Attracting the interprofessional collaboration between physical therapy, speech therapy and ABSN nursing students working with patients diagnosed with stroke during simulation
Bibliographic record
Abstract
The purpose of this mixed methods interprofessional simulation was to assess health science university students in physical therapy, speech therapy, and nursing to the positive role of interprofessional collaboration by means of a live actor stroke simulation. The interprofessional simulation was divided into two segments which was comprised of: 1) the application of various teaching methods and orientation to the simulation lab, and 2) taking part in the organized simulated interprofessional care plan and subsequently participating in the debriefing and self-reflective exercises learning experiences. Logistic regression was used to measure quantitative outcomes including the Simulation Evaluation Survey questionnaire. The results were statistically significant. Qualitative data was obtained during simulation debriefing sessions, and was coded and analyzed. Incorporating the importance of inter-professional collaboration in professional program students helps promote team work, leadership, problem solving, critical thinking, and communication. The authors recommend incorporating interprofessional simulation in the curriculum for health care educational programs.
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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 | 0.004 | 0.017 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".