The impact of a stress management intervention including cultural components on stress biomarker levels and mental health indicators among indigenous women
Bibliographic record
Abstract
We examined the effectiveness of a 26-week culture-inclusive intervention on reducing salivary stress biomarker levels, and perceived stress, depressive, and post-traumatic stress disorder (PTSD) symptoms measured using scales in 53 Indigenous women in Ontario, Canada. Statistical analyses compared the average biomarker levels, and the area under the curve (AUC) of biomarkers. Differences in biomarkers and mental health scale scores pre- and post-intervention were compared using mixed models with a random intercept. Interaction terms were included between the intervention and age, education, disability, and HIV status, individually, to test for sub-group differences. Cortisol AUC post-intervention was decreased compared to pre-intervention (β -1.29 µg/dL; 95%CI -2.35, -0.23). There was a slight decrease in perceived stress levels (aOR: -2.80; 95%CI -5.09, -0.50). The associations were stronger among women of younger age, higher education, and no disabilities. These interventions can be effective, but future interventions should target Indigenous population sub-groups to address individual needs.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".