患者对谈话人工智能的看法对于心房的自我管理:定性分析
Ritu Trivedi1, Tim Shaw1,2, Brodie Sheahen1
1Westmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia.
Journal of medical Internet research
|March 12, 2025
概括
患者发现对话式人工智能 (AI) 参与心房动 (AF) 自主管理和教育. 主要改进包括更灵活的对话和个性化内容,以更好地支持患者.
科学领域:
- 数字健康数字健康
- 医疗保健中的人工智能
- 患者支持系统 患者支持系统
背景情况:
- 交谈式人工智能 (AI) 提供了引人入胜的互动,但其用于支持心房动 (AF) 患者的用途尚不清楚.
- 在AF患者护理中,人工智能的可接受性,障碍和促进因素需要探索.
研究的目的:
- 在CHAT-AF试验中,探索患者对接受对话性AI程序支持的观点.
- 调查患者对人工智能驱动的健康支持的经验,以管理心房动.
主要方法:
- 与30名接受6个月对话性AI干预的AF患者进行了半结构化采访.
- 该干预涉及使用语音识别和自然语言处理进行健康评估和自我管理支持的自动电话.
- 采访数据被主题分析,以确定患者的主题.
主要成果:
- 出现了四个主题:交互质量 (类似人类,响应限制,可信度),参与因素 (个性化,交付方式,频率),改善对护理/信息的访问,以及增强自我管理能力.
- 患者欣赏了持续的支持,并加强了获得健康信息的机会.
- 人工智能鼓励健康的习惯,并提供放心,赋予患者在他们的AF自我管理.
结论:
- 交谈式人工智能被认为是AF教育和自我管理支持的有吸引力的工具.
- 患者希望进行更灵活的对话,以进行自然对话,并更好地将AI内容定制到他们特定的健康环境中.
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