Types and Number of Traumas Associated With Suicidal Ideation and Suicide Attempts in PTSD: Findings From a U.S. Nationally Representative Sample
Bibliographic record
Abstract
Posttraumatic stress disorder (PTSD) is associated with suicidal ideation and suicide attempt; however, research has largely focused on specific samples and a limited range of traumas. We examined suicidal ideation and suicide attempt relating to 27 traumas within a nationally representative U.S. sample of individuals with PTSD. Data were from the National Epidemiologic Survey of Alcohol and Related Conditions (N = 34,653). Participants were assessed for lifetime PTSD and trauma history, suicidal ideation, and suicide attempt. We calculated the proportion of individuals reporting suicidal ideation or suicide attempt for each trauma and for the number of unique traumas experienced. Most traumas were associated with greater suicidal ideation and suicide attempt in individuals with PTSD compared to individuals with no lifetime trauma or with lifetime trauma but no PTSD. Childhood maltreatment, assaultive violence, and peacekeeping traumas had the highest rates of suicidal ideation (49.1% to 51.9%) and suicide attempt (22.8% to 36.9%). There was substantial variation in rates of suicidal ideation and suicide attempt for war and terrorism-related traumas. Multiple traumas increased suicidality, such that each additional trauma was associated with an increase of 20.1% in rate of suicidal ideation and 38.9% in rate of suicide attempts. Rates of suicidal ideation and suicide attempts varied markedly by trauma type and number of traumas, and these factors may be important in assessing and managing suicidality in individuals with PTSD.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".