Intraindividual variability is related to cognitive change in older adults: Evidence for within-person coupling.
Bibliographic record
Abstract
In this study, the authors addressed the longitudinal nature of intraindividual variability over 3 years. A sample of 304 community-dwelling older adults, initially between the ages of 64 and 92 years, completed 4 waves of annual testing on a battery of accuracy- and latency-based tests covering a wide range of cognitive complexity. Increases in response-time inconsistency on moderately and highly complex tasks were associated with increasing age, but there were significant individual differences in change across the entire sample. The time-varying covariation between cognition and inconsistency was significant across the 1-year intervals and remained stable across both time and age. On occasions when intraindividual variability was high, participants' cognitive performance was correspondingly low. The strength of the coupling relationship was greater for more fluid cognitive domains such as memory, reasoning, and processing speed than for more crystallized domains such as verbal ability. Variability based on moderately and highly complex tasks provided the strongest prediction. These results suggest that intraindividual variability is highly sensitive to even subtle changes in cognitive ability.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".