An introduction to Interpretative Phenomenological Analysis

introduction to Interpretative Phenomenological Analysis

 

Interpretative Phenomenological Analysis (IPA) is an increasingly popular approach to qualitative inquiry and essentially an attempt to understand how participants experience and make meaning of their world. Although not to be confused with the now ubiquitous style of beer with the same initials (India Pale Ale), Interpretative Phenomenological Analysis is similarly accused of being too frequently and imperfectly brewed (Hefferon and Gil-Rodriguez 2011).



While you will often see it described as a ‘method’ or even an analytical approach, I believe it is better described as more akin to an epistemology, with its own philosophical concepts of explaining the world. Like grounded theory, it has also grown into a bounded approach in its own right, with a certain group of methodologies and analytical techniques which are assumed as the ‘right’ way of doing IPA.



At its heart, interpretative phenomenological analysis is an approach to examining data that tries to see what is important to the participant, how they interpret and view their own lives and experiences. This in itself is not ground-breaking in qualitative studies, however the approach originally grew from psychology, where a distinct psychological interpretation of how the participant perceives their experiences was often applied. So note that while IPA doesn’t stand for Interpretative Psychological Analysis, it could well do.



To understand the rationale for this approach, it is necessary to engage with some of the philosophical underpinnings, and understand two concepts: phenomenology, and hermeneutics. You could boil this down such that:

   1. Things happen (phenomenology)

   2. We interpret this into something that makes sense to us (hermeneutics - from the Greek word for translate)



Building on the shoulders of the Greek thinkers, two 20th century philosophers are often invoked in describing IPA: Husserl and Heidegger. From Husserl we get the concept of all interpretation coming from objects in an external world, and thus the need for ‘bracketing’ our internal assumptions to differentiate what comes from, or can describe, our consciousness. The focus here is on the individual processes of perception and awareness (Larkin 2013). Heidegger introduces the concept of ‘Dasein’ which means ‘there-being’ in German: we are always embedded and engaged in the world. This asks wider questions of what existence means (existentialism) and how we draw meaning to the world.



I’m not going to pretend I’ve read ‘Being and Time‘ or ‘Ideas’ so don’t take my third hand interpretations for granted. However, I always recommend students read Nausea by Sartre, because it is a wonderful novel which is as much about procrastination as it is about existentialism and the perception of objects. It’s also genuinely funny, and you can find Sartre mocking himself and his philosophy with surrealist lines like: “I do not think, therefore I am a moustache”.



Applying all this philosophy to research, we consider looking for significant events in the lives of the people we are studying, and trying to infer through their language how they interpret and make meaning of these events. However, IPA also takes explicit notice of the reflexivity arguments we have discussed before: we can’t dis-embody ourselves (as interpreters) from our own world. Thus, it is important to understand and ‘bracket’ our own assumptions about the world (which are based on our interpretation of phenomenon) from those of the respondent, and IPA is sometimes described as a ‘double hermeneutic’ of both the researcher and participant.



These concepts do not have to lead you down one particular methodological path, but in practice projects intending to use IPA should generally have small sample sizes (perhaps only a few cases), be theoretically open, exploratory rather than testing existing hypotheses, and with a focus on experience. So a good example research question might be ‘How do people with disabilities experience using doctor surgeries?’ rather than ‘Satisfaction with a new access ramp in a GP practice’. In the former example you would also be interested in how participants frame their struggles with access – does it make them feel limited? Angry that they are excluded?



So IPA tends to lead itself to very small, purposive sampling of people who will share a certain experience. This is especially because it usually implies very close reading of the data, looking for great detail in how people describe their experiences – not just a line-by-line reading, but sometimes also reading between the lines. For appropriate methodologies then, focus groups, interviews and participant diaries are frequently applied. Hefferon and Gil-Rodriguez (2011) note that students often try and sample too many people, and ask too many questions. IPA should be very focused on a small number of relevant experiences.



