There are some differences between interpretative phenomenological analysis (IPA) and TA; however, the end result of an IPA and a TA analysis can be very similar.
Let’s consider the divergences between IPA and TA first, which result mainly from:
- The fact that IPA is better thought of as a methodology (a theoretically informed framework for how you do research) rather than a method (a technique for collecting/analysing data), whereas TA is just a method.
- Differences of procedure between IPA and TA.
We can think of IPA as like a piece of ready-made furniture – all the design choices (colour-scheme, dimensions, materials etc.) have been made for you. As well as outlining a range of analytic procedures, IPA specifies:
- what the ontological and epistemological underpinnings of your research are (critical realism and contextualism; see Larkin, Watts & Clifton, 2006),
- what theoretical framework should inform your research (phenomenology),
- what types of research questions you can ask (about people’s experiences and perspectives),
- what sampling strategy you should use (homogenous, small N), and
- how (ideally) you should collect data (qualitative interviews) (see Smith, Flowers & Larkin, 2009).
Obviously, we are simplifying the characteristics of IPA a bit, but the main point to take away is that IPA provides an entire framework for conducting research.
By contrast, TA is like the piece of furniture you build yourself, where you choose your colour scheme, the dimensions of the piece, the materials, etc. Because TA is just a method and the hallmark of TA is its flexibility:
- It can be used across the epistemological and ontological spectrum (TA can be realist or constructionist),
- It can be underpinned by phenomenology, as well as by any number of other theories,
- It can be used to address a wide range of research questions (including questions about people’s experiences and perspectives)
- There are no specific requirements for sampling in TA (we would generally recommend a larger N than for PA studies because TA does not share IPA’s ideographic focus – more on this below – but some degree of homogeneity in sampling is helpful in smaller studies), and
- It can be used to analyse most types of qualitative data (interviews, focus groups, diaries, qualitative surveys, secondary sources, vignettes, story completion tasks etc.)
IPA has a dual focus on the unique characteristics of individual participants (the idiographic focus mentioned above) and on patterning of meaning across participants. In contrast, TA focuses mainly on patterning of meaning across participants (this is not to say it can’t capture difference and divergence in data).
In terms of analytic procedures, both IPA and TA involve coding and theme development, but these processes are somewhat different for each method. Coding in TA begins after a process of data familiarisation, in which the researcher notes any initial analytic observations about each data item and the entire data-set. The researcher then codes across all of the data items. The researcher either collates the data relevant to each code as they code, or they collate all the relevant data at the end of the coding process. By contrast, coding in IPA consists of a process of ‘initial commenting’ or ‘initial noting,’ in which the researcher writes their initial analytic observations about the data on the data item (if working with interview transcripts, initial notes are usually recorded in a wide margin on the right hand side of the transcript). These initial notes are brief commentaries on the data (rather than succinct codes). This means initial noting in IPA lies somewhere between data familiarisation and coding in TA.
Another difference is that in IPA, the researcher codes their first data item then progresses to developing themes for that data item, rather than coding across the entire dataset, and then progressing to theme development. So IPA focuses on developing each stage of the analysis for each data item, before moving to the next; whereas TA involves developing each stage of analysis across the whole dataset.
With regard to types of code, IPA refers to both ‘descriptive’ and ‘conceptual’ comments and these are very similar to ‘semantic’ and ‘latent’ codes in TA .
In terms of procedures for theme development, there are two levels of theme development in IPA and one level in TA. In IPA, these are referred to as ‘emergent’ and ‘superordinate’ themes. Emergent themes are noted on the data item (if working with interview transcripts, emergent themes are usually recorded in a wide margin on the left hand side of the transcript). Superordinate themes are developed from emergent themes. Once coding and theme development is complete for each data item, the researcher develops superordinate themes across the dataset. In TA, themes are developed from the codes (and collated data), across all data items.
As a general rule, there will be a lot more emergent themes generated from an IPA compared to the number of themes generated from a TA; this means that emergent themes in IPA lie somewhere between codes and themes in a TA (somewhat akin tosubthemes in a TA). An IPA will generate roughly the same number of superordinate themes as the number of themes generated from a TA. However, another difference is that superordinate themes in an IPA simply provide an organising framework for the analysis, it is the emergent themes that are discussed in detail in the write-up.
Overall, IPA procedures help the researcher to stay close to the data, because you develop codes and themes on the actual data item, and to focus on the unique characteristics of each individual participant, because you code and develop themes for each data item in turn. By contrast, the procedures of TA help the researcher to identify patterns across the entire data-set.
Despite these procedural differences, the end result of an IPA and a phenomenologically-informed TA of interview data would potentially be quite similar – analytic procedures play some role in shaping analysis, but, in general, our conceptual lenses play a much greater role.
So what does this all mean for choosing whether to use IPA or TA? We’d recommend using TA when you want to address research questions that are not about people’s experiences or perspectives, when you want to use data that do not capture first-person accounts of personal experiences (such as focus groups or story completion tasks), and when working with larger samples. If you are asking an experiential-type question within a phenomenological framework based on the analysis of interview data – how do you choose between IPA and TA? There’s not a lot in it, but we’d recommend using IPA if you are working with a smaller sample and want to maintain a more idiographic focus, and TA if you are working with a larger sample and want to focus more on patterned meaning across the data-set.
- Larkin, M., Watts, S. & Clifton, E. (2006) Giving voice and making sense in interpretative phenomenological analysis. Qualitative Research in Psychology, 3, 102-120.
- Smith, J. A., Flowers, P. & Larkin, M. (2009) Interpretative phenomenological analysis: Theory, method and research. London: Sage.