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Record W4404112303 · doi:10.1093/schizbullopen/sgae028

Attention Deficit Hyperactivity Disorder Among Youth at Clinical High Risk of Psychosis

2024· article· en· W4404112303 on OpenAlexaff
Amy Braun, Lu Liu, Carrie E. Bearden, Kristin S. Cadenhead, Barbara A. Cornblatt, Matcheri S. Keshavan, Daniel H. Mathalon, Diana O. Perkins, William S. Stone, Ming T. Tsuang, Elaine F. Walker, Scott W. Woods, Tyrone D. Cannon, Jean Addington

Bibliographic record

VenueSchizophrenia Bulletin Open · 2024
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversity of Calgary
FundersNational Institute of Mental HealthCommonwealth of Massachusetts
KeywordsPsychosisPsychiatryAttention deficit hyperactivity disorderPsychologyClinical psychology

Abstract

fetched live from OpenAlex

Background: Attention Deficit Hyperactivity Disorder (ADHD) affects a significant proportion of the population and is associated with numerous adverse outcomes including lower educational attainment, occupational challenges, increased substance use, and various mental health issues including psychosis. This study examined the demographic, clinical, cognitive, social cognitive, and functional differences between youth at clinical high-risk (CHR) for psychosis with and without comorbid ADHD. Method: Data were drawn from the North American Prodrome Longitudinal Studies (NAPLS2 and NAPLS3), which included 764 and 710 CHR individuals, respectively. After applying exclusion criteria, the sample consisted of 271 CHR participants with ADHD and 1118 without ADHD. All data were examined cross-sectionally. Results: Compared with the non-ADHD group, the ADHD group was younger, had more difficulties with role functioning, premorbid functioning, and social cognition, were more likely to have a comorbid learning disorder, and reported less depression symptoms. There were no significant differences between the groups on positive or negative psychotic symptoms, transition rates, adverse events, or other comorbid disorders including substance use and depression. Discussion: Comorbid ADHD is likely not a significant predictor of transition to psychosis among CHR youth; however, those CHR with ADHD may experience symptoms at a younger age than those without and present with a distinct clinical profile.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.038
GPT teacher head0.340
Teacher spread0.302 · 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; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2024
Admission routes1
Has abstractyes

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