Evaluation of a Unique Interprofessional Education Program Involving Medical and Pharmacy Students
Bibliographic record
Abstract
Objective. To measure changes in interprofessional competencies among pharmacy and medical students following a half-day event focusing on interprofessional learning. Methods. There were 118 pharmacy students and 28 medical students who participated in the Healthcare Interprofessional Education Day (HIPED) which consisted of three stations (communication, patient interviewing, and prescribing) in which pharmacy and medical students had to work collaboratively. The standardized Interprofessional Collaborative Competency Attainment Survey (ICCAS) was used to evaluate the effectiveness of the program. Results. There were 133 surveys completed for a response rate of 91%. All 20 items measured by the ICCAS showed a significant improvement. The strongest effect sizes were in the collaboration, roles & responsibilities, and collaborative practice/family-centered approach categories. The least robust effects were in the conflict management/resolution category. Conclusion. The HIPED activity was an effective IPE experience. The strong and consistent improvement in all ICCAS scores suggest a framework for pharmacy and medical school training to move from siloed educational experiences to synergistic learning opportunities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".