Hello again fellow graduate students! My stint on the SPSP GSC may have come to an end, but (unfortunately) my dissertation struggles are still alive and well. In previous Dissertation Diaries installments, I wrote about choosing a topic and provided some tricks that I have been using to get organized. This month, I want to tackle something a little different: knowing when to call it quits.

No, I am not quitting graduate school, and I haven’t given up on my dissertation (not yet, anyway). Instead, I mean recognizing that you have the makings of a great dissertation in your possession already, and setting aside plans to collect more data. When I first began the dissertation process, I assumed that I needed to start from scratch: to do something totally novel, totally unique, and totally distinct from all of my other research. As such, it is perhaps not surprising that these beliefs left me completely panic-stricken. I thought to myself: “Even if I find the time to run all of these studies, what if some of them don’t work out as planned? I won’t possibly have time to fix any problems that arise!” Throughout this process, it never occurred to me that there might be an easier way.

As a personality psychologist, I am used to collecting large amounts of data. Whenever I run a study, I collect my variables of interest, plus a few extras just in case. Once I had my idea for my dissertation, and organized my plan for executing it, I found that in reality, I had already run some of my planned studies! They may not have been for the same purpose, and were not perfect, but the data could be reworked to adequately answer my questions of interest. After realizing this, it has become clear that I only need to run one new study (provided that this study works out, of course).  No doubt many of you out there have some buried treasure in the form of old datasets as well – you just have to recognize it.

Reimagining your current datasets so that they might be applied to your dissertation question of interest may not be flashy, and it may not be exciting, but it will save you a lot of time and effort. You likely are already very familiar with them, and they are (hopefully) well organized, allowing you to start the fun stuff (testing your hypotheses) right away. Even if they are not yours, and instead have come from a public record of some kind, you still will be giving yourself a head start by eliminating the recruitment and data collection phases.

If you think you would like to try this approach, always remember to keep an open mind. These datasets will not be ideal; they may not include all of the scales you hoped for, or may not contain your exact dependent variable of interest. Still, they can often contribute a certain breadth to your research, and if not replicate, at the very least supplement and extend. Trust me: anything that will allow you to conserve energy during this highly stressful and insanely busy time is a very, very good thing.