Prevalence and predictors of psychopathology in the war-afflicted Syrian population
Bibliographic record
Abstract
Research on the psychological impact of war on affected populations is important for the planning and provision of interventions. However, most studies that address the effects of political violence have been restricted to Western countries, and even after six years of civil war in Syria, there has been no study addressing its psychological impact on the general population. The present study used an online survey to examine the level of psychological symptoms and correlates of distress in a sample of 387 subjects from different areas of Syria. We used t-tests to compare symptoms across zones with different levels of war activity, and multiple regression models to identify predictors of distress. Results indicate a high level of psychological distress indicative of psychopathology in all regions across the country. Rates were higher in areas with more intensive exposure (‘hot’ zones). Greater symptom severity was associated with living in a hot zone, female gender, older age, the number of potentially traumatic events, daily stressors, and (low) perceived feeling of safety; whereas social support, religiosity, and religious coping were associated with lower levels of symptoms. The elevated levels of mental health problems and direct relation between the level of exposure to violence and poorer mental health point to the need for mental health services. Reducing daily stressors and ensuring safety could contribute significantly to better mental health, although this does not replace the need for evidence-based psychotherapy. The planning and delivery of psychological interventions by NGOs should be informed by issues related to stigma, lack of understanding and acceptance of psychological care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".