Memory and aging: What is the real impact of age?
Why this work is in the frame
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Bibliographic record
Abstract
<strong>Goals</strong>. Memory impairment is one of the types of cognitive impairment that most affects the elderly. Age is considered one of the major factors in memory impairment, including by the elderly themselves. Research has shown that there are other factors affecting memory of elderly persons. It remains, however, unclear what is the real impact of age in memory when controlling the influence of other variables. Thus, this study aims to analyze the impact of age on memory functioning of elderly persons and check if the potential impact remains when controlling the role of other variables (sex, education, profession, marital status, residential status, and clinical situation).<strong>Methods</strong>. The global sample comprised 1126 subjects (283 men and 843 women, 226 residents in the community and 900 institutionalized<strong> </strong>elderly) aged from 60 to 100 years. The assessment included items from the <em>Mini-Mental State Examination</em> (working memory), the <em>Montreal Cognitive Assessment</em> factor (verbal declarative memory), and <em>Rey-Osterrieth Complex Figure </em>(visuospatial memory).<strong>Results</strong>. Overall, age, education, profession, marital, residential, and clinical condition have differently influenced memory, depending on the type of memory. The hierarchical regression analysis showed that age is a predictive factor in all types of memory. However, other predictors have emerged with higher regression coefficients compared to age, according to the type of memory (except in working memory).<strong>Conclusions</strong>. Age, education and profession influence memory, as well as factors that potentially stimulate cognitively and socially (like having a partner and living in the community). The results indicate the importance of intervening, especially among institutionalized elderly, older, unmarried, with low education, and manual profession.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.199 | 0.001 |
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 it