How to Do a Thematic Analysis: A Complete UK Guide

Learning how to do a thematic analysis is an essential skill for UK university students. Thematic analysis is one of the most widely used methods for analysing qualitative data — interviews, open-ended surveys, focus groups and texts. It identifies patterns of meaning (themes) across a dataset. This complete UK guide explains what thematic analysis is, walks through Braun and Clarke's six phases, and shows how to report themes rigorously.

How to do a thematic analysis: Step-by-Step Guide

What Is Thematic Analysis?

Thematic analysis is a method for identifying, analysing and reporting patterns (themes) within qualitative data. It is flexible, widely taught, and suits interviews, focus groups and open-text responses across many disciplines.

For further guidance on how to do a thematic analysis, visit the Prospects guide to studying in the UK — a trusted resource for UK students and graduates.

Braun and Clarke's Six Phases

The most cited approach has six phases:

✓  Familiarisation with the data.
✓  Generating initial codes.
✓  Searching for themes.
✓  Reviewing themes.
✓  Defining and naming themes.
✓  Writing up.

Coding Your Data

Coding means labelling meaningful segments of data. Work systematically through your transcripts, attaching codes to relevant extracts. Codes are the building blocks — related codes are later grouped into broader themes.

From Codes to Themes

Cluster related codes into candidate themes, then review them against the data and your research question. A good theme captures something important and recurs meaningfully across the dataset — not just a single mention.

Reporting Themes Rigorously

Present each theme with a clear definition and representative quotes, and explain what it means in relation to your question and the literature. Rigour comes from showing how themes were derived, not just asserting them. See our results chapter guide.

Common Mistakes and Tips

✓  Themes that are just topic summaries.
✓  No clear coding process.
✓  Quotes with no analysis.
✓  Too many overlapping themes. Tip: follow the six phases, code systematically, and define themes clearly with evidence.

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Reflexive Thematic Analysis: The Braun and Clarke Approach

In 2019, Braun and Clarke significantly revised and developed their original 2006 thematic analysis framework, introducing the concept of “reflexive thematic analysis.” This is now the standard approach for thematic analysis in UK social science, psychology, and health research dissertations. Understanding the key principles of reflexive TA is essential for writing a credible methodology chapter.

Themes are not “found” in data — they are constructed: Reflexive TA is not a mechanical coding procedure that generates objectively correct themes. Themes are developed through the researcher’s active interpretation and meaning-making. This requires the researcher to engage reflexively with their own role in the analysis — acknowledging how their prior knowledge, assumptions, and positionality shape their interpretations.

Themes must be analytically meaningful: A common mistake in student thematic analysis is producing themes that are purely descriptive summaries of what participants said (e.g., “participants talked about stress”) rather than analytical themes that make an interpretive claim about the data (e.g., “stress as a normalised feature of academic identity”). Strong themes have a clear central organising concept and an analytical claim.

Themes are not frequencies: In reflexive TA, a theme does not have to appear in every participant’s data to be valid. A pattern that appears in only a few participants’ accounts may be analytically significant. Avoid the temptation to count how many participants mentioned something — this is content analysis, not thematic analysis.

Thematic Analysis vs. Other Qualitative Methods

Thematic Analysis vs. Grounded Theory: Grounded theory is a methodology, not just an analysis method — it involves systematic theoretical sampling and aims to generate substantive theory. Thematic analysis is more flexible and does not require theoretical sampling or the generation of new theory. Most UK undergraduate and master’s dissertations use TA rather than full grounded theory.

Thematic Analysis vs. Interpretative Phenomenological Analysis (IPA): IPA focuses on the lived experience and meaning-making of specific individuals, using a smaller, homogeneous sample (typically 4–10 participants). TA is more flexible in terms of sample size and research focus. IPA is more appropriate when the phenomenological experience of the individual is the primary focus.

