Intraindividual reaction time variability is malleable: feedback- and education-related reductions in variability with age
Bibliographic record
Abstract
Intraindividual variability (IIV) in trial-to-trial reaction time (RT) is a robust and stable within-person marker of aging. However, it remains unknown whether IIV can be modulated experimentally. In a sample of healthy younger and older adults, we examined the effects of motivation- and performance-based feedback, age, and education level on IIV in a choice RT task (four blocks over 15 min). We found that IIV was reduced with block-by-block feedback, particularly for highly educated older adults. Notably, the baseline difference in IIV levels between this group and the young adults was reduced by 50% by the final testing block, this advantaged older group had improved such that they were statistically indistinguishable from young adults on two of three preceding testing blocks. Our findings confirmed that response IIV is indeed modifiable, within mere minutes of feedback and testing.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".