Psychometric validation of the Posttraumatic Stress Disorder Checklist for DSM-5 (PCL-5) in adults with substance use disorders.
Bibliographic record
Abstract
OBJECTIVE: (PCL-5) is one of the most widely used instruments in clinical practice, but there remain ongoing debates about its factor structure. Further, no study to date has undertaken psychometric validation of the PCL-5 among individuals seeking treatment for substance use disorder (SUD), a population for whom PTSD is highly concurrent and relevant to clinical care. The present study sought to examine three PTSD structural models and measurement invariance across sex and age in patients with SUD. METHOD: = 41.17; 71.03% male) who completed the PCL-5 at admission to inpatient treatment for SUD. Confirmatory factor analysis and tests of measurement invariance (age, sex) were conducted. RESULTS: Confirmatory factor analysis revealed that previously observed six-factor anhedonia and seven-factor hybrid models provided superior fit over the original four-factor model of PTSD, with optimal results found for the hybrid model. Configural, metric, and scalar measurement invariance for the six- and seven-factor models were observed for sex (males vs. females) and age (median split: < 41 vs. ≥ 41). CONCLUSION: Collectively, this study adds to growing evidence in support of a seven-factor model and validates the use of the PCL-5 in adult SUD treatment populations. Limitations of some of the alternative structures and priorities for future research on the overlap of PTSD and SUD are discussed. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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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 | 0.018 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".