Examining Memory Performance in Senior Adults: A Comparative Cross-Sectional Study
Bibliographic record
Abstract
This study investigates memory performance among 73 adults over 60 years old, utilising Memory Impairment Screening (MIS) and self-reported memory failures assessed by the Memory Failures in Everyday questionnaire (MFE-28). Participants were divided into four groups: individuals with depressive symptoms, healthy individuals, individuals with depressive symptoms and mild cognitive impairment, and individuals with mild cognitive impairment only. Groups were organised according to their Montreal Cognitive Assessment (MoCA) and the 15-item Geriatric Depression Scale (GDS-15) scores. The study aims to analyse MIS scores and self-reported memory failures across these groups as measured with the 28-item Memory Failures Everyday (MFE-28) scale. Correlation analyses were conducted for the complete sample, while variance analyses were carried out for the four classification groups above. Bivariate linear regression analysis was carried out to explore how the combination of cognitive and depressive symptoms status influenced memory performance. Results show that subjective memory complaints and memory performance are related to depressive symptoms, and the latter is associated with worse cognitive performance. Lastly, our study highlights that individuals with mild cognitive impairment and depressive symptoms exhibit worse performance in recall tasks and report more subjective memory complaints compared to those with mild cognitive impairment alone.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".