How many girls are we missing in ASD? An examination from a clinic- and community-based sample. Issue 3 (3rd July 2019)

• Record Type: Journal Article
• Authors: Barnard-Brak, Lucy; Richman, David; Almekdash, M. Hasan
• Is Part Of: Advances in autism. Volume 5:Issue 3(2019)
• Page Start: 214
• Page End: 224
• Publication Date: 2019-07-03
• Subjects: Assessment -- Identification -- Autism spectrum disorder; Autism -- Periodicals; Autistic people -- Services for -- Periodicals; 362.19685882
• DOI: 10.1108/AIA-11-2018-0048
• Languages: English
• ISSNs: 2056-3876

Abstract

Abstract : Purpose: Research has indicated that males diagnosed with autism spectrum disorder (ASD) outnumber females diagnosed with ASD, which has been attributed to a number of potential biological and genetic risk factors. The purpose of this paper is to estimate how many girls may be missing from ASD via a two-study format, comparing two distinct data sets to Centers for Disease Control and Prevention population estimates for sex distribution of males vs females in ASD. Design/methodology/approach: In Study 1, the authors utilized data from the National Database for Autism Research as a clinic-based sample. In Study 2, the authors utilized data from the National Survey of Children's Health as a community-based sample. Findings: The current study estimates that approximately 39 percent more girls should be diagnosed with ASD. The authors estimate that the sex distribution in ASD should be approximately 28 percent female and 72 percent male based upon current practices. Thus, it appears that more females are being identified as potentially having ASD but were not subsequently being diagnosed with ASD as compared to their male counterparts. Originality/value: These results could suggest that a leaky pipeline in the assessment of girls with ASD may exist along one or more points in the ASD diagnostic process, with one potential point at the level of ASD-specific screening (i.e. the SCQ in Study 1) in the clinic setting and another in the community setting as a whole for universal screening (i.e. NSCH data in Study 2).