ABAS-II Ratings and Correlates of Adaptive Behavior in Children with HFASDs

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1 J Dev Phys Disabil (2012) 24: DOI /s ORIGINAL ARTICLE ABAS-II Ratings and Correlates of Adaptive Behavior in Children with HFASDs Christopher Lopata & Jeffery D. Fox & Marcus L. Thomeer & Rachael A. Smith & Martin A. Volker & Courtney M. Kessel & Christin A. McDonald & Gloria K. Lee Published online: 24 March 2012 # Springer Science+Business Media, LLC 2012 Abstract This study was conducted to extend the research on adaptive functioning of children, ages 7 12, with high-functioning autism spectrum disorders (HFASDs; n041) using the Adaptive Behavior Assessment System-II. Specific purposes included examination of (1) the ABAS-II adaptive profile; (2) relative strengths and weaknesses; and (3) predictors (age, IQ, and ASD symptomatology) of adaptive functioning for children with HFASDs. Results indicated significant deficits on overall adaptive functioning and all three adaptive composites. Relative weaknesses were found in the skill areas of social, home living, and self-direction and relative strengths in academics and community use. Analyses indicated that age and IQ did not predict ABAS-II composites, whereas total ASD symptoms negatively predicted overall adaptive functioning. Significant inverse correlations were found between the ASD symptoms of restricted and repetitive behaviors and the ABAS-II social and practical daily living skills composites. No significant correlations were found between ASD social symptoms and adaptive social skills or between ASD communication symptoms and adaptive language/communication skills. Keywords ABAS-II. Adaptive functioning. High-functioning ASDs Assessment of adaptive functioning is a necessary component of comprehensive evaluations for individuals with high-functioning autism spectrum disorders (HFASDs) as it provides information on the degree to which self-sufficiency and daily functioning are C. Lopata (*) : M. L. Thomeer : C. M. Kessel Institute for Autism Research, Canisius College, 2001 Main Street, Buffalo, NY 14208, USA lopatac@canisius.edu J. D. Fox Autistic Services Inc., 4444 Bryant Stratton Way, Williamsville, NY 14221, USA R. A. Smith : M. A. Volker : C. A. McDonald : G. K. Lee University at Buffalo, State University of New York, Buffalo, NY , USA

2 392 J Dev Phys Disabil (2012) 24: impaired (Klin et al. 2005). This information is imperative as it characterizes the individual s abilities (strengths and weaknesses in daily functioning), in contrast to ASD symptomatology which characterizes the diagnostic disability (Klin et al. 2007). For individuals with HFASDs, relative strengths in cognitive and language abilities are insufficient to overcome the adaptive deficits. The inability of these individuals to translate their relative strengths into adaptive functioning has been observed in longterm negative outcomes including social isolation, limited attainment and maintenance of employment, and prolonged financial and interpersonal dependence on family members (Portway and Johnson 2005; Shattuck et al. 2011). These findings strongly support the need for studies of adaptive functioning in individuals with HFASDs as adaptive skills and behaviors are necessary for self-sufficiency, independence, and social participation. While there have been few studies of adaptive functioning in HFASDs (Klin et al. 2007), the few that have been conducted have generally indicated significant deficits. In contrast to findings suggesting more parity between IQ and adaptive functioning in lower-functioning individuals with ASDs, those with HFASDs have exhibited adaptive functioning significantly below normative levels, comparison groups, and/or their cognitive level (e.g., Kanne et al. 2011; Klin et al. 2007; Perry et al. 2009). In studies of 7 18 year olds with HFASDs specifically, significant adaptive behavior deficits have been reported relative to the groups IQs and population means (generally> 1 to> 3 SD discrepant), with socialization most severely impaired (Klin et al. 2007; Saulnier and Klin 2007). In a similar study, Volker et al. (2010) found that the adaptive behaviors of 6 16 year olds with HFASDs fell significantly below normative expectations and the group s IQ level (> 1.5 SD discrepant). To better understand adaptive functioning of individuals with ASDs/HFASDs, researchers have examined its association with other features including age, cognitive ability/iq, and ASD symptomatology. While some have reported significant negative associations between age and adaptive behaviors and positive associations between cognitive