Thematic Analysis: A Step-by-Step Guide

Thematic analysis is the most commonly used qualitative analysis method, largely because Braun and Clarke's six-phase framework gives it a structure that's both flexible and defensible to a committee. Here's how the six phases actually work.

The six phases

1. Familiarization — reading and re-reading your data (transcripts, field notes) before coding anything, noting initial impressions.
2. Generating initial codes — systematically labeling features of the data relevant to your research question, working through the entire dataset rather than cherry-picking illustrative quotes.
3. Searching for themes — sorting codes into candidate themes, looking for patterns that recur across participants or data sources.
4. Reviewing themes — checking themes against the coded extracts and the full dataset; themes that don't hold up get split, merged, or dropped here.
5. Defining and naming themes — writing a clear definition of what each theme captures and doesn't, with a name that's specific rather than generic.
6. Producing the report — weaving themes together with data extracts into a coherent analytic narrative, not just a list of themes with quotes attached.

Inductive vs deductive coding

Decide upfront whether you're coding inductively (themes emerge from the data itself, bottom-up) or deductively (coding against a pre-existing framework or theory, top-down). Many studies use a hybrid approach — state which you're using and why, since this affects how your codebook is built and how you justify your themes.

Common mistakes

• Treating themes as simply summarizing what participants said, rather than an interpretive account of patterned meaning across the dataset.
• Themes that overlap too much to be analytically distinct from one another.
• No clear audit trail from raw data to codes to themes — committees and reviewers expect to be able to trace this.
• Reporting only supporting quotes without addressing disconfirming or divergent data.