How to Do Thematic Analysis in Qualitative Research

People frequently share their thoughts and experiences through various channels, including interviews, surveys, reviews, social media posts, and everyday conversations. While this kind of feedback is valuable, it is often scattered and unstructured, making it hard to see the bigger picture just by reading individual responses. 

That’s where thematic analysis becomes useful. Instead of treating each comment individually, it helps you step back and look for patterns that appear repeatedly. By grouping similar ideas and experiences into themes, thematic analysis makes it easier to understand what people are really saying and why it matters, transforming a mass of voices into insights that can be effectively applied. 

This guide will explain what thematic analysis is and provide a step-by-step approach on how to do thematic analysis. It will also highlight the advantages of thematic analysis, discuss its disadvantages, and give guidance on when to use thematic analysis, offering a complete overview for anyone interested in applying this method effectively. 

What is a Thematic Analysis?

Thematic analysis is a method used in qualitative research to identify and make sense of patterns or themes within data. It focuses on understanding the underlying meanings and insights in what people say, write, or express, rather than just counting words or responses, allowing researchers to go beyond surface-level descriptions.  

The process involves carefully reading through your data, coding specific pieces of information, and grouping similar codes to form broader themes that capture the most important aspects of the data. This makes it especially useful for exploring beliefs, attitudes, and cultural or social influences, and for drawing out shared insights across a group rather than relying solely on numbers. 

Thematic analysis is highly flexible and can be applied to various types of qualitative data, including interviews, focus groups, surveys, and observations. It is especially helpful when you want to explore complex experiences, emotions, and social phenomena, allowing you to move from raw data to meaningful insights about people’s lives, behaviors, and motivations. 

In short, thematic analysis helps you see patterns in the stories people tell, giving depth and clarity to your research findings. 

When to Use Thematic Analysis?

Thematic analysis is most useful when you want to delve into rich, detailed qualitative data and gain a deeper understanding of people’s experiences, opinions, or viewpoints. It works well for exploring how people react to different situations and for spotting patterns in their behavior, emotions, or relationships—insights that more structured methods often overlook. 

You might choose thematic analysis when you want to understand the “how” and “why” behind experiences, not just the “what.” Some common situations include: 

• Perceptions: Understanding how people interpret situations, like patients’ experiences with doctors.
• Experiences: Exploring personal experiences, such as young women’s experiences on dating apps.
• Ideas and Opinions: Investigating public views on broader topics, like climate change.
• Cultural Constructs: Looking at how social ideas, like gender, are understood and enacted in contexts such as schools.
• Patterns Across Perspectives: Spotting recurring themes across different participants or groups.
• Under-Researched Areas: Studying topics where little is already known.

Although thematic analysis is sometimes compared to content analysis, they are different. Content analysis is good for measuring patterns across large amounts of text, like news articles or social media posts. Thematic analysis, on the other hand, is about digging deeper into meaning, helping you understand not just what happened but how people make sense of it—like seeing not just the challenges students face, but how they adapt and learn from them.¹ 

Organizing your data carefully is key. Tools like CAQDAS (e.g., Delve) can help keep transcripts, notes, and codes in one place, making it easier to spot patterns as they emerge. Thematic analysis is flexible and insightful, but it does require reflection to make sure important details are not overlooked or misinterpreted. 

Approaches to Thematic Analysis

Once you choose to use thematic analysis, you can take one of the following approaches depending on whether you want the themes to emerge from the data or be guided by existing theories:² 

• Inductive Approach: With an inductive approach, themes come straight from the data itself. You do not start with a theory or set expectations—instead, you read the data closely and let patterns develop naturally. This makes it a good choice when you are exploring something new or not well studied, and you do not want existing ideas to shape what you find too early.
  Example: Reading interviews with first-time remote workers and discovering unexpected challenges, such as feelings of isolation or difficulties switching off from work, that were not considered beforehand.

• Deductive approach: A deductive approach starts with a clear idea or theory in mind. Here, you use existing research or frameworks to guide how you code the data and shape your themes. This works well when you want to see how real-life experiences fit with, support, or challenge an established theory.
  Example: Analyzing student interviews using concepts from Self-Determination Theory—like autonomy or motivation—to see how closely students’ experiences match the theory.

• Semantic vs. Latent: While not always classified separately, the inductive and deductive approaches can also be applied at the semantic level (explicit content) or latent level (underlying ideas and assumptions).

• Combination: Researchers sometimes use a hybrid approach, starting with theory-driven codes (deductive) while remaining open to new themes that emerge from the data (inductive). Example: Investigating workplace stress using known stress categories, but also capturing unexpected stressors mentioned by employees.

How to Do a Thematic Analysis (Step by Step)

The Braun and Clarke method is a popular approach for doing thematic analysis in qualitative research.³ It gives a simple six-step process to help researchers find, organize, and report patterns or themes in their data. This method is flexible and can be applied to various types of qualitative data while maintaining a clear and systematic analysis. 

• Familiarize: Read through your data carefully and jot down anything that stands out.
• Code: Go through the data and label sections that seem important or interesting.
• Search for Themes: Look for patterns in your code and start grouping them into possible themes.
• Review Themes: Make sure the themes really match the data, and adjust them if needed by combining, splitting, or removing themes.
• Define and Name: Assign each theme a concise description and a name that accurately captures its essence.
• Write Up: Present your themes in a clear narrative, using examples from the data to show what each theme means.

Advantages and Disadvantages of Thematic Analysis

Advantages: 

• Flexible: Works well with different research questions, types of data, and theoretical approaches, making it easy to adapt to many studies.
• Accessible: Straightforward to learn and apply, even for those new to qualitative research.
• Rich insights: Helps bring out patterns, meanings, and different perspectives hidden within complex data.
• Data reduction: Makes large amounts of qualitative data more manageable by organizing it into clear, meaningful themes.
• Supports reflexivity: Encourages researchers to think meticulously about their own role, assumptions, and interpretations during the analysis.

Disadvantages: 

• Time-consuming: Careful coding and developing well-defined themes can take significant time and effort.
• Subjectivity: The analysis is heavily influenced by the researcher’s interpretation, which can introduce potential biases.
• Risk of oversimplification: Important nuances or contextual information may be overlooked if themes are defined too broadly.
• Limited generalizability: The results are largely descriptive and interpretive, which limits their applicability to larger populations.
• Requires careful reporting: The analysis needs to be clearly explained and documented to uphold transparency and credibility.

Key takeaways

• Thematic analysis is a flexible approach to working with qualitative data that helps identify and understand patterns, or themes, in what people say or write.
• It is well-suited for exploring experiences, perceptions, and behaviors using data from interviews, focus groups, surveys, or documents.
• The process involves becoming familiar with the data, coding meaningful sections, developing and refining themes, and then interpreting and reporting the findings.
• It is relatively easy to learn and use, which makes it accessible for beginners, while still allowing for rich and detailed insights.
• However, it is time-consuming and relies heavily on the researcher’s judgment, who may miss important nuances if the analysis is not carried out carefully.

Frequently Asked Questions

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References 

1. Vaismoradi, M., Turunen, H., & Bondas, T. (2013). Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study. Nursing & Health Sciences, 15(3), 398-405.

2. Finlay, L. (2021). Thematic analysis: the ‘good’, the ‘bad’ and the ‘ugly’. European Journal for Qualitative Research in Psychotherapy, 11, 103-116.

3. Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589-597.