P01-176 - Validation of the Peritraumatic Dissociative Experiences Questionnaire and Peritraumatic Distress Inventory in School-aged Victims of Road Traffic Accidents
Bibliographic record
Abstract
Objectives Although the Peritraumatic Distress Inventory (PDI) and Peritraumatic Dissociative Experiences Questionnaire (PDEQ) are both useful for identifying adults at risk of developing acute and chronic post-traumatic stress disorder (PTSD), they have not been validated in school-aged children. The present study aims at assessing the psychometric properties of the PDI and PDEQ in a sample of French-speaking school children. Methods One-hundred and thirty-three school-aged victims of road traffic accidents were consecutively enrolled into this study via the emergency room. Mean(SD) age was 11.7(2.2) and 56.4% (n=75) of them were of male gender. The 13-item self-report PDI (range 0-52) and the 10-item self report PDEQ (range 10-50) were assessed within one week of the accident. Symptoms of PTSD were assessed 1 and 6 months later using the 20-item self-report Child Post-Traumatic Stress Reaction Index (CPTS-RI) (range 0-80). Results Mean(SD) PDI and PDEQ scores were 19.1(10.1) and 21.1(7.6), respectively, while mean(SD) CPTS-RI scores at 1- and 6-months were 22.6(12.4) and 20.6(13.5), respectively. Cronbach's alpha coefficients were 0.8 and 0.77 for the PDI and PDEQ, respectively. The 1-month test-retest correlation coefficient (n=33) was 0.77 for both measures. The PDI demonstrated a 2-factor structure while the PDEQ displayed a 1-factor structure. As with adults, the two measures were inter-correlated (r=0.52) and correlated with subsequent PTSD symptoms (r=0.21−0.56; p< 0.05). Conclusions The PDI and PDEQ are reliable and valid in school-aged children, and predict PTSD symptoms.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".