Comparing Automatic Eye Tracking and Manual Gaze Coding Methods in Young Children with Autism Spectrum Disorder

Autism Res. 2020 Feb;13(2):271-283. doi: 10.1002/aur.2225. Epub 2019 Oct 17.

Abstract

Eye-gaze methods offer numerous advantages for studying cognitive processes in children with autism spectrum disorder (ASD), but data loss may threaten the validity and generalizability of results. Some eye-gaze systems may be more vulnerable to data loss than others, but to our knowledge, this issue has not been empirically investigated. In the current study, we asked whether automatic eye-tracking and manual gaze coding produce different rates of data loss or different results in a group of 51 toddlers with ASD. Data from both systems were gathered (from the same children) simultaneously, during the same experimental sessions. As predicted, manual gaze coding produced significantly less data loss than automatic eye tracking, as indicated by the number of usable trials and the proportion of looks to the images per trial. In addition, automatic eye-tracking and manual gaze coding produced different patterns of results, suggesting that the eye-gaze system used to address a particular research question could alter a study's findings and the scientific conclusions that follow. It is our hope that the information from this and future methodological studies will help researchers to select the eye-gaze measurement system that best fits their research questions and target population, as well as help consumers of autism research to interpret the findings from studies that utilize eye-gaze methods with children with ASD. Autism Res 2020, 13: 271-283. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: The current study found that automatic eye-tracking and manual gaze coding produced different rates of data loss and different overall patterns of results in young children with ASD. These findings show that the choice of eye-gaze system may impact the findings of a study-important information for both researchers and consumers of autism research.

Keywords: autism; children; data quality; eye tracking; language processing; methodology.

Publication types

  • Research Support, N.I.H., Extramural