Using Thematic Analysis in Psychology

Thematic analysis is a flexible method for identifying and interpreting patterns of meaning in qualitative data. In psychology, it is often used to explore people’s experiences, perspectives and understandings—for example, how people cope with grief, experience therapy or make sense of living with a health condition.

The method can be applied to interviews, focus groups, open-ended survey responses, diaries and other forms of qualitative material. Its flexibility makes it accessible to researchers using different theoretical approaches, but it also means that researchers need to be clear about how they conduct and interpret their analysis.

What is a theme?

A theme captures a pattern of meaning that is relevant to a research question. It is more than a topic that appears in the data. For instance, “work” might be a topic, while “work as a source of identity during recovery” expresses a more developed idea about what work means to participants.

Themes are not simply discovered in the data as if they were hidden objects. Researchers develop them through close engagement with the material, guided by their research question, theoretical position and interpretative decisions. Different researchers may therefore produce different, yet well-supported, accounts of the same dataset.

A widely used approach

One influential approach, developed by Virginia Braun and Victoria Clarke, describes thematic analysis as a process involving six phases. These phases are a guide rather than a strict checklist: researchers may move back and forth between them as their understanding develops.

1. Familiarising yourself with the data.

   Read and re-read the material, listening to recordings where appropriate. Note initial observations, striking phrases and possible patterns.

2. Generating initial codes.

   Identify features of the data that may be relevant to the research question. A code is a concise label for an idea or segment of meaning, such as “fear of judgement” or “feeling responsible for others”.

3. Developing candidate themes.

   Bring related codes together and consider what broader pattern of meaning they might form. A theme should make a clear point, rather than merely collect material on a general subject.

4. Reviewing themes.

   Check whether each candidate theme is supported by the coded extracts and whether it makes sense in relation to the dataset as a whole. Themes may be revised, combined, divided or set aside.

5. Defining and naming themes.

   Clarify the central idea of each theme, its scope and how it relates to the other themes. Choose a concise name that communicates its meaning.

6. Writing the analysis.

   Present a coherent account that connects the themes to the research question and relevant literature. Use extracts from the data to illustrate the analysis, explaining what they show rather than leaving quotations to speak for themselves.

Choosing an analytic approach

Thematic analysis can be conducted in different ways, and the choices should fit the purpose of the study.

• Inductive analysis develops codes and themes primarily from the data, rather than applying a detailed framework established in advance.
• Deductive analysis is guided more directly by existing theory, concepts or specific research questions.
• Semantic analysis focuses on what participants explicitly say.
• Latent analysis examines underlying assumptions, ideas or meanings that may shape what is said.

These are not always absolute alternatives. A study may combine inductive and deductive reasoning, or attend to both explicit and underlying meanings. The important thing is to describe the approach clearly and use it consistently.

Reflexivity and the researcher’s role

In qualitative psychology, researchers are part of the analytic process. Their training, experiences, assumptions and relationship with the research topic can influence what they notice and how they interpret it. Reflexivity means considering and documenting these influences, rather than claiming to remove them entirely.

Researchers can support reflexive practice by keeping notes throughout the analysis, recording changes in their thinking and explaining how their standpoint informed the work. Reflexivity is not a brief statement added at the end; it is an ongoing part of making thoughtful, transparent analytic decisions.

Quality and common pitfalls

A strong thematic analysis offers a clear, well-supported interpretation of the data. Readers should be able to understand how the themes address the research question and how the extracts support the claims being made. A useful account also explains the analytic choices made, including how the data were coded and how themes were developed.

Common pitfalls include:

• treating interview questions or broad subjects as themes without developing an analytic point;
• selecting quotations that illustrate a claim but ignoring material that complicates it;
• presenting a list of codes or extracts without explaining the pattern of meaning;
• making claims that go beyond what the dataset can support; and
• describing procedures without explaining the researcher’s interpretative decisions.

Inter-coder agreement—the extent to which different researchers apply the same codes—is sometimes used in qualitative research. Whether it is appropriate depends on the particular form of thematic analysis. In reflexive thematic analysis, differences between researchers may prompt useful discussion rather than indicate that one person has coded incorrectly. Researchers should avoid combining assumptions from incompatible approaches without explaining why.

Strengths and limitations

Thematic analysis is adaptable, can be used with many types of qualitative data and provides a systematic way to develop an account of shared patterns. It can be valuable in applied psychological research because it helps researchers communicate participants’ perspectives while connecting them to wider concepts and questions.

However, flexibility is not the same as a lack of structure. Without careful decisions and transparent reporting, an analysis can become superficial or difficult to evaluate. Thematic analysis also does not, by itself, explain every aspect of a dataset. Other qualitative methods may be better suited when the main interest is, for example, the detailed structure of conversation, the development of a personal narrative or the interpretation of a particular social practice.

Conclusion

Thematic analysis is a versatile method for exploring patterns of meaning in psychological research. Its value depends on more than following a set of steps: researchers need to make thoughtful choices about their approach, engage closely with the data and explain how their interpretation was developed. Used with care, it can provide a nuanced account of how people understand and experience the world.