Determinants of stress reactivity and memory performance in older adults
Bibliographic record
Abstract
It is commonly believed that memory capacities decline with advanced age. Among various biological mechanisms investigated, the stress hormone (cortisol) has received much attention. When cortisol levels are elevated, they impair cognitive performance. Yet evidence shows that there is considerable variability in older adults' cortisol levels and cognitive performance, and the basis for this variability is not well understood. The work of the current thesis sought to investigate some factors that may explain some of the variability observed in stress reactivity and memory performance among older adults. Specifically, we investigated the roles of internalizing negative aging perceptions and stressful testing environments on cortisol levels and memory performance. The current work also aimed to determine whether differential reactivity to testing environments impacts the association between the hippocampus (brain structure involved in memory performance) and cortisol levels in older adults. Our results showed that while negative aging perceptions were not significantly associated with cortisol levels, they were associated with subjective memory complaints and depressive symptoms; two known risk factors for cognitive impairment and cortisol dysregulation. Our findings also showed that unfavourable (stressful) testing environments induce high cortisol levels and memory impairments in older adults. Yet, in a more favourable testing environment they showed lower cortisol levels and less forgetting. We also found that in both young and older adults, hippocampal volume is only correlated with cortisol levels when testing occurs in unfavourable testing environments for their respective age group. These results are important in showing that internalizing negative aging perceptions increases risk factors for cognitive impairment and dysregulation of cortisol levels. Moreover, stressful testing environments can increase cortisol levels, impair memory performance and modulate associations between hippocampal volume and cortisol.Finally, considering the important implications of the findings on stressful testing environments, we followed with a knowledge translation project to disseminate the findings to clinicians, researchers and health professionals who will use the knowledge to improve their practice and the validity of their findings, as well as the quality of life for older adults and their families.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".