Using network analysis to improve understanding and utility of the 10-item Autism-Spectrum Quotient
The 10-item Autism-Spectrum Quotient (AQ10) is a measure of autistic traits used in research and clinical practice. Recently, the AQ10 has garnered critical attention, with research questioning its psychometric properties and clinical cutoff value. To help inform the utility of the measure, we condu...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2022-01-01
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| Series: | Experimental Results |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2516712X22000077/type/journal_article |
| _version_ | 1811156281769066496 |
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| author | Lucy H. Waldren Lucy A. Livingston Florence Y. N. Leung Punit Shah Gregory Postal |
| author_facet | Lucy H. Waldren Lucy A. Livingston Florence Y. N. Leung Punit Shah Gregory Postal |
| author_sort | Lucy H. Waldren |
| collection | DOAJ |
| description | The 10-item Autism-Spectrum Quotient (AQ10) is a measure of autistic traits used in research and clinical practice. Recently, the AQ10 has garnered critical attention, with research questioning its psychometric properties and clinical cutoff value. To help inform the utility of the measure, we conducted the first network analysis of the AQ10, with a view to gain a better understanding of its individual items. Using a large dataset of 6,595 participants who had completed the AQ10, we found strongest inter-subscale connections between communication, imagination, and socially relevant items. The nodes with greatest centrality concerned theory of mind differences. Together, these findings align with cognitive explanations of autism and provide clues about which AQ10 items show greatest utility for informing autism-related clinical practice. |
| first_indexed | 2024-04-10T04:47:52Z |
| format | Article |
| id | doaj.art-0f8f1122390f43018de86ebc4c50ce2c |
| institution | Directory Open Access Journal |
| issn | 2516-712X |
| language | English |
| last_indexed | 2024-04-10T04:47:52Z |
| publishDate | 2022-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Experimental Results |
| spelling | doaj.art-0f8f1122390f43018de86ebc4c50ce2c2023-03-09T12:34:17ZengCambridge University PressExperimental Results2516-712X2022-01-01310.1017/exp.2022.7Using network analysis to improve understanding and utility of the 10-item Autism-Spectrum QuotientLucy H. Waldren0https://orcid.org/0000-0001-5618-0053Lucy A. Livingston1https://orcid.org/0000-0002-8597-6525Florence Y. N. Leung2Punit Shah3https://orcid.org/0000-0001-5497-4765Gregory Postal4Department of Psychology, University of Bath, Bath, United KingdomNeuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United KingdomDepartment of Psychology, University of Bath, Bath, United KingdomDepartment of Psychology, University of Bath, Bath, United KingdomUniformed Services University of the Health Sciences F Edward Hebert School of Medicine, Psychiatry, 130 South Churchill Drive, Fayetteville, North Carolina, United States, 28303-5065The 10-item Autism-Spectrum Quotient (AQ10) is a measure of autistic traits used in research and clinical practice. Recently, the AQ10 has garnered critical attention, with research questioning its psychometric properties and clinical cutoff value. To help inform the utility of the measure, we conducted the first network analysis of the AQ10, with a view to gain a better understanding of its individual items. Using a large dataset of 6,595 participants who had completed the AQ10, we found strongest inter-subscale connections between communication, imagination, and socially relevant items. The nodes with greatest centrality concerned theory of mind differences. Together, these findings align with cognitive explanations of autism and provide clues about which AQ10 items show greatest utility for informing autism-related clinical practice.https://www.cambridge.org/core/product/identifier/S2516712X22000077/type/journal_articleautismautistic traitsnetwork analysisneurodiversitypsychometrics |
| spellingShingle | Lucy H. Waldren Lucy A. Livingston Florence Y. N. Leung Punit Shah Gregory Postal Using network analysis to improve understanding and utility of the 10-item Autism-Spectrum Quotient Experimental Results autism autistic traits network analysis neurodiversity psychometrics |
| title | Using network analysis to improve understanding and utility of the 10-item Autism-Spectrum Quotient |
| title_full | Using network analysis to improve understanding and utility of the 10-item Autism-Spectrum Quotient |
| title_fullStr | Using network analysis to improve understanding and utility of the 10-item Autism-Spectrum Quotient |
| title_full_unstemmed | Using network analysis to improve understanding and utility of the 10-item Autism-Spectrum Quotient |
| title_short | Using network analysis to improve understanding and utility of the 10-item Autism-Spectrum Quotient |
| title_sort | using network analysis to improve understanding and utility of the 10 item autism spectrum quotient |
| topic | autism autistic traits network analysis neurodiversity psychometrics |
| url | https://www.cambridge.org/core/product/identifier/S2516712X22000077/type/journal_article |
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