Prevalence and Correlates of Cognitive Impairment No Dementia (CIND) Status: The Midlife in the United States Study.
Bibliographic record
Abstract
Abstract Cognitive impairment no dementia (CIND) status – a multi-test profile and impairment classification – is a promising indicator of cognitive health, leveraging intraindividual variability in performance across multiple domains. CIND profiles have exhibited considerable utility for differentiating adults exhibiting neuropsychological impairment (>-1SD below age- and education-adjusted norms) on one (CIND-single) or more (CIND-multiple) tasks, from those who are comparatively unimpaired or exhibit transient low scores due to temporary factors (e.g., minor illness). Research employing CIND profiles has focused on older populations, leaving questions about the prevalence, distribution, and correlates of CIND status among midlife adults, who are at risk for dementia. Using data from the MIDUS II study (N = 4,241; Mage=55.6, SD = 12.2, Range=28-84; 55%=women), participants completed the Brief Test of Adult Cognition via Telephone (BTACT), which includes tests of executive function and episodic memory abilities. CIND status prevalences were 50.2% non-CIND, 26.8% CIND-single, and 23.0% CIND-multiple. Significantly more men (p=.03), non-White (p<.0001), and lower-educated (p<.0001) adults met CIND-single and CIND-multiple criteria. Response time inconsistency (RTI), an index of central nervous system integrity and impairment/dementia risk, was greater among CIND-single (Cohen’s d=.20, p<.01) and CIND-multiple (Cohen’s d=.52, p<.001) participants, relative to non-CIND participants. Covariate-adjusted multinomial logistic regression models revealed RTI was associated with increased odds of CIND-single (p<.006) and CIND-multiple (p<.0001) statuses. Further, gender, education, and self-rated health also exhibited independent associations indicative of increased CIND classification risk (ps<.0001). Discussion will focus on the utility of CIND status for understanding patterns and profiles of cognitive health, and early detection of dementia risk.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".