Complex PTSD symptoms predict positive symptoms of psychosis in the flow of daily life
Bibliographic record
Abstract
BACKGROUND: Post-traumatic stress disorder (PTSD) has been shown to predict psychotic symptomology. However, few studies have examined the relative contribution of PTSD compared to broader post-traumatic sequelae in maintaining psychosis. Complex PTSD (cPTSD), operationalized using ICD-11 criteria, includes core PTSD (intrusions, avoidance, hyperarousal) as well as additional "disturbances of self-organisation" (DSO; emotional dysregulation, interpersonal difficulties, negative self-concept) symptoms, more likely to be associated with complex trauma histories. It was hypothesized that DSOs would be associated with positive psychotic symptoms (paranoia, voices, and visions) in daily life, over and above core PTSD symptoms. METHODS: = 153) employed a baseline subsample of the Study of Trauma And Recovery (STAR), a clinical sample of participants with comorbid post-traumatic stress and psychosis symptoms. Core PTSD, DSO and psychosis symptoms were assessed up to 10 times per day at quasi-random intervals over six consecutive days using Experience Sampling Methodology. RESULTS: DSOs within the preceding 90 min predicted paranoia, voices, and visions at subsequent moments. These relationships persisted when controlling for core PTSD symptoms within this timeframe, which were themselves significant. The associations between DSOs and paranoia but not voices or visions, were significantly stronger than those between psychosis and core PTSD symptoms. CONCLUSIONS: Consistent with an affective pathway to psychosis, the findings suggest that DSOs may be more important than core PTSD symptoms in maintaining psychotic experiences in daily life among people with comorbid psychosis and cPTSD, and indicate the potential importance of addressing broad post-traumatic sequelae in trauma-focused psychosis interventions.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".