{"id":458,"date":"2025-12-02T13:49:15","date_gmt":"2025-12-02T13:49:15","guid":{"rendered":"http:\/\/postgradproofreader.co.uk\/blog\/?p=458"},"modified":"2025-12-04T09:34:45","modified_gmt":"2025-12-04T09:34:45","slug":"common-thematic-analysis-pitfalls-and-how-to-avoid-them","status":"publish","type":"post","link":"http:\/\/postgradproofreader.co.uk\/blog\/2025\/12\/02\/common-thematic-analysis-pitfalls-and-how-to-avoid-them\/","title":{"rendered":"Common thematic analysis pitfalls – and how to avoid them"},"content":{"rendered":"

If you\u2019re a qualitative researcher, you will be familiar with Braun and Clarke\u2019s reflexive thematic analysis (RTA). Originally outlined in their 2006 methodological paper \u201cUsing thematic analysis in psychology\u201d, it is probably the most common \u2018first foray\u2019 into qualitative research for psychologists. Since 2006, Braun and Clarke have refined and reworked their 6-step method<\/a>, producing papers, books<\/a>, YouTube videos (from both Clarke<\/a> and Braun<\/a>) and an entire website<\/a> dedicated to supporting the conduct of quality RTA.<\/p>\n

Despite this clear and helpful guidance, we regularly come across a handful of common errors in the conduct and write-up of RTA studies here at PGPR.<\/p>\n

1. Themes do not<\/strong> emerge!<\/p>\n

If you\u2019ve ever used the term \u201cthe themes that emerged\u2026\u201d or similar in your RTA study, you\u2019re in good company \u2013 it\u2019s an error so commonly commented on that it\u2019s spawned its own meme.<\/p>\n

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Pin badge (now discontinued, sadly) designed by Dr Heidi R Green, “Science On A Postcard”<\/em><\/p>\n

But why does this seemingly innocent phrase cause so much uproar in the RTA community? It comes down to its positivist implications: saying that the themes emerged, were identified, or even were found<\/strong> in the data, suggests that, if we look hard enough, we can find objective themes which truly exist, regardless of the researcher\u2019s analytic process.<\/p>\n

Themes, in an RTA sense, are not real<\/strong> \u2013 they are constructed through the analytic process. Braun and Clarke, true to form, say it best: \u201cIn reflexive TA, themes are generated, created or constructed (for example), they are not identified, found or discovered, and they definitely don\u2019t just \u2018emerge\u2019 from data like a fully-grown Venus arising from the sea and arriving at the shore in Botticelli\u2019s famous painting\u201d (Braun & Clarke, 2022<\/a>). Is this semantic pedantry? Some might argue that it is, but this edict has become the shibboleth by which seasoned RTAers recognise whether or not their students have familiarised themselves with Braun and Clarke beyond 2006!<\/p>\n

2. So where do<\/strong> themes come from..?<\/p>\n

They are developed! You won\u2019t know what your themes will be until you\u2019ve engaged in the analytic process, so none of this \u201cwe expect the themes to be\u2026\u201d nonsense in your introduction, please. Depending on your research aims and specific approach (inductive, deductive \u2013 RTA is delightfully flexible), you may have specific areas of the data you want to focus on, but try to also allow for unexpected insights. And definitely steer clear of topic summaries as theme names \u2013 a theme named \u201chow patients use online patient portals\u201d doesn\u2019t tell an interpretative story (and probably doesn\u2019t go much beyond the initially stated research aim). But theme names such as \u201ctaking ownership of my healthcare\u201d communicates a core message \u2013 a message that cannot be conceptualized prior to<\/strong> analysis.<\/p>\n

To put it simply: themes come from a combination of the data, the analytic process, the sociocultural context in which the data was collected and analysed, and the specific context that you, as the analyst, bring to the analytic process. If, for example, Johanna and I were to analyse the same set of transcripts, we would very likely construct a different set of themes. If we were to analyse the data together, a third distinct set of themes would probably be developed. And that is because\u2026<\/p>\n

3. You are a tool of the analytic process<\/p>\n

\u2026not a contaminant to be contained. Again, this comes down to a question of philosophical frameworks \u2013 RTA is not constructed on a bedrock of positivist paradigms.<\/p>\n

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Photo by Lachlan Donald<\/a> on Unsplash<\/a><\/p>\n

Unlike in much quantitative research, the aim of RTA is not to control for or eliminate researcher bias \u2013 the reflexive aspect of RTA acknowledges that the researcher plays an active role in developing themes. As the analyst, your position, context, and yes, bias, bring something unique to the analytic process \u2013 so own it, don\u2019t deny it. Engage reflexively throughout the analytic process to explain how and why you developed the themes as you did. This can be done as a group process, with multiple coders or analysts, but not in an effort to \u201ccontrol for bias\u201d. Inter-rater reliability has no place here.<\/p>\n

4. Leave the concept of saturation to the grounded theorists<\/p>\n

In a similar vein to \u201cinter-rater reliability\u201d, we all too often read references to saturation in RTA studies. I wonder if this is in an effort to appease positivist editors or supervisors, or a desperate bid to cling to something concrete to guide sample sizes. You might be showing your positivist hand if you insist that \u201cinterviews will be conducted until data saturation is reached\u201d. The concept of saturation is that there comes a point after which \u201cno new information\u201d is produced by further interviews (or focus groups, or whatever mode of data collection is being undertaken). This makes sense in a grounded theory study, where the analyst is interested in finding the solution to a specific problem and will use theoretical sampling to simultaneously collect data as they analyse, thus allowing them to narrow down further and further towards an understanding of their new theory.<\/p>\n

However, in RTA, Braun and Clarke have been pretty clear on the topic: \u201c\u2026when it comes to reflexive TA, data saturation is not a particularly useful, or indeed theoretically coherent, concept\u201d (Braun & Clarke, 2019<\/a>). The more data you collect, the more possibilities for interpretation arise \u2013 the themes you develop after 10 interviews may look very different from the themes you might have developed if you conducted 20 interviews. You\u2019ll just have to make a pragmatic, interpretative judgement (and possibly be guided by Braun & Clarke\u2019s Thematic Analysis FAQ<\/a>). Try to be comfortable with the uncertainty.<\/p>\n

5. There isn\u2019t just one approach to Thematic Analysis<\/p>\n

\u2026although you\u2019d be forgiven for thinking so. Braun and Clarke\u2019s 2006 methodological paper \u201cUsing thematic analysis in psychology\u201d has several hundred thousand citations now, and their approach is used across a broad range of disciplines. However, theirs is not the only way, even if it is my favourite \u2013 clearly, I\u2019m not alone in this! There are other modes of thematic analysis, some of which have more neo-positivist roots. Thematic analysis\u2019 multiplicity is part of the reason why, post-2006, Braun and Clarke chose to differentiate by naming their method reflexive<\/strong> thematic analysis.<\/p>\n

If you are undertaking an RTA study, be explicit about this by naming it as such \u2013 and try to cite sources beyond that 2006 paper, to demonstrate your reflexive chops. And don\u2019t forget: be reflexive!<\/strong><\/p>\n

If you want help ensuring that your RTA is working as well as it can, just get in touch with us via the box below. We’ll be happy to help.<\/p>\n

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