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评估人工智能生成的关于妊娠期糖尿病的患者教育材料:内容和质量评估
1Author's Affiliation: Midwifery Department, Faculty of Health Sciences, Sinop University, Sinop, Turkey.
The Journal of perinatal & neonatal nursing
|July 29, 2025
概括
人工智能为孕期糖尿病 (GDM) 生成的患者教育材料具有高度可读性和可操作性. 聊天GPT和双子座制作了专家们发现易于理解的GDM孕妇的内容.
科学领域:
- 医疗教育 医学教育
- 医疗保健中的人工智能
- 患者教育 患者教育
背景情况:
- 有效的疾病管理依赖于可访问的知识来源.
- 人工智能 (AI) 平台正在成为患者教育材料的潜在主要来源.
- 评估人工智能产生的内容对于其融入医疗保健至关重要.
研究的目的:
- 评估AI创建的关于妊娠糖尿病 (GDM) 的患者教育材料的内容质量和可读性.
- 为了比较ChatGPT和Gemini为GDM患者生成的教育材料.
主要方法:
- 使用描述性研究设计,从GDM指南中产生问题.
- 问题被提交给ChatGPT和Gemini,以创建患者教育材料.
- 内容由11名专家使用PEMAT-P工具进行评估,可读性使用Ateşman和枪雾指数进行评估.
主要成果:
- 人工智能平台从32个GDM相关问题中生成了教育材料.
- 可读性得分为77.8 (阿特斯曼) 和16.25 (枪雾).
- 专家通过PEMAT-P. 评价可理解性为91.36%,可操作性为89.67%.
结论:
- 人工智能生成的GDM教育材料具有很高的可读性,对患者来说是可以理解和可操作的.
- 这些人工智能工具显示出开发患者教育资源的巨大潜力.
- 需要进一步的实验研究来证实人工智能生成的患者教育材料的长期有效性.
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