Introduction and evaluation of an interprofessional undergraduate simulation program in obstetrics and gynaecology - getting started and lessons learned
Bibliographic record
Abstract
Objective: Interprofessional education (IPE) occurs when two or more professions learn about, from and with each other to improve the quality of care. In Canada, the increasing need for IPE has been acknowledged on a national level.The objective of this project was to assess the implementation and evaluation of an interprofessional simulation curriculum in Obstetrics and Gynaecology (Ob/ Gyn) clerkship. Methods: Three obstetrical emergency simulations were presented to small interprofessional groups of undergraduate students (103): medicine (80), nursing (14), respiratory therapy (1), and paramedicine (8) between September 9, 2016 to August 8, 2017. A paper-based evaluation form was completed by all students.The purpose was to use this evaluation form to conduct a quality assurance review following the completion of the first year of this new interprofessional simulation program. Results: Ninety-nine percent of students indicated the session would benefit their clinical performance; 97.1% found the debriefing exercise helpful; 93% indicated the session was appropriate to their level of training; 98.1% felt it provided valuable team skills training; 92.2% indicated it helped them understand the roles of other health professionals; 96.1% indicated it helped improve collaborative leadership; and 87.1% noted a better understanding of the unique skillset of other health professionals.All students felt they were in a safe learning environment. Conclusion:To our knowledge, this is the first simulation program in Ob/Gyn clerkship in Canada designed to promote IPE amongst the four learner groups described above. Interprofessional simulation in Ob/Gyn Clerkship is valuable and well received by students from all health professional programs involved. It improves communication, role clarification, and collaboration.
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 | 0.011 | 0.022 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".