20344
Early Social Communication Predictors of Clinical Diagnosis from 18 to 24 Months

Thursday, May 14, 2015: 5:30 PM-7:00 PM
Imperial Ballroom (Grand America Hotel)
T. N. Day1, W. Guthrie1, C. Schatschneider2 and A. M. Wetherby1, (1)Florida State University Autism Institute, Tallahassee, FL, (2)Florida State University, Tallahassee, FL
Background: Social communication deficits are often the first noticeable ‘red flags’ of autism spectrum disorder (ASD), as typically developing (TD) children demonstrate robust intentional modes of social communication (i.e., to engage another person in their requesting and expressing interest) by one year of age. Previous studies have identified differences in social communication in children with ASD (Chawarska et al., 2014; Clifford et al., 2007; Wetherby et al., 2007), but some of these studies have not had the power to detect potential differences between children with ASD and developmental delay (DD). Given the average age of diagnosis at 4-5 years (CDC, 2014), it is important to identify early indicators that can reliably differentiate TD, DD, and ASD. Since communication delays are usually present by the second year of life and may be more readily identified by parents and professionals than other red flags (e.g., repetitive behaviors), these social communication skills represent an important measure for early screening.

Objectives: (1) Examine differences in social communication at 18-24 months between children diagnosed with ASD, DD, and TD and (2) Identify significant predictors of diagnosis of ASD compared to DD or TD.

Methods: Children participated in the FIRST WORDS® Project at Florida State University and were administered the Communication and Symbolic Behavior Scales (CSBS; Wetherby & Prizant, 2002) Behavior Sample between 18-24 months. They also received a concurrent diagnostic battery to determine best-estimate diagnosis of ASD (n=275), DD (n=93), or TD (n=99).

Results: An ANCOVA, controlling for age and nonverbal skills, revealed that the ASD group had lower CSBS Cluster scores, which measure seven distinct dimensions of social communication, than the TD group (p<.001). All Cluster scores were significantly lower in ASD than DD (p<.05), except for Word Use. Logistic regressions examined z-scored CSBS Clusters to identify significant predictors of clinical diagnosis. In comparing ASD and TD, four significant predictors emerged (p<.05): Emotion & Eye Gaze (odds ratio [OR]=.30), Gestures (OR=.38), Sounds (OR=.40), and Understanding (OR=.57). Overall, 88% of children were accurately classified as either ASD or TD (sensitivity: 93%, specificity: 77%). In the model comparing ASD and DD, Emotion & Eye Gaze (OR=.32) and Gestures (OR=.55) were significant predictors (p<.05) of clinical diagnosis. In total, 80% of the children were accurately classified as either ASD or DD (sensitivity: 92%, specificity: 53%).

Conclusions: Results indicate that social communication deficits measured by the CSBS discriminate children with ASD from both DD and TD. Four of the seven clusters differentiated ASD from TD, resulting in 88% correct classification. Impressively, just two clusters (Emotion & Eye Gaze and Gestures) resulted in 80% correct classification of ASD and DD. This suggests that screening should focus on gaze, facial expressions, and gestures to most efficiently identify children with ASD. Given the high sensitivity rates found, the CSBS may serve as a useful ASD screening tool to identify children in need of ASD-specific testing. Higher specificity in the TD than DD analyses suggests that many “false positives for ASD” may indicate non-ASD delays requiring intervention services.