Academic Book (Qualitative Research / Research Methods), 2021, SAGE.

I decided to do some research into some useful methods of analysing qualitive data for when my data collecting is complete. At the moment i still have a week until i will have all the interviews done so this is in preporation for then.

Braun and Clarke’s Thematic Analysis: A Practical Guide develops their approach to reflexive thematic analysis, a method for identifying and interpreting patterns of meaning across qualitative data. The book builds on their original 2006 paper and focuses on familiarisation, coding, developing themes, interpretation and writing up qualitative findings.

I chose to explore this method because I now have a growing collection of qualitative interview responses from autistic adults. Rather than simply selecting interesting quotes or counting repeated answers, I need a consistent method for understanding what the responses collectively reveal.

Initial Reflections

What I find most useful about reflexive thematic analysis is that it allows me to look for patterns across participants while still recognising individual experiences.

This feels appropriate for my project because autistic experiences of travel are highly varied. I do not want to suggest that every participant experiences the same barriers, but I do want to understand whether shared patterns are beginning to emerge. Braun and Clarke also emphasise that the researcher plays an active role in interpreting the data. My themes will therefore not simply “appear” from the interviews; I will make analytical decisions about what is relevant to my research question and reflect on how my own perspective influences those decisions.

The Six-Phase Process

Braun and Clarke describe six flexible phases for reflexive thematic analysis. These are not intended to be followed as rigid rules, and the researcher may move backwards and forwards between stages.

1. Familiarisation

Read and re-read all interview responses and make notes about anything that appears significant.

2. Coding

Give short labels to meaningful pieces of data that relate to the research question.

For example:

“Security can be very overwhelming.”

Possible codes could include:

airport security / overwhelm / anxiety

3. Generating Initial Themes

Begin grouping related codes together to identify wider patterns of meaning.

4. Developing and Reviewing Themes

Return to the original interviews and check whether the themes genuinely represent the dataset. Themes may be combined, changed or removed.

5. Refining and Naming Themes

Clearly define what each theme means and give it a useful name.

6. Writing Up

Use participant evidence alongside my interpretation to explain what each theme reveals and how it connects to the research question.

Codes Are Not the Same as Themes

One distinction I need to remember is that a code represents a specific idea within a piece of data, whereas a theme represents a broader recurring pattern organised around a central idea.

For example:

Codes: noise, crowds, alarms, physical proximity

could potentially contribute to a wider theme around

Sensory Pressure Within the Airport

Braun and Clarke warn against simply turning interview questions or broad topics into themes. A theme should communicate something meaningful about the shared pattern within the data rather than simply summarising everything participants said about one subject.

Connection to My Project

I plan to use reflexive thematic analysis to examine my interviews with autistic adults.

I will initially code the responses without forcing them into themes I have already identified through my literature research. This is important because I want the primary research to both challenge and support my assumptions. The final themes should help me identify where the strongest design opportunities exist, rather than choosing an intervention first and then searching the interviews for evidence to support it.