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Record W605763161

Psychotic disorders comorbid with attention-deficit hyperactivity disorder: an important knowledge gap.

2015· article· en· W605763161 on OpenAlexaff
Emmanuelle Lévy, Alexandru Traicu, Srividya N. Iyer, Ashok Malla, Ridha Joober

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsDouglas Mental Health University Institute
Fundersnot available
KeywordsPsychosisAttention deficit hyperactivity disorderPsychiatryComorbidityMethylphenidatePsychologyAtomoxetineSchizophrenia (object-oriented programming)Substance abuseClinical psychologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

Psychotic disorders (PDs) and attention-deficit hyperactivity disorder (ADHD) are frequently comorbid. Clinicians are often reticent to treat ADHD in patients with psychosis, fearing that psychostimulants will worsen psychotic symptoms. Advances in neurobiology have challenged the simplistic dichotomy where PD is considered a disorder of high dopamine (DA), treated by DA antagonists, and ADHD a disorder of low DA, treated by DA agonists. In our paper, we review the literature on comorbid ADHD and psychosis. Treating ADHD with psychostimulants may be considered in patients with PD who have been stabilized with antipsychotics (APs). Not treating ADHD may have consequences because ADHD may predispose patients to drug abuse, which further increases the risk of PD. Nevertheless, more systematic studies are needed as there remains some uncertainty on the combined use of APs and psychostimulants in comorbid PD and ADHD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.060
GPT teacher head0.309
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations36
Published2015
Admission routes1
Has abstractyes

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Same venuePubMedSame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207