Physical and cognitive performance in older adults with fatigue: Comparing subjective and objective measurements..
Bibliographic record
Abstract
AbstractBackground:Fatigue is common among older adults and is associated with reduced functional capacity, impaired cognitive performance, and decreased quality of life. Its assessment remains challenging due to reliance on subjective tools that may not reflect objective impairment.Objectives:To compare subjective fatigue assessment tools with objective measures of physical and cognitive performance in community-dwelling older adults.Methods:This case–control study included 130 adults aged ≥60 years, divided into a fatigue group (n=65) and a non-fatigue group (n=65). Fatigue was assessed using the Fatigue Severity Scale (FSS) and Modified Fatigue Impact Scale (MFIS). Objective measures included the 6-Minute Walk Test (6MWT), 30-second Chair Stand Test (CST), Cognitive Timed Up and Go (Cog TUG), Digit Span test, and Montreal Cognitive Assessment–Basic (MoCA-B). Depression was evaluated using the Geriatric Depression Scale-15. Statistical analyses included group comparisons, correlations, and ROC analysis.Results:Participants with fatigue were older and had a higher prevalence of diabetes, hypertension, and ischemic heart disease (p<0.001). They showed significantly poorer physical performance (6MWT and CST) and cognitive performance (Cog TUG) (p<0.001). Despite higher MoCA-B scores, the fatigue group demonstrated impaired working memory, with lower digit span scores (p<0.001). FSS and MFIS correlated strongly with physical and cognitive measures, particularly digit span (rho = −0.61 to −0.82).Conclusion:Subjective fatigue scales, especially FSS, correlate well with objective measures. Working memory tests are more sensitive than global cognitive screening in detecting fatigue-related deficits. Combining subjective and objective assessments provides a more comprehensive evaluation.
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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 | 0.002 | 0.005 |
| 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 | 0.000 |
| 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".