Validation of a French Version of the Impact of Event Scale-Revised
Bibliographic record
Abstract
OBJECTIVE: This report presents a French translation and validation of the Impact of Event Scale-Revised (IES-R) in a population of women exposed to a natural disaster during or preceding pregnancy. METHOD: A total of 223 francophone women who were either pregnant at the time of the 1998 ice storm or who became pregnant shortly thereafter completed the IES-R and other questionnaires 6 months after the disaster. RESULTS: The French IES-R has good internal consistency, with alpha coefficients ranging from 0.81 to 0.93 for its 3 subscales and total score. The test-retest reliability of the scale, although examined with another sample, proved to be satisfactory, with correlation coefficients ranging from 0.71 to 0.76 for its 3 subscales and total score. Its convergent validity with perceived life threat and general psychiatric symptoms was judged to be marginally acceptable. Finally, a principal components analysis was conducted and a 3-factor solution, which explained 56% of the variance, was retained: a hyperarousal factor (7 items), an avoidance factor (6 items), and an intrusion factor (6 items). CONCLUSIONS: The French version of the IES-R has satisfactory internal validity and test-retest reliability. Further, the factor structure of the translation was similar to the proposed theoretical structure of the IES-R.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".