I recently read an article in the May 2016 volume of C&RL News about the validity of survey data. The author, Emma Oxford, draws on her own experience to say that “some data is only better than no data if it is good data. Bad data is never better than no data”.

I have created exactly one survey for research purposes in my very limited time working in the field of library and information science. Suffice it to say, it did not go well. I spent weeks during an internship for my MLIS researching, designing, and gaining IRB approval for my survey project. I love research in all its forms and was so excited to finally be conducting my own official research project. I am fairly certain that I was dancing around in my chair when I sent the survey out via Qualtrics.

A week went by with two responses. I sent out a reminder email, which prompted an additional half response (somehow, the respondent managed to answer only three of the fifteen questions). By the time five weeks had passed, my internship was over and I had given up. It was, without a doubt, one of the most disappointing things to happen to me, which perhaps says more about my privileged life than anything.

So now I come across Oxford’s piece and I wonder if perhaps I dodged a bullet. My target participants were scientific researchers, who are notoriously busy and hard to engage outside of their field. If they had taken the time to look at my survey, there is a very real possibility that they would have responded with satisificing, which includes “nondifferentiation…skipping items, rushing, or quitting early” (Oxford, 2016). I actually did experience the last item in my survey. So perhaps it was better that I received no data at all, as opposed to faulty data that would have led me to false conclusions. 

Still, it would have been nice to get a response rate greater than 12%.

Oxford, E. (2016). Survey data: When what you see is not what you wanted to get. C&RL News, 77(5), 249-250.