Evidence map›Paper›PMID 36245756›Full record

ArticleOphthalmology science2022

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

Mina Iskander, Galen Hu, Shefali Sood, Noah Heilenbach, Victor Sanchez, Titilola Ogunsola, Dinah Chen, Ceyhun Elgin, Vipul Patel, Andrew Wronka and 1 more

Registry-linked trialOpen access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Ophthalmology science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06076785 (Impact of ODYSight in the Management of patientS With imparairEd Visual acuitY), which is not on this map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06076785 unknown statusnot on this mapstarted 2023, after this paper: background citation

Impact of ODYSight in the Management of patientS With imparairEd Visual acuitY (ODYSSEY).

TypeobservationalSponsorTilak HealthcareRan2023 to 2024Enrolled300ConditionsImpaired Visual AcuityArmsOdySight
3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Validity and Reliability of WHOeyes Application in Community-based Visual Acuity Screening Program.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine · 2026
    Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 2 countries.

Mina IskanderDepartment of Ophthalmology, Grossman School of Medicine, New York University, New York, New York.
Galen HuDepartment of Ophthalmology, Grossman School of Medicine, New York University, New York, New York.
Shefali SoodDepartment of Ophthalmology, Grossman School of Medicine, New York University, New York, New York.
Noah HeilenbachDepartment of Ophthalmology, Grossman School of Medicine, New York University, New York, New York.
Victor SanchezDepartment of Ophthalmology, Grossman School of Medicine, New York University, New York, New York.
Titilola OgunsolaDepartment of Ophthalmology, Grossman School of Medicine, New York University, New York, New York.
Dinah ChenDepartment of Ophthalmology, Grossman School of Medicine, New York University, New York, New York.
Ceyhun ElginDepartment of Ophthalmology, Grossman School of Medicine, New York University, New York, New York.
Vipul PatelDepartment of Ophthalmology, Grossman School of Medicine, New York University, New York, New York.
Andrew WronkaDepartment of Ophthalmology, Grossman School of Medicine, New York University, New York, New York.
Lama A Al-AswadDepartment of Ophthalmology, Grossman School of Medicine, New York University, New York, New York.
New York University · USBoğaziçi University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

logMAR, logarithm of the minimum angle of resolutionNYU, New York UniversityOphthalmologySmartphone-based visual acuity testTelemedicineTeleophthalmologyVA, visual acuityVisual acuity

Identifiers

PMID36245756
PMCPMC9560635
OpenAlexW4282929833

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.