Assessing Autism Knowledge Across the Global Landscape Using the ASK-Q.

Substantial variability exists with regard to autism service provision around the world. Service disparities observed in many low- and middle-income countries may be driven, in part, by limited autism knowledge; however, measurement limitations have made it difficult to quantify autism knowledge across countries. The current study uses the autism stigma and knowledge questionnaire (ASK-Q) to quantify autism knowledge and stigma between different countries and demographics. The current study compiled data from 6830 participants collected using adapted versions of the ASK-Q administered in 13 different countries, representing four different continents. Structural equation modeling was used to examine how autism knowledge varied across country and individual factors. Results reveal cross country variability with a large, 17-point difference between the countries with the highest knowledge (Canada) and the lowest knowledge (Lebanon). As expected, countries with higher economies had higher levels of knowledge. We also documented differences based on country worldview, participant occupation, gender, age, and education level. These results help to identify specific regions and populations that might most need greater information about autism.

Development and Psychometric Evaluation of the Autism Stigma and Knowledge Questionnaire (ASK-Q).

ASD knowledge deficits contribute to disparities in the timing and quality of ASD services. To address the limitations with existing measures of ASD knowledge, we developed and examined the Autism Stigma and Knowledge Questionnaire (ASK-Q), which comprehensively assesses multiple subdomains of ASD knowledge while maintaining strong psychometric support and cross-cultural utility. ASK-Q items derived from the published research are organized into four subscales: (i) diagnosis, (ii) etiology, (iii) treatment, and (iv) stigma. ASK-Q items were selected based on ratings of face, construct, and cross-cultural validity by a group of 16 international researchers. Using Diagnostic Classification Modeling we confirmed the proposed factor structure and evaluated the statistical validity of each item among a lay sample of 617 participants.