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相关概念视频

Data Validation01:03

Data Validation

5.3K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
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Reliability and Validity01:29

Reliability and Validity

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Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
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Formulating and Validating Nursing Diagnosis II01:25

Formulating and Validating Nursing Diagnosis II

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Nursing diagnoses represent a problem validated by major defining characteristics. There are four categories of nursing diagnoses: problem-focused, risk, health promotion or wellness, and syndrome. The anatomy of a nursing diagnosis includes three components: problem statement or diagnostic label, defining characteristics, and related factors.
Risk nursing diagnoses represent clinical judgments of an individual, family, or community more vulnerable to developing the health problem than others...
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The Scientific Method in Nursing Process01:18

The Scientific Method in Nursing Process

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The scientific method provides the foundation for any research. It is the most reliable and objective of all forms of gaining knowledge and guides in applying research-based evidence in practice and conducting future research.
When using research findings to change practice, one must understand the process used to guide a study. The scientific method is a systematic, step-by-step process that supports the data's validity, reliability, and generalizability. As a result, findings can be...
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Cross-Sectional Research01:50

Cross-Sectional Research

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In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
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Nursing Interventions II: Selecting and Classifying the Nursing Interventions01:29

Nursing Interventions II: Selecting and Classifying the Nursing Interventions

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Creating and executing a nursing diagnosis helps nurses plan care and guide patient, family, and community interventions. They are developed based on a patient's physical evaluation and support measuring the outcomes. It is not recommended to select random interventions throughout the planning process. Instead, consider the following six essential factors when choosing interventions:
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Updated: Sep 12, 2025

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
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了解基于证据的护理:在双国多中心研究中验证因子结构

Florian Kücking1, Jane Vavanikunnel1, Hanna Burkhalter2

  • 1Research Centre of Health and Social Informatics, Osnabrück University of Appl. Sci., Osnabrück, Germany.

Studies in health technology and informatics
|August 8, 2025
PubMed
概括
此摘要是机器生成的。

了解知识,信任和实践等基于证据的护理 (EBN) 维度对于医疗保健至关重要. 这项研究在德国和瑞士护士中验证了这些维度,证实了它们的结构,以更好地使用EBN和临床决策支持系统 (CDSS).

关键词:
基于证据的实践实践.尺寸 尺寸 尺寸 尺寸 尺寸 尺寸护理 护理 护理

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科学领域:

  • 护理科学 护理科学
  • 医疗保健信息学 医疗保健信息学

背景情况:

  • 基于证据的护理 (EBN) 对于高质量的患者护理和有效使用临床决策支持系统 (CDSS) 是必不可少的.
  • 之前的研究发现了EBN的三个核心维度:知识,信任和实践.
  • 为了进行标准化的评估,需要在不同的环境中验证这些维度.

研究的目的:

  • 在双国,多中心的环境中验证EBN的三个维度 (知识,信任,实践).
  • 在德国和瑞士的护士中确认EBN维度的因数结构.
  • 为改善EBN实践和利用CDSS提供基础.

主要方法:

  • 使用先前开发的EBN问卷对402名护士的答案进行了因子分析.
  • 两国和多中心的研究设计,涉及来自德国和瑞士的护士.
  • 统计分析以确定和验证EBN的基础因素结构.

主要成果:

  • 确定了EBN (信任,知识,实践) 的强大的三维因子结构,解释了52.9%的差异.
  • 因素结构在德国和瑞士保持一致,表明跨文化有效性.
  • 每个维度都有特定的组件:信任 (动机,重要性,态度,使用),知识 (态度,行为) 和实践 (团队,患者,知识导向).

结论:

  • 该研究成功验证了EBN在不同机构和国家的三维结构.
  • 鉴定的因素结构为评估EBN提供了可靠的框架.
  • 进一步的研究应该集中在比较测量仪器和开发一个统一的工具标准化EBN评估,以提高实践和CDSS利用.