Assessment of Benzodiazepine Withdrawal Syndrome: French Psychometric Validation of the Clinical Institute Withdrawal Assessment-Benzodiazepines (CIWA-B) Scale
Bibliographic record
Abstract
Background. Benzodiazepines (BZs) use is common in the treatment of insomnia. Discontinuation induces withdrawal symptoms, notably rebound insomnia and anxiety, which contribute to resumption of use, despite medical advice, and ultimately, long-term dependence. The Clinical Institute Withdrawal Assessment-Benzodiazepines (CIWA-B), derived from the CIWA-Ar for alcohol withdrawal, was adapted by Busto et al. (1989) to assess the severity of BZs withdrawal. Objective. This study aimed to conduct the French cross-cultural validation of the CIWA-B and to evaluate its psychometric properties in the context of hypnotic benzodiazepine use. Methods. One hundred and seven chronic users of hypnotic BZS enrolled in a withdrawal protocol participated in the study. Construct validity, internal consistency, test-retest reliability, as well as divergent, convergent, and discriminant validity were assessed. Results. Exploratory factor analysis revealed a three-factor structure comprising anxiety, physiological symptoms, and sleep. Internal consistency, test-retest reliability, and convergent, divergent, and discriminant validity were good. The sensitivity of the scale could not be evaluated in this study. Conclusion. The 20-item French version of the CIWA-B demonstrates satisfactory psychometric properties and represents a relevant tool for assessing benzodiazepine withdrawal syndrome. Further validation in populations using BZs for anxiolytic purposes and in less gradual withdrawal contexts is warranted.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".