Abstract
There is a gap in autism research from Low- and Middle-Income Countries (LMIC) where most children with autism live. This has contributed to a lack of culturally validated diagnostic instruments for autism and is a major barrier to early diagnosis, intervention, and research. The Arabic Language Autism Diagnostic Inventory (ALADIN) was developed based on the DSM-5 criteria and adapted to Arabic language and culture using primary source data. The aim of this study was to validate the Arabic Language Autism Diagnostic Inventory for the diagnostic evaluation of autism. A case-control study design was used to test the instrument for sensitivity and specificity for diagnosis of autism in children 2-5 years of age. Parents of 48 children with autism and 152 neurotypical children in Jordan completed the ALADIN. Demographic information from the participants in each group was summarized, and a Receiver Operating Curve (ROC) was fit to the data. A total score of 24 on the ALADIN had 77% sensitivity and 98% specificity for autism. The area under the curve (AUC) was 0.976, indicating strong performance in identifying children with autism. The ALADIN is the first instrument created specifically for Arab populations and is informed by cultural and linguistic data from the target population. Initial validation shows it has high diagnostic specificity for autism. Culturally informed instruments can improve access to early diagnosis and intervention and enhance autism research to improve care and outcomes in global populations.