Onset and exacerbation of first episode psychosis associated with cannabis withdrawal: A case series
Bibliographic record
Abstract
• Abrupt cannabis cessation following long-term use can induce or exacerbate psychotic symptoms leading to an acute psychotic episode in vulnerable individuals. • Starting cannabis use in adolescence use may increase the risk of cannabis withdrawal induced psychosis. • Gradual reductions in frequency, quantity, and THC potency of cannabis when wanting to decrease use may lower the risk of developing psychotic symptoms during withdrawal. High levels of cannabis use have been established as a risk factor for the development of psychotic disorders and may exacerbate existing mental illness. Despite extensive research on the adverse effects of cannabis, less attention has been given to a concerning phenomenon: the onset and exacerbation of acute psychotic symptoms following abrupt cessation of cannabis use. This case series presents three individuals who developed their first episode of psychosis shortly after discontinuing heavy cannabis use (several grams daily). These cases underscore the potential link between cannabis withdrawal and the emergence or exacerbation of psychotic symptoms which may led to a psychotic episode, highlighting the need for greater public health awareness of safe cannabis use practices. The discussion explores potential mechanisms such as dysregulation of the endocannabinoid and dopamine systems following long-term cannabis use, which may predispose individuals to psychosis during withdrawal. The findings advocate for safer cannabis discontinuation guidelines, suggesting gradual reduction in cannabis use and potency of product consumed as preventive measures. Further research is essential to explore predictive risk factors and refine approaches to mitigate the risk of psychosis associated with cannabis withdrawal in vulnerable populations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".