ability and adaptive behaviors (Kanne et al. 2011; Klin et al. 2007; Liss et al. 2001; Perry et al. 2009; Saulnier and Klin 2007), others have failed to find these significant associations (e.g., Kenworthy et al. 2010). Results characterizing the relationship between ASD symptomatology and adaptive behaviors have also been mixed, with some reporting moderate-to-strong negative correlations (Liss et al. 2001; Perry et al. 2009) and others reporting non-significant or negligible associations (Kanne et al. 2011; Klin et al. 2007; Saulnier and Klin 2007). Some of the contradictory findings may be a result of different measures used to assess ASD symptomatology. For example, Kanne et al. (2011), Klin et al. (2007), and Saulnier and Klin (2007) used the ADOS to assess ASD symptoms whereas Liss et al. (2001) and Perry et al. (2009) used other ASD measures. Additionally, Klin et al. (2007) and Saulnier and Klin (2007) used samples comprised exclusively of individuals with HFASDs. Factors such as these may account for some of the discrepant findings across studies. According to Klin et al. (2007), the most commonly used and studied adaptive behavior measure for ASDs/HFASDs is the Vineland Adaptive Behavior Scales (VABS; Sparrow et al. 1984). What is known about adaptive functioning in this population has largely come from studies that have used the VABS. One recent exception was a study by Kenworthy et al. (2010) that assessed adaptive behaviors of year olds with HFASDs (n040) compared to matched controls (n030) using

3 J Dev Phys Disabil (2012) 24: the Adaptive Behavior Assessment System-Second Edition (ABAS-II; Harrison and Oakland 2003). Results indicated significant deficits for the HFASD group in overall adaptive behavior, as well as on the three composite scores (Social, Conceptual, and Practical) and all nine skill areas (i.e., subscales). The social skills subscale was most severely impaired and significantly more individuals with HFASDs exhibited a relative weakness in this area compared to controls. Composite scores for the HFASD group were generally 1.5 SD below the population mean and fell far below the group s IQ level (IQ M ). Age was not significantly related to adaptive behavior and IQ was only significantly correlated (positively) with one of the four composite scores (i.e., Conceptual). Significant negative correlations were found between ASD communication symptoms and all four adaptive composites and between ASD social symptoms and the overall adaptive composite and Social composite. While these significant negative correlations were consistent with Perry et al. (2009) and Liss et al. (2001), they differed from Klin et al. (2007) and Saulnier and Klin (2007) who similarly used samples of individuals with HFASDs. Kenworthy et al. (2010) concluded that the ABAS-II effectively documented adaptive deficits in this sample of year olds with HFASDs, yet identified the lack of children with HFASDs in the sample as a limitation. They also identified the need for additional studies of adaptive behaviors in individuals with HFASDs using the ABAS-II as the ABAS-II effectively captures the adaptive deficits associated with HFASDs and it can be done independently and quickly by parents. Study Rationale and Aims While preliminary findings have begun to document adaptive deficits among individuals with HFASDs, the adaptive performance of children with HFASDs is understudied and not well documented (Klin et al. 2007). Many of the existing studies have used heterogeneous samples comprised of individuals from a wide age range and/or from the broader ASD population. This has led some to recommend studies of adaptive behaviors in more narrowly defined (i.e., age and IQ) groups (Fenton et al. 2003). Studies of adaptive functioning in more narrowly defined groups are warranted as little is known about the adaptive behaviors of individuals with HFASDs of differing ages (Klin et al. 2007) and including individuals from a wide age range can obscure important age-related features (Stone et al. 1999). Additionally problematic is the fact that investigations into predictors and correlates of adaptive functioning in HFASDs have yielded mixed findings. Ongoing research involving factors associated with adaptive performance of children with HFASDs is needed as it may yield important information for intervention/treatment planning (Klin et al. 2007). Lastly, there is a need for adaptive behavior studies that utilize measures other than the VABS (Kenworthy et al. 2010) because the skills assessed by a specific measure can affect conclusions about adaptive functioning (Liss et al. 2001). This study was conducted to address specific limitations in the existing research. Specifically, this study examined the adaptive behaviors and predictors of adaptive behaviors of children with HFASDs using the ABAS-II. Specific aims of the study included (1) examination of the adaptive behaviors of a sample of children with HFASDs using the ABAS-II, (2) identification of relative strengths and weaknesses

