Validation of the Peritraumatic Dissociative Experiences Questionnaire self-report version in two samples of French-speaking individuals exposed to trauma
Bibliographic record
Abstract
OBJECTIVE: Peritraumatic dissociation is a risk factor for developing PTSD. The Peritraumatic Dissociative Experiences Questionnaire (PDEQ) is a self-report inventory used to assess dissociation that occurred at the time of a trauma. The aim of this study was the validation the PDEQ in French. METHOD: Ninety French speaking traumatized victims presenting to the emergency department were recruited. They were administered the PDEQ shortly after exposure and others trauma-related measures 2 weeks and 1 month posttrauma. RESULTS: Principal components factor analyses suggested a single factor solution for the PDEQ. Significant correlations between the PDEQ and acute and posttraumatic stress symptoms indicated moderate to strong convergent validity. The PDEQ also showed satisfactory test-retest reliability and internal consistency. CONCLUSION: This study is the first one to investigate such detailed psychometric findings on the PDEQ. This confirms the unity of the concept of peritraumatic dissociation and the value of the PDEQ-French Version to assess it.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".