解锁患者教育的未来:聊天GPT与 LexiComp®作为患者教育材料的来源
概括
与 LexiComp® 相比,ChatGPT 患者教育材料在可理解性方面相似,但阅读水平和可变准确性更高. 在例行使用前需要进一步评估药物信息.
科学领域:
- 医疗保健技术 技术 医疗保健 技术
- 人工智能的人工智能
- 患者教育 患者教育
背景情况:
- 像ChatGPT这样的对话式人工智能 (AI) 越来越多地用于医疗保健.
- 评估人工智能产生的健康信息的准确性和可理解性至关重要.
研究的目的:
- 评估ChatGPT与药物相关的患者教育材料 (PEMs) 的可理解性,可读性和准确性.
- 将ChatGPT PEM与基于证据的第三级参考资源 LexiComp®进行比较.
主要方法:
- 8种常见药物的PEMs是由ChatGPT和 LexiComp®生成的.
- 材料使用可打印的患者教育材料评估工具 (PEMAT-P),Flesch阅读方便性,Flesch Kincaid等级水平和准确性检查清单进行评估.
- 调查人员的共识确定了准确性标准,以 LexiComp® 为对照.
主要成果:
- 在ChatGPT和 LexiComp® (77.9%和72.5%) 之间,PEMAT-P可理解性得分没有显著差异.
- 聊天GPT表现出更高的阅读等级水平 (8.6对5.6) 和较低的字数.
- 聊天GPT PEM 显示了可变的准确性,平均为 61% (29%-86%).
结论:
- 聊天GPT PEM 显示了相似的可理解性,但没有达到目标学年级水平.
- 虽然减少单词数和被动句子可能有利于患者,但不一致的准确性限制了目前用于药物教育的使用.
- 在ChatGPT可以被例行采用用于生成与药物相关的患者教育材料之前,需要进一步验证.
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