Evidence map›Paper›PMID 42553429›Full record

ArticleTherapeutic advances in ophthalmology

Podcast reassurance to equity of implementation: Expanding the therapeutic potential of charles bonnet syndrome education.

Rajeev Kumar Jha, Ranjay Kumar Choudhary, Mulavagili Vijayasimha

Abstract readLetter
In one paragraph

Article in Therapeutic advances in ophthalmology. 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

3 authors.

Rajeev Kumar JhaSchool of Health Sciences, The Neotia University, Kolkata, West Bengal, India.
Ranjay Kumar ChoudharyOman Medical Laboratory Sciences, A'Sharqiyah University, Ibra, Oman.
Mulavagili VijayasimhaDepartment of MLT, University Institute of Allied Health Science, Chandigarh University, Mohali, Punjab, India.ORCID https://orcid.org/0000-0003-2038-7006

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Charles Bonnet syndrome (CBS) is a condition that can cause people with vision loss to see things that are not actually present, such as patterns, objects, animals, or people. Although these experiences are usually not a sign of mental illness, many individuals feel worried, confused, or reluctant to discuss their symptoms with healthcare professionals. A recent study in Therapeutic Advances in Ophthalmology showed that an educational podcast helped people with CBS better understand their condition and reduced some of the emotional distress associated with hallucinations. This finding highlights the value of simple, accessible educational tools in supporting patients. In our letter, we suggest that educational podcasts should be viewed as the first step in a broader support strategy. Education can help patients feel reassured, but it should be combined with routine screening, opportunities to discuss symptoms with healthcare providers, and clear pathways for referral when additional support is needed. We also emphasize the importance of making educational resources available in different languages and formats so they can reach people with varying levels of digital access and health literacy. By combining patient education with structured clinical support, healthcare systems may improve awareness of CBS, reduce stigma, encourage earlier disclosure of symptoms, and enhance quality of life for people living with this often-overlooked condition. Our goal is to promote practical, equitable, and patient-centred approaches that can be adopted in eye care services worldwide.

Identifiers

PMID42553429
PMCPMC13434090

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Registered trials

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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.