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How reliable are ChatGPT and Google’s answers to frequently asked questions about unicondylar knee arthroplasty from a scientific perspective?

2025·4 Zitationen·Journal of orthopaedic surgeryOpen Access
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4

Zitationen

2

Autoren

2025

Jahr

Abstract

IntroductionUnicondylar knee arthroplasty (UKA) is a minimally invasive surgical technique that replaces a specific compartment of the knee joint. Patients increasingly rely on digital tools such as Google and ChatGPT for healthcare information. This study aims to compare the accuracy, reliability, and applicability of the information provided by these two platforms regarding unicondylar knee arthroplasty.Materials and MethodsThis study was conducted using a descriptive and comparative content analysis approach. 12 frequently asked questions regarding unicondylar knee arthroplasty were identified through Google's "People Also Ask" section and then directed to ChatGPT-4. The responses were compared based on scientific accuracy, level of detail, source reliability, applicability, and consistency. Readability analysis was conducted using DISCERN, FKGL, SMOG, and FRES scores.ResultsA total of 83.3% of ChatGPT's responses were found to be consistent with academic sources, whereas this rate was 58.3% for Google. ChatGPT's answers of 142.8 words, compared to Google's 85.6-word average. Regarding source reliability, 66.7% of ChatGPT's responses were based on academic guidelines, whereas Google's percentage was 41.7%. The DISCERN score for ChatGPT was 64.4, whereas Google's was 48.7. Google had a higher FRES score.ConclusionChatGPT provides more scientifically accurate information than Google, while Google offers simpler and more comprehensible content. However, the academic language used by ChatGPT may be challenging for some patient groups, whereas Google's superficial information is a significant limitation. In the future, the development of Artificial Intelligence-based medical information tools could be beneficial in improving patient safety and the quality of information dissemination.

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Themen

Artificial Intelligence in Healthcare and EducationTotal Knee Arthroplasty OutcomesRadiomics and Machine Learning in Medical Imaging
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