数据和和信息力量:定性研究中的样本大小 - 什么时候足够,如何评估?
Sara-Jane Roberts1, Martha Abshire Saylor2, Serra Ivynian1
1University of Technology Sydney, Improving Palliative, Aged and Chronic Care through Clinical Research and Translation (IMPACCT), PO Box 123, Broadway, NSW 2007, Australia.
European journal of cardiovascular nursing
|February 16, 2026
概括
定性研究的样本大小是由数据和而不是功率计算决定的. 信息力量为估计样本大小提供了一个框架,确保在定性研究中提供足够的数据以进行可靠的调查结果.
科学领域:
- 卫生科学 卫生科学 卫生科学
- 社会科学 社会科学 社会科学
背景情况:
- 定性调查对于理解患者在心血管保健方面的经验至关重要,它补充了定量数据.
- 传统的定量研究使用了对样本大小的功率计算,这种方法不适用于定性研究.
- 数据和,定义为"没有新信息出现",是确定定性样本大小的当前标准,但在没有方法透明度的情况下可能存在问题.
研究的目的:
- 探索数据和,信息冗余,并引入信息力量作为在定性研究中确定适当样本大小的替代方案.
- 为研究人员提供一个框架,用于在定性研究中估计样本大小,协助资助申请和持续的数据收集/分析.
主要方法:
- 讨论数据和及其操作定义.
- 介绍和探索信息力量的概念.
- 确定评估信息力量的五个关键考虑因素:狭窄的研究目标,样本特异性,理论使用,对话质量和分析策略.
主要成果:
- 在定性研究中,信息力量为估计样本大小提供了一个结构化的方法.
- 信息力量的概念在研究前和研究期间提供指导,以确定适当的样本大小.
- 五个因素有助于在定性研究中实现足够的信息能力.
结论:
- 信息力量是一个有价值的概念,可以确保在定性研究中获得适当的样本大小,超越简单的数据和的局限性.
- 该框架有助于研究人员对样本大小做出明智的决定,提高定性研究的严谨性和透明度.
- 提出的方法有助于研究人员选择最合适的方法来确定"足够"的数据来支持定性发现.
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