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By Qual Academy partner Elly Phillips
This is another post inspired by a frequently asked question on the IPA discussion forum.
Qualitative researchers have strong feelings on both sides about whether Qualitative Data Analysis software, such as NVivo, should be used in general and for conducting IPA in particular. The main concerns include that software isn’t appropriate for IPA and generally that it encourages superficial engagement with data and the analytic process. On the other hand, I’ve seen comments from students (and some faculty) suggesting that they believe software is necessary to conduct a ‘good’ analysis.
There are strengths and limitations to using data analysis software, and this post provides both objective pros and cons and some more personal observations from my experience. I hope these help you decide what would work best for you.
Let’s start on a positive note!
Pros
The ‘objective’ ones
✅ Software makes it easier to organise and manage large quantities of data. You can navigate to your data files and your analysis from a central location without worrying about setting up folders and finding files.
✅ The search functionality quickly finds instances of words or concepts. It’s handy to track down something you’re SURE you read in your data, or when you have an idea you want to check with the larger data corpus.
✅ You can create mind maps or other visual representations of your data (if that works for you), and you can often create links between items.
✅ It’s ‘tidier’ than using Word comments or Excel (which I have used as an alternative when I haven't had access to NVivo), especially if you want to link one piece of data with several different ideas.
✅ You can see how much of the transcript is covered by your initial noting, how much data you have with each label, and quickly combine or rename your exploratory notes as they develop. Although ‘how many’ isn’t a criterion in most qual research, it can be a useful overview.
✅ You can share with supervisors and collaborate with others. You can export all the data with one 'label' to files, quickly bringing together extracts to manipulate in other packages.
My personal experiences
✅ I avoid the experience of ‘analysis paralysis’ that I get from pages of printed data.
✅ I can easily tweak what I’ve done (initial noting, extending or reducing the amount of data included in a note).
✅My handwriting is also terrible, so I can read what I’ve written later!
Example of exploratory noting by Dr Fiona Holland
Cons
The ‘objective’ ones
👎 Learning to use software can be a steep learning curve, and you might not want to take the time or feel comfortable with that.
👎 The functions provided don’t map well to the steps of IPA, so you’ll need ways to implement other parts of the analysis process. From what I’ve seen, everyone finds different ways that work best for them.
👎 I’ve heard people struggle to bring order to their analysis, even using software (see points below).
👎 You need a licence, so if you’re not at an institution with a subscription, then you might be priced out.
My personal experiences
👎 I don’t always find NVivo that user-friendly.
👎 I'm sure I don't use all the functionality as thoroughly as I could.
I realise this list is short, but that's a reflection of the fact that I DO use software in my analysis!
Whether you conduct your analysis on paper or using software, these things are tools. You do the work of analysis, and neither guarantees a ‘good’ analysis, that you’ve done ‘enough’ or that you are are adhering to the conventions of your approach.
Image by Thierry Milherou from Pixabay
If you're on the fence, you should:
Figure out how you like to work: if you love the physicality of writing, manually organising your slips of paper with your data extracts, and the visual satisfaction from using coloured pens or pencils, etc., then go for it.
Keep checking in about whether your chosen strategy is working for you, and don’t be afraid to change direction, especially early on when you’re figuring out your process.
In any case, you must:
Be mindful of the process associated with your chosen approach and ensure you’re conducting it in a transparent and traceable way. Don’t let the limitations of the software drive your analysis.
Stay focused on the content and meaning of your data and the aims of your research.
I’ve used Excel as an alternative when I didn’t have access to NVivo, and it offers other benefits, for example, spreadsheets make it easy to lay out tables with quotes and themes, as well as sort and filter them. I share that in our workshops and can also work with you 1:1 to help create a data management strategy that works for you.
Where to find more
In Wagstaff et al. (2014), various people share their experiences using IPA, including my remarks about using NVivo for my PhD.
There are also multiple discussions on the IPA forum about this, if you want to see other opinions or perspectives.
Reference
Wagstaff, C., Jeong, H., Nolan, M., Wilson, T., Tweedlie, J., Phillips, E., Senu, H., & Holland, F. (2014). The accordion and the deep bowl of spaghetti: Eight researchers’ experiences of using IPA as a methodology. The Qualitative Report, 19(47), 1–15.
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