ArticleJournal of optometry
Clinical validation of a novel smartphone application for measuring best corrected visual acuity.
Article in Journal of optometry. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- A comparative analysis of an AI-assisted virtual reality platform with technician-based examination for visual field, visual acuity, and color vision in neuro-ophthalmology.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Article
- Enhancing access and clinical triage in primary eye care through digital vision testing: validation of the SightConnect mobile application.Frontiers in digital health · 2026Article
- Preliminary evaluation of smartphone-based addition measurement in a presbyopic population.Journal of optometryArticle
- Standardization of distance visual acuity measurement using optonet computerized vision charts: A multicentric study.Journal of optometryArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposePersonal mobile devices such as smartphones are proving their usefulness in ever more applications in tele-eyecare. An inconvenience and potential source of error in these past approaches stemmed from the requirement for the subjects to situate their devices at a distance. The present study aims to clinically validate best corrected visual acuity (BCVA) measures carried out by a novel smartphone application "vision.app" (VisionApp Solutions S.L.) using comparative statistics against clinical measurements. MATERIALS AND
methodsBCVA was measured in both eyes of 40 subjects using vision.app which displayed a black Landolt-C optotype with crowding on a white background, and utilized a 4 forced-choice procedure for the subjects to find (by means of swiping in either of four directions) the smallest optotype size they could resolve. Results were compared to BCVA measurements taken using a standard Snellen chart placed at 20 feet (6 m).
resultsThe t-test revealed no significant differences between the app- and clinically-measured VA (p = 0.478 (OD) and 0.608 (OS)), with a mean difference between clinical and app measurements of less than one line of the eye chart (-0.009 logMAR (OD) and -0.005 logMAR (OS)). A limit of agreement for a 95% confidence interval of ± 0.08 logMAR for OD and OS was found.
conclusionsThe results show the potential use of a smartphone to measure BCVA at a handheld distance. The newly validated study results can hold major future advancements in tele-eyecare and provide eye care professionals with a reliable and accessible method to measure BCVA.
Indexed as
Identifiers
What OpenQuestion holds
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.