先进实践护士领导行为的决定因素和结果:人工智能辅助混合方法系统审查协议
Vincent Put1, Hanne Kindermans1, Ann Van Hecke2,3
1Faculty of Medicine and Life Sciences, Research Group Healthcare & Ethics, UHasselt, Agoralaan, Diepenbeek, 3590, Belgium.
Systematic reviews
|December 30, 2025
概括
这项研究系统地审查高级实践护士的领导行为,确定影响他们及其结果的因素. 人工智能工具将增强证据合成,以改善护理领导力计划.
科学领域:
- 护理 护理 护理
- 医疗保健管理的管理
- 医疗保健服务研究 医疗服务研究
背景情况:
- 高级实践护士 (APN) 对医疗保健创新和患者的结果至关重要.
- 领导力是APN的核心能力,但在领导角色中面临挑战.
- 缺乏关于APN领导力决定因素和结果的全面证据基础.
研究的目的:
- 系统地审查高级实践护士领导行为决定因素和结果.
- 为制定授权APN担任领导角色的计划提供信息.
- 探索人工智能在提高系统审查效率方面的实用性.
主要方法:
- 根据PRISMA-P 2015指南进行系统审查.
- 跨定量,定性和混合方法研究的资格标准的SPIDER工具.
- 使用ASReview LAB进行人工智能辅助的标题和摘要选,并进行人类验证.
- 量化数据的叙述综合和定性数据的元聚合.
主要成果:
- 本协议概述了一种系统的方法来识别影响APN领导力的因素.
- 它详细介绍了合成关于APN领导力决定因素和结果的证据的方法.
- 该研究将为APN的基于证据的领导力发展计划提供基础.
结论:
- 解决了理解APN领导力的关键差距.
- 调查结果将为定制的计划提供信息,以最大限度地发挥APN的领导潜力.
- 展示了人工智能在护理高效和严格的研究合成中的作用.
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