Mapping Patterns and Correlates of in-Vivo Social Interactions of Adults with and without ASD Via Ecological Momentary Assessment

Poster Presentation
Thursday, May 10, 2018: 5:30 PM-7:00 PM
Hall Grote Zaal (de Doelen ICC Rotterdam)
A. H. Gerber1, S. B. Scott2, M. Finsaas2, J. M. Girard3 and M. D. Lerner2, (1)Stony Brook University, Stony Brook, NY, (2)Psychology, Stony Brook University, Stony Brook, NY, (3)Psychology, University of Pittsburgh, Pittsburgh, PA
Background: Research suggests that adults with Autism Spectrum Disorder (ASD) have limited social interactions, both in number and in normative patterning of such interactions (i.e., socializing when others prefer to do so); however, these data are almost exclusively provided via caregiver interview (Orsmond, Krauss, & Seltzer, 2004). Indeed, to date virtually no research has directly examined whether adults with ASD have limited social contact. Ecological momentary assessments (EMA) collected via smartphone represent a method of enhancing reporting accuracy through reducing retrospective biases. Only one study has addressed the social interactions of individuals with ASD using EMA, indicating low levels of social participation relative to other activities (Chen et al., 2017). Caregiver report indicates that age, ASD symptom severity, and functional impairment significantly predict total social interactions for adults with ASD (Orsmond et al., 2004); likewise, recent work suggests that alexithymia may be a particularly strong predictor of social-emotional deficits in ASD (Cook et al., 2013).

Objectives: We investigated patterns and predictors of social interactions in adults with ASD over one week. We hypothesized that individuals with ASD would report fewer total social interactions. Additionally, we hypothesized that alexithymia and ASD severity would negatively relate with number of social interactions, while IQ (proxy for functional impairment) would positively relate with interactions, when controlling for age.

Methods: Seventy-seven adults (26 ASD, 34%), ages 18 to 47 years (M=22.50 years, SD=5.84; 34 male, 44%) completed an EMA protocol in which they reported all social interactions via their smartphone over one week. Participants received 12 random-interval reminders each day between 9 am and 9 pm. Participants completed measures of ASD symptomatology (AQ; Baron-Cohen et al., 2001), IQ (K-BIT; Kaufman & Kaufman, 2004), and alexithymia (TAS; Parker, Taylor, & Bagby, 2003) prior to the EMA period.

Results: Results demonstrated no difference in total number of social interactions between participants with ASD (M=50.25, SD=37.96) and those without ASD (M=48.04, SD=25.80), t(27.11)=0.24, p= .81. Nonetheless, participants with ASD appeared to have more variation in their total interaction counts (see Figure 1). Negative binomial regression was used to examine predictors of total interaction counts. Age, gender, IQ, ASD severity, and alexithymia severity were entered into the model. Results indicated that alexithymia and age were significant predictors of the total number of interactions (both ps <.04; see Figure 2).

Conclusions: This is the first study to map patterns of in-vivo social interactions of adults with ASD in comparison to typically developing adults. We found no difference in the total number of social interactions between adults with and without ASD; however, high variability among individuals with ASD suggests that individual differences may best account for anecdotal reports of reduced social interaction among those with ASD. Through use of a novel measure of social activity, findings extend recent research indicating alexithymia, not ASD symptom severity, may drive social isolation for individuals with ASD (Shah et al., 2016). Given the high levels of alexithymia in ASD (Hill, Berthoz, & Frith, 2004), pre-treatment levels are an important factor when implementing social skills interventions.