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Application of Latent Class Analysis to Identify Subgroups of Children with Autism Spectrum Disorders who Benefit from Social Skills Training
With Latent Class Analysis applied on data of 98 children with autism spectrum disorder (ASD) (9–12 years; 17 girls) participating in social skills training (SST) in a randomized controlled trial (Dekker et al. 2019), four subgroups were detected, based on social-communicative skills before, and res...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer US
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124042/ https://www.ncbi.nlm.nih.gov/pubmed/32892235 http://dx.doi.org/10.1007/s10803-020-04678-y |
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author | Dekker, Vera Nauta, Maaike H. Timmerman, Marieke E. Mulder, Erik J. Hoekstra, Pieter J. de Bildt, Annelies |
author_facet | Dekker, Vera Nauta, Maaike H. Timmerman, Marieke E. Mulder, Erik J. Hoekstra, Pieter J. de Bildt, Annelies |
author_sort | Dekker, Vera |
collection | PubMed |
description | With Latent Class Analysis applied on data of 98 children with autism spectrum disorder (ASD) (9–12 years; 17 girls) participating in social skills training (SST) in a randomized controlled trial (Dekker et al. 2019), four subgroups were detected, based on social-communicative skills before, and response patterns to training. Two subgroups improved after SST. Characterizing the subgroups based on participant and intervention characteristics showed that improvement was related to lower parent-reported perceived difficulty of social-communicative skills at start, higher verbal ability, younger age and milder symptoms of ASD and anxiety. The lowest performing non-improving subgroup participated more often in SST without parent/teacher involvement, compared to all other subgroups. Response to SST in ASD seems to vary depending on participant characteristics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10803-020-04678-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-8124042 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-81240422021-05-26 Application of Latent Class Analysis to Identify Subgroups of Children with Autism Spectrum Disorders who Benefit from Social Skills Training Dekker, Vera Nauta, Maaike H. Timmerman, Marieke E. Mulder, Erik J. Hoekstra, Pieter J. de Bildt, Annelies J Autism Dev Disord Original Paper With Latent Class Analysis applied on data of 98 children with autism spectrum disorder (ASD) (9–12 years; 17 girls) participating in social skills training (SST) in a randomized controlled trial (Dekker et al. 2019), four subgroups were detected, based on social-communicative skills before, and response patterns to training. Two subgroups improved after SST. Characterizing the subgroups based on participant and intervention characteristics showed that improvement was related to lower parent-reported perceived difficulty of social-communicative skills at start, higher verbal ability, younger age and milder symptoms of ASD and anxiety. The lowest performing non-improving subgroup participated more often in SST without parent/teacher involvement, compared to all other subgroups. Response to SST in ASD seems to vary depending on participant characteristics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10803-020-04678-y) contains supplementary material, which is available to authorized users. Springer US 2020-09-05 2021 /pmc/articles/PMC8124042/ /pubmed/32892235 http://dx.doi.org/10.1007/s10803-020-04678-y Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Paper Dekker, Vera Nauta, Maaike H. Timmerman, Marieke E. Mulder, Erik J. Hoekstra, Pieter J. de Bildt, Annelies Application of Latent Class Analysis to Identify Subgroups of Children with Autism Spectrum Disorders who Benefit from Social Skills Training |
title | Application of Latent Class Analysis to Identify Subgroups of Children with Autism Spectrum Disorders who Benefit from Social Skills Training |
title_full | Application of Latent Class Analysis to Identify Subgroups of Children with Autism Spectrum Disorders who Benefit from Social Skills Training |
title_fullStr | Application of Latent Class Analysis to Identify Subgroups of Children with Autism Spectrum Disorders who Benefit from Social Skills Training |
title_full_unstemmed | Application of Latent Class Analysis to Identify Subgroups of Children with Autism Spectrum Disorders who Benefit from Social Skills Training |
title_short | Application of Latent Class Analysis to Identify Subgroups of Children with Autism Spectrum Disorders who Benefit from Social Skills Training |
title_sort | application of latent class analysis to identify subgroups of children with autism spectrum disorders who benefit from social skills training |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124042/ https://www.ncbi.nlm.nih.gov/pubmed/32892235 http://dx.doi.org/10.1007/s10803-020-04678-y |
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