Measuring Changes in Collaborative Networks Among Parents and Autism Intervention Providers

Saturday, May 14, 2016: 11:30 AM
Hall B (Baltimore Convention Center)
E. McGhee Hassrick1 and K. Carley2, (1)Weill Cornell Medical College, Ossining, NY, (2)Carnegie Mellon University, Pittsburgh, PA
Background:  To manage a child’s autism treatment effectively, parents need to learn specialized knowledge, skills and scientific information about autism and its treatment; master particular teaching skills; obtain information about where to find services; gain familiarity with special education laws; negotiate on behalf of their children with many different types of clinical providers and coordinate interventions with school providers, where children with autism receive many of their services. Who do parents collaborate with as they manage their child’s interventions, over their child’s life course? We do not currently have a systematic way of mapping the emergence and subsequent changes in collaborative networks among parents, community providers and teachers, around individual children with ASD, to examine how these emergent networks influence intervention selection and implementation and a parent’s knowledge or monitoring capacity for their child.

Objectives:  This research study used innovative dynamic social networks techniques to measure changes over time in the collaborative networks that emerged around 45 individual children with ASD, situated in two different urban, public schools, named “Aspire” and “Flores”. For each child’s collaborative network, we analyzed changes over the course of one school year in the implementation and alignment of interventions; the use of autism resources; and the completion of autism trainings. We concurrently tracked changes in the coordination, problem solving and trust networks that provided interventions for each child. Examining the social network processes that emerge around the child help us to identify interactional mechanisms that inform the ongoing treatment of children diagnosed with autism, as they develop across the life course.

Methods:  We conducted 90 network surveys with school teachers, aides, clinicians and parents, at the fall, spring and summer of one school year, wherein they reported coordination, resource, training and intervention implementation for forty five children diagnosed with autism spectrum disorder. Parent and autism provider network survey data was analyzed using ORA for dynamic, multi-modal networks and network visualizations.

Results:  Findings confirmed that problem solving and collaboration between parents and school staff varied across children and across schools, with most parents at Aspire frequently connected to multiple staff throughout the school year, compared with few parents at Flores.  Child treatments at Aspire were more often shared among providers, with low exclusivity scores (0.2 to 4.0), while at Flores, they were idiosyncratic, with higher exclusivity scores (2.0 to 8.0).  See Figure 1. Autism resource and training networks were also clustered among parents and staff at Aspire as compared with Flores. Parents and staff at both schools accessed far more general autism resources, than specific, and was more robust in fall.

Conclusions:  Findings suggest that dynamic networks of children at Aspire were aligned around a particular group of treatments with related resources and trainings, making each child’s map more similar, over time, at Aspire. Dynamic networks at Flores were more idiosyncratic, with lower overall levels of frequent problem solving between parents and school providers, suggesting a more individualized, less aligned approach to management.