Development and Validation of Response Time Inconsistency in the Midlife in the United States (MIDUS) Study
Bibliographic record
Abstract
Abstract Response time inconsistency (RTI), the trial-to-trial variability on a RT-based cognitive task, is an important behavioral indicator of cognitive health, cognitive aging, and an early indicator of cognitive pathology, and central nervous system (CNS) dysfunction. Although RTI is well-studied through computer-based speeded tasks, little research has examined the validity of RTI obtained from: (1) telephone-based cognitive assessments employing voice-triggered response time protocols; or (2) midlife cohorts who are at risk for dementia. Using data from the second wave of the MIDUS study (N = 4,285; Mage=55.6, SD = 12.2, Range=28-84; 55%=women; 75% having at least some college education), participants completed the Brief Test of Adult Cognition via Telephone (BTACT), which includes tests of executive function and episodic memory abilities, as well as a RT-based stop-go switching (SGS) task. RTI was derived from 20 trials of the SGS non-switch condition and quantified as an intraindividual standard deviation (ISD) residualized for trial number. RTI was greater with age (r=.26, p<.0001), being less educated (r=-.16, p<.0001), and among women (Cohen’s d=.15, p<.0001). Importantly, RTI was associated with slower task switching performance, lower scores on the BTACT, episodic memory, and executive function cognitive composites (rs=-.19 to -.41, ps<.0001), as well as poorer self-rated mental (r=-.13) and physical (-.18, ps<.0001) health. RTI was not significantly related to self-rated positive affect (r=-.02, p=.24) or negative affect (r=.02, p=.17). Discussion will focus on the validity and promise of RTI obtained from telephone-based cognitive assessments for characterizing CNS integrity and dementia risk in large-scale surveys.
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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 | 0.014 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| 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".