Evidence map›Paper›PMID 42199325›Full record

ReviewClinical ophthalmology (Auckland, N.Z.)2026

Social Media and Telemedicine in Ophthalmology: Misinformation, Patient Perception, and the Evolving Digital Patient.

Chisom M Chinedu-Obi, Annika Jyothi, Molly Pluenneke, Lyra E A Seaborn, Kevin E Lai, Andrew G Lee

Abstract readReview
In one paragraph

Review in Clinical ophthalmology (Auckland, N.Z.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Chisom M Chinedu-ObiSchool of Medicine, Tulane University School of Medicine, New Orleans, LA, USA.
Annika JyothiSchool of Medicine, Baylor College of Medicine, Houston, TX, USA.ORCID 0009-0002-5111-2208
Molly PluennekeSchool of Medicine, Baylor College of Medicine, Houston, TX, USA.
Lyra E A SeabornSchool of Medicine, Baylor College of Medicine, Houston, TX, USA.
Kevin E LaiDepartment of Ophthalmology, Indiana University School of Medicine, Indianapolis, IN, USA.
Andrew G LeeSchool of Medicine, Baylor College of Medicine, Houston, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital platforms have become a dominant source of ophthalmic health information, shaping how patients understand visual symptoms, form treatment expectations, and make decisions before clinical evaluation occurs. Although increased access to online content has the potential to improve patient engagement and reach underserved populations, ophthalmology remains uniquely vulnerable to misinformation due to its visually driven nature, reliance on image-based interpretation, and limited availability of high-quality, evidence-based, ophthalmic content within high-engagement digital spaces. Across platforms such as Instagram, TikTok, and YouTube, content remains variable; although some institutionally affiliated videos may demonstrate higher educational quality metrics, visually compelling content often spreads widely regardless of accuracy, resulting in inconsistent information quality, patient misconceptions, and challenges during clinical counseling. Despite growing awareness of these issues, their implications for clinical practice and patient communication remain incompletely understood. In this review, we synthesize current evidence on social media-driven patient education, misinformation dynamics, and the expanding role of digital technologies across ophthalmic practice, education and telemedicine and introduces infodemiology as a conceptual tool to characterize information spread and inform targeted clinical and public health interventions. Beyond patient education, digital technologies are reshaping how eye care professionals are trained and how care is delivered, with increasing reliance on simulation-based learning and teleophthalmology models. While these innovations offer meaningful opportunities to improve access and efficiency, they also introduce challenges related to digital and health literacy gaps, diagnostic limitations, privacy concerns, and inequitable access to technology. Effective integration of digital ophthalmology requires aligning technological innovation with clinical rigor, equity, and evidence-based communication to ensure digital transformation strengthens, rather than undermines, high-quality ophthalmic care.

Indexed as

AI in ophthalmologydigital ophthalmologymisinformationpatient educationsocial mediatelemedicine

Identifiers

PMID42199325
PMCPMC13199737

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.