Stimulant Medication and Psychotic Symptoms in Offspring of Parents With Mental Illness
Bibliographic record
Abstract
BACKGROUND: Stimulants, such as methylphenidate, are among the most commonly used medications in children and adolescents. Psychotic symptoms have been reported as rare adverse reactions to stimulants but have not been systematically inquired about in most previous studies. Family history of mental illness may increase the vulnerability to drug-induced psychotic symptoms. We examined the association between stimulant use and psychotic symptoms in sons and daughters of parents with major mood and psychotic disorders. METHODS: We assessed psychotic symptoms, psychotic-like experiences, and basic symptoms in 141 children and youth (mean ± SD age: 11.8 ± 4.0 years; range: 6-21 years), who had 1 or both parents with major depressive disorder, bipolar disorder, or schizophrenia, and of whom 24 (17.0%) had taken stimulant medication. RESULTS: Psychotic symptoms were present in 62.5% of youth who had taken stimulants compared with 27.4% of participants who had never taken stimulants. The association between stimulant use and psychotic experiences remained significant after adjustment for potential confounders (odds ratio: 4.41; 95% confidence interval: 1.82-10.69; P = .001) and was driven by hallucinations occurring during the use of stimulant medication. A temporal relationship between use of stimulants and psychotic symptoms was supported by an association between current stimulant use and current psychotic symptoms and co-occurrence in cases that were assessed on and off stimulants. CONCLUSIONS: Psychotic symptoms should be monitored during the use of stimulants in children and adolescents. Family history of mood and psychotic disorders may need to be taken into account when considering the prescription of stimulants.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".