When it comes to interpretation and analysis, a bottom-up, inductive coding approach is often taken. While this should not be confused with the theory building aims of grounded theory, the researcher should similarly try and park or bracket their own pre-existing theories, and let the participant’s data suggest the themes. Thematic analysis is usually applied in an iterative approach where many initial themes are created, and gradually grouped and refined, within and across sources.



Usually this entails line-by-line coding, where each sentence from the transcript is given a short summary or theme – essentially a unique code for every line focusing on the phenomena being discussed (Larking, Watts and Clifton – 2006). Later would come grouping and creating a structure from the themes, either by iterating the process and coding the descriptive themes to a higher level, or having a fresh read though the data.



A lot of qualitative software packages can struggle with this kind of approach, as they are usually designed to manage a relatively small number of themes, rather than one for each line in every source. Quirkos has definitely struggled to work well for this type of analysis, and although we have some small tweaks in the imminent release (v1.5) that will make this bearable for users, it will not be until the full memo features are included in v1.6 that this will really be satisfactory. However, it seems that most users of line-by-line coding and this method of managing IPA use spreadsheet software (so they can have columns for the transcript, summary, subordinate and later superordinate themes) or a word-processor utilising the comment features.

 

However you approach the analysis, the focus should be on the participant’s own interpretation and meaning of their experiences, and you should be able to craft a story for the reader when writing up that connects the themes you have identified to the way the participant describes the phenomenon of interest.



I’m not going to go much into the limitations of the approach here, suffice it to say that you are obviously limited to understanding participant’s meanings of the world through something like the one-dimensional transcript of an interview. What they are willing to share, and how they articulate may not be the complete picture, and other approaches such as discourse analysis may be revealing. Also, make sure that it is really participant’s understandings of experiences you want to examine. It posits a very deep ‘walk two moons in their moccasins‘ approach that is not right for boarder research questions, perhaps when wanting to contrast the broad opinions of a more diverse sample. Brew your IPA right: know what you want to make, use the right ingredients, have patience in the maturation process, and keep tasting as you go along.



As usual, I want to caution the reader against taking anything from my crude summary of IPA as being gospel, and suggest a true reading of the major texts in the field are essential before deciding if this is the right approach for you and your research. I have assembled a small list of references below that should serve as a primer, but there is much to read, and as always with qualitative epistemologies, a great deal of variety of opinion in discourse, theory and application!

 

 

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Finally, don't forget to give Quirkos a try, and see if it can help with your qualitative analysis. We think it's the easiest, most affordable qualitative software out there, so download a one month free trial and see for yourself!



References

Biggerstaff, D. L. & Thompson, A. R. (2008). Qualitative Research in Psychology 5: 173 – 183.
http://wrap.warwick.ac.uk/3488/1/WRAP_Biggrstaff_QRP_submission_revised_final_version_WRAP_doc.pdf

Hefferson, K., Gil_Rodriguez, E., 2011, Methods: Interpretative phenomenological analysis, October 2011, The Psychologist, 24, pp.756-759

Heidegger, M. ( 1962). Being and time (J. Macquarrie & E. Robinson, Trans.). Oxford, UK: Blackwell. (Original work published 1927)

Husserl, E. ( 1931). Ideas: A general introduction to pure phenomenology (W.R. Boyce Gibson, Trans.). London, UK: Allen & Unwin.

IPARG (The Interpretative Phenomenological Analysis Research Group) at Birkbeck college http://www.bbk.ac.uk/psychology/ipa

Larkin, M., Watts, S., & Clifton, E. 2006. Giving voice and making sense in interpretative phenomenological analysis. Qualitative Research in Psychology, 3, 102-120.

Larkin, M., 2013, Interpretative phenomenological analysis - introduction, [accessed online] https://prezi.com/dnprvc2nohjt/interpretative-phenomenological-analysis-introduction/

Smith, J., Jarman, M. & Osborn, M. (1999). Doing interpretative phenomenological analysis. In M. Murray & K. Chamberlain (Eds.) Qualitative health psychology, London: Sage.