4 394 J Dev Phys Disabil (2012) 24: in the ABAS-II skills areas, and (3) evaluation of predictors (age, IQ, and ASD symptomatology) of adaptive functioning for the sample. Results of the current review failed to identify any other studies that have examined the adaptive behaviors and correlates of adaptive behaviors of children with HFASDs using the ABAS-II. Method Participants At present, there is disagreement regarding whether the disorders that make up HFASDs are distinct or better characterized along a continuum (see Klin et al. 2005). Shared relative strengths in cognitive and language abilities, along with studies that have failed to find differences between the groups (e.g., Macintosh and Dissanayake 2006) have resulted in researchers including children with Asperger s, autism [high-functioning], and PDDNOS in their studies of HFASDs. Participants included 41 children, ages 7 to 12 years enrolled in two treatment studies for children with HFASDs (i.e., Asperger s, autism [high-functioning], or PDDNOS). As part of the screening for the treatment studies, children completed IQ testing and parents completed an autism diagnostic interview to confirm the children s diagnostic status. Among the inclusion criteria were a Wechsler Intelligence Scale for Children-4th Edition (WISC-IV; Wechsler 2003) short-form IQ>70 and a score meeting ASD criteria on the Autism Diagnostic Interview-Revised (ADI-R; Rutter et al. 2003). All testing to determine eligibility for the treatment trials was done by members of the research team. The sample for the current study was predominantly male (97.6 %) and Caucasian (90.2 %), with an average parent education of years. Average short-form IQ for the child participants was (for a detailed description of the sample, see Table 1). Instruments Wechsler Intelligence Scale for Children-4th Edition (WISC-IV) Cognitive ability was evaluated using a four-subtest short-form of the WISC-IV (Wechsler 2003) consisting of Block Design, Similarities, Vocabulary, and Matrix Reasoning subtests. Methods provided by Tellegen and Briggs (1967) were used to calculate short-form reliability and validity coefficients based on standardization information in the WISC-IV technical manual. The short-form composite yielded an internal consistency estimate of.95 and correlated.92 with the Full Scale IQ. Autism Diagnostic Interview-Revised (ADI-R) The ADI-R (Rutter et al. 2003) is a 93- item standardized diagnostic interview administered to a caregiver familiar with the developmental history and current behavior of the person being evaluated. The interview focuses on three domains (i.e., Reciprocal Social Interactions, Language/ Communication, and Restricted, Repetitive, and Stereotyped Behaviors and Interests). Item inter-rater reliability for a sample of 5 29 year olds was reportedly.80. Validity evidence indicates that the ADI-R effectively discriminates between ASD and non-asd samples (Rutter et al. 2003).

5 J Dev Phys Disabil (2012) 24: Table 1 Demographic characteristics of sample Characteristic Participants n041 WISC-IV Wechsler intelligence scale for children-4th edition; ADI-R autism diagnostic interview-revised; QARSI qualitative abnormalities in reciprocal social interactions; QAC qualitative abnormalities in communication; RRSB restricted, repetitive, and stereotyped patterns of behavior. Mean (SD) Age in Years 9.28 (1.60) Parent Education in Years (2.02) WISC-IV Short-Form Full Scale IQ (12.85) ADI-R QARSI (5.57) QAC (4.70) RRSB 6.37 (3.06) Total (10.31) n (% of total) Gender Male040 (97.6 %) Female01 (2.4 %) Ethnicity Caucasian037 (90.2 %) African-American01 (2.4 %) Asian-American02 (4.9 %) Other01 (2.4 %) Adaptive Behavior Assessment System-Second Edition (ABAS-II) Parent Form (Ages 5 21) The ABAS-II Parent Form (Ages 5 21; Harrison and Oakland 2003) is a comprehensive measure of adaptive functioning in the home and community. It consists of 232 items, each rated on a scale from 00Is Not Able to 30Always/Almost Always. The Parent Form (Ages 5 21) includes 10 skill areas (Communication, Community Use, Functional Academics, Home Living, Health and Safety, Leisure, Self-Care, Self-Direction, Social, and Work [Work is only for individuals 17]) which are combined to form three composites including Conceptual (CON; Communication, Functional Academics, Self-Direction), Social (SOC; Leisure, Social), and Practical (PRAC; Self-Care, Home Living, Community Use, and Health and Safety), as well as an overall General Adaptive Composite (GAC). Composite scores have a norm-referenced M0100 (SD015) and skill area scores have a norm-referenced M010 (SD03). Reported average internal consistency reliability estimates range from for composites and for skill area scales. For the 5 12 age range, corrected test-retest reliabilities were.87 for all skill area scores and composites. Validity is supported in age-difference sensitivities (i.e., increased scores for each skill area as age increases). Concurrent validity is supported in moderate-to-strong correlations with other measures of adaptive functioning (e.g., VABS). For additional psychometric details, see Harrison and Oakland (2003). Procedures The studies which generated these data were approved by the Institutional Review Board and conducted in accordance with the approved protocols. As noted, the

6 396 J Dev Phys Disabil (2012) 24: children were participants in two separate clinical trials and all met strict inclusion criteria. Included among the rating scales completed by parents at the beginning of treatment was the ABAS-II. Parent-completed forms were reviewed upon return for response errors (omitted items, items with multiple endorsements, etc.) and immediately corrected with parents. To ensure accuracy in scoring, ABAS-II protocols (and other protocols) were scored independently by two research assistants with advanced training in the measures, with any discrepancies resolved by a third scorer. Using a similar protocol, scores from the ABAS-II (and other measures) were entered into a database and independently checked by a second member of the research team, with discrepancies resolved by a third team member. Data Analysis Plan Several statistical procedures were used to analyze the data. Descriptive data are presented to characterize the ABAS-II adaptive profile of the sample, along with Bonferroni-corrected one-sample t-tests for the composite scores. As in Kenworthy et al. (2010), only the composites were analyzed to reduce the number of comparisons in this study. Relative strengths and weaknesses for the nine skill areas were examined by calculating the difference between each skill area s score and the mean area score (average score from the nine skill areas) for each participant according to the procedures in the ABAS-II manual. Each participant s difference score was then compared to the critical value provided in the manual for each area to determine whether that particular skill area was significantly discrepant (p<.05) from her/his skill area average score. This information was compiled to determine the percentage who demonstrated a significant discrepancy (i.e., relative strengths and weaknesses) for each of the nine skill areas. Multiple regression analyses and Pearson correlations were calculated to examine the relationship between age, IQ, and ASD symptoms and ABAS-II composites. Results ABAS-II Composites and Skill Areas Composites and skill area scale scores are presented in Table 2. Results of the Bonferroni-corrected one-sample t-tests were significant (p<.001) for the overall GAC and each of the three ABAS-II composites (CON, SOC, and PRAC). Examination of mean scores indicated significantly lower adaptive scores for the sample with HFASDs compared to normative expectations. While the effect size estimates (Cohen s d) were large for each of the composites (CON01.16; PRAC01.42; and GAC01.69; Cohen 1988), the SOC composite had the largest effect size reflecting the greatest degree of impairment (d01.81). Descriptively, average skill area scores were lowest for Social (> 2 SD), Home Living (nearly 2 SD), and Self Direction (> 1.5 SD) and in the average range for Functional Academics, Health and Safety, and Community Use. Relative strengths and weaknesses were further examined based on the total percentage of the sample who exhibited relative strengths and weakness for each skill area. As indicated in

