Depressive symptoms, cortisol, and cognition during human aging: The role of negative aging perceptions
Bibliographic record
Abstract
Depressive symptoms and memory impairments are associated with heightened stress hormone levels during aging. A factor that is related to memory deficits during aging is internalized negative aging stereotypes; the idea people have about the process of aging. In this study, we assessed the associations between internalized negative aging stereotypes, depressive symptoms, subjective and objective memory assessments, and cortisol concentration among older adults. Forty older adults aged between 58 and 85 years (18 females and 22 males; mean age ± SD: 71.25 ± 8.80 years) were assessed in this study. Measures of internalized negative aging stereotypes, depressive symptoms, and both subjective and objective memory performance were assessed. Salivary samples were obtained for measurement of cortisol concentration. Stepwise linear regressions were executed in our main analyses. Internalized negative aging stereotypes were associated with increased depressive symptoms and subjective memory complaints. No significant differences were observed for objective memory performance, or cortisol concentration. Internalized negative aging stereotypes are associated with increased depressive symptomatology and subjective complaints of memory; however, they do not predict increased cortisol concentration nor objective memory performance during aging. These results indicate that the mechanism underlying the association between internalized negative aging stereotypes and cognitive impairments may not be related to dysregulations of cortisol secretion among older adults.
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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 | 0.001 |
| 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) | 0.000 | 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".