Precipitating and Predisposing Events and Symptoms For Admission to Assisted Living or Nursing Home Care
Bibliographic record
Abstract
BACKGROUND: In Canada, the rise of private-pay assisted living facilities is changing the long-term care landscape. Even so, few clinical implications of having these facilities in the spectrum of care have been studied. Our objective was to compare events and symptoms that might predispose and precipitate a move of older adults to assisted living or to a nursing home. METHODS: Cross-sectional, descriptive Nova Scotia survey of residents and family members on admission. Health-care use and dementia diagnosis were recorded from the admission record. Dementia was staged using the Global Deterioration Scale and the Dependence Scale. The SymptomGuide, a standardized dementia symptom inventory, was used to assay which symptoms were most influential in the decision to seek long term care. Caregiver stress was elicited by a self-report questionnaire. RESULTS: Of 353 people admitted during the enrolment period, 174 (49%) took part in the survey. Most (97; 55.7%) were involved in a move from the community to a nursing home, 54 (31.0%) from the community to assisted living, and 23 (13.2%) from assisted living to a nursing home. In each setting, dementia was the commonest predisposing factor (seen in >90%) with a precipitating event seen in 120 (69%) people. The precipitating events included a medical illness (n = 97; 55%) or caregiver illness, death or move (33; 19%). Dependence was associated with place of care, with more severely impaired people more commonly represented in people who moved to nursing homes. CONCLUSIONS: People move from the community chiefly due to dementia, and often with a precipitant. Compared with a move to assisted living, moving to nursing homes generally indicates greater dependence, and typically worse dementia severity. Even so, assisted-living facilities are not just for the "worried well", but are used by people with dementia, caregiver stress, and recent hospitalization.
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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 | 0.002 |
| 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) | 0.003 | 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".