How Useful are Current Chatbots Regarding Urology Patient Information? Comparison of the Ten Most Popular Chatbots' Responses About Female Urinary Incontinence

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dc.authoridSAHIN, MEHMET FATIH/0000-0002-0926-3005
dc.contributor.authorMalak, Arzu
dc.contributor.authorSahin, Mehmet Fatih
dc.date.accessioned2025-04-06T12:23:55Z
dc.date.available2025-04-06T12:23:55Z
dc.date.issued2024
dc.departmentTekirdağ Namık Kemal Üniversitesi
dc.description.abstractThis research evaluates the readability and quality of patient information material about female urinary incontinence (fUI) in ten popular artificial intelligence (AI) supported chatbots. We used the most recent versions of 10 widely-used chatbots, including OpenAI's GPT-4, Claude-3 Sonnet, Grok 1.5, Mistral Large 2, Google Palm 2, Meta's Llama 3, HuggingChat v0.8.4, Microsoft's Copilot, Gemini Advanced, and Perplexity. Prompts were created to generate texts about UI, stress type UI, urge type UI, and mix type UI. The modified Ensuring Quality Information for Patients (EQIP) technique and QUEST (Quality Evaluating Scoring Tool) were used to assess the quality, and the average of 8 well-known readability formulas, which is Average Reading Level Consensus (ARLC), were used to evaluate readability. When comparing the average scores, there were significant differences in the mean mQEIP and QUEST scores across ten chatbots (p = 0.049 and p = 0.018). Gemini received the greatest mean scores for mEQIP and QUEST, whereas Grok had the lowest values. The chatbots exhibited significant differences in mean ARLC, word count, and sentence count (p = 0.047, p = 0.001, and p = 0.001, respectively). For readability, Grok is the easiest to read, while Mistral is highly complex to understand. AI-supported chatbot technology needs to be improved in terms of readability and quality of patient information regarding female UI.
dc.identifier.doi10.1007/s10916-024-02125-4
dc.identifier.issn0148-5598
dc.identifier.issn1573-689X
dc.identifier.issue1
dc.identifier.pmid39535651
dc.identifier.scopus2-s2.0-85209226695
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1007/s10916-024-02125-4
dc.identifier.urihttps://hdl.handle.net/20.500.11776/17255
dc.identifier.volume48
dc.identifier.wosWOS:001353779000001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofJournal of Medical Systems
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250406
dc.subjectArtificial Intelligence
dc.subjectFemale Urinary Incontinence
dc.subjectGPT-4
dc.subjectClaude
dc.subjectGrok
dc.subjectMistral
dc.subjectGoogle Palm
dc.subjectLlama
dc.subjectHuggingchat
dc.subjectCopilot
dc.subjectGemini
dc.subjectPerplexity
dc.titleHow Useful are Current Chatbots Regarding Urology Patient Information? Comparison of the Ten Most Popular Chatbots' Responses About Female Urinary Incontinence
dc.typeArticle

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