Abstract
Many adults with autism spectrum disorder (ASD) remain undiagnosed. Specialist assessment clinics enable the detection of these cases, but such services are often overstretched. It has been proposed that unnecessary referrals to these services could be reduced by prioritizing individuals who score highly on the Autism-Spectrum Quotient (AQ), a self-report questionnaire measure of autistic traits. However, the ability of the AQ to predict who will go on to receive a diagnosis of ASD in adults is unclear. We studied 476 adults, seen consecutively at a national ASD diagnostic referral service for suspected ASD. We tested AQ scores as predictors of ASD diagnosis made by expert clinicians according to International Classification of Diseases (ICD)-10 criteria, informed by the Autism Diagnostic Observation Schedule-Generic (ADOS-G) and Autism Diagnostic Interview-Revised (ADI-R) assessments. Of the participants, 73% received a clinical diagnosis of ASD. Self-report AQ scores did not significantly predict receipt of a diagnosis. While AQ scores provided high sensitivity of 0.77 [95% confidence interval (CI) 0.72-0.82] and positive predictive value of 0.76 (95% CI 0.70-0.80), the specificity of 0.29 (95% CI 0.20-0.38) and negative predictive value of 0.36 (95% CI 0.22-0.40) were low. Thus, 64% of those who scored below the AQ cut-off were 'false negatives' who did in fact have ASD. Co-morbidity data revealed that generalized anxiety disorder may 'mimic' ASD and inflate AQ scores, leading to false positives. The AQ's utility for screening referrals was limited in this sample. Recommendations supporting the AQ's role in the assessment of adult ASD, e.g. UK NICE guidelines, may need to be reconsidered.
Highlights
Autism spectrum disorders (ASD) are a family of lifelong neurodevelopmental syndromes with a prevalence of at least 1% (Baird et al 2006; Baron-Cohen et al 2009; Brugha et al 2011a; DevelopmentalDisabilities Monitoring Network Surveillance Year 2010 Principal Investigators, 2014)
In order to address the question of whether Autism-Spectrum Quotient (AQ) scores are predictive of the severity of autism spectrum disorder (ASD) symptoms as continuous variables, we examined Pearson productmoment correlations between AQ scores and total scores on the Autism Diagnostic Observation Schedule-Generic (ADOS-G) and the Autism Diagnostic Interview-Revised (ADI-R)
ADI-R totals were correlated with the selfreport AQ10 (r = 0.12, p = 0.045) and the AQ50 (r = 0.13, p = 0.030), albeit weakly. These results show that self-reported ASD traits, measured using the AQ, are not correlated with clinician-rated current ASD behaviours (ADOS-G), but are weakly associated with retrospectively reported early-life ASD symptoms (ADI-R)
Summary
Autism spectrum disorders (ASD) are a family of lifelong neurodevelopmental syndromes with a prevalence of at least 1% (Baird et al 2006; Baron-Cohen et al 2009; Brugha et al 2011a; DevelopmentalDisabilities Monitoring Network Surveillance Year 2010 Principal Investigators, 2014). And accurate diagnosis of ASD is crucial to enable affected individuals to receive treatment and support (Koegel et al 2014). Undiagnosed ASD is increasingly recognized as a significant problem in general adult psychiatry, and as an important differential diagnosis in this setting Many adults with autism spectrum disorder (ASD) remain undiagnosed. The ability of the AQ to predict who will go on to receive a diagnosis of ASD in adults is unclear
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