7 J Dev Phys Disabil (2012) 24: Table 2 ABAS-II composite and skill area scores, and tests of significance and effect sizes for composite scores Composite/Skills Area Mean (SD) t-value (df) p-value Cohen s d Composite scores (M0100; SD015) Conceptual (12.07) (40) <.001* 1.16 Social (11.68) (40) <.001* 1.81 Practical (16.34) 8.35 (40) <.001* 1.42 General adaptive composite (12.85) (40) <.001* 1.69 Skills areas (M010; SD03) Communication 6.15 (2.61) Community use 7.22 (3.57) Functional academics 8.78 (2.52) Home living 4.20 (2.93) Health and safety 7.54 (2.88) Leisure 6.07 (2.43) Self-care 6.44 (3.05) Self-direction 5.07 (3.16) Social 3.27 (2.80) Sample n041 children with HFASDs for all comparisons. All p-values were based on two-tailed tests. Standards for Cohen s d: small00.20, medium00.50, and large00.80 (Cohen 1988). *p<.012 Bonferroni adjusted critical value for composites (.05/4) Fig. 1, the largest percentage of children exhibited significant relative deficits in Social (71 %), Home Living (54 %), and Self-Direction (34 %) and significant relative strengths in Functional Academics (59 %) and Community Use (42 %). Correlates of Adaptive Functioning Initially, four multiple regression models were conducted to determine whether age, IQ, and ADI-R Total predicted scores on each of the ABAS-II composites (Table 3). Age and IQ did not significantly predict any of the ABAS-II composites; however, the ADI-R Total significantly predicted the GAC and PRAC composites in the negative direction with standardized coefficients approximating.40 in both cases (ADI-R Total was not a significant predictor of the CON or SOC composites). To parallel the analyses by Kenworthy et al. (2010) and gain further insight into the association between specific ASD features and adaptive functioning, bivariate correlations were computed for the three ADI-R area scores and the three ABAS-II composites. As indicated in Table 4, all correlations between the ADI-R areas of Abnormalities in Social Interaction and Abnormalities in Communication and the three ABAS-II composites were negative and non-significant (p>.05). In contrast, the ADI-R area of Restricted and Repetitive Behaviors correlated significantly (negatively) with two of the three ABAS-II composites (SOC r0.329 and PRAC r0.360). The correlations for these significant scales were moderate. This pattern of correlations suggests

8 398 J Dev Phys Disabil (2012) 24: Fig. 1 Graphic display of relative strengths and weaknesses. COMM0Communication; CU0Community Use; FA0Functional Academics; HL0Home Living; HS0Health and Safety; LEI0Leisure; SC0Self-Care; SD0Self-Direction; SOC0Social that the significant relationship between the ADI-R Total score and ABAS-II GAC and PRAC composites found in the regression models can be explained by the Restricted, Repetitive, and Stereotyped Patterns of Behavior subscale of the ADI-R. Discussion As previously noted, there have been few studies documenting adaptive behaviors in HFASDs and studies of predictors/correlates of adaptive functioning in this population have yielded mixed results. Additionally, most of what is known has been determined using the VABS. One study was identified that examined the adaptive behaviors of adolescents and young adults with HFASDs using the ABAS-II (Kenworthy et al. 2010). Results of that study found the ABAS-II effectively documented the adaptive behavior deficits of the sample with HFASDs. No studies were identified, however that have examined the adaptive behaviors of children with HFASDs using the Table 3 Multiple regression results for ABAS-II composite scores and age, IQ, and ADI-R total scores Predictor CON SOC PRAC GAC Age IQ ADI-R Total *.394* R Coefficients are standardized. CON conceptual; SOC social; PRAC practical; GAC general adaptive composite; ADI-R autism diagnostic interview-revised. *p<.05

9 J Dev Phys Disabil (2012) 24: Table 4 Pearson correlations between ABAS-II composite scores and ADI-R area scores ADI-R Scale ABAS-II CON ABAS-II SOC ABAS-II PRAC QARSI QAC RRSB *.360* CON conceptual; SOC social; PRAC practical; ADI-R autism diagnostic interview-revised; QARSI qualitative abnormalities in reciprocal social interactions; QAC qualitative abnormalities in communication; RRSB restricted, repetitive, and stereotyped patterns of behavior. * p<.05 ABAS-II. This study was conducted to extend the research on adaptive behaviors in HFASDs by examining ABAS-II parent ratings and correlates of adaptive functioning for a sample of 7 12 year olds with HFASDs. Results indicated significant overall adaptive behavior deficits relative to normative expectations, as well as compared to the group s IQ (standard scores generally SD below normative expectations and/or their average IQ). While the adaptive composite ratings all reflected significant impairment, the deficit was greatest for the Social composite (social performance) which was predicted given the central role of social impairment in HFASDs (American Psychiatric Association 2000). The Conceptual composite was the highest composite which was also not surprising as it includes language and academic skills (areas often identified as relative strengths) among others. Composite