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Eyes don’t lie: Indifferent to AI-generated depression screenings

Shahsavar, Yeganeh1; Choudhury, Avishek1

Research facility: West Virginia University
Published Jul 28, 2025 on Dryad. https://doi.org/10.5061/dryad.80gb5mm2d

Data files

Jul 28, 2025 version files 107.31 MB

Abstract

This study explored how users respond to a depression self-diagnosis app with two outcomes: “doctor-generated” and “AI-generated.” The doctor-generated result was based on participants’ actual PHQ-9 depression scores, while the AI-generated result was randomly selected and sometimes matched the true diagnosis. Participants (n = 47) with depressive symptoms used the app while pupil dilation was recorded using a Tobii Pro Spectrum eye tracker. Pupil dilation was analyzed before and during the decision phase. Participants who chose the doctor-generated result showed no difference in pupil dilation compared to those who chose AI. Our Extreme Gradient Boosting (XGB) model predicted trust with an AUROC of 0.871. These findings show that users engage equally with both AI and doctor-labeled diagnoses, but pupil diameter is indicative of their trust.