Systemic, Institutional, and Teaching Factors in the Delivery of Interprofessional Education Curriculum in Canada
Bibliographic record
Abstract
The Canadian federal and several provincial governments are currently collaborating to establish ‘team-based’ primary healthcare—or interprofessional collaborative practice (IPCP), which can be effectively accomplished when interprofessional education (IPE) is sustainably delivered by health and social care (HASC) professional education programs. Indeed, achieving the intended patient/client-oriented outcomes of IPE and subsequent IPCP requires deliberate and purposeful considerations of several systemic, institutional, and teaching factors. Regrettably, the analyses of the extent to which these factors have influenced effective IPCP is currently under-researched. In this integrated-article dissertation, we took a purposeful and systematic approach to explore the extent to which these multi-tiered factors influence effective IPCP in the Canadian context. First, we conducted a systematic review (Chapter 2) to familiarize ourselves with and explore when and where IPE has been implemented over the past decade (2010–2020). Next, we conducted a comparative document analysis (Chapter 3) of Canadian HASC professional accreditation standards documents, through which we evaluated the accountability of interprofessional-relevant accreditation standards―to which accrediting organizations can hold their respective academic programs accountable. These two research studies revealed three major research gaps: (1) that most IPE initiatives lacked use of theoretical/conceptual frameworks; (2) that the IPE-relevant accreditation standards overwhelmingly emphasized Students and Educational Program domains, thereby potentially compromising the sustainability of IPE; and (3) that longer IPE initiatives with greater intensity and more rigorous methodological and assessments methods are warranted. To address the first research gap, we present a conceptual paper (Chapter 4) in which we discussed the importance of curriculum and learning theories to HASC professional education processes and proposed a theoretical framework for productive engaged learning, through which IPE opportunities may be grounded. To address the second and third research gaps, we explored the integration of IPE curriculum models in the programmatic structures at four, large Canadian post-secondary institutions (Chapter 5). We further explored the enablers, barriers/challenges, limitations, and outcomes of these curriculum models, as perceived by IPE facilitators and preceptors and whether they truly lead to effective IPCP (Chapter 6). This research reinforces global and national efforts to promote sustainable IPE with aim to improve patient/client-centred care.
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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 | 0.017 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.017 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".