scores from the present sample were largely similar to those reported by Kenworthy et al. (2010) for adolescents and young adults with HFASDs using the ABAS-II. The one exception was that the Social composite was clearly most impaired in the current sample, whereas the Social and Practical composites were similarly and most impaired in the Kenworthy et al. (2010) study. In both studies, the skill area of Functional Academics was rated the highest and Social was rated lowest. The consistency of these findings across the two different aged samples supports the proposition that individuals with HFASDs fail to translate their relative cognitive strength into adaptive performance (Klin and Volkmar 2000) and that the degree of social impairment (as measured by the ABAS-II) appears relatively stable from childhood into young adulthood. Since the pattern of stability in social impairment across these two studies was based on two different samples with HFASDs, additional longitudinal research is needed to determine if this pattern is observed for the same sample over time. The observed disparity between the group s IQ and ratings of adaptive functioning also parallels that reported in other studies of children and adolescents with HFASDs using the VABS (Klin et al. 2007; Saulnier and Klin 2007). Similar to that reported by Kenworthy et al. (2010), the current findings suggest that the ABAS-II accurately captures the adaptive deficits of individuals with HFASDs, especially the pathognomonic ASD feature of social impairment (p. 421). This study also found no significant association between adaptive functioning and age and IQ. While these findings are in contrast to other studies of HFASDs (e.g., Klin et al. 2007), they are largely similar to Kenworthy et al. (2010) who found no significant relationship between age and ABAS-II composites, and non-significant

10 400 J Dev Phys Disabil (2012) 24: correlations between IQ and three of the four ABAS-II composites. The findings are also partially consistent with Saulnier and Klin (2007) who found verbal and performance IQ was largely unrelated to adaptive behaviors (with the exception of VIQ and VABS Communication) for 7 18 year olds with Asperger s. Examination of the association between ASD symptoms and adaptive behaviors yielded some interesting findings. Higher levels of overall ASD symptoms were found to significantly predict lower levels of overall adaptive behavior. Further examination of specific areas of ASD symptoms found no significant relationship between ASD social symptoms and adaptive behaviors or between ASD communication symptoms and adaptive behaviors. Whereas these findings are in contrast to Kenworthy et al. (2010) who found several areas of ABAS-II adaptive behaviors were significantly (negatively) correlated with social and communication ASD symptoms (ADOS) in year olds with HFASDs, they are similar to Klin et al. (2007) and Saulnier and Klin (2007) who reported small and weak relationships between social and communication ASD symptoms (ADOS) and social and communicative adaptive behaviors (VABS). Some of the differences between the current findings and those of Kenworthy et al. (2010) may be a function of different measures used to assess ASD symptoms (Kenworthy et al. [2010] used the ADOS and the current study used the ADI-R). This can only be considered a partial explanation given the similarity between the current study findings and those of Klin et al. (2007) and Saulnier and Klin (2007) who also used the ADOS. Interestingly, in the current study higher levels of repetitive/stereotyped ASD behaviors were significantly associated with lower levels of social and practical (basic and instrumental daily living skills) adaptive behaviors. This was not found by Kenworthy et al. (2010) which may suggest that different ASD symptoms are implicated in adaptive functioning at different ages. More specifically, repetitive/ stereotyped behaviors may be more pronounced and disruptive to social and basic daily living skills for children with HFASDs, however social and communication ASD symptoms may be more predominant and disruptive to adaptive functioning for adolescents and young adults with HFASDs. The manner in which ASD symptoms negatively impact different areas of adaptive functioning cannot be determined based on the current findings however the differing associations observed between the current study and that of Kenworthy et al. (2010) suggest that age may be an important area of further study in HFASDs. Since Klin et al. (2007) and Saulnier and Klin (2007) did not report the association between repetitive/stereotyped ASD symptoms and adaptive