Health checks for adults with intellectual and developmental disabilities in a family practice.
Bibliographic record
Abstract
OBJECTIVE: To provide tips and tools for primary care practitioners carrying out health checks for adult patients with intellectual and developmental disabilities (IDD) and for implementing a systematic program of health checks in a group or team practice. SOURCES OF INFORMATION: The "Primary Care of Adults with Intellectual and Developmental Disabilities. 2018 Canadian Consensus Guidelines" literature review and interdisciplinary input. Experience in implementing health checks in family practices was obtained through the primary care project of H-CARDD (Health Care Access Research and Developmental Disabilities). MAIN MESSAGE: Annual comprehensive health assessments ("health checks") are a recommendation of the 2018 Canadian consensus guidelines for primary care of adults with IDD because of evidence of benefit in this population. Although health checks might require more time to complete for people with IDD than is usual for encounters in primary care, family physicians are in an ideal position to provide this service because of the attributes of family medicine, which include both an orientation to proactive care and the ability to provide continuity of care. Tips and tools are provided for carrying out health checks for adult patients with IDD and for implementing a systematic program of health checks in a group or team practice. CONCLUSION: Health checks can help enhance a family physician's approach to providing care for adults with IDD.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".