Piloting Interprofessional Education Interventions with Veterinary and Veterinary Nursing Students
Bibliographic record
Abstract
Interprofessional education (IPE) has received little attention in veterinary education even though members of the veterinary and nursing professions work closely together. The present study investigates veterinary and veterinary nursing students' and practitioners' experiences with interprofessional issues and the potential benefits of IPE. Based on stakeholder consultations, two teaching interventions were modified or developed for use with veterinary and veterinary nursing students: Talking Walls, which aimed to increase individuals' understanding of each other's roles, and an Emergency-Case Role-Play Scenario, which aimed to improve teamwork. These interventions were piloted with volunteer veterinary and veterinary nursing students who were recruited through convenience sampling. A questionnaire (the Readiness for Interprofessional Learning Scale [RIPLS]) was modified for use in veterinary education and used to investigate changes in attitudes toward IPE over time (pre-intervention, immediately post-intervention, and four to five months afterward). The results showed an immediate and significant positive change in attitude after the intervention, highlighting the students' willingness to learn collaboratively, their ability to recognize the benefits of IPE, a decreased sense of professional isolation, and reduced hierarchical views. Although nearly half of the students felt concerned about learning with students from another profession before the intervention, the majority (97%) enjoyed learning together. However, the positive change in attitude was not evident four to five months after the intervention, though attitudes remained above pre-intervention levels. The results of the pilot study were encouraging and emphasize the relevance and importance of veterinary IPE as well as the need for further investigation to explore methods of sustaining a change in attitude over time.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 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".