Reference Standard for the Measurement of Loss of Autonomy and Functional Capacities in Long-Term Care Facilities
Bibliographic record
Abstract
The vast majority of people living in long-term care facilities (LTCFs) are octogenarians (i.e., in Québec, 57.4% of the residents are age 85 or older, 26.2% are between age 75 and 84, 10.7% are between age 65 and 74, and 5.7% are below age 65 (1)), who are affected by a great loss of physical or cognitive autonomy due to illnesses and are unable to maintain their independence, safety and mobility at home. For the majority of them, their last living environment will be a LTCF. Moreover, the annual turnover in LTCFs is one-third of all residents (2) while the average length of stay is 823 days (1). Therefore the main challenges for caregivers in LTCFs are the maintenance of functional capacities and preventing patients from becoming bedridden and isolated. Measuring the level of autonomy and functional capacities is therefore a key element in the care of institutionalized people. Several validated tools are available to quantify the degree of dependence and the functional capacities of older people living in long-term care facilities. This narrative review aims to present the characteristics of the specific population living in long-term care facilities and describe the most widely used and validated tools to measure their level of autonomy and functional capacities.
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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 | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".