Development of a Team Performance Scale to Assess Undergraduate Health Professionals
Bibliographic record
Abstract
PURPOSE: Interprofessional simulation-based team training is strongly endorsed as a potential solution for improving teamwork in health care delivery. Unfortunately, there are few teamwork evaluation instruments. The present study developed and tested the psychometric characteristics of the newly developed KidSIM Team Performance Scale checklist. METHOD: A quasi-experimental research design engaging a convenience sample of 196 undergraduate medical, nursing, and respiratory therapy students was completed in the 2010-2011 academic year. Multidisciplinary student teams participated in a simulation-based curriculum that included the completion of two acute illness management scenarios, resulting in 282 independent reviews by evaluators from medicine, nursing, and respiratory therapy. The authors investigated the underlying factors of the performance checklist and examined the performance scores of an experimental and a control team-training-curriculum group. RESULTS: Participation in the supplemental team training curriculum was related to higher team performance scores (P < .001). All teams at Time 2 achieved higher scores than at Time 1 (P < .05). The reliability coefficient for the total performance scale was α = 0.90. Factor analysis supported a three-factor solution (accounting for 67.9% of the variance) with an emphasis on roles and responsibilities (five items) and communication (six items) subscale factors. CONCLUSIONS: When simulation is used in acute illness management training, the KidSIM Team Performance Scale provides reliable, valid score interpretation of undergraduates' team process based on communication effectiveness and identification of roles and responsibilities. Implementation of a supplementary team training curriculum significantly enhances students' performance in multidisciplinary simulation-based scenarios at the undergraduate level.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".