Thematic analysis is a research method which uses qualitative data. However, the term may be more accurately seen as an umbrella term incorporating many different research processes (Joffe, 2011). The aim of the process is to examine the data looking for themes or trends in the data being analysed in order to ascertain the meanings of those patterns (Guest, McQueen and Namey, 2012). Braun and Clarke (2006) provide a succinct definition stating it is “a method for identifying, analyzing and reporting patterns within data.” (p. 79). Although often underappreciated, the methodology has a long history, initially proposed in the 1970s and only more recently gaining more attention (Clarke and Braun, 2013). There are multiple approaches towards thematic analysis, indicating this is a very flexible method that can be adapted based on the type of data being assessed as well as the chosen epistemology and reasoning approaches (Cresswell et al., 2003). However, without a specific universal definition of what a ‘theme’ is, the process may be seen as potentially ambiguous, but this also indicates flexibility. Therefore, it may be applied to many types of research and multiple data types.
Thematic analysis is a methodology which should be applied when there are qualitative datasets. The process is most commonly seen analysis sources such as interview transcripts, social media content, news articles, and literature (Joffe, 2011). It may be applied where there is a broad or a narrow research question or purpose, where the research is drawn on the views, perceptions, or the experiences of people regarding a particular phenomenon (Boyatzis, 1998). The process may be applied to look at surface patterns or investigate data for deeper meanings, as defined by Braun and Clarke (2006) as semantic and latent. The semantic analysis is undertaken looking for the surface of explicit meanings, basing the analysis only on what was said or is in the text (Braun and Clarke, 2006). The latent analysis takes a deeper approach, seeking to identify underlying influences and ideologies that lead to the outcome observed in the data (Braun and Clarke, 2006). Therefore, this is a process that is most suited to research concerning representations and understandings and studies seeking to ascertain how social constructs are created (Braun and Clarke, 2019).
Braun and Clarke (2006) developed an approach referred to as reflective thematic analysis, a theoretically flexible approach, allowing it to be used in a wide range of frameworks. Therefore, it may be used to answer a wide range of different questions across different disciplines, such as how a sample perceive an event, experiences of people in particular circumstances which may also be expanded to consider the causes of the experiential perception, and the reasons why specific actions are undertaken (Boyatzis, 1998).
Another benefit of thematic analysis its comparative ease of application compared to other methodologies. The methodology is also very useful for students who have little research experience due to its flexibility and relatively simple application (Clarke and Braun, 2013; Maguire and Delahunt, 2017). Advocates argue that learning doing is the most effective approach, allowing the practice to lead to the theoretical understanding of the process (Clarke and Braun, 2013).
A major advantage of thematic analysis is its flexibility and potential for use by inexperienced researchers and the processed to be applied do not always need to be set in advance, for example, identification of the themes and the patterns can be identified after the data has been gathered; a process which may create the potential to identify issues that would be missed with more prescriptive approaches. However, this flexibility does not preclude the use of more prescriptive approaches if desired (Braun and Clarke, 2019). For example, the process of identifying the categories after collecting the data is aligned with the inductive approach, but it is also possible to use deductive reasoning by coding utilising existing concepts and predetermined ideas. In addition, semantic and latent approaches may be used; critical realist and constructionist approaches may also be applied (Braun and Clarke, 2019).
Another advantage is the ability to use software to automate some of the analysis processes (Firmin et al., 2017). Programs such as NVivo may be used, which can increase the ease of the analysis as well as the speed when examining a large amount of data (Bazeley and Jackson, 2013). This increases efficiency with the research processes and can facilitate the inclusion of larger data sources (Firmin et al., 2017).
Disadvantages include how the research is reliant on phrases, meaning the researcher may not always fully capture the meaning and nuisances of the phrases and the potential for a very time-consuming process where there is no use of software (Riger and Sigurvinsdottir, 2016). The difficulties may also include challenges identifying and assessing the core issues in the phrases provided. The interpretation of the results may also be seen as potentially weak if they do not have a theoretical grounding (Riger and Sigurvinsdottir, 2016). The flexibility may reduce the robustness of the research, and it is often seen as less credible compared to more widely used methodologies, especially others associated with the positivist epistemology (Guest, McQueen and Namey, 2012). The weakness of interpretation may also be argued as present in the lack of technical claims that can be made regarding the use of language, unlike processes such as narrative of discourse analysis (Riger and Sigurvinsdottir, 2016)
Thematic analysis can be found in many disciplines where the studies involve consideration of the people’s ideas, expressed feeling, perceptions and/or interactions. This means it can be applied to the areas of sociology and psychology, the latter being the focus of Braun and Clarke (2006). However, the approach can also be seen in disciplines as wide-ranging as education (Niccum et al., 2017), marketing (Mogaji and Yoon, 2019), gender studies (Bradford et al., 2019), and healthcare (Shen et al., 2019). In all cases, the subjects’ views, opinion, actions and/or reactions of people.
While there are many ways a thematic analysis may be undertaken, the stages involved in its applications remain the same (Braun and Clarke, 2006; Joffe, 2011; Boyatzis, 1998). Braun and Clarke (2006) present the process in the six stages of familiarisation, coding, the initial generation of themes, review of themes, defining and naming theme, writing up. Other theorists may refer to the stages or phases, but the processes are all similar. These are outlined below.
1. Familiarisation with the date requiring the research to read and then reread the information to become familiar with its contents, this is needed for the coding stage (Braun and Clarke, 2006, 2019).
2. Coding, where labels, or codes, are allocated to different pieces of data which may be useful in answering the research question. The coding should be applied to all the data to allow for correlation of the codes to help with the identification of the themes (Braun and Clarke, 2006, 2019).
