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Analyzing Qualitative Data
November 27, 2013
The benefit of having tastier satsumas is difficult to quantify: to turn into a numerical, comparable value. This is essentially what qualitative work does: measure the unquantifiable quality of something. Just don’t ask what we mean by Quality – that opens a whole other can of worms…
In this context though, quality also means a lack of quality, or even a negative property such as pain. Pain is a great example of something that people want to quantify: to put in a linear scale out of 10 so that clinicians can prioritise patients, and choose appropriate treatments.
But pain is, in a sense, too multidimensional to be rated as one factor. Firstly, intensity doesn’t always seem to be linear, and muscle pain, bone pain and headaches seem to feel very different. People report different tolerances for pain, and how can people accurately report different levels of pain if they have never experienced the upper bounds? How do you know your patient’s headache is the worst pain imaginable if they’ve never given birth?
A typical qualitative approach would open a dialogue with the patient, partly to get to the bottom of some of these quandaries: Have you ever had pain this strong before? Is it a dull ache, or a sharp pain? Can you ignore it? What has worked well for you in the past? A clinician who can gain a deeper level of understanding might make a better treatment decision for the patient, coupled with their own knowledge and experience.
This is great, although it is probably more time intensive for the patient and clinician compared to using a pain thermometer. It’s also something that us typically social humans are really good at doing; talking to others to find out about their experience. When your partner comes home from work, most people don’t ask them to rate their day out of 10 and leave the conversation like that. I’d argue that most people are extremely attuned to qualitative discussion: we use it everyday, in verbal and non-verbal ways to understand each other.
Two of the main problems with this approach are the repeatability, and sharing of this understanding.
Can we have a conversation with different patients, so that every time we get comparable answers? Perhaps not: in fact this is probably not even desirable. If we don’t tailor the conversation to the individual’s patients situation, we might miss something. If we have a script, and the stock question is ‘Where is your pain?’, the answer ‘In my foot’ doesn’t allow us to say ‘Which foot?’ in a way that is not needed if the answer is ‘nose’.
Secondly, if we have spent all day talking to patients about their post-operation pain, how can we share these insights with others? Is that new pain medication working? Are those fancy dissolvable stitches causing problems for people? A nurse who has been asking these questions all day might have what we can crudely call, an intuitive sense of whether peoples pain in general is worse today, but this is difficult to prove and communicate. Another nurse might talk to the same patients, and have a different perspective. The question is: How can we make use of this qualitative data?
We’ll look at this more in the next post. But there are of course many other descriptions and definitions of qualitative approaches, in fact Guest et al. (2013) disturbingly note that
This is from Collecting Qualitative Data: A Field Manual for Applied Research (2013), and since this chapter is freely available online, this is as good a place to start as any.