Online UTI Myths Found Common, Dangerous: Daily Dose

Patient Care brings primary care clinicians a lot of medical news every day—it’s easy to miss an important study. The Daily Dose provides a concise summary of one of the website's leading stories you may not have seen.


On November 22, 2024, we reported on a study published in JAMA Network Open that assessed the content and quality of urinary tract infection (UTI) and asymptomatic bacteriuria (ASB) information on the internet.

The study

For the cross-sectional analysis, researchers conducted Google searches for UTIs in incognito mode between December 2023 and January 2024.

The search terms were developed collaboratively by a team of clinicians specializing in geriatrics and infectious diseases, along with a community advisory board comprising older adults and patient advocates, ensuring terms were both relevant and comprehensive for identifying online content about UTIs and ASB.

Websites met Inclusion criteria if they were freely accessible, written in English, based in the US, and tailored for adult, nonpregnant individuals. The identified 1413 websites. After exclusions, 331 websites were included in the detailed evaluation.

The findings

While nearly all sites (97%) correctly identified at least 1 UTI symptom, 80% also included at least 1 inaccurate UTI symptom, with 74% citing changes in urine color and 69% referencing strong-smelling urine. Only 9% of websites mentioned ASB, and just 3% correctly noted that symptoms must be present for a true UTI diagnosis.

Alarmingly, researchers found just 1 in 5 (21%) of the websites reviewed mentioned antibiotic resistance among individuals. Moreover, only 9% discussed the problem of global antibiotic resistance and just 8% warned of adverse reactions to antibiotics.

Authors' comment

"Although this cross-sectional study found some accurate information about UTI symptoms, diagnosis, and treatment, it was often mixed with misinformation. This misinformation can perpetuate misconceptions about UTIs and ASB, leading to inaccurate patient information and AI summaries of UTI diagnosis and management. Inaccurate information was biased toward overtreatment, which can lead to antibiotic resistance."

Click here for more details.