Cortisol Awakening Response and Acute Stress Reactivity in First Nations People
Bibliographic record
Abstract
First Nations people globally have a higher incidence of mental disorders and non-communicable diseases. These health inequalities are partially attributed to a complex network of social and environmental factors which likely converge on chronic psychosocial stress. We hypothesized that alterations in stress processing and the regulation of the hypothalamic-pituitary-adrenal axis might underlie health disparities in First Nations people. We assessed the cortisol awakening response and the dynamic response to a laboratory induced psychosocial stress of young Indigenous tertiary students (n = 11, mean age 23.82 years) and non-Indigenous students (n = 11) matched for age and gender. Indigenous participants had a blunted cortisol awakening response (27.40 (SD 35.00) vs. 95.24 (SD 55.23), p = 0.002), which was differentially associated with chronic experience of stress in Indigenous (r = -0.641, p = 0.046) and non-Indigenous (r = 0.652, p = 0.03) participants. The cortisol response to the laboratory induced psychosocial stress did not differ between groups. Self-reported racial discrimination was strongly associated with flattened cortisol response to stress (r = -0676, p = 0.022) and with heart rate variability (r = 0.654, p = 0.040). Our findings provide insight into potential biological factors underlying health discrepancies in ethnic minority groups.
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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) | 0.001 | 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".