Functional status among community‐dwelling older adults is determined by cognitive status
Bibliographic record
Abstract
Abstract Background Since 2008, the number of older adults has increased by 34% and is expected to nearly double by 2060. Among US older adults over 70 years of age, 22‐30% report difficulty performing at least one activity of daily living (ADL). ADL performance is associated with functional fitness parameters. Negative longitudinal changes in functional performance among older adults are associated with cognitive decline and may be able to predict future cognitive impairment. Thus, it is imperative to understand the influence of cognition on functional fitness among older adults. Method 84 older adults (80.9+5.4 years) consented to have their functional fitness and cognition assessed. Functional fitness parameters included the following assessments: Short Physical Performance Battery (SPPB), 10‐meter walk (habitual and fast), dual‐task (habitual and fast), power chair stand assessment (average and peak power and velocity). Cognition was assessed using the Montreal Cognitive Assessment (MoCA) and a digital Visual Paired Comparison (VPC) task. Categories of low and high cognitive function were determined using the VPC results. A one‐way ANOVA was conducted to determine differences between cognitive groups. Result Participants with high cognitive performance scored significantly better on the SPPB, 10‐meter fast walk, dual‐task fast condition, and average velocity during the power chair stand assessment. SPPB scores were 10.2% lower among older adults with low cognitive performance (p = .04). The high cognition group walked 16.5% (0.16 m/s) faster when compared to the low cognitive group (p = .04). Dual‐task (fast) performance was 13.2% slower among the low cognition group (p = .03). Additionally, low cognitive older adults moved 16.7% slower when rising from a seated position during the power chair stand task (p = .01). MoCA was 2.76 points lower among the low cognition group (p < .001). Conclusion Based on the current results, a relationship exists between functional fitness and cognitive performance in older adults. However, it remains unknown whether functional fitness can influence cognition or vice versa and how these impact ADL performance. Future research is warranted to determine if and how the relationship between cognitive function and functional fitness changes over time in 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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".