Impact of comorbid cannabis use on outcome in first episode psychosis
Bibliographic record
Abstract
AIM: Comorbid cannabis abuse is common in patients with early psychosis. Little is known about the effect of stopping cannabis use on positive, negative and depressive symptoms. Few studies have controlled for multiple substance use that may mask the specific role that cannabis plays in symptom outcomes. The aim of this study was to investigate whether course and level of cannabis use negatively impacted early psychosis patient symptom profiles (positive, negative and depressive symptoms) over 24 months. METHODS: One hundred and ninety-two patients admitted to an early psychosis intervention programme in a naturalistic setting were followed across three time periods: initial presentation, 12 and 24 months. Patients' clinical characteristics (substance use, positive/negative symptoms and depressive symptoms) were assessed at each time period. RESULTS: There were no significant associations found between cannabis abuse and positive and negative symptoms. Continuation and discontinuation of cannabis use were not significant for cannabis or any other substance when compared to positive and negative symptoms. There was a significant interaction between cannabis and alcohol for depressive symptoms, where depressive symptoms were significantly higher in patients who abused cannabis without co-occurring alcohol abuse when compared to non-cannabis using patients. CONCLUSION: The current study findings indicate a complex interaction between cannabis and alcohol use in a sample of early psychosis patients across 24 months. More research is needed into the association between ceasing cannabis use and long-term outcome for early psychosis patients. Of particular importance is the interaction between level of cannabis and alcohol use as it is related to symptom outcome in early psychosis patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".