Age of Onset of Cannabis Use is Associated with Age of Onset of High-Risk Symptoms for Psychosis
Bibliographic record
Abstract
OBJECTIVE: Increasing interest in the prodromal stage of schizophrenia over the past decade led us to perform our study to monitor people at high risk for developing a psychosis. We hypothesized that cannabis use or a cannabis use disorder at a younger age relates to high-risk symptoms at a younger age. METHOD: People referred to the Academic Medical Centre in Amsterdam, the Netherlands, with an ultra-high risk (UHR) for psychosis were interviewed with the Composite International Diagnostic Interview to assess their cannabis consumption. The Interview for the Retrospective Assessment of the Onset of Schizophrenia was used to collect data about age of onset of high-risk or prodromal symptoms. Nine high-risk symptoms were selected and clustered because of their known relation with cannabis use. RESULTS: Among the 68 included participants, 35 had used cannabis (51.5%), of whom 15 had used recently. Twenty-two participants had been cannabis abusers or cannabis-dependent (32.4%) in the past. Younger age at onset of cannabis use was related to younger age of onset of the cluster of symptoms (rho = 0.48, P = 0.003) and also to 6 symptoms individually (rho = 0.47 to 0.90, P < 0.001 to 0.04). Younger age at onset of a cannabis use disorder was related to younger age of onset of the cluster of symptoms (rho = 0.67, P = 0.001) and also to 6 symptoms individually (rho = 0.50 to 0.93, P = 0.007 to 0.03). CONCLUSION: Cannabis use or a cannabis use disorder at a younger age in a group with an UHR for transition to psychosis is related to onset of high-risk symptoms for psychosis at a younger age.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".