Cannabis use predicts shorter duration of untreated psychosis and lower levels of negative symptoms in first-episode psychosis: a South African study
Bibliographic record
Abstract
OBJECTIVE: Cannabis use/abuse is a common co-morbid problem in patients experiencing a first episode of psychotic illness (FEP). The relationship between the clinical presentation of FEP and cannabis abuse is complex and warrants further investigation, especially within the South African context. METHOD: We tested associations between recent/current cannabis use and duration of untreated psychosis (DUP), age of onset (AO), PANSS-rated (Positive and Negative Syndrome Scale) positive, negative and general psychopathology symptoms and depressive symptoms (Calgary Depression Scale for Schizophrenia) in a sample of 54 patients with FEP. RESULTS: Mean DUP was 34.4 weeks, while mean AO was 24.7 years. Co-morbid cannabis use occurred in 35% of the sample and was significantly associated with shorter DUP (Mann-Whitney U, p=0.026). While not significant, there was also a trend association between cannabis use and lower negative symptoms (Mann-Whitney U, p=0.051). CONCLUSION: Current/recent cannabis use was associated with clinical features of psychosis onset that previously have been associated with better outcome. Medium and long-term outcome for cannabis users however, is likely to depend on whether or not cannabis use is ongoing.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".