大型语言模型在定性护理研究中的应用:一个范围审查
Tingting Zhou1, Mengyao Xing2, Yue Hu3
1School of Nursing, Zhejiang Chinese Medicine University, Hangzhou, Zhejiang Province, China.
Nursing outlook
|September 12, 2025
概括
大型语言模型 (LLM) 在定性护理研究中显示出主题生成和文本分析效率的前景. 然而,它们在理论框架和面试问题开发等领域的应用仍然有限,这表明它们的发展处于早期阶段.
科学领域:
- 护理研究 护理研究
- 医疗保健中的人工智能
- 定性数据分析 数据分析.
背景情况:
- 大型语言模型 (LLM) 为定性护理研究提供先进的自然语言处理.
- 目前对LLM应用背景和护理效果的系统探索是有限的.
研究的目的:
- 在定性护理研究中对LLM应用进行范围审查.
- 探索当前的场景,影响,评估方法和LLMs在这个领域的挑战.
主要方法:
- 范围审查方法遵循乔安娜·布里格斯和PRISMA-ScR标准.
- 在11个数据库中进行文献搜索,截至2025年4月.
- 搜索术语包括护理,大型语言模型和定性研究/分析.
主要成果:
- 从2,478篇文章中包含了11项研究.
- 士课程的应用包括主题生成,角色扮演和面试问题生成.
- 在主题生成和优异的文本分析效率方面,LLM与人类输出具有中等至高的相似性,但在理论框架和代码书开发方面遇到了困难.
结论:
- 在定性护理研究中的LLM应用程序被系统地概述,强调潜在和局限性.
- 目前在护理研究中的LLM应用是新生的,需要进一步开发.
- 未来的研究应该专注于改善LLMs的分析深度,模拟准确性和评估工具.
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