research, writing

Tools of the trade

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I have a few bits of software which I use for my PhD which are not exactly run-of-the-mill (and some actually cost me money, albeit are great value) and I thought I’d write a blog about how they help me in my research.

First up is Scrivener. I have nooooo idea how people could write a PhD thesis using Microsoft Word. Word is hideous. It’s not as bad as Outlook (seriously awful) but having a word processor which crashes all the time (particularly with large documents) and seems to hate its users is not my idea of fun. Scrivener, on the other hand, is a pleasure to use. It was designed by people who actually seem to want to help you to write, and although it is extremely powerful with lots of features, you can just pick it up and start writing and figure out the bits you want to use later. You can dump ideas, web pages and references in there, compare different versions of documents side by side, take snapshots, write in a distraction-free environment, make a writing plan, move stuff around, work on tiny pieces of writing or zoom out to see the bigger picture, stitch different bits of writing together, edit fairly painlessly, add comments in lots of different ways, and probably do a few other million things I haven’t even explored yet. And it has never, ever crashed on me. You can also write on your iPad, or even on your iPhone if you’re a masochist, and your work syncs easily between devices without you having to think about it. It also avoids the problem of version control which plagues Word, so if you edit a document down you can take a snapshot (which you can then ‘roll back’) or you can dump the original version into another folder so it’s still there and accessible but not cluttering up your laptop with ‘final final version 2.1 15thApril2018. doc’.

Next is Quirkos, a simple bit of software for doing qualitative analysis. It’s basically a visual method of coding text by dragging and dropping relevant bits onto coloured bubbles which you can then move around to help your analysis. Although you might want to use something with more features (like NVivo) if you were doing a massive qualitative or group project, for my smallish studies it has been perfect, with almost no learning curve. It’s also very pleasant and pretty to use. The one thing it’s missing is a memo function (which is coming in the future apparently), but you can get round that in different ways. You can add memos to the project itself, which is what I did for my Resolve to Walk study, or you can screenshot the ‘canvas’ and chuck it in Scrivener to write about the big picture, which is what I’m doing for my Walk Jog Smile study (I’m using structured questions so adding memos won’t work for this).  Below is an example of some preliminary coding I’ve been doing for one study, I basically start coding as I add each interview or questionnaire, then keep coding as I go along. Then when I have a whole big mess on the screen and I think some patterns will become apparent I move things around into similar concepts and write about what I’m doing and what’s working and what needs more thinking about. You can click on any of the bubbles to see who said what in what context, you can do an overlap view to see which codes are closest, and you can run queries for different categories (this has been useful for me to compare different study conditions). There are a bunch of other features I don’t use much which are probably useful. The Quirkos blog is interesting and useful, and the developer is also super helpful if you have a problem. Whenever I do a talk and show my pretty Quirkos pics people want to know more, so I think there is definitely a place for Quirkos for those who don’t need the bells and whistles of other software.

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Finally, one more tool of the trade which has been extremely useful is If This Then That. This is a bit hard to explain, but it’s basically a way of linking different apps together to accomplish a certain goal, with no coding required. So you use something happening in one app as a ‘trigger’ to do something in another app. Below are a couple of the ‘healthy habits applets’ showing some different things you could automate if you’re so inclined.

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I’ve been using IFTTT as a way of emailing participants a feedback questionnaire each time they’ve completed an activity. It’s basically a neat way of doing an online diary study, and I’m not sure how else I could have managed this without either some serious technical knowledge or using some kind of commercial gadgetry. Neither of those are really within my research budget of approximately £0.05. It’s also been a massive time saver for me. I had to manually transfer all my app data for a previous study and it took me literally weeks to do and was open to data entry errors, whereas IFTTT does this all for me and pops the data I need into a spreadsheet. Amazing. Now if someone could come up with something similar for transcribing, that would be even more amazing!

 

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