The relationship of cognitive change over time to the self-reported Ascertain Dementia 8-item Questionnaire in a general population
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to examine the relationship between longitudinally assessed cognitive functioning and self-reported dementia status using the Ascertain Dementia 8-item questionnaire (AD8) in a national population-based sample. METHODS: The analysis included 14,453 participants from the REasons for Geographic and Racial Differences in Stroke study. A validated cutoff of ≥2 symptoms endorsed on the AD8 (administered 10 years after enrollment) represented positive AD8 status. Incident cognitive impairment was defined as change from intact to impaired status in the Six-Item Screener score, and cognitive decline was defined by trajectories of Letter "F" Fluency from the Montreal Cognitive Assessment, and Animal Fluency, Word List Learning, and Word List Delayed recall, all from the Consortium to Establish a Registry for Alzheimer's Disease battery. Logistic regression models controlled for demographics, health variables, and depressive symptoms. RESULTS: Sensitivity and specificity of the AD8 to detect incident cognitive impairment were 45.2% and 78.4%, respectively. Incident cognitive impairment and a one-word decline in WLL increased the odds of self-reported positive AD8 by 96% (95% CI: 1.68-2.28) and 27% (95% CI: 1.17-1.37), respectively. There was a strong association between high depression risk and self-reported positive AD8 in sensitivity analyses. CONCLUSIONS: Incident cognitive impairment and high depression risk were the strongest predictors of self-reported positive AD8 in this population-based sample. Our results inform the utility of the AD8 as a self-report measure in a large, national sample that avoids selection biases inherent in clinic-based studies. The AD8 is screening measure and should not be used to diagnose dementia clinically.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".