Patterns, predictors and impact of substance use in early psychosis: a longitudinal study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: The purpose was to determine the prevalence of substance use and its impact on outcome 3 years after presentation for a first-episode of psychosis. METHOD: Subjects were 203 consecutive admissions to an early psychosis program. Assessments included substance use, positive, negative and depressive symptoms and social functioning. Assessments occurred at baseline, and 1-, 2- and 3-year follow-ups. RESULTS: The prevalence of substance misuse was high with 51% having a substance use disorder (SUD), 33% with cannabis SUD and 35% with an alcohol SUD. Numbers with an alcohol SUD declined considerably by 1 year and for cannabis SUD by 2 years. Substance misuse was significantly associated with male gender, young age and age of onset and cannabis misuse with increased positive symptoms. CONCLUSION: This study confirms the high rates of substance misuse, in particular cannabis, in first-episode psychosis. It further demonstrates that these rates can be reduced.
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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) | 0.001 | 0.000 |
| 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) | 0.000 | 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 it