Thematic Analysis vs. Discourse Analysis: Discourse analysis examines how language constructs social reality, focusing on the analysis of text as a social practice rather than on participants’ perspectives or experiences. TA focuses on the meanings participants attach to their experience.

Frequently Asked Questions

What is thematic analysis?
A method for identifying, analysing and reporting patterns (themes) in qualitative data.

What are Braun and Clarke's six phases?
Familiarisation, generating codes, searching for themes, reviewing, defining and naming, and writing up.

What is coding in thematic analysis?
Labelling meaningful segments of data, which are then grouped into themes.

What makes a good theme?
One that captures something important and recurs meaningfully across the dataset.

What data suits thematic analysis?
Interviews, focus groups, open-ended surveys and texts.

How do I report themes?
Define each theme, support it with representative quotes, and interpret it against your question.

Is thematic analysis qualitative?
Yes — it is a qualitative analysis method.

What is the most common mistake?
Producing themes that merely summarise topics rather than capturing patterns of meaning.

Related Study Guides

How to Write a Methodology  •  How to Write a Results Chapter  •  How to Write a Questionnaire  •  How to Write a Dissertation

UK students who master how to do a thematic analysis gain a significant advantage in their academic career. Whether you are in your first year or final year, understanding how to do a thematic analysis thoroughly will improve your overall academic performance and help you achieve better grades.

Approaches to Thematic Analysis: Theoretical Flexibility

One of the most frequently cited strengths of thematic analysis is its theoretical flexibility—it is not tied to a single epistemological position and can be used within a range of qualitative research frameworks. However, this flexibility requires you to make explicit choices about your approach and to reflect on those choices in your methodology chapter.

An inductive approach to thematic analysis allows themes to emerge from the data without imposing a predetermined framework. You code what you see in the data, building themes from the ground up. This approach is epistemologically appropriate when you are exploring a relatively open research question where you want to remain genuinely open to what the data reveals.

A deductive or theory-driven approach applies an existing theoretical framework to guide the coding process. If your research question asks whether a particular theory or concept is reflected in the experiences of your participants, a deductive approach—coding for the concepts specified by the theory—is more appropriate. The risk of a deductive approach is confirmation bias: seeing what you were looking for at the expense of noticing unexpected patterns in the data.

A reflexive approach, as described by Braun and Clarke in their influential 2006 paper and subsequent work, treats themes not as objective features of the data but as constructs actively generated by the researcher through a process of interpretation. This approach requires explicit acknowledgement of the researcher’s role in shaping the analysis, including their theoretical commitments, assumptions, and positionality. Reflexive thematic analysis is increasingly the dominant approach in qualitative health sciences and social science research in the UK.

Reporting Thematic Analysis in Your Dissertation

The results chapter of a dissertation using thematic analysis should present the themes you have generated, with rich illustrative evidence from the data and clear analytical commentary. The goal is not simply to report what participants said but to present your interpretation of what the data means in relation to your research question.

Organise the results chapter by theme rather than by participant. Present each theme in a clearly named section with a brief explanation of what the theme captures and why it is significant. Use direct quotations from your data to illustrate the theme, selecting quotes that are vivid, representative, and analytically relevant. After each quotation, provide your analytical commentary: what does this extract show about the theme, and how does it connect to your research question?

Be transparent about how many participants contributed to each theme, and about any patterns of variation within themes—subthemes that reveal nuances or contradictions in the data. Avoid presenting an overly uniform picture of your findings: qualitative data is rarely entirely consistent, and acknowledging variation is a sign of rigorous, honest analysis.

When writing up your methodology, provide a clear, step-by-step account of how you conducted your thematic analysis, including your data familiarisation process, your coding approach (with examples if possible), and the process by which codes were developed into themes. Citing Braun and Clarke’s foundational work on thematic analysis is standard practice, but also explain how you applied their framework to your specific data and research context. If you need expert guidance on conducting and writing up a thematic analysis for your dissertation, professional academic support from qualitative research specialists can help you produce a rigorous and clearly presented analysis.