Diagnosing Autism Spectrum Disorder in community settings using the development and well-being assessment: validation in a UK population-based twin sample

McEwen, F.S. and Stewart, C.S. and Colvert, E. and Woodhouse, E. and Curran, S. and Gillan, N. and Hallett, V. and Lietz, S. and Garnett, T. and Ronald, Angelica and Murphy, D.G.M. and Happé, F. and Bolton, P. (2016) Diagnosing Autism Spectrum Disorder in community settings using the development and well-being assessment: validation in a UK population-based twin sample. Journal of Child Psychology and Psychiatry 57 (2), pp. 161-170. ISSN 0021-9630.

Abstract

Background: Increasing numbers of people are being referred for assessment for autism spectrum disorder (ASD). The NICE (UK) and the American Academy of Pediatrics recommend gathering a developmental history using a tool that operationalises ICD/DSM criteria. However the best-established diagnostic interview instruments are time-consuming, costly and rarely used outside national specialist centres. What is needed is a brief, cost-effective measure validated in community settings. We tested the Development and Well-Being Assessment (DAWBA) for diagnosing ASD in a sample of children/adolescents representative of those presenting in community mental health settings. Methods: A general population sample of twins (TEDS) was screened and 276 adolescents were selected as at low (CAST score<12; n=164) or high risk for ASD (CAST score≥15 and/or parent reported that ASD suspected/previously diagnosed; n=112). Parents completed the ASD module of the DAWBA interview by telephone or online. Families were visited at home: the ADI-R and ADOS were completed to allow a best-estimate diagnosis of ASD to be made. Results: DAWBA ASD symptom scores correlated highly with ADI-R algorithm scores (rho=.82, p<.001). Good sensitivity (0.88) and specificity (0.85) were achieved using DAWBA computerised algorithms. Clinician review of responses to DAWBA questions minimally changed sensitivity (0.86) and specificity (0.87). Positive (0.82-0.95) and negative (0.90) predictive values were high. Eighty-six percent of children were correctly classified. Performance was improved by using it in conjunction with the ADOS. Conclusions: The DAWBA is a brief structured interview that showed good sensitivity and specificity in this general population sample. It requires little training, is easy to administer (online or by interview), and diagnosis is aided by an algorithm. It holds promise as a tool for assisting with assessment in community settings and may help services implement the recommendations made by NICE and the American Academy of Pediatrics regarding diagnosis of young people on the autism spectrum

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