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.

Details

Title
Machine learning reveals sex differences in distinguishing between conduct-disordered and neurotypical youth based on emotion processing dysfunction
Author
Kohls, Gregor; Elster, Erik M; Tino, Peter; Fairchild, Graeme; Stadler, Christina; Popma, Arne; Freitag, Christine M; De Brito, Stephane A; Konrad, Kerstin; Pauli, Ruth
Pages
1-10
Section
Research
Publication year
2025
Publication date
2025
Publisher
BioMed Central
e-ISSN
1471244X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3165524668
Copyright
© 2025. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.