在线教育材料的可读性,可理解性和质量以及逆行性喉肌肉功能障碍的大型语言模型的可读性,可理解性和质量
Nurullah Türe1, Emel Tahir2, Necati Enver3
1Department of Otorhinolaryngology, Kütahya Health Sciences University, Kütahya, Türkiye. nurullah.ture@ksbu.edu.tr.
概括
在线和人工智能生成的关于逆行性喉功能障碍 (RCPD) 的患者教育很难阅读,缺乏可行的建议. 改善数字健康沟通对于患者的理解和治疗决策至关重要.
科学领域:
- 数字健康传播数字健康传播
- 患者教育材料 患者教育材料
- 医疗保健中的人工智能
背景情况:
- 在线资源和大型语言模型 (LLM) 越来越多地用于患者教育.
- 逆行式喉功能障碍 (RCPD) 信息的可访问性对于患者的自我管理至关重要.
- 评估数字健康信息的质量对于患者的安全和护理至关重要.
研究的目的:
- 评估RCPD在线患者教育材料的可读性,可理解性和质量.
- 将这些材料与领先的大型语言模型 (LLM) 产生的内容进行比较.
- 为RCPD确定数字健康传播的改进领域.
主要方法:
- 在2024年12月进行的全面网络搜索中,评估了51个在线资源和四个LLM (ChatGPT 4.0,Gemini 1.5 Flash,Perplexity GPT-3.5,DeepSeek-V2.5) 在2024年12月.
- 使用Readable.io分析可读性,使用PEMAT评估可理解性和可操作性.
- 使用DISCERN仪器评估了信息质量.
主要成果:
- 在线材料和法学士的回答均为11-12年级的阅读水平,超过了推的患者可访问性.
- 对于LLM,尤其是DeepSeek-V2.5 (24.21),Flesch阅读易度得分最低.
- 可理解性得分充足 (在线:82%,LLMs:79%),但可操作性低 (25-37%) 在所有来源,治疗决策的质量有限.
结论:
- 现有的在线和LLM生成的RCPD材料往往太复杂,无法让患者理解.
- 尽管可理解性充足,但可操作性低,整体质量低,这凸显了以患者为中心的数字健康沟通中存在的巨大差距.
- 对于患有RCPD的患者来说,有必要开发更多可访问,可操作和高质量的数字资源.
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