Evidence map›Paper›PMID 40047903›Full record

ArticleWorld journal of urology2025

Bing chat for kidney stone management questions based on the AUA guidelines: a comparison of chatbot conversation style modes.

Daniel R Hanna, Michael L Creswell, Russell S Terry, Lucas B Vergamini, Mihaela Sardiu, Holly E Du, Amber K McMahon, Wilson R Molina, Bristol B Whiles

Abstract readComparative Study
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In one paragraph

Article in World journal of urology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

9 authors.

Daniel R HannaDepartment of Urology, University of Kansas Health System, 4000 Cambridge Street, Mailstop 3016, Kansas City, KS, USA.
Michael L CreswellDepartment of Urology, University of Kansas Health System, 4000 Cambridge Street, Mailstop 3016, Kansas City, KS, USA.
Russell S TerryDepartment of Urology, University of Florida College of Medicine, Gainesville, FL, USA.
Lucas B VergaminiDepartment of Urology, University of Kansas Health System, 4000 Cambridge Street, Mailstop 3016, Kansas City, KS, USA.
Mihaela SardiuDepartment of Biostatistics & Data Science, University of Kansas, Kansas City, KS, USA.
Holly E DuDepartment of Biostatistics & Data Science, University of Kansas, Kansas City, KS, USA.
Amber K McMahonDepartment of Urology, University of Kansas Health System, 4000 Cambridge Street, Mailstop 3016, Kansas City, KS, USA.
Wilson R MolinaDepartment of Urology, University of Kansas Health System, 4000 Cambridge Street, Mailstop 3016, Kansas City, KS, USA.
Bristol B WhilesDepartment of Urology, University of Kansas Health System, 4000 Cambridge Street, Mailstop 3016, Kansas City, KS, USA. bwhiles@kumc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeArtificial intelligence (AI) technology will inevitably permeate healthcare. Bing Chat is an AI chatbot with different conservation styles. We evaluated each of these response mode answers regarding management of nephrolithiasis.

methodsA total of 20 questions were created based on the AUA Surgical Management of Stones guidelines. Bing Chat's responses were evaluated across Precise, Balanced, and Creative conversation style chat modes by three physicians using the Brief DISCERN tool. Consensus scoring was employed to assess appropriateness, guideline adherence, empathy, recommendation for physician consultation, and inability to answer the inquiry. Responses were also assessed for their directness and the presence of superfluous information. Chat modes were compared using descriptive statistics as well as ANOVA, Chi-Squared tests, and Fisher exact tests.

resultsThe median Brief DISCERN Score in Precise, Balanced, and Creative modes were: 22, 21, and 21, respectively. There was no significant difference in Brief DISCERN scores between the three chat modes (p = 0.68). Guideline adherence by chatbot conversation style was similar (p = 0.37), as was response appropriateness (p = 0.62), directly answering the question asked (p = 0.26) and providing a recommendation to consult with a healthcare provider (p = 0.07). Creative and balanced modes outperformed precise mode when evaluating response empathy. Creative mode was more likely to include superfluous information and less likely to answer the question.

conclusionIn its current iteration, Bing Chat provides low quality urologic healthcare information for nephrolithiasis queries, regardless of the conversation style utilized.

Indexed as

Artificial IntelligenceCommunicationKidney CalculiGenerative Artificial IntelligenceGuideline AdherenceHumansPractice Guidelines as TopicSocieties, MedicalUrologyArtificial intelligenceChatbotKidney stoneMedical question

Identifiers

PMID40047903

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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.