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Machine learning classification of conduct disorder with high versus low levels of callous-unemotional traits based on facial emotion recognition abilities.

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Title: Machine learning classification of conduct disorder with high versus low levels of callous-unemotional traits based on facial emotion recognition abilities.
Authors: Pauli, Ruth, Kohls, Gregor, Tino, Peter, Rogers, Jack C., Baumann, Sarah, Ackermann, Katharina, Bernhard, Anka, Martinelli, Anne, Jansen, Lucres, Oldenhof, Helena, Gonzalez-Madruga, Karen, Smaragdi, Areti, Gonzalez-Torres, Miguel Angel, Kerexeta-Lizeaga, Iñaki, Boonmann, Cyril, Kersten, Linda, Bigorra, Aitana, Hervas, Amaia, Stadler, Christina, Fernandez-Rivas, Aranzazu
Source: European Child & Adolescent Psychiatry. Apr2023, Vol. 32 Issue 4, p589-600. 12p. 1 Diagram, 2 Charts, 2 Graphs.
Subjects: Statistics, Machine learning, Face perception, Fear, Behavior disorders in children, Descriptive statistics, Research funding, Emotions, Sadness
Abstract: Conduct disorder (CD) with high levels of callous-unemotional traits (CD/HCU) has been theoretically linked to specific difficulties with fear and sadness recognition, in contrast to CD with low levels of callous-unemotional traits (CD/LCU). However, experimental evidence for this distinction is mixed, and it is unclear whether these difficulties are a reliable marker of CD/HCU compared to CD/LCU. In a large sample (N = 1263, 9–18 years), we combined univariate analyses and machine learning classifiers to investigate whether CD/HCU is associated with disproportionate difficulties with fear and sadness recognition over other emotions, and whether such difficulties are a reliable individual-level marker of CD/HCU. We observed similar emotion recognition abilities in CD/HCU and CD/LCU. The CD/HCU group underperformed relative to typically developing (TD) youths, but difficulties were not specific to fear or sadness. Classifiers did not distinguish between youths with CD/HCU versus CD/LCU (52% accuracy), although youths with CD/HCU and CD/LCU were reliably distinguished from TD youths (64% and 60%, respectively). In the subset of classifiers that performed well for youths with CD/HCU, fear and sadness were the most relevant emotions for distinguishing them from youths with CD/LCU and TD youths, respectively. We conclude that non-specific emotion recognition difficulties are common in CD/HCU, but are not reliable individual-level markers of CD/HCU versus CD/LCU. These findings highlight that a reduced ability to recognise facial expressions of distress should not be assumed to be a core feature of CD/HCU. [ABSTRACT FROM AUTHOR]
Copyright of European Child & Adolescent Psychiatry is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Machine learning classification of conduct disorder with high versus low levels of callous-unemotional traits based on facial emotion recognition abilities.
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  Data: <searchLink fieldCode="JN" term="%22European+Child+%26+Adolescent+Psychiatry%22">European Child & Adolescent Psychiatry</searchLink>. Apr2023, Vol. 32 Issue 4, p589-600. 12p. 1 Diagram, 2 Charts, 2 Graphs.
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  Data: Conduct disorder (CD) with high levels of callous-unemotional traits (CD/HCU) has been theoretically linked to specific difficulties with fear and sadness recognition, in contrast to CD with low levels of callous-unemotional traits (CD/LCU). However, experimental evidence for this distinction is mixed, and it is unclear whether these difficulties are a reliable marker of CD/HCU compared to CD/LCU. In a large sample (N = 1263, 9–18 years), we combined univariate analyses and machine learning classifiers to investigate whether CD/HCU is associated with disproportionate difficulties with fear and sadness recognition over other emotions, and whether such difficulties are a reliable individual-level marker of CD/HCU. We observed similar emotion recognition abilities in CD/HCU and CD/LCU. The CD/HCU group underperformed relative to typically developing (TD) youths, but difficulties were not specific to fear or sadness. Classifiers did not distinguish between youths with CD/HCU versus CD/LCU (52% accuracy), although youths with CD/HCU and CD/LCU were reliably distinguished from TD youths (64% and 60%, respectively). In the subset of classifiers that performed well for youths with CD/HCU, fear and sadness were the most relevant emotions for distinguishing them from youths with CD/LCU and TD youths, respectively. We conclude that non-specific emotion recognition difficulties are common in CD/HCU, but are not reliable individual-level markers of CD/HCU versus CD/LCU. These findings highlight that a reduced ability to recognise facial expressions of distress should not be assumed to be a core feature of CD/HCU. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of European Child & Adolescent Psychiatry is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s00787-021-01893-5
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