在助产教育中使用生成人工智能的远程医疗模拟:以人为中心和文化响应的护理实践
Hannah Cole McGrew1, Kendra Faucett1, Regina G Russell1
1Vanderbilt University School of Nursing, Nashville, Tennessee.
人工智能 (AI) 模拟提供了一种培训文化敏感远程医疗的新方法. 这项试点研究表明,人工智能可以有效地为学生准备各种患者互动,改善文化上适当的护理.
科学领域:
- 医疗教育
- 数字健康
- 医疗保健中的人工智能
背景情况:
- 助产教育需要多元化的患者互动,
- 助产学生接触不同患者群体的机会有限.
- 健康差异可能会因缺乏文化敏感的护理技能而加剧.
研究的目的:
- 为助产学生提供在线人工智能 (AI) 模拟平台.
- 准备学生以人为本的远程医疗服务,
- 评估人工智能驱动的模拟在助产教育中的可行性和有效性.
主要方法:
- 使用生成性人工智能平台创建交互式虚拟患者化身.
- 学生与人工智能化身进行自发的,适应性的对话.
- 评估了易用性,形象忠实性,文化包容性,学生学习,时间和成本.
主要成果:
- 人工智能平台展示了在文化上响应远程医疗方面的潜力.
- 它们的关键特征是忠实于化身以及能够融入多元文化元素.
- 案例开发需要一个协作和代的方法,以获得最佳的结果.
结论:
- 生成型人工智能模拟提供了一种高效灵活的培训方法.
- 基于人工智能的模拟,就像传统的方法一样,需要规划和汇报以获得最大的学习.
- 这项技术可以提高助产学生对以患者为中心,文化相适应的远程医疗的准备.
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