Machine learning reveals sex differences in distinguishing between conduct-disordered and neurotypical youth based on emotion processing dysfunction
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Theoretical 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. METHODS: Multi-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. RESULTS: Both 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). CONCLUSIONS: These 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.
Source: BMC Psychiatry
Authors: Gregor Kohls, Erik M. Elster, Peter Tino, Graeme Fairchild, Christina Stadler, Arne Popma, Christine M. Freitag, Stephane A. De Brito, Kerstin Konrad, Ruth Pauli
Institutions: Technische Universität Dresden, University of Birmingham, University of Bath, University of Basel, University Hospital of Basel, Universitäre Psychiatrische Kliniken Basel, Amsterdam UMC Location Vrije Universiteit Amsterdam, Goethe University Frankfurt, University Hospital Frankfurt, Jülich Aachen Research Alliance, RWTH Aachen University
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,290
Funders: Brain and Behavior Research Foundation, National Alliance for Research on Schizophrenia and Depression, European Commission, Bundesministerium für Bildung und Forschung, Technische Universität Dresden, Directorate for Biological Sciences, Biotechnology and Biological Sciences Research Council, Economic and Social Research Council
OpenAlex ID: W4407225789
