Introduction: Autism Spectrum Disorder (ASD) is a behaviourally defined disorder characterised by impairments in three domains of social interaction, communication, and repetitive/restricted interests and behaviours (DSM-IV-TR; APA, 2000; ICD-10; WHO, 1992). Recent research suggests that this diagnostic triad may no longer fit as the best way to conceptualise ASD. Although not due for publication until 2013, a proposed revision of autistic disorder for DSM-V has merged three domains into two; i) Social/communication deficits and ii) Fixated interests and repetitive behaviours (APA, 2010). The aim of this study was to examine the structure of ASD symptom domains within the Adult Asperger Assessment (AAA; Baron-Cohen et al., 2005). Method: Confirmatory factor analysis was used to examine data from a clinical population of adults diagnosed with Asperger Syndrome (AS) and High Functioning Autism (HFA). Results: Analysis suggested that none of the theoretically-driven models were supported by the AAA data. However, it did highlight high correlations between social and communication factors (r > 0.9) within unmodified models. Discussion: The results of the analysis did not provide support for the move towards considering ASD as a dyad of ‘social-communication’ impairments and repetitive/restricted interests and behaviours, as none of the models were supported by the AAA data. The validity of the AAA as a diagnostic tool is discussed, as well as limitations and suggestions for future research. Conclusion: This study did not provide the evidence required to endorse a move towards the proposed DSM-V dyad. Further research to understanding the structure of autism symptoms could improve diagnostic and classification systems, and further studies of the genetic and neurobiological bases of ASD.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:586260 |
| Date | January 2012 |
| Creators | Kuenssberg, Renate Katherine Von |
| Contributors | Power, Michael; Morris, Paul |
| Publisher | University of Edinburgh |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1842/7916 |
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