Addressing Age-Related Complexity in Intellectual Disability (AARC-ID): an economic analysis of different support models. Study protocol.
Bibliographic record
Abstract
People with intellectual disability are living longer. While this is a positive development, it may mean living with age-related morbidities which require specialist care to meet needs. While most people with intellectual disability would prefer to remain living in their current homes, if extra supports are not available, they may experience a need to move into residential type settings such as nursing homes. This is usually related to current funding systems not being responsive to developing age-related needs of people with intellectual disability. For example, if a person had been living independently but they are developing mobility issues, there is often no extra budget for staff to assist them. This can result in the person having to move to a different setting to have their needs met. However, such a move may impact on quality of life, wellbeing and personal dignity. This study will build a picture of the future needs of people who are ageing with intellectual disability, what extra supports they require, and the costs of those supports. This will be completed using two secondary data sources– the Intellectual Disability Supplement to the Irish Longitudinal Study on Ageing (IDS-TILDA) and the National Ability Support System (NASS), as well as collecting primary qualitative data to understand perspectives and experiences. The overall aim of the study is to provide economic evidence on the needs, resources and outcomes associated with supporting people aged ≥40 with intellectual disability to age in place. Data from 15 years of IDS-TILDA, the NASS and Health Service Executive costing calculations are available. Using a variety of analytical methods, levels of support will be defined alongside potential economic and policy scenarios. This research will provide evidence to inform policy such that more people with intellectual disability can continue to age at home rather than enter nursing homes.
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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 | 0.022 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.126 | 0.007 |
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".