Cognitive–behavioural, pharmacological and psychosocial predictors of outcome during tapered discontinuation of benzodiazepine
Bibliographic record
Abstract
Eighty-six participants wishing to stop benzodiazepine and who met DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, 4th ed. American Psychological Association, 1994) criteria for anxiety disorder or insomnia were assessed pre- and post-taper on clinical, pharmacological and psychosocial measures. An initial cohort of 41 participants received treatment as usual (taper only) plus physician counselling in the same clinic setting. A second cohort of 45 participants were randomly allocated to group cognitive-behavioural therapy (CBT) plus taper, or group support (GS) plus taper. At 3 months follow-up, the outcomes in both the CBT and the GS subgroups were equivalent. Intention to treat analysis revealed a slight advantage to the CBT over the GS group and the CBT group showed higher self-efficacy post-taper.Over all 86 participants, a high-baseline level of psychological distress, anxiety and dosage predicted a poor outcome, but increase in self-efficacy contributed to a successful outcome particularly in those with initially poor baseline predictors. Although there was a decrease in positive affect during preliminary stages of tapered discontinuation compared to baseline, there was no significant overall increase in negative affect.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".