functioning in their studies using the VABS, it is unknown the extent to which similar relations may or may not exist using the VABS with individuals with HFASDs. While this study had a number of strengths (e.g., well-characterized sample, IQ test scores, a narrowly-defined group with HFASDs, etc.) and extended the research on adaptive functioning in children with HFASDs, several limitations warrant mention. One limitation involved the lack of a control group. While normative comparisons were conducted, inclusion of a matched-control group in future studies will strengthen the conclusions. The sample was also comprised mainly of male children with HFASDs which restricts generalization. Future studies should target recruitment of a greater number of females with HFASDs. The use of the ADI-R as an ASD symptom measure expanded the research but made cross-study comparisons with

11 J Dev Phys Disabil (2012) 24: studies that used the ADOS somewhat tenuous. Ongoing research in this area should consider including both the ADI-R and ADOS as measures of ASD symptoms and examine whether similar relationships are observed between ASD symptoms and adaptive behaviors. Lastly, given the extensive use of the VABS/2 with ASDs, it is unclear how the current findings would compare to those using the VABS2 or other adaptive measures for the same sample of children with ASDs/HFASDs. Future studies are needed directly examining the comparability of the ABAS-II, VABS2, and other adaptive measures for HFASDs. Funding Acknowledgement A portion of the data in this study was collected as part of work supported by Department of Education, Institute of Education Sciences Grant R324A Findings and conclusions are those of the authors and do not necessarily reflect the views of the funding agency. References American Psychiatric Association (2000). Diagnostic and statistical manual of mental disorders (4th ed.), text revision. Washington, DC: Author. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum. Fenton, G., D Ardia, C., Valente, D., Vecchio, I. D., Fabrizi, A., & Bernabei, P. (2003). Vineland adaptive behavior profiles in children with autism and moderate to severe developmental delay. Autism, 7(3), Harrison, P. L., & Oakland, T. (2003). Adaptive behavior assessment system (2nd ed.). Los Angeles, CA: Western Psychological Services. Kanne, S. M., Gerber, A. J., Quirmbach, L. M., Sparrow, S. S., Cicchetti, D. V., & Saulnier, C. A. (2011). The role of adaptive behavior in autism spectrum disorders: Implications for functional outcome. Journal of Autism and Developmental Disorders, 41(8), doi: /s Kenworthy, L., Case, L., Harms, M. B., Martin, A., & Wallace, G. L. (2010). Adaptive behavior ratings correlate with symptomatology and IQ among individuals with high-functioning autism spectrum disorders. Journal of Autism and Developmental Disorders, 40, Klin, A., & Volkmar, F. R. (2000). Treatment and intervention guidelines for individuals with Aspergers syndrome. In A. Klin, F. R. Volkmar, & S. S. Sparrow (Eds.), Asperger syndrome (pp ). New York: Guilford. Klin, A., McPartland, J., & Volkmar, F. R. (2005). Asperger syndrome. In F. R. Volkmar, R. Paul, A. Klin, & D. Cohen (Eds.), Handbook of autism and pervasive developmental disorders: Vol 1. Diagnosis, development, neurobiology, and behavior (3rd ed., pp ). Hoboken, NJ: John Wiley & Sons. Klin, A., Saulnier, C. A., Sparrow, S. S., Cicchetti, D. V., Volkmar, F. R., & Lord, C. (2007). Social and communication abilities and disabilities in higher functioning individuals with autism spectrum disorders: The Vineland and the ADOS. Journal of Autism and Developmental Disorders, 37, Liss, M., Harel, B., Fein, D., Allen, D., Dunn, M., Feinstein, C., et al. (2001). Predictors and correlates of adaptive functioning in children with developmental disorders. Journal of Autism and Developmental Disorders, 31(2), Macintosh, K., & Dissanayake, C. (2006). Social skills and problem behaviors in school aged children with high-functioning autism and Asperger s disorder. Journal of Autism and Developmental Disorders, 36, Perry, A., Flanagan, H. E., Geier, J. D., & Freeman, N. L. (2009). Brief report: The Vineland Adaptive Behavior Scales in young children with autism spectrum disorders at different cognitive levels. Journal of Autism and Developmental Disorders, 39, Portway, S. M., & Johnson, B. (2005). Do you know I have Asperger s syndrome? Risks of a non-obvious disability. Health, Risk and Society, 7(1), Rutter, M., LeCouteur, A., & Lord, C. (2003). Autism diagnostic interview-revised. Los Angeles: Western Psychological Services.

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