Evidence map›Paper›PMID 39915750›Full record

ArticleBMC psychiatry2025

Machine learning reveals sex differences in distinguishing between conduct-disordered and neurotypical youth based on emotion processing dysfunction.

Gregor Kohls, Erik M Elster, Peter Tino, Graeme Fairchild, Christina Stadler, Arne Popma, Christine M Freitag, Stephane A De Brito, Kerstin Konrad, Ruth Pauli

Abstract readMulticenter Study
In one paragraph

Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors.

Gregor Kohls *Department of Child and Adolescent Psychiatry, Faculty of Medicine, TUD Dresden University of Technology, German Center for Child and Adolescent Health (DZKJ), partner site Leipzig/Dresden, Dresden, Germany. gregor.kohls@ukdd.de.
Erik M Elster *Department of Child and Adolescent Psychiatry, Faculty of Medicine, TUD Dresden University of Technology, German Center for Child and Adolescent Health (DZKJ), partner site Leipzig/Dresden, Dresden, Germany.
Peter TinoSchool of Computer Science, University of Birmingham, Birmingham, UK.
Graeme FairchildDepartment of Psychology, University of Bath, Bath, UK.
Christina StadlerDepartment of Child and Adolescent Psychiatry, Psychiatric University Hospital, University of Basel, Basel, Switzerland.
Arne PopmaDepartment of Child and Adolescent Psychiatry, VU University Medical Center, Amsterdam, the Netherlands.
Christine M FreitagDepartment of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany.
Stephane A De BritoCentre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK.
Kerstin KonradChild Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, RWTH Aachen University, Aachen, Germany.
Ruth PauliCentre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTheoretical models of conduct disorder (CD) highlight that deficits in emotion recognition, learning, and regulation play a pivotal role in CD etiology. With CD being more prevalent in boys than girls, various theories aim to explain this sex difference. The "differential threshold" hypothesis suggests greater emotion dysfunction in conduct-disordered girls than boys, but previous research using conventional statistical analyses has failed to support this hypothesis. Here, we used novel analytic techniques such as machine learning (ML) to uncover potentially sex-specific differences in emotion dysfunction among girls and boys with CD compared to their neurotypical peers.

methodsMulti-site data from 542 youth with CD and 710 neurotypical controls (64% girls, 9-18 years) who completed emotion recognition, learning, and regulation tasks were analyzed using a multivariate ML classifier to distinguish between youth with CD and controls separately by sex.

resultsBoth female and male ML classifiers accurately predicted (above chance level) individual CD status based solely on the neurocognitive features of emotion dysfunction. Notably, the female classifier outperformed the male classifier in identifying individuals with CD. However, the classification and identification performance of both classifiers was below the clinically relevant 80% accuracy threshold (although they still provided relatively fair and realistic estimates of ~ 60% classification performance), probably due to the substantial neurocognitive heterogeneity within such a large and diverse, multi-site sample of youth with CD (and neurotypical controls).

conclusionsThese findings confirm the close association between emotion dysfunction and CD in both sexes, with a stronger association observed in affected girls, which aligns with the "differential threshold" hypothesis. However, the data also underscore the heterogeneity of CD, namely that only a subset of those affected are likely to have emotion dysfunction and that other neurocognitive domains (not tested here) probably also contribute to CD etiology. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Conduct DisorderEmotionsMachine LearningAdolescentChildFemaleHumansMaleSex CharacteristicsSex FactorsConduct disorderEmotion dysfunctionEmotion processingFemNAT-CDMachine learningSex differencesYouth

Identifiers

PMID39915750
PMCPMC11800453

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