用GPT增强的社交机器人用于患者沟通:试点研究
Jan-Willem J R van 't Klooster1, Michela Capasso2, Daan van Gorssel1
1Behavioural Management and Social Sciences, University of Twente, Enschede, Netherlands.
Frontiers in digital health
|February 12, 2026
概括
这项研究表明,人工智能社交机器人可以有效地向患者传达健康信息. 这项使用生成预训练变压器 (GPT) 大语言模型 (LLM) 的技术可用于临床应用.
科学领域:
- 医疗保健中的人工智能
- 人与机器人的交互
- 临床通信系统 临床通信系统
背景情况:
- 有效的患者沟通对于高质量的医疗保健至关重要.
- 医疗保健专业人员面临越来越多的需求,需要提供信息的创新解决方案.
- 当前的沟通方法难以满足对可访问的患者信息日益增长的需求.
研究的目的:
- 开发和测试人工智能驱动的社会机器人的可行性,以传递治疗和疾病信息.
- 在临床环境中支持患者的沟通和信息交换.
- 在临床环境中评估使用AI社交机器人的用户体验.
主要方法:
- 一个人工智能增强的社会机器人架构被开发出来,利用一个生成预训练变压器 (GPT) 大语言模型 (LLM).
- 机器人被连接到白名单上,验证的临床信息来源.
- 通过基于实验室的试点研究和在骨关节炎 (OA) 用例中的实施来评估可行性和用户体验,使用用户体验问卷 (UEQ) 和半结构面试.
主要成果:
- 试点测试显示了良好的吸引力,透视性和刺激,具有很好的新性,尽管可靠性和效率低于平均水平.
- 在临床环境中,患者的UEQ得分显示了效率,发明力和可接受性 (平均2.13) 的积极趋势.
- 医疗保健专业的UEQ分数平均为1.89,大多数指标都高于1,除了使用的兴奋.
结论:
- 这项研究表明,在临床实践中实施GPT增强的社交机器人来实现患者沟通的可行性.
- 由人工智能驱动的社交机器人显示出提高患者参与度和信息可访问性的潜力.
- 进一步的开发可以解决诸如可靠性和效率等领域的更广泛的临床采用.
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