A cross-cultural study of autistic traits across India, Japan and the UK.

Abstract:

BACKGROUND: There is a global need for brief screening instruments that can identify key indicators for autism to support frontline professionals in their referral decision-making. Although a universal set of conditions, there may be subtle differences in expression, identification and reporting of autistic traits across cultures. In order to assess the potential for any measure for cross-cultural screening use, it is important to understand the relative performance of such measures in different cultures. Our study aimed to identify the items on the Autism Spectrum Quotient (AQ)-Child that are most predictive of an autism diagnosis among children aged 4-9 years across samples from India, Japan and the UK. METHODS: We analysed parent-reported AQ-Child data from India (73 children with an autism diagnosis and 81 neurotypical children), Japan (116 children with autism and 190 neurotypical children) and the UK (488 children with autism and 532 neurotypical children). None of the children had a reported existing diagnosis of intellectual disability. Discrimination indices (DI) and positive predictive values (PPV) were used to identify the most predictive items in each country. RESULTS: Sixteen items in the Indian sample, 15 items in the Japanese sample and 28 items in the UK sample demonstrated excellent discriminatory power (DI ≥ 0.5 and PPV ≥ 0.7), suggesting these items represent the strongest indicators for predicting an autism diagnosis within these countries. Across cultures, good performing items were largely overlapping, with five key indicator items appearing across all three countries (can easily keep track of several different people's conversations, enjoys social chit-chat, knows how to tell if someone listening to him/her is getting bored, good at social chit-chat, finds it difficult to work out people's intentions). Four items indicated potential cultural differences. One item was highly discriminative in Japan but poorly discriminative (DI