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Analyzing Qualitative Data
April 4, 2019
A research project is often a big logistical undertaking, qualitative or otherwise. Through literature reviews, developing research questions, grant applications and funding, ethics/IRBs, managing co-researchers and supervisors, recruitment, collecting data from respondents, research journals, analysing data and writing up findings, there are a myriad of steps. Each will generate their own documents, data and processes that need to be managed, logged and kept for prosperity (and your review committee).
However, many people don’t realise that qualitative analysis software (like Quirkos, but others as well) and be used to manage and help keep together all the different stages of the research process. After all, they are designed to organise and make sense of unstructured text data. I’ve spoken before about how good CAQDAS/QDA software is for managing a literature or systematic review, but it can also be used to help with many of the other aspects of running a research project.
A good example is participant management. You probably have a target number of respondents to sample, and what their ideal characteristics are. As soon as they have been recruited, you will want to collect not just names and basic demographic data, but information about where and when an interview or focus group will be/was recorded, if they’ve signed and returned their ethics/permission form, and your own reflections on the session. I used to keep a separate Excel spreadsheet with all this information (password protected of course) and was constantly checking it to make sure I was recruiting a representative sample, updating interview dates, or noting reasons people dropped out.
But all this can be recorded in the project file of your qualitative analysis software! In Quirkos, you can ‘tag’ or describe your sources with any number of properties or characteristics, even when the source is empty! So you can create a source to represent each potential participant in the project, and use this to store any information you need on them. And even to remind you when you’ve scheduled an interview! You will need all this data later, so why not just input it into the computer once? You can keep any details like age or gender, whether you got their consent form back, as well as the actual data or transcript of the interview itself.
The beauty of doing it this way is that you can quickly run a query in the software to see which participants still haven’t been interviewed, to see ones that were contacted in a certain date range, or anything else. It becomes like a participant management system! You can update information here at any time, keep notes and comments to yourself, and once the data is coded see results from people that meet any number of these criteria. Want to see coded results just from people who were in a focus group in the first month of your data collection? No problem!
Quirkos will also generate graphs of your source property data, so you can see as you go along what proportion of your respondents are in a certain age range, or if there is an unequal gender distribution emerging. Give access to the project to your co-researchers or participants, and they can see this too, and suggest ways to improve sampling and recruitment as it is happening. Think of it as a master file for your research.
Since Quirkos imports the full text of your sources from the documents you import into the project file, you can keep all your research data in one place – a single file that is easy to search across, and most importantly back up. If everything is in your Quirkos project file, just copy to a USB drive, Dropbox or iCloud to make sure all your data (and ongoing analysis) is safe in multiple locations in case anything happens to your computer. No more searching for folders where you’ve hidden that missing transcript! Since the project can be password protected, you can also ensure the security and confidentiality of the data inside it.
Think of it as your own data repository, where you can keep all (or some) of your literature, data, thoughts and supporting documents, in a categorisable format so you can look at just some or all of these things that would normally be strewn across separate files on your computer.
Once you come to writing up your data, not only will you be able to quickly export interesting quotes from your data, but also tables of all the participant data (anonymised as you need to), and highlights from the literature. If you have a manual or separate system for collating this data it can be time consuming (and often a last minute panic) to creating appendices for papers or a thesis, or visualisations for presentations and posters. But if all this data is in your qualitative software project, it’s available to export with a click.
If you are able to start analysis during data collection, you can also identify gaps that you might need to fill in with more recruitment. You may analyse half your sources and discover you don’t have any comments from women under 35 on a particular topic, so you can either adjust your sampling strategy or your interview guide to make sure you cover this area!
Data management can continue during the writing up process as well. You can create codes to tag quotes that were used in particular papers or chapters to make sure you don’t use the same verbatims too often. Create codes (or bubble Quirks in Quirkos) to keep the best quotes together on any topic, and even create bubbles to represent thoughts, ideas and theories, even if no data is coded to them yet. Since Quirkos lets you move, group and colour-code codes as bubbles in the canvas area, it can also be used as a basic mind-mapping tool.
You also don’t have to actually do any coding in qualitative software: if you have all this information together, why not use it as a reading device – a place where you can keep comments and memos as you conduct your first read-throughs of your data. If you are printing out transcripts or reading data in Word and scribbling notes on the side there, they are likely to get lost or disorganised, and they can be valuable context for later understanding the data.
There’s also the other pieces of qualitative data that you might want to use the data management features of qualitative software to keep together, such as relevant literature, your own reflexive research journal (it’s great to be able to code and quickly find sections of both of these resources) but also even your grant application or original proposal. Keep cross coding to show how your data is meeting key points you’ve promised to cover, and your original predictions.
Feedback from our users tells us that project data management is one of the most important reasons that they use Quirkos, and we’ve designed the software to be as flexible as possible for all kinds of qualitative research projects. The best way to learn the software is to see it in action, or download the free trial and play with it yourself. It’s also cheap to own, and might even make your qualitative analysis and data management fun again!