Democratizing Health Care in the Metaverse: How Video Games can Monitor Eye Conditions Using the Vision Performance Index: A Pilot Study

OBJECTIVE: In a world where digital media is deeply engrained into our everyday lives, there lies an opportunity to leverage interactions with technology for health and wellness. The Vision Performance Index (VPI) leverages natural human–technology interaction to evaluate visual function using visual, cognitive, and motor psychometric data over 5 domains: field of view, accuracy, multitracking, endurance, and detection. The purpose of this study was to describe a novel method of evaluating holistic visual function through video game-derived VPI score data in patients with specific ocular pathology. DESIGN: Prospective comparative analysis. PARTICIPANTS: Patients with dry eye, glaucoma, cataract, diabetic retinopathy (DR), age-related macular degeneration, and healthy individuals. METHODS: The Vizzario Inc software development kit was integrated into 2 video game applications, Balloon Pop and Picture Perfect, which allowed for generation of VPI scores. Study participants were instructed to play rounds of each video game, from which a VPI score was compiled. MAIN OUTCOME MEASURES: The primary outcome was VPI overall score in each comparison group. Vision Performance Index component, subcomponent scores, and psychophysical inputs were also compared. RESULTS: Vision Performance Index scores were generated from 93 patients with macular degeneration (n = 10), cataract (n = 10), DR (n = 15), dry eye (n = 15), glaucoma (n = 16), and no ocular disease (n = 27). The VPI overall score was not significantly different across comparison groups. The VPI subcomponent “reaction accuracy” score was significantly greater in DR patients (106 ± 13.2) versus controls (96.9 ± 11.5), P = 0.0220. The VPI subcomponent “color detection” score was significantly lower in patients with DR (96.8 ± 2.5; p=0.0217) and glaucoma (98.5 ± 6.3; P = 0.0093) compared with controls (101 ± 11). Psychophysical measures were statistically significantly different from controls: proportion correct (lower in DR, age-related macular degeneration), contrast errors (higher in cataract, DR), and saturation errors (higher in dry eye). CONCLUSIONS: Vision Performance Index scores can be generated from interactions of an ocular disease population with video games. The VPI may offer utility in monitoring select ocular diseases through evaluation of subcomponent and psychophysical input scores; however, future larger-scale studies must evaluate the validity of this tool. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.