Does Impaired Executive Functioning Differentially Impact Verbal Memory Measures in Older Adults with Suspected Dementia?
Bibliographic record
Abstract
The purpose of this study was to examine whether executive dysfunction differentially impacts list-learning and story recall tasks in a sample of older adults referred for suspected cognitive impairment. Older adults (N = 61) with mild cognitive impairment (MCI) or probable mild dementia, and those who did not meet criteria for diagnosis of dementia, were assessed using measures of executive function and verbal memory. Two groups were established based on performance on measures of executive function: (a) the No Executive Dysfunction group (NoED; n = 33) consisted of persons without impairment on any obtained measures of executive function; and (b) the Executive Dysfunction group (ED; n = 28) contained persons with impairment on at least one of the measures of executive function. The two groups were compared on performance on two measures of verbal memory, the California Verbal Learning Test-II (CVLT-II) and the Logical Memory (LM) subtest from the Wechsler Memory Scale-Revised (WMS-R). The NoED group performed significantly better than the ED group on the total learning and short delay free recall trials of the CVLT-II. However, there were no significant differences between the groups on the other indices of the CVLT-II (i.e., long delay free recall, recognition, recall repetitions, recall intrusions, or recognition false-positives) or on the immediate and delayed recall trials of the LM measure. These results support previous research demonstrating the impact of executive dysfunction on the acquisition of and short-delay retrieval of verbal information in older adults with suspected cognitive impairment.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".