Mixed methods or mixed up?
By Lorraine McDonagh, on 19 February 2018
In this post, Kingshuk Pal discusses his experiences of moving from qualitative research to quantitative research.
So I’m between research methodologies. It’s a bit awkward as you might imagine. Bumbling my way through a no-man’s land between two opposing paradigms – the self-conscious embarrassment of adolescence an unwelcome companion once more. I question myself constantly. Was I truly unhappy being where I was? Is the promise of happiness at the other end of the rainbow just a fairy tale?
Should I seek to define myself as a qualitative researcher or a quantitative researcher? Can I meaningfully be both? Am I method-fluid, mixed-methods or just mixed-up?
The transition is certainly not an easy process. Language acquisition skills apparently peak by age 7, so the evidence-based solution for learning Stata would be to find a time machine that can transport me back in time 30 years or so. But as my time-machine building efforts are short a DeLorean and flux-capacitor or two, having a study group and working through a short introduction to Stata for biostatistics with my colleague Tom Hartney has certainly proved a remarkably helpful alternative. Amazing what you can learn from copying the homework of someone way smarter than yourself. Sadly my attempts to learn about medical statistics and epidemiology have not gone quite so well. My textbooks are currently gazing down at me judgementally from a shelf where they are gainfully employed as bookends… Maybe I can start a book club… targeting anyone suffering from insomnia. For any readers still awake – thanks – and please let me know if you’ve got any good suggestions for epidemiology or stats courses…
There may be some people curious about what tempted me over to what my qualitative friends suspiciously view as the “dark side”. I’m exploring the links between diabetes and depression by looking at routinely collected primary care data (from the THIN database). Poorly controlled diabetes increases the risk of heart attacks, strokes, amputation, blindness and renal failure (National Collaborating Centre for Chronic Conditions, 2008). The presence of depression increases the risk of poorer outcomes in diabetes as it is associated with poor glycaemic control and increased rates of complications (de Groot et al. 2001; Lustman et al. 2000). Depression has also been found to double the likelihood of being diagnosed with diabetes (Eaton et al. 1996; Kawakami et al. 1999). The relationship between the two might be partly due to shared underlying pathophysiology driven by changes in stress hormones in the hypothalamus-pituitary-adrenal cortex axis and sympathetic nervous system (Renn et al., 2011; Snoek et al., 2015). Both conditions are also associated with subclinical inflammation (Tabák et al., 2014). There are also behavioural factors and complications associated with these conditions that link them through poorer self-care due to raised BMI, reduced physical activity etc. (Lin et al., 2004). The net result is a shared increase in vulnerability to these common chronic conditions and poorer outcomes (including increased mortality) where they co-exist (Park et al., 2013). My area of interest is the use and impact of anti-depressants in people with type 2 diabetes and seeing how that reflects the interactions described above.
In contrast, part of my doctoral work on the HeLP-Diabetes project was qualitative research that touched on the negative emotional burden (diabetes related distress) that was placed on people living with type 2 diabetes (Kingshuk et al., 2018). And now I sometimes think about which might be more helpful for me as a doctor – to understand or measure the impact of depression and distress in people living with type 2 diabetes? Clearly I need to be able to do both. If I don’t understand what it means to be depressed with diabetes, it’s harder for me to engage with patients and frame my advice in terms that are meaningful and relevant for them. But when time and resources are increasingly limited, I need evidence to help guide me as to how hard I look for depression, who I should focus on and what the best treatment option might be.
So as a clinician, I need both. But as a researcher can I do both? There is often debate in the medical profession about the merits of generalists Vs specialists. And most GPs would unsurprisingly mount a passionate case for the role of the generalist providing holistic care and continuity over time which is different to the focused care provided by specialists. So I hope the same is true with research – and maybe somewhere there’s a place for a mixed-up researcher like me…