Abstract
IntroductionGendered differences in autism spectrum disorder (hereafter, ‘autism’) symptomatology, may contribute to delayed diagnoses for autistic females. The aim of this study was to develop a coding system, the Gendered Autism Behavioral Scale (GABS), to identify and measure hypothesized components of non-traditional autism phenotypes. MethodsTwo independent cohorts of autistic individuals completed modules 3 and 4 of the Autism Diagnostic Observation Schedule (ADOS, 2nd edition). Video-recorded ADOS administrations were coded using the GABS, and separate coding teams analyzed each cohort. Cohort 1 from the United Kingdom consisted of 22 males and 22 females, aged 9–15 years. Cohort 2 from the United States consisted of 40 males and 20 females, aged 4–59 years. ResultsThe coders achieved acceptable inter-rater reliability both within and across coding teams. In exploratory analyses, gender differences between codes were assessed within cohorts. Within Cohort 1, there were significant gender differences, of a moderate size, on several individual items as well as the Managing Emotions subscale and the Total GABS score. Within Cohort 2, significant gender differences were found for two individual items. ConclusionsThis study demonstrated the feasibility of the GABS across different sites. Validity tests resulted in partial replication of gender differences on the GABS. Preliminary evidence from the GABS suggests that valuable data on hypothesized non-traditional autism phenotypes could be extracted from widely employed assessments such as the ADOS. Future work could capitalize on the GABS’ utility for secondary data analysis to study gender differences in ASD in larger, adequately powered samples.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: 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.