The Dynamic Relationship Between Physical Function and Cognition in Longitudinal Aging Cohorts
Bibliographic record
Abstract
On average, older people remember less and walk more slowly than do younger persons. Some researchers argue that this is due in part to a common biologic process underlying age-related declines in both physical and cognitive functioning. Only recently have longitudinal data become available for analyzing this claim. We conducted a systematic review of English-language research published between 2000 and 2011 to evaluate the relations between rates of change in physical and cognitive functioning in older cohorts. Physical functioning was assessed using objective measures: walking speed, grip strength, chair rise time, flamingo stand time, and summary measures of physical functioning. Cognition was measured using mental state examinations, fluid cognition, and diagnosis of impairment. Results depended on measurement type: Change in grip strength was more strongly correlated with mental state, while change in walking speed was more strongly correlated with change in fluid cognition. Examining physical and cognitive functioning can help clinicians and researchers to better identify individuals and groups that are aging differently and at different rates. In future research, investigators should consider the importance of identifying different patterns and rates of decline, examine relations between more diverse types of measures, and analyze the order in which age-related declines occur.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".