The Treatment of Sedative-Hypnotic Dependence
Bibliographic record
Abstract
BACKGROUND: The objectives of this 6-month prospective study were to evaluate the efficacy of detoxification treatment for sedative-hypnotic dependence, examine the demographic and clinical predictors of outcome, and determine whether anxiety or other psychiatric comorbidity has a negative impact on outcome. METHOD: Eighty-two patients with alcohol or benzodiazepine dependence (DSM-IV diagnostic criteria) were consecutively recruited upon entering treatment and were assessed by clinical and semistructured interviews, the Global Assessment Scale, the Hamilton Rating Scale for Depression, the Beck Depression Inventory, the revised 90-item Symptom Checklist, and urine drug screening. RESULTS: Both alcohol- and benzodiazepine-dependent patients succeeded in reducing their reported use of sedative-hypnotic substances during the follow-up period. However, at 3 months, benzodiazepine-dependent patients fared less well than alcohol-dependent patients in terms of several outcome measures: they reported a lower rate of achieving abstinence, shorter periods of continuous abstinence, and more frequent drug use. At 6 months, the differences in outcome among the drug groups were not maintained. Variables such as sex, drug group, and indicators of psychiatric status had little impact on outcome measures. Benzodiazepine-dependent patients reported significant decreases in their level of anxiety over the follow-up period despite substantial reductions in benzodiazepine use. CONCLUSION: Clinicians may be encouraged regarding the detoxification of patients who have used benzodiazepines at high doses or for long periods of time, or who have comorbid anxiety or other psychiatric disorders.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".