Thematic analysis has become very popular in the past ten years, and there are many variations of it. I have used Framework method (Dixon-Woods 2011; Ritchie et al. 2013; Smith and Firth 2011), Applied Thematic Analysis (Guest et al. 2012) and Content analysis (Graneheim and Lundman 2004; Hsieh and Shannon 2005) in my research, all of which were suitable for different purposes in different studies.
But a key question is: what are themes, and how do we generate good quality themes?
I recently came across a YouTube video of Clarke (from Braun and Clarke 2006) describing the difference between a domain summary (she describes it as a bucket) and a theme (she described it as a storybook). I thought this was a really good example of distinguishing between a real/good quality theme, and a poor theme (if you get a chance, I would recommend you watch the video).
In summary, there are two different types of ‘themes’ that researchers tend to narrate in research papers:
1. A domain summary is a summary of an area (domain) of the data. For example, a summary of everything the participants said in relation to an interview question or a particular theme. So for example, a domain summary type theme could be titled: “Perceived risks of taking insulin medication”. This ‘theme title’ has come directly from a question asked. This is not a theme and should be avoided. If you have come up with this type of ‘theme’, you need to go back to the data, and do further analysis to draw out a real theme (See #2).
2. A theme identifies an area of the data that tells the reader something about it. It illustrates patterns in the data that are underpinned by a central concept that organises the analytic observations. So for example, a theme in relation to medication could be “Exerting control” for example.
My way of explaining the difference would be that a ‘theme’ is a complete sentence, and can sit alone without requiring the text beneath it (so “Exerting Control” is meaningful), whereas a ‘domain summary’ is the opposite; it requires further explanation (so ‘perceived risks of taking insulin medication’, alone doesn’t actually tell you anything meaningful about your data, nor does it narrate a story). Domain summaries are therefore not themes, and should be avoided when reporting qualitative analysis.
- Braun, V. & Clarke, V. (2006) Using thematic analysis in psychology. Qualitative research in psychology. [Online] 3 (2), Taylor & Francis, 77–101. Available from: doi:10.1191/1478088706qp063oa.
- Dixon-Woods, M. (2011) Using framework-based synthesis for conducting reviews of qualitative studies. BMC medicine. [Online] 9 (1), BioMed Central Ltd, 39. Available from: doi:10.1186/1741-7015-9-39 [Accessed: 4 November 2012].
- Graneheim, U.H. & Lundman, B. (2004) Qualitative content analysis in nursing research: concepts, procedures and measures to achieve trustworthiness. Nurse education today. [Online] 24 (2), 105–12. Available from: doi:10.1016/j.nedt.2003.10.001.
- Guest, G., MacQueen, K.M. & Namey, E.E. (2012) Applied Thematic Analysis. USA, SAGE Publications.
- Hsieh, H.-F. & Shannon, S.E. (2005) Three approaches to qualitative content analysis. Qualitative health research. [Online] 15 (9), 1277–88. Available from: doi:10.1177/1049732305276687.
- Ritchie, J., Lewis, J., Nicholls, C.M. & Ormston, R. (2013) Qualitative Research Practice: A Guide for Social Science Students and Researchers. 2nd edition. London, SAGE Publications.
- Smith, J. & Firth, J. (2011) Qualitative data analysis: the framework approach. Nurse researcher. [Online] 18 (2), 52–62. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21319484.
The University of Auckland has a really useful resource on this topic, explaining the difference between, codes, domain summary and themes.
For my own reference (and in-case the resource goes missing) I am going to copy the key points from the resource directly here:
What’s the difference between a domain summary and a theme?
The difference between a theme and a domain summary is a source of frequent confusion in much published TA research. A domain summary is a summary of an area (domain) of the data; for example, a summary of everything the participants said in relation to a particular topic or interview question. Unlike themes, there isn’t anything that unifies the description of what participants said about this topic – there is no underlying concept that ties everything together and organises the analytic observations. In our approach to TA, themes are conceptualised as patterns in the data underpinned by a central concept that organises the analytic observations; this is rather different from a domain summary, and the two should ideally not be confused when using our approach. More simply put, a theme identifies an area of the data and tells the reader something about it. To make things complicated, some approaches to TA do conceptualise themes as domain summaries – this conceptualisation of themes is evident in both coding reliability approaches (see Boyatzis, 1998; Guest et al., 2012) and codebook approaches, such as template, framework and matrix analysis. Sometimes the confusion between domain summaries and themes is simply an issue of poorly named themes – the theme itself is a conceptually founded pattern, but the theme name does not reflect this. ‘Experiences of Y’ or ‘Benefits of X’ are classic examples of domain-summary type theme names. These theme names identify that, for example, ‘benefits of X’ was an important area of the data in relation to the research question(s), but they don’t communicate the essence of this theme; they don’t tell the reader something specific about these benefits and what underlying concept underpinned what the participants had to say about the benefits of X.
To understand more about the differences between domain summaries and fully realised themes, we recommend the following three papers:Connelly, L. M. & Peltzer, J. N. (2016). Underdeveloped themes in qualitative research: Relationships with interviews and analysis. Clinical Nurse Specialist, January/February, 51-57.DeSantis, L. & Ugarriza, D.N. (2000). The concept of theme as used in qualitative nursing research. Western Journal of Nursing Research, 22(3), 351-372.Sandleowski, M. & Leeman, J. (2012). Writing usable qualitative health research findings. Qualitative Health Research, 22(10), 1404-1413. SOURCE
What’s the difference between a code and a theme?
A theme captures a common, recurring pattern across a dataset, clustered around a central organising concept. A theme tends to describe the different facets of that singular idea, demonstrating the theme’s patterning in the dataset.
Codes tend to be more specific than themes. They capture a single idea associated with a segment of data, and consist of pithy labels identifying what is of interest in the data (in relation to the research question). Codes can be conceptualised as the building-blocks that combine to create themes – so multiple codes typically are combined to create themes, during the process of TA.
What is a central organising concept and why is it important in thematic analysis?
A central organising concept captures the essence of a theme. It is an idea or concept that captures and summarises the core point of a coherent and meaningful pattern in the data. If you can identify the central organising concept of a theme, you can capture the core of what your theme is about. If you cannot do this, your theme may lack coherence.