To saturate or not to saturate? Questioning data saturation as a useful concept for thematic analysis and sample-size rationales
To saturate or not to saturate? Questioning data saturation as a useful concept for thematic analysis and sample-size rationales
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DOI：
10.1080/2159676x.2019.1704846
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发表时间：
2019-12-27
影响因子：
4.9
通讯作者：
Clarke, Victoria
中科院分区：
文献类型：
--
作者：
Braun, Virginia;Clarke, Victoria
数据饱和的概念，定义为“信息冗余”或没有新的主题或代码从数据中“出现”的点，被广泛引用的主题分析（TA）研究在体育和运动，以及超越。一些研究人员试图“操作化”数据饱和，并提供具体的指导，多少访谈，或焦点小组，足以实现某种程度的数据饱和在TA研究。我们不同意这种试图为TA“捕获”数据饱和的做法，这导致了我们的评论。在这里，我们有助于批判性的讨论的饱和度概念在定性研究中，通过询问周围的实践和程序的TA，告知这些数据饱和度的“实验”的假设，和饱和度的概念化信息冗余。我们认为，虽然数据，主题或代码饱和，甚至意义饱和的概念，是一致的新实证主义，发现导向，意义挖掘项目的编码可靠性类型的TA，他们是不符合的价值观和假设的自反性TA。我们鼓励体育和运动以及其他使用反身性TA的研究人员处理不确定性，并认识到意义是通过对数据的解释而产生的，而不是从数据中挖掘出来的，因此关于“有多少”数据项以及何时停止数据收集的判断是不可避免的，主观的，并且不能在分析之前（完全）确定。
The concept of data saturation, defined as 'information redundancy' or the point at which no new themes or codes 'emerge' from data, is widely referenced in thematic analysis (TA) research in sport and exercise, and beyond. Several researchers have sought to 'operationalise' data saturation and provide concrete guidance on how many interviews, or focus groups, are enough to achieve some degree of data saturation in TA research. Our disagreement with such attempts to 'capture' data saturation for TA led us to this commentary. Here, we contribute to critical discussions of the saturation concept in qualitative research by interrogating the assumptions around the practice and procedures of TA that inform these data saturation 'experiments', and the conceptualisation of saturation as information redundancy. We argue that although the concepts of data-, thematic- or code-saturation, and even meaning-saturation, are coherent with the neo-positivist, discovery-oriented, meaning excavation project of coding reliability types of TA, they are not consistent with the values and assumptions of reflexive TA. We encourage sport and exercise and other researchers using reflexive TA to dwell with uncertainty and recognise that meaning is generated through interpretation of, not excavated from, data, and therefore judgements about 'how many' data items, and when to stop data collection, are inescapably situated and subjective, and cannot be determined (wholly) in advance of analysis.