3. Initial generation of themes based on the correlation of the codes, identifying the general patterns and assessing the viability of each of the topics within the context of the research scope (Braun and Clarke, 2006, 2019).
4. Review the themes identified and determine whether they can provide a convincing answer to the research questions based on the available data. This phases normally includes refining of the categories, and a potential assessment of underlying themes were the analysis is not based on a semantic methodology (Braun and Clarke, 2006, 2019).
5. The final themes used ion the analysis are defined and detailed, with the data within each theme or categories assessed concerning the research question. This stage also requires the final naming of the themes (Braun and Clarke, 2006, 2019).
6. Writing up the results includes the correlation of the results and the ‘weaving together’ of the different themes with an analytical narrative ready for presentation (Braun and Clarke, 2006, 2019).
Where thematic analysis is used, there should be a citation back to the authors describing the method employed, in line with the style instructed or chosen for the work. The intext details should include the author name, and usually the year, and possibly the page number depending on the style. Full publication detail should then be placed into the end reference list of bibliography. Examples are provided throughout this text.
A template for the analyse which may be used is presented below, assuming the data has been collected and then read and reread. The initial coding should be undertaken in the actual text, or with Software.
What themes have emerged which are relevant for the research questions
How can the themes be made more relevant, condensing the themes or expanding them to increase their validity for answering the research question?
Which themes are left after eliminating those which do not add value to the research
Define and name final themes
Weave the themes together to ensure they answer research questions viability. If they do not, return to re-examining the data
Draw conclusion and present
This process has been illustrated by Miles and Huberman (1994) is presented below.
(Miles and Huberman, 1994, p. 12)
A thematic analysis examining if weather impacted on the decision to exercise outdoor may result in identifying themes associated with the different types of weather, the impact the weather has on emotions and motivation, and how this influences the level and type of exercise taken. The results, once correlated, may indicate that winder cold weather is more likely to have a negative impact when the light is fading, with rain and brightness interrelated, and when combined, they appear to be negatively correlated with outdoor exercise. However, these may be mitigated when a third party organises the exercise or an official event, increasing motivation levels. The themes may also identify different attitudes of the sample based on the type of exercise, and other variables that manifest from the data.
Bazeley, P. and Jackson, K. (2013) Qualitative Data Analysis with NVivo, London, Sage Publications Ltd.
Boyatzis, R. (1998) Transforming Qualitative Information: Thematic Analysis and Code Development, London, Sage Publications Ltd.
Bradford, N. J., Rider, G. N., Catalpa, J. M., Morrow, Q. J., Berg, D. R. and Spencer, K. G. (2019) Creating gender: A thematic analysis of genderqueer narratives, International Journal of Transgenderism, 20(2–3), pp. 155–168.
Braun, V. and Clarke, V. (2019) Thematic analysis: a reflexive approach, The University of Auckland, [online] Available from: https://www.psych.auckland.ac.nz/en/about/thematic-analysis.html.
Braun, V. and Clarke, V. (2006) Using thematic analysis in psychology, Qualitative Research in Psychology, 3(2), pp. 77–101.
Clarke, V. and Braun, V. (2013) Methods: Teaching thematic analysis, The Psychologist, 25, pp. 120–123.
Cresswell, J. W., Clark, V. L. P., Gutmann, M. V. L. and Hanson, W. E. (2003) Advanced Mixed Methods Research Design, In Handbook of Mixed Methods in Social & Behavioral Research, Tashakkori, B., Teddlie, C., and Teddlie, C. B. (eds.), London, Sage Publications, pp. 209–240.
Firmin, R. L., Bonfils, K. A., Luther, L., Minor, K. S. and Salyers, M. P. (2017) Using text-analysis computer software and thematic analysis on the same qualitative data: A case example, Qualitative Psychology, 4(3), pp. 201–210.
Guest, G. S., McQueen, K. M. and Namey, E. E. (2012) Applied Thematic Analysis, London, Sage Publications.
Joffe, H. (2011) Thematic Analysis, In Qualitative Research Methods in Mental Health and Psychotherapy: A Guide for Students and Practitioners, Harper, D. and Thompson, A. R. (eds.), London, John Wiley & Sons, Ltd, pp. 209–223.
Maguire, M. and Delahunt, B. (2017) Doing a Thematic Analysis: A Practical, Step-by-Step Guide for Learning and Teaching Scholars, All Ireland Journal of Higher Education, 3, pp. 3351–33514, [online] Available from: file:///C:/Users/Terri/Downloads/335-Article Text-1557-1-10-20171031.pdf.
Miles, M. B. and Huberman, M. A. (1994) Qualitative Data Analysis, 2ND ed, London, Sage Publications.
Mogaji, E. and Yoon, H. (2019) Thematic analysis of marketing messages in UK universities’ prospectuses, International Journal of Educational Management, 33(7), pp. 1561–1581.
Niccum, B. A., Sarker, A., Wolf, S. J. and Trowbridge, M. J. (2017) Innovation and entrepreneurship programs in US medical education: a landscape review and thematic analysis, Medical Education Online, 22(1), p. 1360722.
Riger, S. and Sigurvinsdottir, R. (2016) Thematic Analysis, In Handbook of Methodological Approaches to Community-based Research: Qualitative, Quantitative, and Mixed Methods, Jason, L. and Glenwick, D. (eds.), Oxford, Oxford University Press, pp. 33–41.
Shen, M. J., Freeman, R., Karpiak, S., Brennan-Ing, M., Seidel, L. and Siegler, E. L. (2019) The Intersectionality of Stigmas among Key Populations of Older Adults Affected by HIV: a Thematic Analysis, Clinical Gerontologist, 42(2), pp. 137–149.
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