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Understanding Friendship Sex Heterophily and Relational Characteristics to Optimize the Selection of Peer Models for Children with Autism Spectrum Disorder.

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Title: Understanding Friendship Sex Heterophily and Relational Characteristics to Optimize the Selection of Peer Models for Children with Autism Spectrum Disorder.
Authors: Locke, Jill, Anderson, Ariana, Frederick, Lindsay, Kasari, Connie
Source: Journal of Autism & Developmental Disorders. Dec2018, Vol. 48 Issue 12, p4010-4018. 9p. 3 Charts, 3 Graphs.
Subjects: Autism, Friendship, Sex distribution, Social networks, Affinity groups
Abstract: This study used social network analysis to evaluate whether sex heterophily, the degree to which peers are different in sex, between 126 children with autism (ages 5-12 years) and their peers affected social network connectivity. Results indicate that: (1) the quantity and sex of friends were more important in predicting social network connectivity than the relational characteristics of the friends (friendship nominations and social network salience/popularity); and (2) sex heterophily is an important factor in predicting social network connectivity. For males with autism, having friends of the same sex was associated with better social network connectivity; this was not true for females with autism. These findings have important implications for the selection of peer models for elementary-aged children with autism. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Autism & Developmental Disorders 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.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Understanding Friendship Sex Heterophily and Relational Characteristics to Optimize the Selection of Peer Models for Children with Autism Spectrum Disorder.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Autism+%26+Developmental+Disorders%22">Journal of Autism & Developmental Disorders</searchLink>. Dec2018, Vol. 48 Issue 12, p4010-4018. 9p. 3 Charts, 3 Graphs.
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  Data: <searchLink fieldCode="DE" term="%22Autism%22">Autism</searchLink><br /><searchLink fieldCode="DE" term="%22Friendship%22">Friendship</searchLink><br /><searchLink fieldCode="DE" term="%22Sex+distribution%22">Sex distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Social+networks%22">Social networks</searchLink><br /><searchLink fieldCode="DE" term="%22Affinity+groups%22">Affinity groups</searchLink>
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  Label: Abstract
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  Data: This study used social network analysis to evaluate whether sex heterophily, the degree to which peers are different in sex, between 126 children with autism (ages 5-12 years) and their peers affected social network connectivity. Results indicate that: (1) the quantity and sex of friends were more important in predicting social network connectivity than the relational characteristics of the friends (friendship nominations and social network salience/popularity); and (2) sex heterophily is an important factor in predicting social network connectivity. For males with autism, having friends of the same sex was associated with better social network connectivity; this was not true for females with autism. These findings have important implications for the selection of peer models for elementary-aged children with autism. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Autism & Developmental Disorders 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/s10803-018-3662-2
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      – SubjectFull: Sex distribution
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              Text: Dec2018
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