<scp>ICD</scp>‐11 <scp>PTSD</scp> and complex <scp>PTSD</scp> amongst Syrian refugees in Lebanon: the factor structure and the clinical utility of the International Trauma Questionnaire
Bibliographic record
Abstract
OBJECTIVE: Support for ICD-11 post-traumatic stress disorder (PTSD) and complex PTSD (CPTSD) is growing; however, few studies include refugees or examine the clinical utility of PTSD/CPTSD classifications. This study sought to provide the first evaluations of (i) the factor structure of ICD-11 PTSD/CPTSD amongst refugees in the Middle East; and (ii) the clinical utility of the International Trauma Questionnaire (ITQ) to identify PTSD/CPTSD in a humanitarian context. METHOD: Participants were 112 treatment-seeking Syrian refugees living in Lebanon. Factorial validity was assessed using confirmatory factor analysis (CFA) based on responses to the ITQ. Clinical utility of the ITQ was assessed through semi-structured interviews with six Lebanese psychotherapists. RESULTS: Complex PTSD (36.1%) was more common than PTSD (25.2%), and no sex or age differences were observed at the prevalence or symptomatic levels. CFA results supported a two-factor higher-order model consistent with ICD-11 PTSD/CPTSD. Qualitative findings indicated that the ITQ is generally positively regarded, with some limitations and suggested modifications noted. CONCLUSION: This is the first study to support the ICD-11 PTSD/CPTSD amongst refugees in the Middle East and the clinical utility of the ITQ in a humanitarian context. Findings support the growing evidence for the cross-cultural applicability of ICD-11 PTSD/CPTSD.
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 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 | 0.001 | 0.003 |
| 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) | 0.003 | 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".