A Systematic Review of Intellectual and Developmental Disability Curriculum in International Pre-Graduate Health Professional Education
Bibliographic record
Abstract
Abstract Background Despite the increasing global population of individuals with intellectual and developmental disabilities (IDD), this population remains especially vulnerable to health disparities through several factors such as a lack of access to sufficient medical care and poor determinants of health. To add, numerous studies have shown that healthcare professionals are still insufficiently prepared to support this population of patients. This review synthesizes the literature on current pre-graduate IDD training programs across healthcare professions with the goal of informing the creation of evidence-based curricula. Methods Four major databases were searched for current pre-graduate IDD training interventions for healthcare professionals. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis flow diagram and the Best Evidence Medical Educations systematic review guide were used to frame our collection and analysis. Results Of the 6236 studies screened, 24 studies were identified, with most studies involving medical students (50%). Of note, 38% of studies were interprofessional. Most interventions utilized multiple pedagogical methods with a majority including clinical experiences (83%) followed by theoretical teaching (50%). Kirkpatrick outcomes showed 13% were level 0, 9% were level 1, 17% were level 2, 33% were level 2B, 25% were level 3, 4% were level 4A, and none were level 4B. Conclusions There is a paucity of formally evaluated studies in pre-graduate health professional IDD education. As well, there are a lack of longitudinal learning opportunities and integration into formal curriculum. Strengths identified were the use of multimodal approaches to teaching, including interprofessional approaches to optimize team competencies.
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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 | 0.012 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".