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Using the big data approach to clarify the structure of restricted and repetitive behaviors across the most commonly used autism spectrum disorder measures

BACKGROUND: Restricted and repetitive behaviors (RRB) in autism spectrum disorder (ASD) encompass several distinct domains. However, commonly used general ASD measures provide broad RRB scores rather than assessing separate RRB domains. The main objective of the current investigation was to conduct...

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Autores principales: Uljarević, Mirko, Jo, Booil, Frazier, Thomas W., Scahill, Lawrence, Youngstrom, Eric A., Hardan, Antonio Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8162018/
https://www.ncbi.nlm.nih.gov/pubmed/34044873
http://dx.doi.org/10.1186/s13229-021-00419-9
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author Uljarević, Mirko
Jo, Booil
Frazier, Thomas W.
Scahill, Lawrence
Youngstrom, Eric A.
Hardan, Antonio Y.
author_facet Uljarević, Mirko
Jo, Booil
Frazier, Thomas W.
Scahill, Lawrence
Youngstrom, Eric A.
Hardan, Antonio Y.
author_sort Uljarević, Mirko
collection PubMed
description BACKGROUND: Restricted and repetitive behaviors (RRB) in autism spectrum disorder (ASD) encompass several distinct domains. However, commonly used general ASD measures provide broad RRB scores rather than assessing separate RRB domains. The main objective of the current investigation was to conduct a psychometric evaluation of the ability of the Social Responsiveness Scale (SRS-2), the Social Communication Questionnaire (SCQ), the Autism Diagnostic Interview-Revised (ADI-R) and the Autism Diagnostic Observation Schedule (ADOS) to capture different RRB constructs. METHODS: Exploratory Structural Equation Modeling (ESEM) was conducted using individual item-level data from the SRS-2, SCQ, ADI-R and the ADOS. Data were obtained from five existing publicly available databases. For the SRS-2, the final sample consisted of N = 16,761 individuals (M(age) = 9.43, SD = 3.73; 18.5% female); for the SCQ, of N = 15,840 (M(age) = 7.99, SD = 4.06; 18.1% female); for the ADI-R, of N = 8985 (M(age) = 8.86, SD = 4.68; 19.4% female); and for the ADOS, of N = 6314 (M(age) = 12.29, SD = 6.79; 17.7% female). RESULTS: The three-factor structure provided the most optimal and interpretable fit to data for all measures (comparative fit index ≥ .983, Tucker Lewis index ≥ .966, root mean square error of approximation ≤ .028). Repetitive-motor behaviors, insistence on sameness and unusual or circumscribed interests factors emerged across all instruments. No acceptable fit was identified for the ADOS. LIMITATIONS: The five datasets used here afforded a large as well as wide distribution of the RRB item scores. However, measures used for establishing convergent and divergent validity were only available for a portion of the sample. CONCLUSIONS: Reported findings offer promise for capturing important RRB domains using general ASD measures and highlight the need for measurement development. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13229-021-00419-9.
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spelling pubmed-81620182021-06-01 Using the big data approach to clarify the structure of restricted and repetitive behaviors across the most commonly used autism spectrum disorder measures Uljarević, Mirko Jo, Booil Frazier, Thomas W. Scahill, Lawrence Youngstrom, Eric A. Hardan, Antonio Y. Mol Autism Research BACKGROUND: Restricted and repetitive behaviors (RRB) in autism spectrum disorder (ASD) encompass several distinct domains. However, commonly used general ASD measures provide broad RRB scores rather than assessing separate RRB domains. The main objective of the current investigation was to conduct a psychometric evaluation of the ability of the Social Responsiveness Scale (SRS-2), the Social Communication Questionnaire (SCQ), the Autism Diagnostic Interview-Revised (ADI-R) and the Autism Diagnostic Observation Schedule (ADOS) to capture different RRB constructs. METHODS: Exploratory Structural Equation Modeling (ESEM) was conducted using individual item-level data from the SRS-2, SCQ, ADI-R and the ADOS. Data were obtained from five existing publicly available databases. For the SRS-2, the final sample consisted of N = 16,761 individuals (M(age) = 9.43, SD = 3.73; 18.5% female); for the SCQ, of N = 15,840 (M(age) = 7.99, SD = 4.06; 18.1% female); for the ADI-R, of N = 8985 (M(age) = 8.86, SD = 4.68; 19.4% female); and for the ADOS, of N = 6314 (M(age) = 12.29, SD = 6.79; 17.7% female). RESULTS: The three-factor structure provided the most optimal and interpretable fit to data for all measures (comparative fit index ≥ .983, Tucker Lewis index ≥ .966, root mean square error of approximation ≤ .028). Repetitive-motor behaviors, insistence on sameness and unusual or circumscribed interests factors emerged across all instruments. No acceptable fit was identified for the ADOS. LIMITATIONS: The five datasets used here afforded a large as well as wide distribution of the RRB item scores. However, measures used for establishing convergent and divergent validity were only available for a portion of the sample. CONCLUSIONS: Reported findings offer promise for capturing important RRB domains using general ASD measures and highlight the need for measurement development. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13229-021-00419-9. BioMed Central 2021-05-27 /pmc/articles/PMC8162018/ /pubmed/34044873 http://dx.doi.org/10.1186/s13229-021-00419-9 Text en © The Author(s) 2021 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Uljarević, Mirko
Jo, Booil
Frazier, Thomas W.
Scahill, Lawrence
Youngstrom, Eric A.
Hardan, Antonio Y.
Using the big data approach to clarify the structure of restricted and repetitive behaviors across the most commonly used autism spectrum disorder measures
title Using the big data approach to clarify the structure of restricted and repetitive behaviors across the most commonly used autism spectrum disorder measures
title_full Using the big data approach to clarify the structure of restricted and repetitive behaviors across the most commonly used autism spectrum disorder measures
title_fullStr Using the big data approach to clarify the structure of restricted and repetitive behaviors across the most commonly used autism spectrum disorder measures
title_full_unstemmed Using the big data approach to clarify the structure of restricted and repetitive behaviors across the most commonly used autism spectrum disorder measures
title_short Using the big data approach to clarify the structure of restricted and repetitive behaviors across the most commonly used autism spectrum disorder measures
title_sort using the big data approach to clarify the structure of restricted and repetitive behaviors across the most commonly used autism spectrum disorder measures
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8162018/
https://www.ncbi.nlm.nih.gov/pubmed/34044873
http://dx.doi.org/10.1186/s13229-021-00419-9
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