Building inclusive rehabilitation education: A scoping review protocol on EDI approaches and impact
Bibliographic record
Abstract
INTRODUCTION: Equity, diversity, and inclusion (EDI) interventions are critical in fostering accessible and supportive educational environments in rehabilitation professions such as physiotherapy, occupational therapy, and speech-language pathology. These interventions promote cultural competence and reduce systemic inequities, enabling rehabilitation providers to address healthcare disparities and meet the diverse needs of patient populations. Despite increasing awareness, the scope, implementation, and impact of EDI interventions in rehabilitation education remain underexplored. AIM: This scoping review aims to map the existing literature on EDI interventions in rehabilitation education, focusing on methods, strategies, and their impact on learners' outcomes, including cultural competence, professional practice, and attitudes toward diversity. METHODS: The review follows the Joanna Briggs Institute methodology and PRISMA-Scr guidelines. Studies involving healthcare students and educators in rehabilitation disciplines are eligible. The concept includes EDI-focused interventions, such as curricular reforms, diversity training, and inclusive teaching practices. Eligible contexts include academic and healthcare settings. A comprehensive search strategy will be applied across databases including MEDLINE, EMBASE, and CINAHL, supplemented by grey literature searches. Inclusion criteria follow the Population, Concept, and Context (PCC) framework. RESULTS: This review will chart interventions, their educational context, and their outcomes. Key data to be extracted include study design, intervention details, and learner outcomes, emphasizing cultural competence and attitudes. CONCLUSION: Findings will provide a consolidated framework for developing evidence-based EDI interventions in rehabilitation education, addressing gaps in preparing a workforce capable of delivering equitable care in diverse contexts. Recommendations will guide future research and practice, advancing inclusivity and equity in rehabilitation education.
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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 | 0.102 | 0.091 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.015 | 0.014 |
| Bibliometrics | 0.028 | 0.027 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.062 | 0.011 |
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".