Support‐staging model for caregivers of adults with intellectual disability affected by dementia
Bibliographic record
Abstract
Abstract Background Adults with intellectual disability (ID) and dementia are a sub‐population of persons who are often un‐ or underserved. Most adults with ID are integrated within the general community (living autonomously, or in apartments/group residences); but significant numbers also reside with their families, particularly adults with Down syndrome. Family help/counseling approaches, such as the New York University‐Caregiver Intervention (NYUCI), might benefit from a support‐staging model assessment focus on what specific aid a family requires to meet their needs. Patterns of such needs have been identified that can help with providing dementia‐capable care. Objective needs include: (a) information on signs and symptoms, (b) diagnostic advice, (c) understanding behavioral changes and managing dementia‐related behaviors, (d) adapting homes, (e) determining daily routines most conducive to calming, (f) planning for the future, (g) finding and navigating resources, and (h) responding to end‐of‐life needs. Subjective needs include: (a) being informed at time of diagnosis and throughout the course of dementia, (b) coping with a profound sense of loss from knowing the diagnosis, (c) fearing the future [including financial concerns], (d) formulating long‐term plans, (e) accessing community‐based coordinated care, (f) facing difficulties from the medical community, (g) feeling overwhelmed by caregiving demands, (h) feeling a sense of isolation and abandonment, and (i) facing end‐of‐life issues. A working group emanating from the 2016 Glasgow Summit on Intellectual Disability and Dementia organized a schema encapsulating these concerns into a support‐staging model. The schema suggested four fluid stages: Diagnostic (seeking cause of changes in function, abilities, personality), Explorative (exploring dementia capable interventions), Adaptive (coping with and managing the symptoms/changes), and Closure (resolving / relief from responsibilities). Using this schema, a process (utilizing the NYUCI) is underway to operationalize a support‐staging assessment instrument which would enable counseling staff to frame the state of a family’s concerns, build relationships through this knowledge of the caregiver and provide tailored services to them. The outcome will enable systematic coding and organizing both objective and subjective data so that specific interventions and counseling can be adapted to meet both intermittent and continuous caregiver needs.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".