The Ups and Downs of Cognitive Function: Neuroticism and Negative Affect Drive Performance Inconsistency
Bibliographic record
Abstract
OBJECTIVES: Response time inconsistency (RTI)-or trial-to-trial variability in speeded performance-is increasingly recognized as an indicator of transient lapses of attention, cognitive health status, and central nervous system integrity, as well as a potential early indicator of normal and pathological cognitive aging. Comparatively, little research has examined personality predictors of RTI across adulthood. METHODS: We evaluated the association between the personality trait neuroticism and RTI in a community-dwelling sample of 317 adults between the ages of 19-83 and tested for two indirect pathways through negative affect (NA) and cognitive interference (CI). RESULTS: The personality trait neuroticism predicted greater RTI independent of mean response time performance and demographic covariates; the results were age-invariant. Furthermore, NA (but not CI) accounted for this association and moderated mediation model results indicated that older adults were more vulnerable to the adverse effects of NA. DISCUSSION: Neuroticism predicts greater RTI irrespective of mean performance and this effect is driven largely by heightened negative emotionality that may be particularly detrimental for 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 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".