Braun and Clarke’s Approach to Thematic Analysis
Thematic analysis (TA) is a foundational method in qualitative research, providing a structured yet flexible approach to analysing data. Virginia Braun and Victoria Clarke’s approach to thematic analysis, introduced in their seminal 2006 paper, has become a cornerstone for researchers looking to identify, analyse, and report patterns (themes) within data. Here’s a closer look at Braun and Clarke’s method and why it’s so valuable.
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What is Thematic Analysis?
Thematic analysis is a method for identifying, analysing, and reporting patterns (themes) within data. It is not tied to a particular theoretical framework, making it adaptable and versatile across various research contexts. Braun and Clarke’s approach is particularly celebrated for its clarity and accessibility, providing a detailed step-by-step guide for conducting TA.
Braun and Clarke’s approach is often referred to as reflexive thematic analysis. In this approach, themes are not treated as objective features that simply “emerge” from the data. Instead, they are actively developed by the researcher through sustained, reflective engagement with the dataset. This emphasis on researcher interpretation distinguishes Braun and Clarke’s method from more positivist or codebook-driven forms of thematic analysis.
The Six Phases of Braun and Clarke’s Thematic Analysis
Braun and Clarke outline six key phases for conducting thematic analysis:
1. Familiarising Yourself with the Data
The first step involves immersing yourself in the data to become deeply familiar with its content. This includes reading and re-reading the data, and noting down initial ideas. It’s a time-intensive process, but crucial for understanding the depth and breadth of the content.
2. Generating Initial Codes
In this phase, you start identifying interesting features of the data systematically across the entire dataset. This involves coding segments of data that appear relevant to your research question. Codes are the smallest units of analysis that capture interesting information about the data.
3. Searching for Themes
Once you have a list of codes, the next step is to collate them into potential themes. Themes are broader than codes and represent significant patterns in the data. During this phase, you start organising codes into overarching themes and sub-themes.
4. Reviewing Themes
In this phase, you refine the themes. This involves two levels of review: checking that the themes work in relation to the coded extracts and the entire dataset. If themes do not work, you need to revisit and revise them. This ensures that your themes are coherent and accurately represent the data.
5. Defining and Naming Themes
Here, you refine each theme and identify the essence of what each theme is about. You define the specifics of each theme and the overall story they tell about the data. Clear and concise names for each theme are developed to reflect the content and scope of the themes.
6. Producing the Report
The final phase involves writing up the analysis. This includes weaving together the analytic narrative and data extracts to tell the story of the data in a compelling way. The report should provide a coherent, concise, logical, and non-repetitive account of the data within and across themes.
Common Misunderstandings About Braun and Clarke’s Thematic Analysis
Misconception 1: Themes simply “emerge” from the data
Braun and Clarke explicitly reject the notion of emergence, particularly in their later work (2019, 2021). This position underpins their description of thematic analysis as reflexive: themes are not treated as pre-existing entities waiting to be uncovered, but as analytic constructions developed through sustained engagement with the data. For this reason, when using Braun and Clarke’s approach, researchers should avoid statements such as “themes emerged from the data.” More appropriate formulations include “themes were developed through inductive analysis” or “themes were generated through reflexive thematic analysis.”
No qualitative analytic technique treats themes as literally “emerging” from data; even in inductive approaches, themes are actively developed through analytic judgement rather than discovered as pre-existing entities.
Misconception 2: NVivo or software does the analysis
Analytic decisions — including how data are coded, how codes are combined, and how themes are constructed — are always made by the researcher. In Braun and Clarke’s reflexive thematic analysis, this distinction is particularly important: software may facilitate engagement with the data, but it does not replace reflexive judgement, theoretical sensitivity, or interpretive work. Statements such as “NVivo generated the themes” or “themes were identified using NVivo” therefore misrepresent the analytic process. A more accurate description is that software was used to support data organisation and retrieval, while the analysis itself was conducted by the researcher.
NVivo and similar software assist with coding and data management, but they do not conduct qualitative analysis or produce themes.
Misconception 3: Inter-coder reliability is required
Within this framework, subjectivity is not treated as a problem to be minimised but as an analytic resource. The researcher’s theoretical position, disciplinary background, and experiential knowledge shape how patterns are identified and interpreted, adding depth and nuance to the analysis. As a result, the aim of collaborative work in reflexive thematic analysis is not to achieve statistical agreement or consensus, but to enrich interpretation through discussion, reflexive dialogue, and critical engagement with alternative readings of the data.
In reflexive thematic analysis, inter-coder reliability is neither required nor appropriate, because themes are constructed through interpretation rather than objectively identified.
Misconception 4: Braun and Clarke’s thematic analysis is atheoretical or methodologically neutral
It is sometimes assumed that Braun and Clarke’s approach to thematic analysis is atheoretical, or that it can be applied in a methodologically neutral way without reference to epistemology or theoretical positioning. While thematic analysis is often described as flexible, this flexibility does not mean that it is theory-free. Braun and Clarke emphasise that all thematic analysis is shaped by the researcher’s theoretical assumptions, research questions, and analytic choices, whether these are made explicit or not.
