由ChatGPT生成的定制教育表提高了家长访问满意度和儿童心脏导管注射之前的程序知识
Sarah Pradhan1, Kate McCormick2, Luc Mertens2
1Labatt Family Heart Center, The Hospital for Sick Children, Division of Cardiology, Temerty School of Medicine, Toronto, ON, Canada. sarah.pradhan6@gmail.com.
Pediatric cardiology
|October 29, 2025
概括
像GPT-4这样的大型语言模型 (LLM) 可以创建个性化的儿科心脏导管教育材料. 这提高了家庭的理解和诊所的满意度,使复杂的信息适应特定的阅读水平.
科学领域:
- 儿童心脏病学 儿童心脏病学
- 医疗教育 医学教育
- 医疗保健中的人工智能
背景情况:
- 书面教育材料是有效的手术前信息传递.
- 根据父母教育水平量身定制的使用大语言模型 (LLM) 的个性化教育材料尚未在儿科心脏病学中被描述.
研究的目的:
- 评估ChatGPT在产生不同读数级别的儿科心脏导管信息表中的实用性.
- 改善家庭对程序的理解和对诊所的满意度.
主要方法:
- 一项前性质量改进研究利用ChatGPT创建了6年级和10年级阅读水平的信息表.
- 调查评估了家长的理解和临床满意度,使用利克特尺度.
- 26个家庭参与了这项研究.
主要成果:
- 在要求的阅读水平上,ChatGPT迅速生成了准确的信息表.
- 父母对心脏导管程序的理解显著改善 (平均利克尔特分数增加0.57,p <0.01).
- 96%的家庭报告说,了解程度有所改善,家庭报告说,诊所访问满意度更高 (平均得分为4.5±0.8).
结论:
- 像GPT-4这样的大型语言模型 (LLM) 是将医学教育定制为特定阅读水平的有价值工具.
- 通过提高家庭对复杂儿科心脏病手术的理解和满意度,LLM可以增加手术前访问.
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