The RIPPER Experience: A 3 Year Evaluation of an Australian Interprofessional Rural Health Education Pilot
Bibliographic record
Abstract
AbstractBackground: The Rural Interprofessional Program Educational Retreat (RIPPER) uses interprofessional learning and educational strategies to prepare final year Tasmanian nursing, medical, and pharmacy students for effective healthcare delivery. RIPPER provided students (n = 90) with the opportunity to learn about working in an interdisciplinary team using authentic and relevant situational learning. RIPPER allowed students to work and learn interprofessionally in small teams and to apply their different professional skills and knowledge to a variety of rural healthcare situations.Methods and Findings: This article reports on three years of results from the program’s evaluation which used a pre-post test mixed method design. The findings show a significant and positive shift in students’ attitudes and understanding of interprofessional learning and practice following their participation in RIPPER. The evaluation findings suggest the need for sustainable interprofessional rural health education that is embedded in undergraduate curricula.Conclusion: The evaluation of RIPPER suggests that exposure of healthcare students to interprofessional education can positively affect their perceptions of collaboration, patient care, and teamwork. The evaluation also points to the rural context as an ideal place to showcase elements of effective interprofessional practice.
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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 | 0.027 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".