Factor structure of posttraumatic stress disorder (PTSD) in Australian Vietnam Veterans: Confirmatory factor analysis of the Clinician-Administered PTSD Scale for DSM–5
Bibliographic record
Abstract
Introduction: The Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM–5) brought a change to the symptom clusters of posttraumatic stress disorder (PTSD). In line with the DSM–5 changes, an updated version of the Clinician-Administered PTSD Scale (CAPS–5) was released. The CAPS–5 is considered to be the gold-standard measure of PTSD; however, examinations of the psychometric properties and optimal factor structure of this scale are underrepresented in PTSD studies. Methods: This study used confirmatory factor analysis (CFA) to assess the factor structure of the CAPS–5 using a sample of 267 male Australian Vietnam Veterans. Models drawn from the PTSD CFA literature were used to test the underlying dimensions of PTSD: the four-factor DSM–5 model, six-factor externalizing behaviour and anhedonia models, and seven-factor hybrid model. Results: The results found that the DSM–5 model showed slightly less than adequate fit (comparative fit index [CFI] = 0.90, Tucker–Lewis index [TLI] = 0.88, root mean square error of approximation [RMSEA] = 0.064), however, other models showed acceptable fit. The anhedonia model provided a significantly better fit than the other models (CFI = 0.92, TLI = 0.90, RMSEA = 0.059). Discussion: Overall, the results supported the anhedonia model. This result may indicate that the underlying dimensions of PTSD in Australian Vietnam Veterans may best be represented by six distinct factors.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".