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Validation of a CBCL/6-18 ASD-Scale: Differentiation of Youths with ASD from Comparison Groups

Poster Presentation
Saturday, May 4, 2019: 11:30 AM-1:30 PM
Room: 710 (Palais des congres de Montreal)
K. S. Ellison, P. J. Castagna and T. E. Davis, Department of Psychology, Louisiana State University, Baton Rouge, LA
Background: Broadband measures have been used to identify youth at risk for Autism Spectrum Disorder (ASD), including the Childhood Behavior Checklist/6-18 (CBCL/6-18). Only one study has created a 9-item ASD-scale utilizing items from CBCL/6-18 to differentiate children with ASD from comparison groups (Ooi et al., 2010). However, its validity has not been examined

Objectives: This study investigated differences among children with ASD, Social Anxiety Disorder (SAD), Specific Phobia (SP), and those having no diagnoses (NODX) on the eight CBCL/6-18 syndrome scales. The 9-item ASD-scale was examined to determine its ability to differentiate the ASD group from the other groups.

Methods: Nine youths with ASD (8 male; M=9.66 years-old), 9 with SAD (4 male; M=10.22 years-old), 9 with SP (5 male; M=9.22 years-old), and 9 with NODX (7 male; M=12.78 years-old) were included as part of a larger IRB-approved study. Diagnoses were confirmed by the Childhood Autism Rating Scale, Second Edition (CARS-2) and the Anxiety Disorders Interview Schedule (ADIS-IV-C/P). Full-Scale IQ was measured using the WISC-V (ASD M=94.00, SD=13.83; SAD M=99.67, SD=10.61; SP M=101.67, SD=7.97; NODX M=103.44, SD=8.03). The CBCL/6-18 was completed by the primary caretaker. Consent/assent was obtained.

Results: A one-way MANOVA was run to determine the effect of diagnosis on the eight CBCL/6-18 syndrome scales. The differences between diagnosis on the combined dependent variables was significant, F(24, 73)=2.05, p=.01; Wilks' Λ=.23. Follow-up univariate ANOVAs showed that Anxious/Depressed (F(3, 32)=3.30, p=.03), Social Problems (F(3, 32)=5.82, p<.001), and Aggressive Behavior (F(3, 32)=6.17, p<.001), scales were statistically significantly different between groups. Games-Howell post-hoc tests showed that the ASD group had significantly higher mean scores on Anxious/Depressed (p=.04), Social Problems (p=.03) and Aggressive Behavior (p=.03) than the NODX group and higher Social Problems (p=.04) than the SAD group. Cronbach’s alpha was computed for the ASD-scale, for each group separately and the full sample. Surprisingly, ASD group had poor internal consistency (.43); when one item was removed (#66. Repeats acts over and over) it improved to .61. Acceptable internal consistency was found for the SP (.91), NODX (.77) groups and the full sample (.79). Three logistic regressions were used to test the ability of the ASD-scale to differentiate the ASD group from the comparison groups. All logistic regression analyses yielded significant results (p<.05), with variance accounted for by the ASD-scale ranging from 28.3% (ASD vs. SP) to 84% (ASD vs. NODX). Overall prediction success rates at 83.3% (sensitivity 88.9%, specificity 77.8%) for the ASD vs. SAD and SP groups, and an overall predication success rate of 88.9% for ASD vs. NODX.

Conclusions: The CBCL/6-18 may be used in differentiating children with ASD from those with other disorders. High scores on the ASD-scale identified the majority of children in the ASD group, especially compared to the SAD and SP groups; low scores identified the majority of children being contrasted with the ASD group. Future research should address the limitations of the current study specifically, the small sample size, in order to determine if the internal consistency and predictive utility of the scale can be improved.