Victims of war—Psychoendocrine evidence for the impact of traumatic stress on psychological well‐being of adolescents growing up during the Israeli–Palestinian conflict
Bibliographic record
Abstract
Violent conflicts are severe traumatic stressors with detrimental effects on physical and mental health, with children and adolescents being particularly at risk. For the hypothalamic-pituitary-adrenal (HPA) axis, characteristic patterns of dysregulation in trauma-exposed individuals have been shown. This study set out to investigate self-reported mental well-being in Palestinian adolescents growing up during the Israeli-Palestinian conflict. Hair cortisol concentrations (HCC) as a psychoendocrine marker for long-term HPA axis aberrations along with the potential protective factor sense of coherence (SoC; i.e., the global mindset to interpret the world and emerging stressors as comprehensible, manageable, and meaningful) were examined. Between 2014 and 2016, posttraumatic stress disorder (PTSD), depression, anxiety, HCC, and SoC were examined in 233 adolescents aged 11 to 16 from the West Bank. More than half of the participants reported trauma exposure, with 40% fulfilling the criteria of a preliminary PTSD diagnosis and a high prevalence of anxiety and depression. HCC was significantly elevated in the PTSD subgroup compared to the subgroup not exposed to any traumatic events (p = 0.046), with trauma-exposed individuals in between. HCC was further associated with typical sequelae of traumatic stress. Notably, SoC was inversely related to self-reported psychopathology, as well as to HCC in the trauma group. The results illustrate the situation of adolescents exposed to chronic traumatic stress and extend the literature on aberrant HPA axis functioning under such conditions. They also point out a central role of SoC, which may imply new strategies to aid individuals exposed to ongoing conflicts.
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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 | 0.001 | 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) | 0.001 | 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".