Victims of War: Dehydroepiandrosterone Concentrations in Hair and Their Associations with Trauma Sequelae in Palestinian Adolescents Living in the West Bank
Bibliographic record
Abstract
Due to its anti-glucocorticoid properties, the steroid hormone dehydroepiandrosterone (DHEA) might play a role for coping with traumatic stress and posttraumatic stress disorder (PTSD). The majority of studies report elevated DHEA secretion and decreased cortisol/DHEA ratio associated with traumatic stress, however, contrasting results have also been published. One reason for this heterogeneity might be that in past studies, DHEA has been measured in plasma or saliva samples reflecting acute hormone levels. In comparison, the current study assessed the hair levels of DHEA and cortisol as long-term markers along with self-reported data on psychopathology and coping in 92 female adolescents aged 11–16 from the West Bank affected by the Israeli–Palestinian conflict. Results showed that trauma-exposed individuals had significantly higher DHEA levels (p = 0.013) and lower cortisol/DHEA ratios (p = 0.036) than participants from the non-trauma group. Furthermore, DHEA and cortisol/DHEA ratio emerged as associated with trauma load and timing, but not with coping. By applying the novel method of DHEA analysis from hair samples, this study adds to the growing literature on the interplay of DHEA, cortisol, traumatic stress and coping, and provides valuable starting points for further research.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".