Neuroimaging Insights into Subjective Cognitive Decline: Differential Sensitivity of Cognitive Change Index and Everyday Cognition Scale
Bibliographic record
Abstract
Abstract Introduction Cognitively healthy older adults may experience self-perceived memory and cognitive deficits, known as subjective cognitive decline (SCD), increasing their risk for dementia- related brain and cognitive changes. This study investigated if questions from the Cognitive Change Index (CCI) and Everyday Cognition Scale (ECog) show similar associations with dementia-related changes. Methods Cognitively healthy older adults (n=332) from the Alzheimer’s Disease Neuroimaging Initiative were included. Partial-least-squares observed the latent variables (LVs) that maximize the relationship between the two questionnaires. Results Two LVs ( p’s <0.001) explained 85.89% and 8.30% of the cross-block covariance. In the first LV, several CCI questions correlated with older age and frontal, parietal, and temporal WMHs, lower hippocampal and entorhinal cortex volume, and larger ventricles. The second LV showed younger individuals with higher SCD scores on three CCI questions correlated with temporal and parietal WMHs and entorhinal cortex volumes. Conclusion More questions from the CCI are associated with neuroimaging markers, unlike the ECog questions. These questionnaires may thus be measuring different neural decline patterns and may be sensitive to different etiologies.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".