A Narrative Review Exploring Attention Deficit/Hyperactivity Disorder in Patients with Early Psychosis
Bibliographic record
Abstract
While both Attention deficit hyperactivity disorder (ADHD) and schizophrenia are considered to have neurodevelopmental origins with associated impairments in executive functioning, there is a paucity of clinical guidelines pertaining specifically to this comorbidity. We sought to summarize the existing literature on ADHD in early psychosis patients, focusing on issues that would be most relevant to clinical practice. For this narrative review, we completed a search on PubMed and PsycINFO with 22 papers meeting criteria for review. Overall, it appears that a diagnosis of ADHD in childhood increases the risk of the subsequent development of a primary psychotic disorder. This risk may be modified by higher rates of substance use and could be related to shared premorbid risk factors for both conditions, such as obstetrical complications. Stimulant use has been associated with the onset of psychotic symptoms in some individuals, but it is unclear whether certain subgroups are more susceptible. Despite the fact that these two conditions co-occur relatively frequently, there is currently a lack of objective diagnostic tests for ADHD specific to populations with primary psychotic disorders, and a paucity of evidence on whether stimulants are effective for ADHD symptoms in this sub-group. Future research is warranted to investigate whether stimulant treatment confers any additional risks for symptom exacerbation in individuals with primary psychotic disorders taking antipsychotic maintenance treatment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".