Literature DB >> 29610409

Network Measures of Collaborative Support for Young Adults With Autism.

Elizabeth McGhee Hassrick1, Paul Shattuck2, Kathleen Carley3.   

Abstract

OBJECTIVES: The treatment of autism requires complex, multimodal interventions, provided by parents and providers across settings. As young adults with autism spectrum disorder (ASD) transition into adulthood, new stakeholders are added to support planning for postsecondary employment. In this article, we investigate the use of dynamic social network measures that describe the resources of young adults throughout transition.
METHODS: A longitudinal, dynamic social network survey (Social Dynamics of Intervention [SoDI]) was conceptualized, designed, and conducted as a feasibility test, measuring changes in collaboration among parents and school staff members who provided interventions for children with ASD in 2 urban public schools. Using the SoDI, we tracked the following over time: the team who provided interventions, their locations, the interventions they provided, the autism trainings they attended, and the density of the team's problem-solving network for the child.
RESULTS: Using the SoDI, we successfully identified stakeholders across settings who provided interventions for each child. Results indicated variation in the density of problem-solving and trust related to ASD intervention across teams as well as variation in intervention and autism knowledge networks during the school year. Adaptations of the SoDI for mapping pre- and posttransition resources and social connectivity across stakeholders for young adults with ASD are proposed in the Discussion section.
CONCLUSIONS: Dynamic social network approaches can be used to capture changes in intervention, autism knowledge, and social connectivity, providing informative descriptive data about how vocational rehabilitation policies might increase employment supports during the transition process for young adults with ASD.
Copyright © 2018 by the American Academy of Pediatrics.

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Mesh:

Year:  2018        PMID: 29610409      PMCID: PMC5877126          DOI: 10.1542/peds.2016-4300E

Source DB:  PubMed          Journal:  Pediatrics        ISSN: 0031-4005            Impact factor:   7.124


  10 in total

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  10 in total
  1 in total

Review 1.  Best Practices for Modeling Egocentric Social Network Data and Health Outcomes.

Authors:  Jacqueline M Burgette; Jacquelin Rankine; Alison J Culyba; Kar-Hai Chu; Kathleen M Carley
Journal:  HERD       Date:  2021-05-11
  1 in total

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