Examining Distraction and Avoidance Information Processing Mechanisms Among Children with Autism Spectrum Disorder

Background:

Research ubiquitously supports that children with ASD demonstrate impairments in social attention such as a reduction of attention to social stimuli in the majority of contexts (Guillon, Hadjikhani, Baduel, & Rogé, 2014). Less is known about the mechanisms that contribute to diminished social attention in ASD. The social motivation theory posits that individuals with ASD simply find social stimuli less rewarding and do not show the same preference for social stimuli that typically developing children do (Chevallier, Kohls, Troiani, Brodkin, & Schultz, 2012). Other research suggests that competition from circumscribed interests (Cis) may better explain the emergence of the social attention deficit in ASD (Sasson, Turner‐Brown, Holtzclaw, Lam, & Bodfish, 2008).

Objectives:

Use an information-processing paradigm (commonly used to examine attention biases in individuals with internalizing disorders) to examine profiles of attention in children with ASD. Evaluate whether children with ASD demonstrate a causal mechanism accounting for diminished social attention more in line with avoidance of social stimuli as compared to distraction by circumscribed objects.

Methods:

The current study compared attentional allocation patterns in children ages 6 to 17 years diagnosed with ASD (n = 16) to a typically developing (TD) control group (n = 19). The study utilized an ASD-specific passive viewing task to examine information processing styles (Harrison & Gibb, 2014). The task was designed so that each quadrant or area of interest (AOI) depicted two social images, a familiar face (FS) and a control face (NFS), and two objects, a parent identified CI (FCI) and an unfamiliar control object (UFO). This presentation allows for the examination of the proportion of attentional allocation across stimulus type.

Results:

Initial analyses using a 2 (diagnostic group: ASD, TD) x 4 (AOI: FS, NFS, FCI, UFO) repeated measures ANOVA to examine differences in mean dwell time for each of the four stimulus types. Results from this study did not reveal a diagnostic group by stimulus type interaction. However, children with ASD and TD children demonstrated systematic differences in attentional allocation. More specifically, children with ASD demonstrated less attention than TD children to all stimulus types: CI objects, F (1, 33) = 5.21, p = .03, control objects, F (1, 33) = 10.77, p = .002, familiar faces, F (1, 33) = 4.52, p = .04 and unfamiliar faces, F (1, 33) = 12.24, p = .001.

Conclusions:

These initial results demonstrate that children with ASD are attending to all stimuli less than TD children; however, information regarding which mechanism is contributing to diminished attention was not revealed from these analyses. Follow-up analyses will examine group by stimulus type interactions using several other dependent eye tracking variables. More specifically, rather than examining overall total dwell time, an adjusted estimate of attentional allocation will be calculated for each participant to take into account individual variation in total attention. The proportion of time spent looking at each quadrant or AOI as compared to total attention across each trial will allow for an examination of individualized patterns of attentional allocation.