Effect of Olanzapine and Risperidone on Subjective Well-Being and Craving for Cannabis in Patients with Schizophrenia or Related Disorders: A Double-Blind Randomized Controlled Trial
Bibliographic record
Abstract
OBJECTIVE: To examine whether subjective well-being and craving for cannabis were different in patients with schizophrenia or related disorders treated with either olanzapine or risperidone. METHOD: A 6-week, double-blind, randomized trial of olanzapine and risperidone was carried out in 128 young adults with recent onset schizophrenia or related disorders. Primary efficacy measures were the mean baseline-to-endpoint change in total scores on the Subjective Well-Being under Neuroleptics scale, the Obsessive-Compulsive Drug Use Scale, the Drug Desire Questionnaire, and the cannabis use self-report. An analysis of covariance was used to test between-group differences. RESULTS: Estimated D(2) receptor occupancy did not differ between olanzapine (n = 63) and risperidone (n = 65). Similar improvements in subjective well-being were found in both groups. In the comorbid cannabis-using group (n = 41, 32%), a similar decrease in craving for cannabis was found in both treatment conditions. CONCLUSIONS: Both olanzapine and risperidone were associated with improved subjective well-being. No evidence was found for a differential effect of olanzapine or risperidone on subjective experience or on craving for cannabis in dosages leading to comparable dopamine D(2) occupancy. CLINICAL TRIAL REGISTRATION NUMBER: ISRCTN46365995.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".