A beginner’s guide to thematic analysis
Thematic analysis (TA) is a commonly used data analysis approach in various disciplines and for many different data types. At least half of the researchers attending my NVivo webinars and workshops are planning to undertake TA of some kind, and NVivo is certainly a helpful tool to assist with the TA process. However, TA is an approach that is often misunderstood, with confusion regarding whether it’s a “real” approach and many researchers are unaware that there are different approaches to TA.
The term “thematic analysis” is often used in a generic manner to refer to the process of qualitative analysis and coding. There’s a bit more to it than that though, and while some claim that TA is not a distinct method or that there are no guidelines for its use, some variations of TA (e.g., reflexive TA and template analysis) have been extremely well developed and documented.
Braun and Clarke (2022) note that when researching for their latest book, they discovered at least 20 different versions of TA, so if you’re considering this technique for your research, it would pay to understand the different approaches out there. There are commonalities in the various TA approaches in that they all look for patterns of meaning across a dataset and involve a process of data familiarisation and coding. However, there are key differences in terms of how themes are understood, how the coding process is conducted, and whether a deductive or inductive orientation (or both) can be taken. The role of researcher subjectivity and how quality is assessed also varies across different TA approaches.
How do you choose a TA approach? My advice would be to start with understanding the range of possibilities. Excellent overviews of the various approaches can be found in Braun and Clarke (2022), Finlay (2021), King and Brooks (2018), and Terry and Hadfield (2021). Chapter 8 of Braun and Clarke’s book provides a particularly accessible overview. Once you’ve understood the different possibilities, think carefully about how these fit with your research question, purpose and wider research philosophy and methodology. If you’re unsure what I mean by this, this will make more sense when you read more about TA – I don’t intend to go down the epistemological/ontological rabbit hole in such a short blog post!
In terms of other useful resources, there are extremely helpful reading lists, not to mention plenty of questions and answers, on Braun and Clarke’s reflexive TA website and Nigel King’s template analysis website. Braun and Clarke’s (2021) article comparing TA to other approaches is also extremely helpful (this compares TA to grounded theory, content analysis, interpretative phenomenological analysis [IPA], and discourse analysis). Finally, David Thomas’ (2006) general inductive approach shouldn’t be overlooked as an accessible and straightforward TA approach.
Can’t I just use NVivo I hear you ask? Why do I need to worry about which TA approach I’m following? NVivo is simply a tool to assist you with your analysis – the software won’t decide on your codes/themes or complete the coding process. Nor will it do any of the analytic work or thinking for you. This is your role as the researcher, and it’s important that you follow a specific data analysis approach (and that you do so in a rigorous way). Before jumping into using NVivo, it would pay to take some time to explore which data analysis approach is a good fit for your project, whether that’s a variation of TA or one of the many other approaches such as grounded theory, content analysis, IPA, discourse analysis, narrative analysis or something else entirely!
If you’re interested in learning more, we cover TA (including using NVivo for TA) as part of our Research Accelerator membership. For those interested in template analysis more specifically, we’re delighted to be hosting Professor Nigel King for a workshop in September. There are still a few places left in this, but we recommend registering asap.
Braun, V., & Clarke, V. (2021). Can I use TA? Should I use TA? Should I not use TA? Comparing reflexive thematic analysis and other pattern‐based qualitative analytic approaches. Counselling and Psychotherapy Research, 21(1), 37–47. https://doi.org/10.1002/capr.12360
Braun, V., & Clarke, V. (2022). Thematic analysis: A practical guide. SAGE.
Finlay, L. (2021). Thematic analysis: The ‘good’, the ‘bad’ and the ‘ugly.’ European Journal for Qualitative Research in Psychotherapy, 11, 103–116.
King, N., & Brooks, J. (2018). Thematic analysis in organisational research. In C. Cassell, A. L. Cunliffe, & G. Grandy (Eds.), The SAGE handbook of qualitative business and management research methods (pp. 219–236). SAGE. https://doi.org/10.4135/9781526430236.n14
Terry, G., & Hayfield, N. (2021). Essentials of thematic analysis. American Psychological Association. Thomas, D. R. (2006). A general inductive approach for analyzing qualitative evaluation data. American Journal of Evaluation, 27(2), 237–246. https://doi.org/10.1177/1098214005283748