Evidence map›Paper›PMID 38573757›Full record

ArticleJMIR formative research2024

Using Smartphones to Enhance Vision Screening in Rural Areas: Pilot Study.

Zheng Wang, John Kempen, Gang Luo

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Deep learning-empowered low-cost portable automated refraction system: A solution to the inadequate effective correction rate of refractive errors in resource-limited areas.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2025
    Trial
  2. Article
  3. Subjective Refraction Test Using a Smartphone for Vision Screening.Journal of visualized experiments : JoVE · 2024
    Article
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

3 authors at 2 institutions in 2 countries.

Zheng WangSchool of Medicine, Jiaxing University, Jiaxing, China.ORCID https://orcid.org/0000-0002-3497-1361
John KempenSchepens Eye Research Institute, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0000-0002-2967-4792
Gang LuoSchepens Eye Research Institute, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0000-0003-0623-6236
Massachusetts Eye and Ear Infirmary · USJiaxing University · CN

Funding

The Harvard Clinical and Translational Science CenterUL1TR002541 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2018 to 2022
$93.0M
Overcome the barriers of vision care in Africa using smartphonesR33EY034345 · NEI · SCHEPENS EYE RESEARCH INSTITUTE · PI JOHN H KEMPEN, Gang Luo · 2024 to 2026
$1.1M
Mobile medical application for cost-effective strabismus screeningR44EY025902 · NEI · EYENEXO LLC · PI HOUSTON, KEVIN EDWARD, LUO, GANG · 2017 to 2018
$1.0M
Overcome the barriers of vision care in Africa using smartphonesR21EY034345 · NEI · SCHEPENS EYE RESEARCH INSTITUTE · PI KEMPEN, JOHN H, LUO, GANG · 2022 to 2023
$492k
NCATS NIH HHS UL1 TR002541NEI NIH HHS R21 EY034345NEI NIH HHS R33 EY034345NEI NIH HHS R44 EY025902
6 · The paper itself

Abstract

backgroundWhile it is treatable, uncorrected refractive error is the number one cause of visual impairment worldwide. This eye condition alone, or together with ocular misalignment, can also cause amblyopia, which is also treatable if detected early but still occurs in about 4% of the population. Mass vision screening is the first and most critical step to address these issues, but due to limited resources, vision screening in many rural areas remains a major challenge.

objectiveWe aimed to pilot-test the feasibility of using smartphone apps to enhance vision screening in areas where access to eye care is limited.

methodsA vision screening program was piggybacked on a charity summer camp program in a rural county in Sichuan, China. A total of 73 fourth and fifth graders were tested for visual acuity using a standard eye chart and were then tested for refractive error and heterophoria using 2 smartphone apps (a refraction app and a strabismus app, respectively) by nonprofessional personnel.

resultsA total of 5 of 73 (6.8%, 95% CI 2.3%-15.3%) students were found to have visual acuity worse than 20/20 (logarithm of minimal angle of resolution [logMAR] 0) in at least one eye. Among the 5 students, 3 primarily had refractive error according to the refraction app. The other 2 students had manifest strabismus (one with 72-prism diopter [PD] esotropia and one with 33-PD exotropia) according to the strabismus app. Students without manifest strabismus were also measured for phoria using the strabismus app in cover/uncover mode. The median phoria was 0.0-PD (IQR 2.9-PD esophoria to 2.2-PD exophoria).

conclusionsThe results from this vision screening study are consistent with findings from other population-based vision screening studies in which conventional tools were used by ophthalmic professionals. The smartphone apps are promising and have the potential to be used in mass vision screenings for identifying risk factors for amblyopia and for myopia control. The smartphone apps may have significant implications for the future of low-cost vision care, particularly in resource-constrained and geographically remote areas.

Indexed as

appapplicationapplicationsappseyeeyesfeasibilitymHealthmobile healthophthalmologyoptometryrefractive errorscreeningsmartphonestrabismusvisionvision screeningvisualvisual acuity

Identifiers

PMID38573757
PMCPMC11027048
OpenAlexW4393933871

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.