The evidence base for interprofessional education within health professions education: A protocol for an update review
Bibliographic record
Abstract
Interprofessional education (IPE) interventions aiming to promote collaborative competence and improve the delivery of health and social care processes and outcomes continue to evolve. This paper reports on a protocol for an update review that we will conduct to identify and describe how the IPE evidence base has evolved in the last 7 years. We will identify literature through a systematic search of the following electronic databases: Medline, Embase, CINAHL, Education Source, ERIC, and BEI. We will consider all IPE interventions delivered to health professions students and accredited professionals. Peer-reviewed empirical research studies published in any language from June 2014 onwards will be eligible for inclusion. The outcomes of interest are changes in the reaction, attitudes/perceptions, knowledge/skills acquisition, behaviors, organizational practice, and/or benefits to patients. We will perform each task of screening, critical appraisal, data abstraction, and synthesis using at least two members of the review team. The review will enable an update and comprehensive understanding of the IPE evidence base to inform future IPE developments, delivery and evaluation across education and clinical settings.
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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 | 0.088 | 0.134 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.011 | 0.016 |
| Bibliometrics | 0.023 | 0.024 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.054 | 0.012 |
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".