Addressing co‐occurring suicidal thoughts and behaviors and posttraumatic stress disorder in evidence‐based psychotherapies for adults: A systematic review
Bibliographic record
Abstract
Posttraumatic stress disorder (PTSD) is a well-established risk factor for suicidal thoughts and behaviors. Historically, guidelines for treating PTSD have recommended against the use of trauma-focused therapies for patients who are at high risk for suicide, likely due to concerns about potential suicide-related iatrogenesis, specifically the "triggering" of suicidal behaviors. This systematic review examined evidence of the impact of treatments specifically designed to treat PTSD or suicide on both PTSD- and suicide-related outcomes. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, and a total of 33 articles met the full inclusion criteria: 23 examining PTSD treatments, four examining suicide-focused treatments, and six examining combined treatments. PTSD and combined treatments reduced both PTSD- and suicide-related outcomes, with most studies focusing on cognitive processing therapy or prolonged exposure. Suicide-focused treatments (e.g., cognitive therapies for suicide prevention) also reduced suicide-related outcomes, but the findings were mixed for their impact on PTSD-related outcomes. Overall, PTSD treatments had the most support, primarily due to a larger number of studies examining their outcomes. This supports current clinical guidelines, which suggest utilizing PTSD treatments for individuals who have PTSD and are at risk for suicide. Suicide-focused and combined treatments also appeared to be promising formats, although additional research is needed. Future research should seek to compare the effectiveness of the approaches to the treatment of PTSD and suicidal thoughts and behaviors concurrently as well as to inform guidelines aimed at supporting decisions about the selection of an appropriate treatment approach.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".