The multiple dimensions of frailty: physical capacity, cognition, and quality of life
Bibliographic record
Abstract
BACKGROUND: Frailty is a complex health state of increased vulnerability associated with adverse outcomes such as disability, falls, hospitalization, and death. Along with physical impairments, cognition and quality of life may be affected in frail older adults. Yet, evidence is still lacking. The aim of this study was to compare frail and non-frail older adults on physical, cognitive, and psychological dimensions. METHODS: Thirty-nine frail and 44 non-frail elders were compared on several measures of physical capacity, cognition, and quality of life. Frailty status was based on a geriatric examination and scored using the Modified Physical Performance Test. RESULTS: After controlling for demographic and medical characteristics, physical capacity measures (i.e. functional capacities, physical endurance, gait speed, and mobility) were significantly lower in frail participants. Frail participants showed reduced performances in specific cognitive measures of executive functions and processing speed. On the quality of life dimension, frail elders reported poor self-perceptions of physical capacity, cognition, affectivity, housekeeping efficacy, and physical health. CONCLUSION: In addition to the reduced physical capacity, frailty might affect selective components of cognition and quality of life. These dimensions should be investigated in intervention programs designed for frail older adults.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".