Smith J., Flowers P., Larkin M., 2009, Interpretative phenomenological analysis: theory, method and research, London: Sage.
https://us.sagepub.com/sites/default/files/upm-binaries/26759_01_Smith_et_al_Ch_01.pdf

 

 

Qualitative research on the Scottish Referendum using Quirkos

quirkos overlap or cluster view of bias in the media

 

We've now put up the summary report for our qualitative research project on the Scottish Referendum, which we analysed using Quirkos. You can download the PDF of the 10 page report from the link above, I hope you find something interesting in there! The full title is "Overview of a qualitative study on the impact of the 2014 referendum for Scottish independence in Edinburgh, and views of the political process" and here's the summary findings:

 

"The interviews revealed a great depth of understanding of a wide range of political issues, and a nuanced understanding of many arguments for and against independence. Many people described some uncertainty about which way to vote, but it did not seem that anyone had changed their mind over the course of the campaigning.


There was a general negative opinion towards the general political system, especially Westminster, from both yes and no voters. Participants had varying opinions on political leaders and parties, even though some people were active members of political parties. Yes and No supporters both felt that the No campaign was poorly run, and used too many negative messages, this feeling was especially strong in No voters.
The most important concerns for responders was about public finances, financial stability of an independent Scotland, the issue of currency for Scotland was often mentioned, but often with distrust of politicians comments on the subject. Westminster induced austerity and the future of the NHS also featured as important policy considerations.


People expressed generally negative views of the media portrayal of the referendum, most feeling that newspapers and especially the BBC had been biased, although No supporters were more likely to find the media balanced.


In general, people felt that the process had been good for Scotland, even No supporters, and there was general support for greater devolution of powers. People had seen the process as being very positive for the SNP, and nearly all respondents felt the Yes campaign had been well run. People expressed a negative view of the Labour party during the campaign, although voters also mentioned strong criticism of Labour’s wider policy position in recent years. People had generally positive opinions of Nicola Sturgeon, mixed reactions to Alex Salmond, and generally negative comments on Ed Miliband’s public image, while also stating that this should not be an important factor for voters. People believed that the polls would be correct in predicting a swing from Labour to the SNP in Scotland.


Many expressed a belief that the level of debate in Edinburgh had been good, and that the Yes campaign was very visible. Respondents were positive about the inclusion of voters from the age of 16, were surprised at how much support the Yes campaign generated, and some felt that a future referendum would be successful in gaining independence for Scotland."

 

The report also contains some information about the coding process using Quirkos:

 

"The interviews together lasted 6.5 hours and once transcribed comprised just under 58000 words, an average of 4800 words per interview. 75 themes were used to code the project, with 3160 coding events logged, although each text may cover multiple coding events. In total, 87% of the text was coded with at least one topic. The coding took an experienced coder approximately 7 hours (over a three day period) once any breaks longer than 5 minutes were removed, an average of one code every 8 seconds."

 

Personally, I've been really happy doing this project with Quirkos, and especially with how quick it took to do the coding. Obviously, with any qualitative analysis process there is a lot of reading, thinking and mind-changing that happens from setting the research questions to writing up a report. However, I really do think that Quirkos makes the coding and exploration process quicker, and I do love how much one can play with the data, just looking to see how much keywords come up, or whether there are connections between certain themes.


In this project, the cluster views (one for media bias shown above) were really revealing, and sometimes surprising. But the side-by-side queries were also really useful for looking to see differences in opinions between Yes and No supporters, and also to demonstrate there was little difference in the quotes from men and women – they seemed to largely care about the same issues, and used similar language.


Feel free to see for yourself though, all the transcripts, as well as the coded project file can be downloaded from our workshop materials pages, so do let me know if Quirkos lets you have a different view on the data!