Exploring the factor structure of the PTSD checklist for DSM–5 in psychotic disorders.
Bibliographic record
Abstract
OBJECTIVE: The PTSD Checklist for DSM (PCL) is the most widely used screener to assess posttraumatic stress disorder (PTSD) in those with psychotic disorders (psychosis), though previous research has questioned its validity in psychosis. Considerable symptom overlap between the 2 disorders (e.g., concentration difficulties, avoidance, etc.) along with the general underdiagnosing of PTSD in psychosis speaks to the need for consensus regarding brief screeners. This hypothesis-generating study is the first to explore the PCL-5 (its most recent iteration) factor structure in psychosis to assess if a more valid underlying structure may exist. METHOD: PTSD criterion A traumatic event following an interview subsequently completed the PCL-5. Exploratory factor analysis was conducted to explore the latent structure of the PCL-5 in psychotic disorders. RESULTS: 4-factor model emerged as the best fitting model. Resulting PCL-5 dimensions in psychosis were identified as (1) Reexperiencing/Negative Affect; (2) Depressive; (3) Externalizing Anxious Behaviors; and (4) Avoidance/Physiological Reactivity. CONCLUSIONS: Results guide the hypothesis that the latent structure of the PCL-5 may be unique in psychosis, which will have important clinical implications. Research is now needed to confirm the proposed model in larger samples of individuals with psychosis. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".