Evidence map›Paper›PMID 40611577›Full record

ArticleUrology research & practice2025

Unraveling Online Perspectives and Misinformation Surrounding Urinary Tract Infections: A Thematic Analysis of 1200 Instagram Posts.

Raya Dean, Patrick Juliebø-Jones, Amelia Pietropaolo, Naeem Bhojani, Wissam Kamal, Bhaskar Somani

Erratum issuedAbstract read
In one paragraph

Article in Urology research & practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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

5 · Who and what money

Authors and funding

6 authors.

Raya DeanDepartment of Urology, University Hospital Southampton, Southamptom, The UK.
Patrick Juliebø-JonesDepartment of Urology, Haukeland University Hospital, Bergen, Norway.
Amelia PietropaoloDepartment of Urology, University Hospital Southampton, Southamptom, The UK.
Naeem BhojaniDivision of Urology, Centre Hospitalier de L'Université de Montréal, Quebec, Canada.
Wissam KamalUrology Unit, King Fahd General Hospital, Jeddah, Saudi Arabia.
Bhaskar SomaniDepartment of Urology, University Hospital Southampton, Southamptom, The UK.ORCID 0000-0002-6248-6478

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Urinary tract infections are burdensome for patients. Social media is increasingly used as a platform for patients and public to seek and share support. The study aimed to evaluate what patients encounter when they turn to Instagram for urinary tract infection-related support and advice. Methods: The first 200 posts appearing on the "top posts" section of Instagram for 6 key hashtags (#UTI, #UTIs, #urinarytractinfection, #urinarytractinfections, #bladderin- fection, #bladderinfections) were selected. Thematic analysis (TA) was used to identify themes present in the Instagram captions. Results: Across 1200 posts analyzed, 5 main themes were identified. 1) "We can help…," this was largely commercial advertising with the promotion of healthcare clinics. 2) "I'm suffering," which contained first-person narratives about an unpleasant experience with a disease or treatment as well as frustration at health services. 3)!"Warning signs," posts describing signs or symptoms that the creator claims indicate poor health. 4)!"Remedies," these posts detailed therapies to try, often herbal. 5) "Avoid and change," which covered triggers to avoid symptom flare ups. Conclusion: There is a large amount of content on social media related to UTIs. Urologists should be aware that patients may have sought out advice using these platforms and may therefore have received misinformation and products that have been advertised but lack scientific evidence.

Identifiers

PMID40611577
PMCPMC12257834

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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.