Interdisciplinary education in undergraduate health programs: A scoping review / Interdisziplinäre Ausbildung in den Gesundheitsberufen. Ein Scoping Review.
Bibliographic record
Abstract
Abstract Background Patients rely on multiple healthcare providers working cohesively as a team. However, learners in health-related disciplines are typically trained in isolation from one another. While some literature has explored how collaborative learning at the graduate level, undergraduate health programs are often not included in this discourse. Objectives This study aims to identify literature detailing collaborative, or interdisciplinary education (IDE), initiatives, attitudes, and interventions in undergraduate health-related programs. Methods The Arksey and O’Malley scoping review methodological framework was followed. A search was conducted (December 2023) using CINAHL, Embase, ERIC, Ovid MEDLINE, PsychInfo, and Web of Science. Studies were included if they involved two or more disciplines (at least one health-related) and/or post-secondary undergraduate learners, and if they were related to education. Studies were excluded if they discussed learners outside direct-entry undergraduate programs, were studies on working health professionals, or did not focus on IDE. Using the Donabedian model, results were synthesized into IDE structure, process, and outcomes. Results Thirty-five studies met the inclusion criteria. Micro, meso, and macro structures were found to facilitate or pose barriers to IDE. Regarding process, there were various disciplines, intervention types, durations, and teaching modalities. Positive outcomes included student knowledge, skills, attitudes and beliefs, and behaviors. Challenges included lack of support and difficulties with resources and logistics, learning activities, student group dynamics, and attitudes and beliefs. Studies offered recommendations for IDE. Our analysis revealed gaps in the literature concerning reporting of IDE process and outcomes. Conclusions We make recommendations for education researchers, educational developers, and policymakers regarding the design, implementation, evaluation, and reporting of IDE.
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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 | 0.016 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.020 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".