AGE DIFFERENCES IN EVERYDAY DISCRIMINATION AND CORTISOL DYNAMIC RANGE IN DAILY LIFE
Bibliographic record
Abstract
Abstract Extensive work has linked everyday discrimination with poorer health. However, research testing age differences in this relationship is limited. The current study examined everyday discrimination and cortisol dynamic range, and whether the association differed by age. Cortisol dynamic range is believed to reflect physiological responsiveness to external demands such as stressors, with a compressed range indicating less responsiveness. Participants were 250 community-based adults living in British Columbia (ages 25-88, mean=46 years, 64% White, 68% women). At baseline, participants completed the Everyday Discrimination Scale, followed by four days of at-home saliva collection 3x per day: upon waking, 30 minutes post-waking, and before bed. Cortisol dynamic range was calculated as the log-cortisol peak minus log-cortisol nadir across the four days. Multiple regression controlled for race/ethnicity, education, gender, medications, average length of waking day, and depressive symptoms. Results showed a negative association between age and cortisol dynamic range, such that older age was associated with a smaller range (b=-0.01, SE=0.003, p<0.001). There was no main effect of everyday discrimination on cortisol dynamic range. However, there was a significant interaction between age and everyday discrimination. Among younger adults, more frequent everyday discrimination was associated with a smaller cortisol dynamic range. In contrast, among middle-aged adults, more frequent everyday discrimination was associated with a larger range (b=0.37, SE=0.08, p<0.001). There was no significant association between discrimination and cortisol dynamic range among older adults. Findings indicate differing patterns in discrimination and cortisol dynamic range between younger, middle-aged, and 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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".