Babchuk Wayne A
Anthropology, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.
Educational Psychology, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.
Fam Med Community Health. 2019 Apr 1;7(2):e000040. doi: 10.1136/fmch-2018-000040. eCollection 2019.
The primary purpose of this article is to provide family physician researchers interested in conducting a qualitative research study a concise guide to the analysis. Drawing from approaches outlined in popular research methodology textbooks and employing an exemplar from a minority health disparities research study, this article outlines specific steps useful for researchers and practitioners in the field of family medicine. This process of qualitative data analysis is situated within the larger framework of qualitative research to better position those new to qualitative designs to more effectively conduct their studies. A 10-step process useful for guiding qualitative data analysis is provided. The 10 steps include (1) assembling data for analysis, (2) refamiliarising oneself with the data, (3) open or initial coding procedures, (4) generating categories and assigning codes to them, (5) generating themes from categories, (6) strategies of validation, (7) interpreting and reporting findings from the participants, (8) interpreting and reporting findings from the literature, (9) visual representations of data and findings, and (10) strengths, limitations, delimitations and suggestions for future research. This work provides clear and accessible guidelines for conducting qualitative data analysis for emerging researchers that is applicable across a wide array of topics, disciplines and settings.
本文的主要目的是为有兴趣开展定性研究的家庭医生研究人员提供一份简洁的分析指南。本文借鉴了流行的研究方法教科书中概述的方法，并采用了一项少数族裔健康差异研究的范例，概述了对家庭医学领域的研究人员和从业者有用的具体步骤。定性数据分析过程置于定性研究的更大框架内，以便让那些对定性设计不熟悉的人能更好地更有效地开展他们的研究。本文提供了一个有助于指导定性数据分析的10步流程。这10个步骤包括：（1）收集用于分析的数据；（2）重新熟悉数据；（3）开放式或初始编码程序；（4）生成类别并为其分配代码；（5）从类别中生成主题；（6）验证策略；（7）解释和报告参与者的发现；（8）解释和报告文献中的发现；（9）数据和发现的可视化表示；以及（10）优势、局限性、界定范围和对未来研究的建议。这项工作为新兴研究人员进行定性数据分析提供了清晰易懂的指南，适用于广泛的主题、学科和环境。
