AIRB3: Measuring Collaborative Networks Among Parents and Autism Intervention Providers during the Pre-Transition Period.

Saturday, May 13, 2017: 12:00 PM-1:40 PM
Golden Gate Ballroom (Marriott Marquis Hotel)
E. McGhee Hassrick1, K. M. Carley2, N. R. Tomy1, J. Chow3, L. Hauptman3, B. Bronstein4, D. S. Mandell4, A. C. Stahmer5 and C. Kasari3, (1)A.J. Drexel Autism Institute, Drexel University, Philadelphia, PA, (2)Carnegie Mellon University, Pittsburgh, PA, (3)University of California Los Angeles, Los Angeles, CA, (4)University of Pennsylvania, Philadelphia, PA, (5)Psychiatry and Behavioral Sciences, University of California at Davis MIND Institute, Sacramento, CA
Background: Finding and arranging interventions for children with ASD and coordinating them across the life course presents many challenges for people with autism, their parents and providers. Collaboration is particularly challenging during transitions, such as when moving from preschool to kindergarten or middle school to high school.

Objectives: To use social networks techniques to measure collaboration for children with ASD.

Methods: Participants were 6 children with ASD from families with incomes below the poverty line who were transitioning to a new school: 3 children transitioning from middle to high school, 2 from elementary to middle and 1 from pre-school to kindergarten. We used a three stage snowball process to identify individuals involved during the pre-transition period. This process yielded 59 key people, from which we recruited 42. The Social Dynamics of Intervention (SoDI) survey tool was conducted at the end of the school year before the transition to the new school.

Results:  Child team size varied from 15 to 30, with a mean of 12 people identified as “key” and 10 identified as “not key”. Most school and district staff identified were from the pre-transition school (mean = 76%). Fewer were identified as district staff (mean = 17%). Only 2 teams identified people from the post-transition school. Participants often named people as team members that parents did not identify. On average, 52% of relied on providers that were not named by the parent. About half of identified team members were considered “inner circle” providers (mean = 47%) and 1/3 (mean = 38%) were “outer circle” providers. The majority of team members were school and district providers (mean = 61%). Fewer healthcare providers (mean = 10%), community members (mean = 10%) and family members (mean = 14%) were identified. Parents were identified as essential inner/outer participants team members by a small number of people per team (mean = 3.5 participants). Meanwhile, parents identified more team members as essential (mean = 9.3 participants). See Table 1 for summary of results. Social network analysis indicated that an average of 3.50 team members (per team) reported that they relied on the primary parent for essential support with the child’s interventions and primary parents reported that they relied on an average of 4.80 team members (per team) for essential support with the child’s interventions. Parents varied in the degree of leadership they had within each team (eigenvector centrality). Only one parent had a high eigenvector score (.85 SD above random mean). See Figure 1 for sociograms.

Conclusions: On average, parents did not identify 52% of the people identified as essential. This suggests that parents did not rely on many of their child’s everyday providers. With the exception of one team, none or few people from the post transition context were involved with the child’s team during the pre-transition period. Network findings suggest that parents relied on other team members more than other team members relied on them for support of the child’s everyday interventions. Only one parent emerged as a leader among team members.