Approach to providing care for aging adults with intellectual and developmental disabilities.
Bibliographic record
Abstract
OBJECTIVE: To provide an approach to caring for aging adults with intellectual and developmental disabilities (IDD) in the context of the onset of new or worsening chronic illnesses and the need for planning for the end of life. SOURCES OF INFORMATION: A MEDLINE search identified few review articles in the past 10 years. This review builds on relevant articles and the experiences of the author and colleagues working with aging adults with IDD and their families, physicians, and other caregivers. MAIN MESSAGE: To provide care to this patient group, physicians must understand the diverse cognitive abilities of adults with IDD; the risk factors for physical and mental illnesses; concerns related to diagnostic overshadowing; and the need for coordinating individual care plans for those with serious and terminal illnesses. CONCLUSION: Primary care physicians can provide and coordinate appropriate care for patients with IDD as they face the health challenges associated with aging and dying. Being aware of patients' baseline cognitive abilities and decision-making skills, as well as changes in cognitive abilities associated with aging and complexity of illness, will help determine patients' capacity to consent, identify appropriate treatment choices, and guide coordination of care. Further research and consensus statements are needed to guide best practices based on the Canadian experience and to allow continuing development of caring, professional, and competent providers to support aging adults with all levels of 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".