Evidence map›Paper›PMID 36457596›Full record

ArticleCureus2022

Smartphone Color Vision Testing as an Alternative to the Conventional Ishihara Booklet.

Muhammad A Khizer, Umer Ijaz, Taimoor A Khan, Summaya Khan, Talha Liaqat, Abdullah Jamal, Izza Zahid, Hira G Shah, Muhammad A Zahid

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. 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 · 2026
    Article
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  4. 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

9 authors at 5 institutions in 4 countries.

Muhammad A KhizerOphthalmology, National University of Medical Sciences, Rawalpindi, PAK.
Umer IjazOphthalmology, National University of Medical Sciences, Rawalpindi, PAK.
Taimoor A KhanOphthalmology, National University of Medical Sciences, Rawalpindi, PAK.
Summaya KhanOphthalmology, National University of Medical Sciences, Quetta, PAK.
Talha LiaqatMedicine, Army Medical College, National University of Medical Sciences (NUMS), Rawalpindi, PAK.
Abdullah JamalGeneral Medicine, National University of Medical Sciences, Rawalpindi, PAK.
Izza ZahidAnaesthesiology, James Cook University, Townsville, AUS.
Hira G ShahOphthalmology, Alshifa Trust Eye Hospital, Rawalpindi, PAK.
Muhammad A ZahidEmergency Medicine, Casey Hospital, Monash Health, Berwick, AUS.
Bolan Medical College · PKMonash Health · AUNational University of Medical Sciences · PKDar Al-Shifa Hospital · PSInstitute of Ophthalmology · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Color vision testing was first seen as a parameter to be tested in the 1700s. Nowadays, it is a well-known phenomenon with significant quality-of-life implications. Structures involved in color vision include the lens, pupil, retinal cone photopigments, and several photoreceptor processes that translate the incoming spectrum of different light wavelengths into a processed colored image. An initial color vision assessment was made simply by comparing the color perception of the individual to that of the examiner. The most commonly used tools to screen for color vision defects today are color plates, such as the Ishihara color plates. In the modern age, smartphones have evolved to become an essential part of our everyday lives with applications such as Eye Handbook, which allow easier access to color vision testing using color plates displayed on smartphone screens. In this study, we compared color vision testing on Android and iOS devices to the standard Ishihara booklet. Materials and methods A cross-sectional validation study was performed on patients presenting to the Armed Forces Institute of Ophthalmology, Rawalpindi, Pakistan for six months. The sample size collected was 162 with a 95% confidence interval. The age range of the sample population was kept at 12-70 years. A patient was selected for participation in the study, and a color vision assessment was performed using the Ishihara color plates and Android and iOS smartphones. The collected data was then entered into IBM SPSS (Statistical Package for the Social Sciences) Statistics 25 for analysis, with the p-value being kept at 0.05. Results The sample size was 162, with the gender distribution being predominantly male (69.14%). The average age of the participants was 35.94 (

Indexed as

androidcolor vision deficiencyiphoneishihara platesscreensmartphone

Identifiers

PMID36457596
PMCPMC9705065
OpenAlexW4307362586

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.