When feasibility trumps robustness

While my PhD journey is nearing the final chapter (writewritewrite) I have naively decided to take on one last research study.  Over the past few years my research has morphed and changed into something quite different than I initially intended but I keep getting pulled back to my original concept.  One aspect of my research has been creating and developing informational resources for health workers in remote regions of Nepal.  It has been challenging but I’ve ended up with a resource that I feel quite proud of (thanks to many many people along the way).  So, now we want to know if this resource will actually have an impact for women with symptomatic prolapse in Nepal.

As a fresh face PhD student, my dreams and ideas were large and lofty 🙂  I wanted to create and develop informational resources then conduct a full RCT to test the impact of the resources.  I quickly learnt that you don’t just pull out any random number for the sample size but there is a sample size calculation that powers your study.  All of sudden my dreams seemed unachievable.  There was no way I could manage a study on my own with such high participant numbers in a country where I don’t speak the language.  I would need to rely heavily on local Nepali people to help me conduct the study and with no money to pay research partners, I had to lower my aspirations.

During the following years, I completed three studies that were all realistic and feasible.  The problem is that they all have poor study designs.  Now that I’m writing up the results, the flaws in study design stare at me glaringly.  The thought of writing up my results into peer reviewed journal articles makes me feel a little anxious and also a tad disappointed in myself.

So now I have one last chance to get it right, but I’m faced with the exact same dilemmas.  It’s not only that I don’t have funding to conduct a full RCT but it doesn’t feel right to add work to an already overstretched health system in Nepal.  Conducting a full RCT would require the local doctors to assess over 200 women at baseline then again 12 weeks later.  I don’t think I can ask them to take the time to help me, even if I was to pay them.

Is it worth designing a study that lacks robustness but is both realistic and feasible given the context of the setting?  Of course I would love to have the biggest and bestest study design but I am just one person and it’s just not going to happen.  I am always a health professional first and researcher second and I still think there are interesting and worthwhile findings in less than ideal research designs.  Sometimes I think studies that are scrappy appear to be more ‘real life’ and take into account that we can’t control every variable especially when working with humans in low resource settings.

I am prepared for my study designs to be criticised and dismissed but I’m not following my research questions in order to win research methodology awards but to really see if we can find any possible solutions in very difficult circumstances.  Go ahead and disagree if you so wish 😉


Published by Delena-Mae PhD


One thought on “When feasibility trumps robustness

  1. I haven’t pondered your argument for more than a few minutes, but I agree with what you’ve decided. I like your summation that you are a medical professional first and a researcher second. I so admire your passion and mission for helping these women. I believe that this will all work out, even if you must use smaller studies. I can’t help but think about Ben’s arduous PhD process. Very different field from yours, of course, but in the realm of PhD students, I have seen that much is painfully similar. Even within a year from the “finish line,” he was not sure that what he had would be enough. He could only work with the results he got, and real life scenarios don’t always give the desired results. Just keep doing your thing, D! So proud of you, girlfriend!!


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