Experiences, attitudes, and knowledge of medical students regarding intellectual and developmental disability: a Canadian study
Bibliographic record
Abstract
BACKGROUND: As the healthcare of individuals with intellectual and developmental disabilities (IDD) shifts toward community-based services, physicians in all areas of medicine are more likely to care for this population. To ensure that all physicians can provide high-quality care to people with IDD, further understanding and attention to undergraduate medical education related to IDD is needed. METHODS: A 24-item survey assessed the experiences, attitudes, knowledge, skills, and future interest of Canadian medical students regarding IDD. Descriptive statistics were calculated for questionnaire responses and responses of students who had more in-depth experience were compared to those of students with minimal past experience. RESULTS: A total of 443 Canadian medical students completed the survey. Students did not feel competent obtaining clear histories from people with IDD. Most students were not confident they could provide quality care to this population but wanted further learning. Students with prior IDD experiences through family/friends felt more knowledgeable and interested in caring for this population than those with community/clinical and minimal experiences. DISCUSSION: Many Canadian medical students lack the knowledge and skills needed to adequately care for people with IDD. Despite this, a majority of students were interested in further learning opportunities to improve care for people with IDD. These findings underscore the necessity of evaluating the current medical curriculum and implementing measures to better prepare students to care for this population.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".