Reliability and validity of the Arabic PTSD Checklist Civilian Version (PCL‐C) in women survivors of intimate partner violence
Bibliographic record
Abstract
Although intimate partner violence (IPV) survivors are at high risk for developing posttraumatic stress disorder (PTSD), PTSD has been considered a disorder specific to Western culture. There is a lack of reliable and valid measures of PTSD symptomology available in the Arab world, and there is still no clear evidence about the underlying factor structure of PTSD symptomology in the context of IPV. Thus, in the present study we investigated the construct validity (factor structure), internal consistency, and concurrent validity of a translated version of the PTSD Checklist Civilian Version (PCL-C) in a sample of 299 Saudi women who had experienced IPV. Four competing models (DSM-IV, Emotional Numbing, Dysphoria, and Dysphoric Arousal) were specified and estimated using confirmatory factor analysis (CFA). The five-factor Dysphoric Arousal model provided superior fit with the data compared to the alternative models, supporting construct validity of the Arabic PCL-C. The factor loadings for the five-factor Dysphoric Arousal model ranged from .31 to .83. A relatively high correlation between the Arabic PCL-C and Arabic Center for Epidemiologic Studies-Depression (CES-D) Scale (r = .78, p < .05) provided evidence of concurrent validity. The total scale also demonstrated internal consistency reliability (α = .89). Overall, the study supports the Dysphoric Arousal model in representing PTSD symptoms among IPV survivors, the reliability and validity of the Arabic version of PCL-C, and the cross-cultural applicability of PTSD 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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".