为理解设计:格式如何影响理解和对人工智能生成的患者友好型放射学报告的信心
Bonnie A Armstrong1, Zhongnan Fang1, Andrew Johnston2
1Department of Radiology, Stanford University, Palo Alto, California, United States; AI Development and Evaluation Lab, Stanford University, Palo Alto, California, United States.
Journal of the American College of Radiology : JACR
|March 11, 2026
概括
人工智能生成的患者友好报告 (PFR) 的格式显著影响理解. 与字典格式相比,句子和块格式提高了理解和信心,基于句子的格式培养了最大的信任.
科学领域:
- 医疗信息学 医疗信息学
- 人与计算机的交互
- 卫生沟通健康沟通
背景情况:
- 人工智能 (AI) 越来越多地用于从复杂的医疗信息中生成患者友好的报告 (PFR).
- 优化人工智能生成的PFR的呈现格式对于有效的患者理解和参与至关重要.
研究的目的:
- 评估不同格式的AI产生的PFR如何影响普通人对医疗信息的理解.
- 为了比较基于字典,块和句子的PFR格式的有效性.
主要方法:
- 一项涉及116名参与者的内科研究.
- 参与者审查了放射学报告与AI生成的PFRs在三个格式:字典,块,和基于句子.
- 测量了客观/主观理解,信心和响应时间.
主要成果:
- 与字典格式相比,句子和块格式显著改善了客观和主观理解.
- 基于句子的格式产生了最高的信任水平,表明信任增强.
- 句子和块格式的响应时间更快;更长的报告和更高的健康信心减缓了响应.
结论:
- 人工智能生成的PFR的呈现格式是普通人理解和信任的关键因素.
- 基于句子和块格式的格式优于PFR的字典格式.
- 用户界面设计对人工智能驱动的患者沟通的有效性起着至关重要的作用.
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