Neurobiological and psychological impact of acute war stress on Ukrainian refugees
Bibliographic record
Abstract
Abstract Based on our research on the impact of extreme stress on Holocaust survivors, we questioned whether the neurobiological and psychological impact of stress could be observed during an ongoing war. We investigated Ukrainian refugee women (UG, n=43) who had been living in the Czech Republic for 2 to 6 months and compared to control group (n=20). Psychological testing: level of posttraumatic stress, Zung Self-Rating Depression Scale, Anxiety Inventory, Intellectual Potential, and Digit Span Wechsler-III. MR imaging: voxel-based morphometry, functional MR, seed-based connectivity, and Montreal Imaging Stress Task (MIST). MRI showed enlargement of the posterior and central parts of the thalamus. The thalamus is connected with the frontal orbital gyrus and insula; the MIST revealed an impact on the parahippocampal gyrus. Conclusion: Acute and ongoing war stress had a significant neurobiological impact on refugees from war-torn Ukraine. The UG scored significantly higher in posttraumatic stress, anxiety, and depression. The thalamus modulates activity in the limbic circuitry. Correlations between MRI activation and levels of posttraumatic stress and anxiety were found in the UG. The data show the impact of acute and ongoing war-related stress on psychological features as well as on the cerebral structure and connectivity of stress-related cortical areas.
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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 | 0.000 | 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".