虚拟患者教育对提高护理学生临床推理的影响
Masoud Bahrami1, Arash Hadadgar2, Masoumeh Fuladvandi3
1Department of Nursing and Midwifery, Cancer Prevention Research Center, School of Nursing and Midwifery, Isfahan University of Medical Sciences, Isfahan, Iran.
Iranian journal of nursing and midwifery research
|January 23, 2026
概括
虚拟患者 (VP) 教育显著提高了护理学生的临床推理 (CR) 技能. 这种创新方法通过为培养批判性思维能力提供实用基础来增强护理教育.
科学领域:
- 护理教育 护理教育
- 医疗模拟 医疗模拟
- 健康 专业 教育 卫生 专业 教育
背景情况:
- 临床推理 (CR) 是护理学生的一个关键能力.
- 在护理课程中,开发有效的CR技能是一个重大挑战.
- 瘤护理教育需要先进的CR能力.
研究的目的:
- 调查虚拟患者 (VP) 教育对提高护理学生CR技能的影响.
- 为了评估基于VP的瘤学模块对护理学生的有效性.
主要方法:
- 一个准实验性的,前测试后测试研究,涉及148名护理学生.
- 随机分配到干预组 (VP教育) 或对照组.
- 经过验证的23项测试 (KF) 评估了6周干预前后的CR技能.
主要成果:
- 两组之间在预测CR得分上没有显著差异.
- 与对照组相比,干预组在测试后的CR得分显著增加 (p ≤0.05).
- 从预测到后测试的干预组中观察到CR技能显著改善 (p ≤0.05).
结论:
- 虚拟患者教育是改善护理学生临床推理的有效策略.
- VP教育为提高护理教育质量提供了有价值的工具.
- 这种方法可以作为未来护士培养更强大的临床决策技能的基础.
相关概念视频
Nursing Clinical Information System
1.3K
Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
1.3K
Reason and Intuition
7.4K
The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
7.4K
Reasoning
416
Reasoning is the action of thinking about something in a logical, sensible way. It is integral to problem-solving, decision-making, and critical thinking. Reasoning can be inductive or deductive. Reasoning involves transforming information into conclusions, which is essential for problem-solving, decision-making, and critical thinking.
Inductive reasoning involves deriving generalizations from specific observations. This type of reasoning helps form beliefs about the world. For example,...
Inductive reasoning involves deriving generalizations from specific observations. This type of reasoning helps form beliefs about the world. For example,...
416
Deductive Reasoning
65.0K
Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning, which means that it uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid.
For example, a researcher can deduce specific predictions...
For example, a researcher can deduce specific predictions...
65.0K
Inductive Reasoning
65.8K
Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. It is uncertain and operates in degrees to which the conclusions are credible. As such, inductive arguments can be weak or strong, rather than valid or invalid, and conclusions can be used to formulate testable, falsifiable hypotheses.
Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or...
Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or...
65.8K
Student t Distribution
13.6K
The population standard deviation is rarely known in many day-to-day examples of statistics. When the sample sizes are large, it is easy to estimate the population standard deviation using a confidence interval, which provides results close enough to the original value. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
The Student t distribution was developed by William S. Goset (1876–1937) of the...
The Student t distribution was developed by William S. Goset (1876–1937) of the...
13.6K


