British and Irish Orthoptic Journal · 2024 · 37 citations · 14 references
ComputingComputer ScienceSurgeryAnesthesiaArtificial IntelligenceNatural Language ProcessingAffective ComputingAnesthesia For Ophthalmic SurgeryConversational InterfacesConversational User InterfacesEmotion RecognitionPatient Information LeafletsChatbot SystemsChatbotsComparative Data AnalysisEmotionsHealth Information ReadabilityMedical Information Seeking
Background and Aim: Eye surgeries often evoke strong negative emotions in patients, including fear and anxiety. Patient education material plays a crucial role in informing and empowering individuals. Traditional sources of medical information may not effectively address individual patient concerns or cater to varying levels of understanding. This study aims to conduct a comparative analysis of the accuracy, completeness, readability, tone, and understandability of patient education material generated by AI chatbots versus traditional Patient Information Leaflets (PILs), focusing on local anesthesia in eye surgery. Methods: Expert reviewers evaluated responses generated by AI chatbots (ChatGPT and Google Gemini) and a traditional PIL (Royal College of Anaesthetists' PIL) based on accuracy, completeness, readability, sentiment, and understandability. Statistical analyses, including ANOVA and Tukey HSD tests, were conducted to compare the performance of the sources. Results: Readability analysis showed variations in complexity among the sources, with AI chatbots offering simplified language and PILs maintaining better overall readability and accessibility. Sentiment analysis revealed differences in emotional tone, with Google Gemini exhibiting the most positive sentiment. AI chatbots demonstrated superior understandability and actionability, while PILs excelled in completeness. Overall, ChatGPT showed slightly higher accuracy (scores expressed as mean ± standard deviation) (4.71 ± 0.5 vs 4.61 ± 0.62) and completeness (4.55 ± 0.58 vs 4.47 ± 0.58) compared to Google Gemini, but PILs performed best (4.84 ± 0.37 vs 4.88 ± 0.33) in terms of both accuracy and completeness (p-value for completeness <0.05). Conclusion: AI chatbots show promise as innovative tools for patient education, complementing traditional PILs. By leveraging the strengths of both AI-driven technologies and human expertise, healthcare providers can enhance patient education and empower individuals to make informed decisions about their health and medical care.
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Sarah J. Shoemaker, Michael S. Wolf, Cindy Brach · Patient Education and Counseling · 2014 · 1.3K citations
Education, Educational Assessment, Educational Measurement +13
Effectiveness of strategies for informing, educating, and involving patients
Angela Coulter, Jo Ellins · BMJ · 2007 · 1.1K citations · Full text
Emily Z. Kontos, Kelly D. Blake, Wen‐Ying Sylvia Chou et al. · Journal of Medical Internet Research · 2014 · 997 citations · Full text
Social Sciences, Health Informatics, Health Communication +13