Validation of the New York University Langone Eye Test Application, a Smartphone-Based Visual Acuity Test - Mina Iskander, BA; Galen Hu, ScB; Shefali Sood, BA; Noah Heilenbach, BA; Victor Sanchez, BA; Titilola Ogunsola, BS; Dinah Chen, MD; Ceyhun Elgin, PhD; Vipul Patel; Andrew Wronka, BS; Lama A. Al-Aswad, MD, MPH (Ophthalmology Science, 2022)
Purpose: To validate and assess user satisfaction and usability of the New York University (NYU) Langone Eye Test application, a smartphone-based visual acuity (VA) test. Design: Mixed-methods cross-sectional cohort study. Participants: Two hundred forty-four eyes of 125 participants were included. All participants were adults 18 years of age or older. Participants’ eyes with a VA of 20/400 (1.3 logarithm of the minimum angle of resolution [logMAR]) or worse were excluded. Methods: Patients were tested using the clinical standard Rosenbaum near card and the NYU Langone Eye Test application on an iPhone and Android device. Each test was performed twice to measure reliability. Ten patients were selected randomly for subsequent semistructured qualitative interviews with thematic analysis. Main Outcome Measures: Visual acuity was the parameter measured. Bland–Altman analysis was used to measure agreement between the results of the NYU Langone Eye Test application and Rosenbaum card, as well as test–retest reliability of each VA. The correlation between results was calculated using the intraclass correlation coefficient. Satisfaction survey and semistructured interview questions were developed to measure usability and acceptability. Results: Bland–Altman analysis revealed an agreement between the application and the Rosenbaum near card of 0.017 ± 0.28 logMAR (iPhone) and 0.009 ± 0.29 logMAR (Android). The correlation between the application and the Rosenbaum near card was 0.74 for both the iPhone and Android. Test–retest reliability was 0.003 ± 0.22 logMAR (iPhone), 0.01 ± 0.25 logMAR (Android), and 0.01 ± 0.23 logMAR (Rosenbaum card). Of the 125 participants, 97.6% found the application easy to use, and 94.3% were overall satisfied with the application. Thematic analysis yielded 6 key themes: (1) weaknesses of application, (2) benefits of the application, (3) tips for application improvement, (4) difficulties faced while using the application, (5) ideal patient for application, and (6) comparing application with traditional VA testing. Conclusions: The NYU Langone Eye Test application is a user-friendly, accurate, and reliable measure of near VA. The application’s integration with the electronic health record, accessibility, and easy interpretation of results, among other features, make it ideal for telemedicine use.