Performance measures rather than self-report measures of functional status predict home care use in community-dwelling older adults
Bibliographic record
Abstract
BACKGROUND: Occupational therapists frequently assess functional status (FS) to determine the home care (HC) service requirements of older adults. However, it is unclear which type of FS measure is most effective for this purpose. PURPOSE: This study investigated the predictive ability of three measures of FS (a self-report measure of usual behaviour, a self-report measure of capacity, and an observational performance measure-the Performance Assessment of Self-Care Skills [PASS]) on formal HC utilization. METHOD: A secondary analysis of 2001 Aging in Manitoba Longitudinal Study (AIM) data was conducted. FINDINGS: The odds of receiving HC within the 30-month follow-up period were 1.32 times (or 30%) higher for each increase in the number of dependent tasks based upon a standardized performance measure. The self-report measures did not predict HC utilization. IMPLICATIONS: This study suggests that standardized performance measures-in particular, the PASS-are more predictive of formal HC use in community-dwelling older adults than self-report measures.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".