Older adults with lower autobiographical memory abilities report less age-related decline in everyday cognitive function
Bibliographic record
Abstract
BACKGROUND: Individuals differ in how they remember the past: some richly re-experience specific details of past episodes, whereas others recall only the gist of past events. Little research has examined how such trait mnemonics, or lifelong individual differences in memory capacities, relate to cognitive aging. We specifically examined trait episodic autobiographical memory (AM, the tendency to richly re-experience episodic details of past events) in relation to complaints of everyday cognitive functioning, which are known to increase with age. Although one might predict that individuals reporting higher trait-level episodic AM would be resistant to age-related decline in everyday function, we made the opposite prediction. That is, we predicted that those with lower trait-level episodic AM would be better equipped with compensatory strategies, practiced throughout the lifespan, to cope with age-related memory decline. Those with higher trait-level episodic AM would have enhanced sensitivity to age-related cognitive changes due to their tendency to rely on their perceived above-average memory function. METHODS: We tested these predictions in 959 older adults aged 50-93 using online subjective and objective measures of memory and cognitive function. Our key measures of interest were the Survey of Autobiographical Memory, a measure of autobiographical memory abilities; and the Cognitive Failures Questionnaire, a measure of everyday cognitive function. RESULTS: In keeping with our prediction, we found that complaints of day-to-day memory slips and errors (normally elevated with age) remained stable or even decreased with age among those reporting lower trait-level episodic AM, whereas those reporting higher trait-level episodic AM reported the expected age-related increase in such errors. This finding was specific to episodic AM and not observed for other autobiographical memory capacities (e.g., semantic, spatial). It was further unaccounted for by response bias or objectively assessed cognitive abilities. CONCLUSIONS: Congenitally low trait-level episodic AM may paradoxically confer a functional advantage in aging. This could be due to well-developed non-episodic strategies not present in those with higher abilities, who are more sensitive to age-related memory decline attributable to medial temporal lobe changes. Our findings emphasize the importance of considering individual differences when studying cognitive aging trajectories.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".