Evaluating an undergraduate interprofessional simulation-based educational module: communication, teamwork, and confidence performing cardiac resuscitation skills
Bibliographic record
Abstract
PURPOSE: Interprofessional (IP) collaboration during cardiac resuscitation is essential and contributes to patient wellbeing. The purpose of this study is to evaluate an innovative simulation-based IP educational module for undergraduate nursing and medical students on cardiac resuscitation skills. METHODS: Nursing and medical trainees participated in a new cardiac resuscitation curriculum involving a 2-hour IP foundational cardiac resuscitation skills lab, followed by three 2-hour IP simulation sessions. Control group participants attended the existing two 2-hour IP simulation sessions. Study respondents (N = 71) completed a survey regarding their confidence performing cardiac resuscitation skills and their perceptions of IP collaboration. RESULTS: Despite a consistent positive trend, only one out of 17 quantitative survey items were significantly improved for learners in the new curriculum. They were more likely to report feeling confident managing the airway during cardiac resuscitation (P = 0.001). Overall, quantitative results suggest that senior nursing and medical students were comfortable with IP communication and teamwork and confident with cardiac resuscitation skills. There were no significant differences between nursing students' and medical students' results. Through qualitative feedback, participants reported feeling comfortable learning with students from other professions and found value in the IP simulation sessions. CONCLUSION: Results from this study will inform ongoing restructuring of the IP cardiac resuscitation skills simulation module as defined by the action research process. Specific improvements that are suggested by these findings include strengthening the team leader component of the resuscitation skills lab and identifying learners who may benefit from additional practice in the role of team leader and with other skills where they lack confidence.
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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 | 0.003 | 0.034 |
| 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 | 0.002 |
| 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".