Social attention abnormalities are a hallmark of Autism Spectrum Disorder (ASD), often characterized by atypical gaze patterns. This report showed the real-world feasibility of an eye-tracking–based screening paradigm for ASD across diverse general population samples. A total of 536 adults participated in public demonstrations. An Autism Index (AI), derived from a previously validated eye-tracking paradigm, was calculated from gaze patterns toward social and nonsocial stimuli. Participants were stratified into typically developing (TD), neurodivergent, and ASD groups based on validated AI cut-offs. Median AI scores differed significantly across groups − 0.31 (TD), 0.53 (neurodivergent), and 0.69 (ASD)- with post-hoc tests confirming higher scores in the ASD and neurodivergent groups versus TD. Gender-based analyses showed that males had significantly higher AI scores than females ( p = 0.028). Among those classified as ASD, 95% reported a formal diagnosis, supporting the validity of the tool. Receiver operating characteristic (ROC) analysis demonstrated excellent diagnostic performance, with an area under the curve (AUC) of 0.997. At the optimal cut-off score of 0.555, the tool achieved 100% sensitivity and 99.4% specificity. This report highlights the feasibility and accuracy of the eye-tracking paradigm as a scalable and objective screening tool for ASD in general adult populations, supporting its potential for broader clinical implementation. Not applicable.
Shaban et al. (Fri,) studied this question.