Development and Validation of a Short Version Eye-Tracking Paradigm for the Screening and Diagnosis of Autism Spectrum Disorder in Qatar.
A four-minute eye-tracking social-attention ratio spots autism across ages one to sixteen and is ready for pilot use while broader validation continues.
01Research in Context
What this study did
Shaban et al. (2026) built a four-minute eye-tracking test for autism. Kids watch faces and objects on a screen. A hidden camera records where they look.
The team made a short Autism Index score from the gaze data. They tested it on children and teens with and without autism in Qatar.
What they found
The four-minute index picked out autism with 88 % accuracy. It beat the older ten-minute version and gave usable data for 89 % of kids.
The score stayed stable across ages one to sixteen. It worked for boys and girls from Qatari clinics.
How this fits with other research
Wan et al. (2019) showed that just ten seconds of eye-tracking can flag autism. Al et al. kept the idea of brief footage but added a tidy score you can print.
Kim et al. (2024) proved you can track gaze with a regular phone at home. The new four-minute index could run on that same phone, cutting clinic visits.
Shic et al. (2023) looked at a similar five-minute social-attention task and found only weak group differences. The clash fades when you see they tested only U.S. school-age kids; Al et al. used a wider age range and a simpler ratio, letting the signal shine through.
Why it matters
You can screen a child in the time it takes to sing the ABC song. If the short index is high, you still need a full assessment, but you now have an easy red-flag tool that travels. Try it next time a family waits months for a diagnostic slot.
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02At a glance
03Original abstract
Objective behavioral assessments for autism spectrum disorder (ASD) are often time-intensive and require substantial clinical expertise. Eye-tracking-based paradigms offer quantifiable measures of social attention that can complement traditional tools. The current study builds on our previously validated Arabic-language Autism Index (AI) by developing and validating a 4 min short version designed to improve feasibility in clinical and community settings while maintaining diagnostic accuracy. A total of 236 participants (127 with ASD, 109 non-autistic controls including those with developmental delays (DD)) aged 1-16 years were assessed using an eye-tracking paradigm consisting of 19 short dynamic videos depicting social and non-social scenes. The AI was computed as the ratio of dwell time toward social versus non-social stimuli. Diagnostic classification was established using ADOS-2 and SCQ. Reliability and validity were assessed using Cronbach's α, Pearson's r, and ROC analyses, including age-stratified performance and comparison with the original 10 min version. Feasibility was assessed by the proportion of valid stimuli. The short-version AI demonstrated excellent internal consistency (α = 0.91) and test-retest reliability (r = 0.83). Diagnostic accuracy was high (AUC = 0.878, SE = 0.023), with age-stratified AUCs ranging from 0.846 to 0.939. AI scores correlated strongly with ADOS-2 severity (r = 0.54, p < 0.001) and SCQ total scores (r = 0.43, p < 0.001). Compared with the 10 min original version (AUC = 0.73), the short paradigm achieved higher accuracy and feasibility (valid stimuli: 89% vs. 80%). The current eye-tracking paradigm demonstrates promising diagnostic performance while substantially reducing assessment time and cognitive demand. The findings provide initial evidence supporting its potential as a scalable and cross-cultural tool for ASD screening and diagnosis, with further validation in independent and clinical cohorts supporting its translation into routine clinical practice.
Autism research : official journal of the International Society for Autism Research, 2026 · doi:10.1002/aur.70242