Functional Assessment of Elderly Clients of a Rural Community-Based Long-Term Care Program: A 10-Year Cohort Study
Bibliographic record
Abstract
ABSTRACT As the demand for home care services increases, health care agencies should be able to predict the intake capacity of community-based long-term care (CBLTC) programs. Two hundred and thirty-seven clients entering a CBLTC program were assessed for activities of daily living (ADL) and cognitive and affective functioning and were then followed to monitor attrition and reasons why clients left the program. Compromised ADL functioning at baseline increased likelihood of death and institutionalization by 2 per cent each year. Over a 10-year period, reduced cognitive functioning at baseline increased the risk of death by 9 per cent and decreased the likelihood of leaving the program due to improvement by 18 per cent. Reduced affective functioning at baseline increased the risk of institutionalization during the course of the study by 3 per cent. Routine functional assessments with the elderly may help in the management of similar home care programs.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".