Medical Teacher· 2020Q1
Thematic analysis of qualitative data: AMEE Guide No. 131
- 3,711citations
- Q1SCImago
- 2020year
Short summary
This guide clarifies thematic analysis, a common but often misunderstood qualitative data method, by defining its philosophical underpinnings, appropriate uses across epistemologies, and providing a six-step framework with examples.
AI-generated from the title and abstract; the full text is not read.
Key points
- Clarifies the philosophical underpinnings of thematic analysis.
- Defines 'theme' precisely to avoid misapplication.
- Outlines a six-step framework for conducting thematic analysis.
- Provides examples to illustrate each step of the analysis process.
AI-generated from the title and abstract; the full text is not read.
Abstract
Thematic analysis is a widely used, yet often misunderstood, method of qualitative data analysis. It is a useful and accessible tool for qualitative researchers, but confusion regarding the method’s philosophical underpinnings and imprecision in how it has been described have complicated its use and acceptance among researchers. In this Guide, we outline what thematic analysis is, positioning it in relation to other methods of qualitative analysis, and describe when it is appropriate to use the method under a variety of epistemological frameworks. We also provide a detailed definition of a theme, as this term is often misapplied. Next, we describe the most commonly used six-step framework for conducting thematic analysis, illustrating each step using examples from our own research. Finally, we discuss advantages and disadvantages of this method and alert researchers to pitfalls to avoid when using thematic analysis. We aim to highlight thematic analysis as a powerful and flexible method of qualitative analysis and to empower researchers at all levels of experience to conduct thematic analysis in rigorous and thoughtful way.
The authors' abstract, as published at the source. Medical Teacher, 2020 · DOI ↗
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Field: Management Science and Operations Research
Management Science and Operations ResearchDecision Sciences