Building patient safety culture by using interprofessional simulation with nursing, paramedic, and emergency telecommunication students: A mixed- methods research study
Bibliographic record
Abstract
Purpose: Healthcare, allied health, and social service professionals have an essential role in fostering student’s attitudes, skills, and behaviours that support safe care. The aim of this study was to offer new insights into assessments of interprofessional education by evaluating student’s perceptions of an interprofessional simulation experience. Principal results: Teams comprised of nursing (n=81), paramedic (n=38), and emergency telecommunication students (n=11) were involved in a high acuity simulated scenario involving a client with a high-risk pregnancy and her family. Both quantitative and qualitative data were evaluated. The findings suggest that the students found the experience important in developing communication, teamwork and collaboration skills that are essential for effective handover communication and patient safety. Major conclusions: Based on thematic coding, 4 themes emerged from the data: communication and collaboration in teamwork; roles and responsibilities, and leadership; patient-centred care and safety; and emotional dynamics and professional growth. Emergency telecommunication students noted ‘feedback being constructive and timely’ as the most important in the simulation design while nursing and paramedic students rated ‘opportunity to obtain feedback from teacher to build knowledge to another level’ as the most important. Students wanted earlier and more frequent interprofessional education experiences. Areas that students identified as needing more clarity included role clarification and collaborative leadership. Key Words: patient safety, interprofessional education, simulation, health professional students, handover communication, mixed methods Please find Quantitative Survey Results for the SPICE-R2 Tool, ANOVA solved to compare results by program.
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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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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; 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".