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Record W4408303109 · doi:10.2196/58882

Living With and Managing Uncomplicated Urinary Tract Infection: Mixed Methods Analysis of Patient Insights From Social Media

2025· article· en· W4408303109 on OpenAlexaboutno aff
Melissa Kramer, José Medina‐Polo, Nishant Kumar, Aruni Mulgirigama, Amina Benkiran

Bibliographic record

VenueJournal of Medical Internet Research · 2025
Typearticle
Languageen
FieldMedicine
TopicUrinary Tract Infections Management
Canadian institutionsnot available
Fundersnot available
KeywordsSocial mediaMedicineFamily medicineSocial supportUrinary systemNursingInternal medicinePsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Uncomplicated urinary tract infections (uUTIs) affect more than half of women in their lifetime and can impact on quality of life. We analyzed social media posts discussing uUTIs to gather insights into the patient experience, including aspects of their disease management journey and associated opinions and concerns. OBJECTIVE: This study aims to gather patient experience insights by analyzing social media posts that discussed uUTI. METHODS: A search string ("urinary tract infection" [UTI] or "bladder infection" or "cystitis" or "UTI" not "interstitial cystitis") was used to identify posts from public blogs and patient forums (June 2021 to June 2023). Posts were excluded if they were not written in English or discussed complicated UTI (posts that mentioned "pregnancy" or "pregnant" or "trimester" or "catheter" or "interstitial"). Posts were limited to publicly available sources and anonymized. The primary objective was to gather patient perspectives on key elements of the uUTI experience, including health care professional (HCP) interactions, diagnosis, treatment, and recurrence. RESULTS: In total, more than 42,000 unique posts were identified (mostly from reddit.com; 29,506/42,265, 70%) and >3600 posts were analyzed. Posts were most commonly from users in the United States (6707/11,180, 60%), the United Kingdom (2261/11,180, 20%), Canada (509/11,180, 5%), Germany (356/11,180, 3%), or India (320/11,180, 3%). Six main themes were identified: symptom awareness and information seeking, HCP interactions, diagnosis and management challenges, management with antibiotics, self-management, and challenges with recurrent UTI. Most posts highlighted the importance of seeking professional medical advice, while some patients raised concerns regarding their HCP interactions and lack of shared decision-making. Patients searched for advice and guidance on the web prior to consulting an HCP, described their symptoms, and discussed lifestyle adjustments. Most patients tried self-management and shared their experiences with nonprescribed treatment options. There was general agreement among posts that antibiotics are necessary to cure UTIs and prevent associated complications. CONCLUSIONS: Social media posts provide valuable insight into the experiences and opinions of patients with uUTIs in Canada, Germany, India, the United Kingdom, and the United States. The insights from this study provide a more complete picture of patient behaviors and highlight the potential for HCP and patient education, as well as better communication through shared decision-making to improve care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.560
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.441
Teacher spread0.381 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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