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. 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.īraun 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.
The term “thematic analysis” is often used in a generic manner to refer to the process of qualitative analysis and coding. 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. 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. Thematic analysis (TA) is a commonly used data analysis approach in various disciplines and for many different data types.
