Predictors of suicidal ideation in treatment-seeking survivors of torture.
Bibliographic record
Abstract
In this study, we examined sociodemographic, persecutor identity, torture, and postmigration variables associated with suicidal ideation in a clinical sample of 267 immigrant survivors of torture who have resettled in New York City. The purpose of this study was to identify variables associated with increased risk for suicidal ideation in survivors of torture before they receive legal, psychological, or medical services for torture-related needs. Results from a binary logistic regression model identified a combination of 3 variables associated with current suicidal ideation at intake into the program. Being female, having not submitted an application for asylum, and a history of rape or sexual assault were significantly associated with suicidal ideation at intake, when also controlling for several other important variables. The final model explained 21.4% of variation in reported suicidal ideation at intake. The discussion will focus on the importance of conducting a thorough assessment of suicidal ideation in refugees and survivors of torture.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".