Different types of research are different
I find posts on “how to do good research” or “how to test your fit for research” extremely useful. Still, whenever I see such a post, I hope that readers don’t over-generalise. Different types of research are very different. It’s worth experimenting with different types of research, to see which one you enjoy and are good at.
I can speak with some authority on this, due to my ragtag background. I have worked with various tools (wet lab research, clinical trials, computational work, macrostrategy-style research), in various roles (junior researcher to supervisor), in various organisations (industry, academia), in various team sizes (solo academic to >5 FTE on the same project). All these things make a difference. I have also worked in various fields (neuroscience, psychiatry, machine learning, infectious disease modelling, immunology, global health), although the field itself probably has the least influence on how the research experience feels like.
How good you are at a type of research obviously depends. To be good at clinical trials, you need high conscientiousness (clinical trials research is pretty logistics-heavy). For wet-lab research, you generally need to be quite hard-working (somebody has to put in the hours to do all the experiments) and actually somewhat dexterous. For computational work, you need to be good with numbers and code. For (some) macrostrategy-style research you need to be pretty creative. And so on. But still, I think there are many generic research skills that transfer a lot between different types of research.
How much you enjoy a type of research can differ even more. I have worked in research positions that I’ve hated and in positions that I have loved. Research positions have been both the best and the worst jobs I’ve had in my life. For example, I’m not a highly curious person (compared to other researchers). In wet-lab research, when you have an idea, you often have to do weeks or months of tedious work to test it. That killed my curiosity and creativity. Now, I’m working in machine learning. If I have an idea, I can sometimes code it up in a few hours, run the experiments overnight, and have results on the next day. Needless to say, I have many more ideas now. The most striking difference, however, is that between solo research and team research. I used to have procrastination problems when doing solo research and then felt bad about myself for not working as much as I wanted. But, at least for me, the procrastination simply goes away when I know that there are other people who are counting on me.
Hear hear. And not to even mention how killing it is for curiousity and happiness to have this the near-obligation to publish in the highest ranking journals in academia.