Comparison of three different eye-tracking tasks for distinguishing autistic from typically developing children and autistic symptom severity.
A half-minute eye-tracking clip of dancing kids spots autism better than two other social-gaze tests in Chinese toddlers.
01Research in Context
What this study did
Researchers tested 2- to young learners Chinese kids. Half had autism. Half were typical.
Each child watched three 30-second videos on an eye-tracker. One showed kids dancing. One showed moving shapes. One showed a face talking.
The team measured where the kids looked. They wanted to know which video best spotted autism.
What they found
The dancing-kids video won. It told autism from typical better than the other two clips.
Kids with autism looked less at the dancers' faces and bodies. Their scores on this task matched their ADOS social scores.
The test took only half a minute and needed no language.
How this fits with other research
Goodwin et al. (2012) said we should screen all toddlers at 18 and 24 months. Juan et al. now give us a faster tool to do that job.
Cao et al. (2023) found that moms with less school have kids with higher autism odds. The new eye test could help reach those low-SES families who often miss clinic visits.
Sinai-Gavrilov et al. (2024) showed parent coaching ESDM works for Chinese toddlers. Quick eye-tracking could spot kids early so they can start that program sooner.
Why it matters
You can add this 30-second eye test to your intake. No extra staff. No extra time. It flags social attention gaps right away. Use it to fast-track kids into early services like ESDM parent coaching.
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02At a glance
03Original abstract
Altered patterns of visual social attention preference detected using eye-tracking and a variety of different paradigms are increasingly proposed as sensitive biomarkers for autism spectrum disorder. However, few eye-tracking studies have compared the relative efficacy of different paradigms to discriminate between autistic compared with typically developing children and their sensitivity to specific symptoms. To target this issue, the current study used three common eye-tracking protocols contrasting social versus nonsocial stimuli in young (2-7 years old) Chinese autistic (n = 35) and typically developing (n = 34) children matched for age and gender. Protocols included dancing people versus dynamic geometrical images, biological motion (dynamic light point walking human or cat) versus nonbiological motion (scrambled controls), and child playing with toy versus toy alone. Although all three paradigms differentiated autistic and typically developing children, the dancing people versus dynamic geometry pattern paradigm was the most effective, with autistic children showing marked reductions in visual preference for dancing people and correspondingly increased one for geometric patterns. Furthermore, this altered visual preference in autistic children was correlated with the Autism Diagnostic Observation Schedule social affect score and had the highest discrimination accuracy. Our results therefore indicate that decreased visual preference for dynamic social stimuli may be the most effective visual attention-based paradigm for use as a biomarker for autism in Chinese children. Clinical trial ID: NCT03286621 (clinicaltrials.gov); Clinical trial name: Development of Eye-tracking Based Markers for Autism in Young Children. Autism Res 2019, 12: 1529-1540. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Eye-tracking measures may be useful in aiding diagnosis and treatment of autism, although it is unclear which specific tasks are optimal. Here we compare the ability of three different social eye-gaze tasks to discriminate between autistic and typically developing young Chinese children and their sensitivity to specific autistic symptoms. Our results show that a dynamic task comparing visual preference for social (individuals dancing) versus geometric patterns is the most effective both for diagnosing autism and sensitivity to its social affect symptoms.
Autism research : official journal of the International Society for Autism Research, 2019 · doi:10.1002/aur.2174