Dissecting through Barriers: A Follow‐up Study on the Long‐Term Effects of Interprofessional Education in a Dissection Course with Healthcare Professional Students
Bibliographic record
Abstract
Several studies have shown significant improvements in the attitudes and perceptions of healthcare professional students toward interprofessional education (IPE) immediately following intervention with IPE courses. However, there remains little evidence on the lasting effects of IPE courses and the long-term influences of these IPE experiences are poorly documented. The purpose of this study is to assess the long-term effects of an intensive, ten-week interprofessional gross anatomy dissection course at McMaster University. Attitudes and perceptions of past participants towards interprofessional learning were evaluated, now that they have started working with other healthcare professionals outside of the IPE course setting. Thirty-four past participants who have clinical experience working in interprofessional settings or are currently working in the healthcare field completed a follow-up questionnaire consisting of a modified Readiness for Interprofessional Learning Scale (RIPLS) and open-ended questions. Quantitative analysis revealed a significant decrease in their attitude towards teamwork and collaboration and respect for other health professions, but a significant improvement in their understanding of roles and responsibilities compared to their results immediately after the IPE intervention. Qualitative analysis of open-ended questions revealed several themes such as developing interprofessional competencies, developing relationships, and remembering the strengths of the IPE dissection course. The results of this study indicate that the IPE experience in anatomy was highly valued by the students and that past participants maintain a clear understanding of their scope of practice, but the reality of clinical practice may have eroded gains made in the program. Anat Sci Educ. © 2018 American Association of Anatomists.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".