-based team-training (SBT) curriculum with and without an additional formalized 30-min team-training (TT) module. A two-group pre- and post-test research design was used to evaluate team competence with respect to leadership, roles and responsibilities, communication, situation awareness and resource utilization. All scenarios were digitally recorded and evaluated using the KidSIM Team Performance Scale by six experts from medicine, nursing and respiratory therapy. The lowest scores occurred for items that reflected situation awareness. All teams improved their aggregate scores from Time 1 to Time 2 (p < 0.05). Student teams in the intervention group achieved significantly higher performance scores at Time 1 (Cohen's d = 0.92, p < 0.001) and Time 2 (d = 0.61, p < 0.01). All student teams demonstrated significant improvement in their ability to work more effectively by Time 2. The results suggest that situational awareness is an advanced expectation for the undergraduate student team. The provision of a formalized TT module prior to engaging student teams in a simulation-based TT curriculum led to significantly higher performances at Time 1 and 2.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".