评估定性研究中的数据充分性。

IF 5.3 2区 教育学 Q1 EDUCATION, SCIENTIFIC DISCIPLINES
Academic Medicine Pub Date : 2025-06-01 Epub Date: 2025-01-06 DOI:10.1097/ACM.0000000000005972
Danica Sims, Francois Cilliers
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引用次数: 0

摘要

摘要:在进行定性研究时,研究人员经常使用数据饱和的概念来证明足够的采样以停止数据收集和分析。我们认为,这揭示了一种与定性研究不相容的实证主义观点,而定性研究则是基于建构主义、解释主义或其他观点。相反,我们推荐了信息力量,2概念深度,3和理论充分性,1,4,5的概念,在研究设计中考虑数据充分性,并在整个抽样,数据收集和分析过程中反复评估。下表为何时需要更多或更少的数据来证明停止数据收集和分析的合理性提供了指导。研究人员和读者都可以使用评估数据充分性的标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing Data Adequacy in Qualitative Research Studies.

When undertaking qualitative research studies, researchers often use the concept of data saturation to justify sufficient sampling to cease data collection and analysis. We argue that this reveals a positivist perspective that is incompatible with qualitative research, 1 which is instead based on constructivist, interpretivist, or other perspectives. Instead, we recommended the concepts of information power , 2conceptual depth , 3 and theoretical sufficiency , 1,4,5 with data adequacy considered during research design and evaluated iteratively throughout the sampling, data collection, and analysis processes. The table below provides guidelines for when more, or less, data are needed to justify cessation of data collection and analysis. Both researchers and readers can use the criteria for assessing data adequacy.

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来源期刊
Academic Medicine
Academic Medicine 医学-卫生保健
CiteScore
7.80
自引率
9.50%
发文量
982
审稿时长
3-6 weeks
期刊介绍: Academic Medicine, the official peer-reviewed journal of the Association of American Medical Colleges, acts as an international forum for exchanging ideas, information, and strategies to address the significant challenges in academic medicine. The journal covers areas such as research, education, clinical care, community collaboration, and leadership, with a commitment to serving the public interest.
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