在护士教育中使用预先训练的基于变压器的虚拟患者进行健康评估和沟通培训:混合方法研究
Jiyoung Kim1, Jiyeong Won1, Yuran Lee1
1School of Nursing, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea.
Nurse education in practice
|September 3, 2025
概括
基于生成预训练变压器 (GPT) 的虚拟患者通过提高沟通自我效能和感知学习环境来增强护理教育. 提供教育效益的同时,还需要技术改进以实现最佳整合.
科学领域:
- 护士教育
- 医疗保健中的人工智能
- 虚拟学习环境
背景情况:
- 传统的护士培训方法有其局限性,包括成本,时间和心理压力.
- 发电预训练变压器 (GPT) 为教育应用提供类似人类的对话能力.
- 在传统的护士教育中, GPT 提供了一种新的方法来克服挑战.
研究的目的:
- 评估基于GPT的虚拟患者在护理教育中的有效性.
- 评估可用性,感知学习环境和沟通中的自我效能.
- 在基于GPT的虚拟患者模拟中确定参与者的经验和改进领域.
主要方法:
- 使用混合方法设计.
- 28名未来的护士与基于GPT的虚拟患者互动,使用头部显示器模拟急性尾炎.
- 分析了用户的可用性,虚拟学习环境的感知,沟通的自我效能和对话的质量.
主要成果:
- 在功能和虚拟学习环境的可访问性方面获得了高分.
- 观察到沟通自我有效性的统计显著增加 (p=. 009).
- 参与者的反强调了教育方面的好处与技术上的局限性,对话的可读性得分高,准确性得分低.
结论:
- 基于GPT的虚拟患者在提高护理教育方面表现有前途,特别是提高沟通技巧和沉浸能力.
- 这项研究表明,GPT有很大的潜力提高学习者信心和参与度.
- 建议进一步开发以解决技术限制,并提高对话准确性以实现更有效的模拟.
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