Finding an analytical mechanism that can be employed to analyse Qualitative research is a road filled with laughter, tears, pain and in some cases misery. With so many differing approaches to choose from it can be a difficult decision to decide on what you feel is a suitable mechanism to help you analyse those interviews, documents and memos, which you have so meticulously collected over the lifetime of your research. Hence today I want to talk about what is a relatively new method of Qualitative Data Analysis called Template analysis (I say new but it is about 15 years old, so still a teenager!). I will discuss this as a viable alternative to IPA (Interpretative Phenomenological analysis).
Template analysis is described as a approach that involves applying a template (categories) based on prior research and theoretical perspectives. This is a relatively new method and while Langdridge (2007) mentions that it is now as well-known as IPA it still provides similar analytical rigour and facilitates the production of similar findings.
In the view of King (2004) template analysis is not associated with a single delineated method, it refers to multiple but related techniques for thematically organising and analysing codes (p. 256), therefore template analysis is a way of thematically analysing qualitative data (Miles & Huberman, 1994). The key difference between IPA and template analysis in the view of Langdridge (2007) is that IPA is always inductive and is grounded in the data with themes emerging from the text, thematic analysis differs from this and often uses pre-selected codes as a way of interrogating the data. The differences do not just stop there, King (2004) argues that template analysis is ideal for handling large data sets in an efficient and timely manner as opposed to other analysis approaches such as IPA, which is a lot more time consuming.
There has been a lot of discussion around the use of pre-defined codes (Priori) in helping to structure and analyse the collected data. This is a very iterative approach and the pre defined codes are valuable in helping to create the initial template. What the diligent researcher may find and will find is that in many cases the initial template does not fully capture the depth and scope of the collected data. Hence multiple read throughs of the data will be required and you will find multiple templates have been created, anything from 3-7 is normal. Also make sure you document the changes between each of the templates, this makes pretty good reading for external examiners and shows that you have been very analytical in your coding and template creation.
In creating the template King (2004) encourages the researcher to conceptualise the form of the template and identify how extensive this should be early on. King (2004) argues that it is easy to get carried away in this process, and where large amounts of data have been collected, it is easy for researchers to become overwhelmed (Auerbach & Silverstein, 2003). In the creation of a template, King (2004) does caution the researcher against developing a template that is to extensive and becomes an obstacle in the data analysis process, or at the other extreme, developing a template that is so sparse that clear direction is lacking.
I hope you found this blog post useful and it has helped you to define your analytical approach. Any comments, likes or shares would be appreciated.
Auerbach, C. F., & Silverstein, L. B. (2003). Qualitative data: An introduction to coding and analysis. NYU press.
Jabbar, A., & Hardaker, G. (2013). The role of culturally responsive teaching for supporting ethnic diversity in British University Business Schools. Teaching in Higher Education, 1–13. doi:10.1080/13562517.2012.725221
King, N. (2004). Using templates in the thematic analysis of texts. In C. Cassell & G. Symon (Eds.), Essential guide to qualitative methods in organizational research (pp. 256–270). London: Sage Publications.
Langdridge, D. (2007). Phenomenological psychology: Theory, research and method. Pearson Education.
Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. Sage.