- Research Methods
Thematic analysis explores patterns of meaning within qualitative research data. Thematic analysis is a qualitative research approach that involves the identification of themes in data. Themes are identified through the use of extended codes, which are assigned to research content based on similarities. These thematic codes tend to be more of a phrase than other codes. These themes aim to indicate what a section of data is about and how the researcher is interpreting the data.
There is no one way to conduct thematic analysis - different approaches can be used depending on the researcher's preferences and needs. There are several different approaches to thematic analysis, with the two main approaches being categorically and phenomenologically (Saldana p259).
Thematic analysis is often used to explore data that is rich in meaning and context. From Clarke, Braun, and Hayfield, thematic analysis is appropriate for research around: Participants' experiences, participants' perspectives, social factors around specific phenomena, participants' practices, representations of topics and contexts, and social construction of a topic.
The Benefits of a Thematic Analysis
Reflexive approaches to thematic analysis allow for greater flexibility in coding and theme development. Flexibility is a main strength because it can be used with different research approaches. Thematic methods for coding are used by mixed method studies for quantitative data results to compare and relate to themes discovered during qualitative data analysis. Thematic analysis is a good fit to help research teams see related topics across large sets of data.
How to Conduct a Thematic Analysis
Thematic analysis can be conducted with or without a specific method to guide the process. Using a thematic analysis method ensures less subjectivity in coding and pattern identification, which contributes to the trustworthiness of results.
Let's have a look at Brauns' 6 phase approach to reflexive thematic analysis...
- Becoming familiar with the data: Review, and re-read the data to get beyond surface interpretations of the data. Focus on the data and not on researcher's prior conceptions, unless you are using a deductive approach guided by pre-existing theory.
- Generating codes: Explore both overt (semantic) and implicit (latent) meaning in the data and assign codes to later retrieve important data and generate themes. This should be an iterative process, codes can be updated each time the data is reviewed to further refine them.
- Generating initial themes: Review how the codes combine to create overall themes in the research. Themes are going to be more descriptive than codes and are likely in the form of phrases to describe ideas.
- Reviewing themes: It's always good to review your initial themes, you will want to go over the themes to ensure they didn't drift from the data's big picture and that they form coherent patterns. You may find you combine, add, or delete themes. You can compare the themes against the coded data as well as the entire data set.
- Defining and naming themes: This is where you will define and refine your themes for presentation in the final analysis. You can create sub-themes but beware of fragmenting your analysis too much (Clarke & Braun p84-103). Provide a description for each theme.
- Producing the report: Since we are focused on UX research, this would be sharing insights, instead of a "report" since reports are often not the best way to evangelize research results in an organization like a company. These should tie back to your original research questions.
Why use a thematic analysis
Thematic analysis methods are often used by researchers who seek to understand participants' experiences, social factors around specific phenomena, participants' practices, and representations of topics and contexts. It can be used with a variety of research methods, including mixed methods to discover across qualitative and quantitative data.