Green Julie, Willis Karen, Hughes Emma, Small Rhonda, Welch Nicky, Gibbs Lisa, Daly Jeanne
Youth Research Centre, Melbourne Education Research Institute, University of Melbourne, Victoria, Australia.
Aust N Z J Public Health. 2007 Dec;31(6):545-50. doi: 10.1111/j.1753-6405.2007.00141.x.
To outline the importance of the clarity of data analysis in the doing and reporting of interview-based qualitative research.
We explore the clear links between data analysis and evidence. We argue that transparency in the data analysis process is integral to determining the evidence that is generated. Data analysis must occur concurrently with data collection and comprises an ongoing process of 'testing the fit' between the data collected and analysis. We discuss four steps in the process of thematic data analysis: immersion, coding, categorising and generation of themes.
Rigorous and systematic analysis of qualitative data is integral to the production of high-quality research. Studies that give an explicit account of the data analysis process provide insights into how conclusions are reached while studies that explain themes anchored to data and theory produce the strongest evidence.
概述在基于访谈的定性研究的实施与报告中,数据分析清晰性的重要性。
我们探究了数据分析与证据之间的明确联系。我们认为,数据分析过程中的透明度对于确定所产生的证据不可或缺。数据分析必须与数据收集同时进行,并且包括一个对所收集数据与分析之间进行“检验契合度”的持续过程。我们讨论了主题数据分析过程中的四个步骤:沉浸、编码、分类和主题生成。
对定性数据进行严谨且系统的分析是高质量研究的必要组成部分。明确阐述数据分析过程的研究能让人深入了解结论是如何得出的,而解释基于数据和理论的主题的研究则能产生最有力的证据。