Associations between traumatic event experiences, psychiatric disorders, and suicidal behavior in the general population of Afghanistan: findings from Afghan National Mental Health Survey
Bibliographic record
Abstract
BACKGROUND: The role of traumatic event exposure and psychiatric disorders as central risk factors for suicidal behavior has been established, but there are limited data in high conflict regions with significant trauma exposures such as Afghanistan. METHODS: A nationally representative, cross-sectional survey was conducted through systematic stratified random sampling in 8 regions of Afghanistan in 2017 (N = 4474). Well-validated instruments were used to establish trauma exposure, psychiatric disorders. Death preference, suicidal ideation, plan, and attempts were assessed. RESULTS: In the total sample, 2.2% reported suicidal ideation in the past 12 months, and 7.1% of respondents reported that they had suicidal ideation at some point in their lives; 3.4% reported a suicide attempt. Women were at higher risk than men. All traumatic event exposures were strongly associated with suicidal behavior. Respondents who reported experiencing sexual violence were 4.4 times more likely to report lifetime suicide attempts (95% CI 2.3-8.4) and 5.8 times more likely to report past 12-month suicidal ideation (95% CI 2.7-12.4). Associations were strong and significant for all psychiatric disorders related to suicidal behavior. Respondents who met criteria for major depressive episodes (OR = 7.48; 95% CI 4.40-12.72), generalized anxiety disorder (OR = 6.61; 95% CI 3.54-12.33), and PTSD (OR = 7.26; 95% CI 4.21-12.51) had the highest risk of past 12-month suicidal ideation. CONCLUSION: Traumatic event exposures and psychiatric disorders increase risk of suicidal behavior in the Afghan general population; women are at high risk. Interventions to reduce trauma exposure, including expansion of a mental health workforce in the region, are critically important.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".