人工智能作为护理学生临床表现的关键预测因素:伊朗的一项横截面研究
Rasool Paygozar1, Noorollah Tahery2, Samaneh Dehghan Abnavy3
1Nursing Midwifery Research Center, Nursing and Midwifery School, Abadan University of Medical Sciences, Abadan, Iran. paygozarrasol@gmail.com.
BMC medical education
|December 13, 2025
概括
人工智能 (AI) 的使用显著提高了护理学生的临床表现,作为一个独立的预测器. 将人工智能素养纳入护理课程对于改善基于证据的实践和患者护理至关重要.
科学领域:
- 护理教育 护理教育
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
背景情况:
- 人工智能 (AI) 在医疗保健教育中的作用正在扩大.
- 它对护理学生临床表现的具体影响,特别是在资源有限的环境中,需要进一步调查.
研究的目的:
- 检查人工智能利用和临床表现在本科护理学生之间的关联.
- 为了控制这种关系中的人口因素.
主要方法:
- 这是一项涉及134名阿巴丹医学科学大学护理学生的横截面研究.
- 通过人工智能护理问卷和临床绩效问卷 (CPQ) 收集的数据.
- 统计分析包括相关性,多重线性回归和单变通用线性建模 (GLM).
主要成果:
- 人工智能使用与整体临床表现有显著的正相关性 (r = 0.424,p < 0.001).
- 在回归模型中,人工智能使用是唯一重要的预测因素,解释了21.1%的性能差异 (R2 = 0.211).
- 人工智能在所有临床子规模中使用独立预测的性能,特别是在研究,以患者为中心的护理和个人管理方面.
结论:
- 人工智能使用是护理学生临床表现的强大,独立的预测指标.
- 研究结果支持将人工智能素养纳入护理课程,以促进基于证据的实践和批判性思维.
- 人工智能对临床护理教育具有变革性的潜力.
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