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Validation of the New York University Langone Eye Test Application, a Smartphone-Based Visual Acuity Test

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....

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Autores principales: Iskander, Mina, Hu, Galen, Sood, Shefali, Heilenbach, Noah, Sanchez, Victor, Ogunsola, Titilola, Chen, Dinah, Elgin, Ceyhun, Patel, Vipul, Wronka, Andrew, Al-Aswad, Lama A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9560635/
https://www.ncbi.nlm.nih.gov/pubmed/36245756
http://dx.doi.org/10.1016/j.xops.2022.100182
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author Iskander, Mina
Hu, Galen
Sood, Shefali
Heilenbach, Noah
Sanchez, Victor
Ogunsola, Titilola
Chen, Dinah
Elgin, Ceyhun
Patel, Vipul
Wronka, Andrew
Al-Aswad, Lama A.
author_facet Iskander, Mina
Hu, Galen
Sood, Shefali
Heilenbach, Noah
Sanchez, Victor
Ogunsola, Titilola
Chen, Dinah
Elgin, Ceyhun
Patel, Vipul
Wronka, Andrew
Al-Aswad, Lama A.
author_sort Iskander, Mina
collection PubMed
description 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.
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spelling pubmed-95606352022-10-14 Validation of the New York University Langone Eye Test Application, a Smartphone-Based Visual Acuity Test Iskander, Mina Hu, Galen Sood, Shefali Heilenbach, Noah Sanchez, Victor Ogunsola, Titilola Chen, Dinah Elgin, Ceyhun Patel, Vipul Wronka, Andrew Al-Aswad, Lama A. Ophthalmol Sci Original Article 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. Elsevier 2022-06-15 /pmc/articles/PMC9560635/ /pubmed/36245756 http://dx.doi.org/10.1016/j.xops.2022.100182 Text en © 2022 by the American Academy of Ophthalmology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Iskander, Mina
Hu, Galen
Sood, Shefali
Heilenbach, Noah
Sanchez, Victor
Ogunsola, Titilola
Chen, Dinah
Elgin, Ceyhun
Patel, Vipul
Wronka, Andrew
Al-Aswad, Lama A.
Validation of the New York University Langone Eye Test Application, a Smartphone-Based Visual Acuity Test
title Validation of the New York University Langone Eye Test Application, a Smartphone-Based Visual Acuity Test
title_full Validation of the New York University Langone Eye Test Application, a Smartphone-Based Visual Acuity Test
title_fullStr Validation of the New York University Langone Eye Test Application, a Smartphone-Based Visual Acuity Test
title_full_unstemmed Validation of the New York University Langone Eye Test Application, a Smartphone-Based Visual Acuity Test
title_short Validation of the New York University Langone Eye Test Application, a Smartphone-Based Visual Acuity Test
title_sort validation of the new york university langone eye test application, a smartphone-based visual acuity test
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9560635/
https://www.ncbi.nlm.nih.gov/pubmed/36245756
http://dx.doi.org/10.1016/j.xops.2022.100182
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