ABAS-II Adaptive Profiles and Correlates in Samples of Children with HFASD or LFASD

Friday, May 13, 2016: 5:30 PM-7:00 PM
Hall A (Baltimore Convention Center)
C. A. McDonald1, B. C. Nasca2, C. Lopata1, J. P. Donnelly1, M. L. Thomeer1 and J. D. Rodgers1, (1)Institute for Autism Research, Canisius College, Buffalo, NY, (2)Counseling, School, And Educational Psychology, SUNY at Buffalo, Buffalo, NY
Background:  There have been few studies that have used the ABAS-II to document adaptive profiles in homogeneous samples of high-functioning children with autism spectrum disorder (HFASD) and children with ASD and co-occurring intellectual disability (LFASD).  Further, prior studies of predictors of adaptive functioning using either the VABS or ABAS-II have yielded mixed results (Lopata et al., 2012; McDonald et al., 2014).  

Objectives:  This study (a) examined the ABAS-II adaptive profile within each sample, (b) compared adaptive functioning and cognitive ability, and (c) assessed predictors (i.e., age, IQ) of adaptive skills. 

Methods:  Participants included 110 children (i.e., 55 with HFASD and 55 with LFASD), ages 6 to 12 years.  The LFASD sample was recruited from a center-based school serving students with ASD and co-occurring cognitive and language deficits.  Inclusion criteria included an independent diagnosis of an ASD and/or educational classification of autism and estimated IQ < 70. The second sample consisted of 55 children with HFASD recruited from prior clinical trials with an independent diagnosis of ASD and WISC-IV short-form IQ ≥ 85.  The dependent measure used was the parent rating form of the Adaptive Behavior Assessment System - Second Edition (ABAS-II).

Results:  Examination of the adaptive profile for the HFASD sample indicated a relative strength in the Conceptual domain (CON), followed by Practical (PRAC), and lastly Social (SOC) domains. Comparisons of cognitive and adaptive abilities within the sample indicated significantly lower scores on the GAC, t(54) = 12.50, p <.001, d = 2.49,  and all of the adaptive domains [CON, t(54) = 10.48, p <.001, d = 1.93;  PRAC, t(54) = 9.64, p <.001, d = 1.95; SOC t(54) = 13.75, p <.001, d = 2.78].  The majority of correlations between adaptive ability and cognitive ability and age were nonsignificant, with the exception of the relationship between age and SOC (r = -.27, p < .05), which was negative and significant.  For the LFASD sample, no significant difference was found between cognitive ability and overall adaptive performance, GAC, t(54) = 1.83, p = .073, d = 0.08, or PRAC t(54) = .54, p = .593, d = -1.00.  However, this sample performed significantly higher than expected on CON, t(54) = -2.91, p < .005, d = -1.17, and SOC, t(54) = -6.35, p <.001, d = -1.33, given their estimated cognitive ability.  All correlations between age and adaptive abilities were nonsignificant (p > .05), while relationships between estimated cognitive ability and all adaptive areas for the LFASD sample were positive and significant (p < .01), with rs ranging from .35-.46. 

Conclusions:  The measurement of adaptive behavior is important both in diagnostic and psychological assessment.  While individuals with LFASD displayed a relative strength in adaptive behavior in comparison to their estimated cognitive ability, individuals with HFASD displayed an overall cognitive strength with relative adaptive deficits.  Results highlighted a need for intervention in the area of adaptive skills for children with ASDs, especially in the area of social skills for those with HFASD.