PERFORMANCE ON THE MOCA IS NOT ASSOCIATED WITH COGNITIVE RESERVE IN COMMUNITY-DWELLING OLDER ADULTS
Bibliographic record
Abstract
Abstract The Cognitive Reserve (CR) hypothesis suggests that more experiential resources (e.g. education, occupation, recreational activities) can help individuals combat age-related cognitive decline and maintain higher cognitive function with age. As such, higher CR has been implicated in greater cognitive resilience potentially correlated to delaying the onset and progression of Alzheimer’s Disease (AD). Previous research in cognitively normal populations found that the Montreal Cognitive Assessment (MoCA), a well-established neuropsychological assessment of global cognition used to identify Mild Cognitive Impairment (MCI) or mild AD in older adults, may reflect CR. However, limited information exists on the association between MoCA and CR for MCI. The present study investigates the relationship between MoCA and CR in older adults with early MCI using the Cognitive Reserve Index questionnaire (CRIq), a proxy measure of CR determined by education, occupational activity, and recreational activity. The study includes 138 older adults aged 50-85 with early MCI, comprising 50 males and 88 females, with an average age of 66.1 ± 7.40. No correlation between MoCA and total CRIq scores (r = 0.12, p = 0.17), or the subcategories of working activity (r = 0.08, p = 0.35), education (r = 0.05, p = 0.54), and leisure time (r = 0.11, p = 0.19) were observed. Age was included as a covariate in the models. There were no differences between sexes for CRIq scores, MoCA scores, or years of education, respectively. These findings suggest that performance on the MoCA is not associated with CR in older adults with early MCI.
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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 | 0.003 |
| 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 | 0.000 |
| Research integrity | 0.001 | 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".