An emotion recognition subtyping approach to studying the heterogeneity and comorbidity of autism spectrum disorders and attention-deficit/hyperactivity disorder
Abstract Background Emotion recognition dysfunction has been reported in both autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). This suggests that emotion recognition is a cross-disorder trait that may be utilised to understand the heterogeneous psychopathology of...
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doaj-35c406902e784393a9e7b2e6f3fc3fbe2020-11-25T01:08:57ZengBMCJournal of Neurodevelopmental Disorders1866-19471866-19552018-11-0110111010.1186/s11689-018-9249-6An emotion recognition subtyping approach to studying the heterogeneity and comorbidity of autism spectrum disorders and attention-deficit/hyperactivity disorderFrancesca Waddington0Catharina Hartman1Yvette de Bruijn2Martijn Lappenschaar3Anoek Oerlemans4Jan Buitelaar5Barbara Franke6Nanda Rommelse7Department of Human Genetics, Radboud University Medical Center NijmegenDepartment of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University Medical Center Groningen, University of GroningenDonders Institute for Brain, Cognition and Behaviour, Radboud UniversityDepartment of Geriatrics, Radboud University Medical CentreDepartment of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University Medical Center Groningen, University of GroningenDonders Institute for Brain, Cognition and Behaviour, Radboud UniversityDepartment of Human Genetics, Radboud University Medical Center NijmegenDonders Institute for Brain, Cognition and Behaviour, Radboud UniversityAbstract Background Emotion recognition dysfunction has been reported in both autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). This suggests that emotion recognition is a cross-disorder trait that may be utilised to understand the heterogeneous psychopathology of ASD and ADHD. We aimed to identify emotion recognition subtypes and to examine their relation with quantitative and diagnostic measures of ASD and ADHD to gain further insight into disorder comorbidity and heterogeneity. Methods Factor mixture modelling was used on speed and accuracy measures of auditory and visual emotion recognition tasks. These were administered to children and adolescents with ASD (N = 89), comorbid ASD + ADHD (N = 64), their unaffected siblings (N = 122), ADHD (N = 111), their unaffected siblings (N = 69), and controls (N = 220). Identified classes were compared on diagnostic and quantitative symptom measures. Results A four-class solution was revealed, with the following emotion recognition abilities: (1) average visual, impulsive auditory; (2) average-strong visual and auditory; (3) impulsive/imprecise visual, average auditory; (4) weak visual and auditory. The weakest performing class (4) contained the highest percentage of patients (66.07%) and the lowest percentage controls (10.09%), scoring the highest on ASD/ADHD measures. The best performing class (2) demonstrated the opposite: 48.98% patients, 15.26% controls with relatively low scores on ASD/ADHD measures. Conclusions Subgroups of youths can be identified that differ both in quantitative and qualitative aspects of emotion recognition abilities. Weak emotion recognition abilities across sensory domains are linked to an increased risk for ASD as well as ADHD, although emotion recognition impairments alone are neither necessary nor sufficient parts of these disorders.http://link.springer.com/article/10.1186/s11689-018-9249-6Factor mixture modellingAutism spectrum disordersAttention-deficit/hyperactivity disorderEmotion recognitionLatent class |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Francesca Waddington Catharina Hartman Yvette de Bruijn Martijn Lappenschaar Anoek Oerlemans Jan Buitelaar Barbara Franke Nanda Rommelse |
spellingShingle |
Francesca Waddington Catharina Hartman Yvette de Bruijn Martijn Lappenschaar Anoek Oerlemans Jan Buitelaar Barbara Franke Nanda Rommelse An emotion recognition subtyping approach to studying the heterogeneity and comorbidity of autism spectrum disorders and attention-deficit/hyperactivity disorder Journal of Neurodevelopmental Disorders Factor mixture modelling Autism spectrum disorders Attention-deficit/hyperactivity disorder Emotion recognition Latent class |
author_facet |
Francesca Waddington Catharina Hartman Yvette de Bruijn Martijn Lappenschaar Anoek Oerlemans Jan Buitelaar Barbara Franke Nanda Rommelse |
author_sort |
Francesca Waddington |
title |
An emotion recognition subtyping approach to studying the heterogeneity and comorbidity of autism spectrum disorders and attention-deficit/hyperactivity disorder |
title_short |
An emotion recognition subtyping approach to studying the heterogeneity and comorbidity of autism spectrum disorders and attention-deficit/hyperactivity disorder |
title_full |
An emotion recognition subtyping approach to studying the heterogeneity and comorbidity of autism spectrum disorders and attention-deficit/hyperactivity disorder |
title_fullStr |
An emotion recognition subtyping approach to studying the heterogeneity and comorbidity of autism spectrum disorders and attention-deficit/hyperactivity disorder |
title_full_unstemmed |
An emotion recognition subtyping approach to studying the heterogeneity and comorbidity of autism spectrum disorders and attention-deficit/hyperactivity disorder |
title_sort |
emotion recognition subtyping approach to studying the heterogeneity and comorbidity of autism spectrum disorders and attention-deficit/hyperactivity disorder |
publisher |
BMC |
series |
Journal of Neurodevelopmental Disorders |
issn |
1866-1947 1866-1955 |
publishDate |
2018-11-01 |
description |
Abstract Background Emotion recognition dysfunction has been reported in both autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). This suggests that emotion recognition is a cross-disorder trait that may be utilised to understand the heterogeneous psychopathology of ASD and ADHD. We aimed to identify emotion recognition subtypes and to examine their relation with quantitative and diagnostic measures of ASD and ADHD to gain further insight into disorder comorbidity and heterogeneity. Methods Factor mixture modelling was used on speed and accuracy measures of auditory and visual emotion recognition tasks. These were administered to children and adolescents with ASD (N = 89), comorbid ASD + ADHD (N = 64), their unaffected siblings (N = 122), ADHD (N = 111), their unaffected siblings (N = 69), and controls (N = 220). Identified classes were compared on diagnostic and quantitative symptom measures. Results A four-class solution was revealed, with the following emotion recognition abilities: (1) average visual, impulsive auditory; (2) average-strong visual and auditory; (3) impulsive/imprecise visual, average auditory; (4) weak visual and auditory. The weakest performing class (4) contained the highest percentage of patients (66.07%) and the lowest percentage controls (10.09%), scoring the highest on ASD/ADHD measures. The best performing class (2) demonstrated the opposite: 48.98% patients, 15.26% controls with relatively low scores on ASD/ADHD measures. Conclusions Subgroups of youths can be identified that differ both in quantitative and qualitative aspects of emotion recognition abilities. Weak emotion recognition abilities across sensory domains are linked to an increased risk for ASD as well as ADHD, although emotion recognition impairments alone are neither necessary nor sufficient parts of these disorders. |
topic |
Factor mixture modelling Autism spectrum disorders Attention-deficit/hyperactivity disorder Emotion recognition Latent class |
url |
http://link.springer.com/article/10.1186/s11689-018-9249-6 |
work_keys_str_mv |
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