In reflexive thematic analysis, researchers are encouraged to be transparent about their epistemological and theoretical positioning, as these influence how data are interpreted and how themes are constructed. Analytic decisions — such as what counts as a meaningful pattern, how themes are bounded, and how findings are written — are always theoretically informed. Treating thematic analysis as neutral or purely technical risks obscuring these assumptions and weakening analytic coherence.
Rather than being atheoretical, Braun and Clarke’s approach explicitly acknowledges the role of theory and reflexivity in qualitative analysis.
Frequently Asked Questions: Braun and Clarke’s Thematic Analysis
The questions below address some of the most common queries students and researchers have about using Braun and Clarke’s thematic analysis in practice.
Is Braun and Clarke’s thematic analysis inductive or deductive?
Braun and Clarke’s thematic analysis can be inductive, deductive, or a combination of both. An inductive approach develops codes and themes primarily from the data, while a deductive approach is guided by existing theory or research questions. Importantly, even inductive analysis involves analytic judgement rather than passive discovery. Researchers should be explicit about their analytic orientation when reporting their method
Can Braun and Clarke’s approach be used with interviews, focus groups, or open-ended surveys?
Yes. Braun and Clarke’s thematic analysis is suitable for a wide range of qualitative data types, including interviews, focus groups, open-ended survey responses, diaries, and textual documents. The key requirement is that the data allow for meaningful pattern identification and interpretation in relation to the research question.
How many themes should a thematic analysis have?
There is no fixed or “correct” number of themes. The number depends on the research question, the size and complexity of the dataset, and the analytic depth of the study. Braun and Clarke caution against having too many superficial themes or too few overly broad ones. What matters is that themes are coherent, distinctive, and analytically meaningful.
Do themes need to appear in every interview or data item?
No. A theme does not need to be present in every interview to be considered valid or important. Themes are defined by their analytic significance, not by frequency alone. In some cases, a theme may be based on a smaller number of accounts if it captures a particularly important pattern or tension in the data.
Is Braun and Clarke’s thematic analysis acceptable for a PhD or a master’s dissertation?
Yes. Braun and Clarke’s reflexive thematic analysis is widely accepted in postgraduate research, including PhD and Master’s dissertations, across disciplines such as psychology, education, health, and the social sciences. What examiners expect is a clear rationale for the approach, reflexive engagement with the data, and transparent reporting of analytic decisions.
Can I use NVivo or other software with Braun and Clarke’s approach?
Yes. Qualitative data analysis software such as NVivo can be used to support coding, organisation, and retrieval of data, but it does not conduct the analysis itself. In reflexive thematic analysis, analytic decisions — including code development and theme construction — remain the responsibility of the researcher.
How is Braun and Clarke’s approach different from other types of thematic analysis?
Braun and Clarke’s approach differs from codebook or reliability-based forms of thematic analysis by emphasising reflexivity, researcher subjectivity, and interpretive judgement. It does not require inter-coder reliability and does not treat themes as objective entities. Instead, themes are understood as analytic constructions developed through engagement with the data.
Why Choose Braun and Clarke’s Approach?
Braun and Clarke’s method is highly regarded for several reasons:
- Flexibility: Their approach is not tied to any specific theoretical framework, making it adaptable to a variety of research questions and data types.
- Clarity: The step-by-step guide is straightforward and detailed, making it accessible even for novice researchers.
- Rigour: By emphasising the thorough and systematic analysis of data, their approach ensures that the findings are robust and credible.
Practical Tips for Conducting Thematic Analysis
- Stay Organised: Use software tools like NVivo or Atlas.ti to manage and code your data efficiently.
- Be Reflexive: Reflect on your own biases and how they may influence your analysis.
- Engage with the Data: Spend ample time immersing yourself in the data to uncover deeper meanings.
- Iterate: Be prepared to revise your codes and themes multiple times to ensure they accurately capture the data.
Summary
Braun and Clarke’s thematic analysis is a powerful tool for qualitative researchers, offering a systematic yet flexible approach to analysing rich, qualitative data. By following their six-phase process, researchers can produce insightful and credible findings that capture the complexities of their data. Whether you’re a seasoned researcher or a novice, their method provides a robust framework for your qualitative analysis journey.
Recommended reading
Braun, V. & Clarke, V. (2006) Using thematic analysis in psychology, Qualitative Research in Psychology, 3:2, 77-101, DOI: 10.1191/1478088706qp063oa
Braun, V. & Clarke, V. (2021) Thematic Analysis: A Practical Guide. London: Sage.
A full-length book from Sage offering comprehensive, step-by-step guidance on reflexive thematic analysis. (View on Amazon).
Need help with your thematic analysis using Braun & Clarke?
If you need support with conducting or reporting a qualitative thematic analysis using Braun and Clarke’s approach, we can help. This includes assistance with developing coding frameworks, refining themes, producing coding matrices and thematic maps, and guidance on how to write up findings and methods sections in line with academic expectations. Support is tailored to your project and focuses on strengthening analytic clarity, rigour, and methodological transparency.
