Which PTSD clusters and symptoms are central to reducing suicidal ideation? A network and cross-lagged analysis among individuals receiving cognitive processing therapy
Bibliographic record
Abstract
BACKGROUND: Posttraumatic stress disorder (PTSD) is associated with suicidal ideation (SI) and SI tends to improve over the course of evidence-based psychotherapy for PTSD. However, it remains unclear which PTSD clusters and symptoms are central to changes in SI throughout treatment. OBJECTIVE: To use (1) network analysis to identify the PTSD clusters and symptoms most uniquely related to SI (at baseline and post-treatment); and (2) cross-lagged analyses to examine whether these PTSD clusters and symptoms prospectively predicted decreases in SI over the course of cognitive processing therapy (CPT). METHOD: Participants were 188 individuals with PTSD receiving CPT as part of an implementation-effectiveness trial. At each session, DSM-IV PTSD clusters and symptoms were assessed using the PTSD Checklist and SI was assessed using the Outcome Questionnaire-45. RESULTS: Multi-staged cross-sectional network analyses indicated that at baseline and post-treatment the avoidance and reexperiencing clusters were uniquely associated with SI. Within these clusters, the symptoms uniquely associated with SI were recurrent thoughts and dreams of trauma, restricted range of affect, and sense of foreshortened future at baseline; and sense of foreshortened future, restricted range of affect, recurrent dreams of trauma, feelings of detachment from others, memory impairment, avoidance of reminders of trauma, and psychological cue reactivity at post-treatment. Multilevel cross-lagged analyses indicated that the avoidance cluster and the restricted range of affect and sense of foreshortened future symptoms, uniquely predicted next-session decreases in SI. CONCLUSIONS: These findings suggest that reductions in SI within treatment may be due to direct targeting of avoidance, affect, and future-related cognitions. Further research remains necessary to determine whether the present findings extend to DSM-5 PTSD clusters and symptoms.
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".