A follow‐up study of mortality, health conditions and associated disabilities of people with intellectual disabilities in a Swedish county
Bibliographic record
Abstract
BACKGROUND: In the planning of services and health care for individuals with intellectual disability (ID), information is needed on the special requirements for habilitation and medical service and associated disabilities. MATERIAL AND METHODS: An unselected consecutive series of 82 adult persons with ID was studied. The medical examination consisted of the individual's health condition, associated impairments and disabilities. Medical and habilitation services and support were studied. RESULTS: The results indicated that 71% of the persons in the series had severe and 29% mild ID. Forty-seven per cent of the persons with severe ID and 35% of those with mild ID had one or more additional central nervous system (CNS) disabilities. Of the persons with ID, 99% had access to a family doctor and 84% attended regular health visits. Notably, half of persons were referred to a specialist examination as a consequence of their present medical examination. Half of the persons with mental health problems were previously undiagnosed and only a few of these had access to a psychiatrist. CONCLUSION: Our study clearly demonstrates the magnitude and importance of neurological and psychiatric impairments in ID. The findings suggest a strong need for multidisciplinary health service.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".