Utilization of the Canadian Interprofessional Health Collaborative as an Evaluation Framework for Student Participation in a Community-Engaged Project
Bibliographic record
Abstract
Purpose: Interprofessional education is a foundational component of many health professions educational programs as it contributes to the goals of the Quadruple Aim by prioritizing collaborative and streamlined quality healthcare. Furthermore, student engagement in interprofessional educational activities provides opportunities to better understand their own and others’ health profession disciplines. The purpose of this project was to utilize Canadian Interprofessional Health Collaborative (CIHC) to evaluate a framework for student engagement in a community-engaged project focused on reducing barriers to care in people living with type 1 diabetes in rural communities. Methods: As members of an interprofessional, type 1 diabetes, community-engaged research team, students from various graduate and pre-health professions programs participated a variety of activities as research assistants to increase their competency as future healthcare practitioners. These activities included research capacity building, interprofessional collaborations, patient and community interactions, and interprofessional healthcare research. Utilizing the CIHC Framework, the learners reflected and assessed their interprofessional competency, growth, professional identify, and understanding of interprofessional collaboration while providing suggestions for future students participating in interprofessional health sciences research. Findings: Learners found the CIHC to be a robust tool for reflecting on their abilities to provide care in an interprofessional team. The community engagement projects heightened their abilities in role clarification, team functioning, and collaborative leadership which were determined by the group to be some of the most essential skills for entering an interprofessional healthcare workforce. Conclusions: Use of the CIHC framework was an effective method to guide learner progress in developing interprofessional skills within a community engagement project. Reflection on achievement of CIHC domains assists learners in identification of growth in professional identity and understanding of interprofessional collaboration.
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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 | 0.144 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.001 | 0.003 |
| 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 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".