Asperger Syndrome in Adults: Evidence for the Validity of Contemporary Screens

1. Asperger Syndrome in Adults: Evidence for the Validity of Contemporary Screens Brenda M. Stoesz1, Janine M. Montgomery1, Kevin P. Stoddart2,3, Lillian Burke3, & Mark Stokes4 1Social Cognition Lab, Department of Psychology, University of Manitoba; 2University of Toronto; 3The Redpath Centre; 4Deakin University Background Preliminary Results Knowledge of Asperger Syndrome (AS) in children has increased substantially in recent years; yet, information on diagnosis in adults is limited. Adult assessment may be difficult for various reasons: early developmental history may be unobtainable; comorbid conditions may be present; and/or experienced and knowledgeable clinicians may be unavailable. Tests to assist in diagnosing adult AS exist, but they have limitations: many tests were created for use with children; information on reliability and validity of test scores are often unavailable; and test developers do not always obtain independent confirmation that their participants actually have AS. Thus, the usefulness of tests for identifying AS in adults remains questionable and may result in inaccurate diagnoses1. Because sample sizes were small for the HFA and ADHD groups, we collapsed the AS and HFA groups and the TD and ADHD groups. The two groups were comparable in terms of age and IQ. In this preliminary report, we describe the results of the KADI, GADS, AQ, EQ, ASDI, and the RAADS-R. Due to time restraints the AAA interview was not administered. In Table 1, we provide evidence for the validity of each measure in the form of Sensitivity (Se), Specificity (Sp), and Overall Correct Classification. Table 1. Sensitivity, Specificity, and Overall Correct Classification. Table 2. Means (SD) of test scores, comparisons between AS/HFA group scores and TD/ADHD group scores using independent samples t-tests (2-tailed). *p < .05, **p < .01 , ***p < .001 An exploratory hierarchical discriminant function analysis was undertaken on diagnosis (TD vs. AS) over the predictors of AQ, EQ, ASDI, GADS, KADI, and RAADS-R. Statistical significance criteria for F were set to allow variables to enter (p < 0.05) or be removed (p > 0.10) from the model. Prior probabilities were computed from group sizes, and the covariance matrix was based upon separate groups. Covariance matrices were assessed for equality by Box’s M (1.82), which was not significant (F(1,438.724) = 1.68, p = 0.19). The model resolved at three steps, with the canonical covariate significantly accounting for 96.2% of variance (λ = 25.91; Wilk’sλ = 0.04, 2(3) = 37.87, p < 0.001; functions at group centroids: TD = 3.87, AS = 5.80). Canonical discriminant function coefficients reveal that ASDI, followed by GADS, and then by RAADS-R contributed most to the model (see Table 3). This model resulted in a classification table with perfect agreement between predicted and observed. When the model was replicated using a within groups covariance matrix, the cross validation (leave-one-out method) table was obtained, also resulting in 100% agreement between predicted and observed cases. Table 3. Canonical discriminant function coefficients, Structure coefficients, Tolerance at step 3, and Unstandardized function coefficients for each group for each of the three retained variables. Objectives Given the above, the goals for our current study were to augment the existing information for several tests of adult AS to determine: how well these instruments discriminate between groups of people with ASD (discriminant validity); if the instruments are strongly related to other tests for AS/ASDs (convergent validity); and if the instruments differ from tests of other conditions (divergent validity). Further, we examined the accuracy of AS diagnoses when instruments are used individually or in combination. Discussion Findings are preliminary and must be interpreted with caution given the small sample sizes for some of the groups and measures, however, they do suggest that some instruments (i.e., GADS, RAADS-R) are better at correctly identifying and discriminating amongst subgroups and that combining selected instruments (i.e., GADS, ASDI, and RAADS-R) improves classification rates. As such, data collection in our laboratory is ongoing to determine whether these findings will be observed in a larger sample. Method In a pilot study, we recruited adults (aged 18+ years; n = 12) with AS and controls in each of three groups: high functioning autism (HFA; n = 2), attention deficit hyperactivity disorder (ADHD; n = 5), and typically developing (TD; n = 228). These groups were chosen to evaluate the sensitivity of existing measures for discriminating between similar (HFA), overlapping (ADHD), and distinct (typically developing) groups. All clinical participants were diagnosed by a clinician prior to their participation and had a verbal IQ ≥ 85. Participants completed various AS assessment instruments: Krug Asperger Disorder Index (KADI)2; Gilliam Asperger’s Disorder Scale (GADS)3; The Autism Quotient (AQ)4 and the Empathy Quotient (EQ)5 from the Adult Asperger Assessment (AAA)6; Asperger Syndrome Diagnostic Interview (ASDI)7; and Ritvo Autism Asperger Diagnostic Scale- Revised (RAADS-R)8]; and other tests included to measure convergent and divergent validity. Conclusions Families and individuals affected by a late diagnosis of AS experience frustrations and difficulties. Many clinicians feel inadequately prepared to assess adults on the spectrum, as resources for late diagnosis are limited. Thus, it is essential that clinicians feel competent to address the unique diagnostic needs of adults suspected of having AS. The results from our study provide a step towards improving this situation at a clinical level, and we anticipate that this will likewise positively impact individuals and families by enabling accurate diagnosis and, thus, access to appropriate supports and treatment. Our findings are essential to informing understanding of AS in adults and improving clinical assessment and diagnosis of AS. • References: 1Stoesz et al. (2011). The Clinical Neuropsychologist, 25, 376-401. 2 Krug & Arick (2003). Krug’s Asperger’s Disorder Index: Examiner’s manual. Austin, TX: Pro-Ed. 3 Gilliam (2003). Gilliam Asperger’s Disorder Scale: Examiner’s manual. Austin, TX: Pro-Ed. 4 Baron-Cohen et al. (2001). . JADD, 31, 5-17. 5 Baron-Cohen & Wheelwright (2004). JADD, 34, 163-175. 6 Baron-Cohen et al. (2005). JADD, 35, 807-819. 7Gillberg et al (2001). Autism, 5, 57-66. 8Ritvo et al. (2011). JADD, 41, 1076-1089. Acknowledgments: This research was supported by two University of Manitoba grants: (1) Kick-Start: A Program to Support Research and Collaboration in Psychology; and (2) the University Research Grants Program. We thank the individuals and their families for their participation in this research. We thank the members of the Social Cognition Laboratory – Kelly Carpick, Katelin Neufeld, Stephany Huynh, Brigitte Jeanson, Daniel Buchman, Melanie Caister, Haidee Baker, Deepak Singh, Leah Funk, and Erica Holiday -- for their help with data collection. Correspondence: umstoes3@cc.umanitoba.ca or montgom0@ad.umanitoba.ca