Update. I re-read one of my older posts when I went through Dennis’ recent discussion on the lessons learned during his PhD, which also included his advice on how to keep your motivation up. Two years ago, I actually wondered where motivation for science comes from in general. Are we driven largely by egoistic motives like money or fame, or are there different factors at play? I am re-blogging one of our old posts from 2012 with minor 2014 updates. These were the answers that I came up with back then. I think they are still relevant. Continue reading
Difficult times. The last two weeks were hard for me scientifically. In addition to having two papers rejected within a week, I learned that a major grant proposal that was rejected. Particularly the latter I didn’t take well, since I was quite convinced that we would make the next round. Also, this was for a project where funding was more than necessary. We all know scientific disappointments in their various forms, and I thought that I would dedicate a post to this topic. Please follow me while I stumble through the internet, looking for the science of disappointment. Continue reading
Why are we doing what we are doing? Academic research appears to be a rat race of high-strung egomaniacs fighting for grant money, impact factors and ultimately their scientific legacy. In this constant struggle you either make it or you don’t, you publish or perish, depending on how good you can elbow your way through. And finally, make no mistake, it’s all about the money. Unfortunately, many young researchers are given this dire, coldhearted perspective by senior scientists and supervisors. Your PhD either results in a Nature or Science paper or you’re gone. Family? Not my problem. Holidays? Why are you even asking. This blog post is about the hidden secrets of human motivation, trying to point out some basic fallacies in these arguments. My brief answer to this is: “This is so 1995…”
Party like it’s 1995. Just imagine we are back in 1995 and we were asked the following question. “I would like you to tell me our opinion about the possible success of two different online encyclopedias. Type A is financed by the world’s largest software company, which has dedicated a generous budget to this project that pays both a highly qualified staff of writers and an experienced management team. Type B is a voluntary encyclopedia with no budget, established through people dedicating their spare time. In 15 years from now, which online encyclopedia will still exist?” In 1995, there was probably not a single person who would have put his or her money on Encyclopedia B based on this description. However, Encyclopedia B has evolved into one of the world’s largest online knowledge repositories, while Encyclopedia A closed its doors for good in 2009.
Wikipedia vs. Encarta. If I tell you that Encyclopedia B is Wikipedia and Encyclopedia A is Microsoft’s Encarta, this story makes sense to you. Daniel Pink provides this example in his book “Drive”, which tries to explain the secrets of human motivation. In brief, in contrast to the prevalent belief that strong incentives such as money or titles are the main drivers of human motivation, this “carrot and stick” method only gets you so far and will produce people being productive for the reward, and not for the issue itself. Pink identifies three elements that are the main drivers of motivation, namely Autonomy, Mastery and Purpose. In brief, Wikipedia became what is today by enabling people to work autonomously, to engage their expertise and to feel a sense of purpose through a shared experience and feedback, something that millions of dollars by Microsoft could not buy.
Motivational theory. Pink’s arguments are nothing new. They are based on scientific investigations by Deci and Ryan in the 1970s, who conducted sophisticated psychological experiments to analyse human motivation and who identified these three elements as part of their self-determination theory of motivation.
Application to research. Uri Alon from the Weizman Institute has re-interpreted these results for the field of science in a freely available comment in Molecular Cell, identifying Competence, Autonomy and Social connectedness as the three elements that apply to science. Competence basically relates to working in an environment that is neither too boring nor too challenging. In research, we are mainly faced with leaving people with a task that is too challenging for their current knowledge level. For example, suggesting that a Young Researcher design a sophisticated genome-wide association study on pediatric pharmacology without any prior knowledge of biostatistics is too challenging, eventually decreasing motivation. Altering the project to a candidate gene screening will eventually increase the researcher’s motivation, despite the possible lack of scientific ingenuity. However, in the end, the second option will be more productive for the team as the young investigator is capable of working at her or his level of competence. Autonomy refers to a related issue. You can only be motivated in science when you perceive a sense of independence and an intermediate level of structure. Not too structured and not too independent. The third strand of motivation in science is Social Connectedness. It’s the proverbial water cooler discussion, the environment that gives you a sense of belonging, the interesting paper that was pointed out by that guy next in the lab next door, the senior postdoc who has nothing to do with your project, but who is happy to have a look at why your PCR isn’t working. Networks have been the main driver of scientific innovations over the past centuries, which is “Where good ideas come from”, as authors Steven Johnson puts it. Naturally, the science network arising from research consortia such as EPICURE or EuroEPINOMICS is much more than just a collection of scientists. These networks are organic entities and the ideal breeding ground for scientific innovation in the field.
When scientific projects are really well suited for you. Uri Alon goes on to re-interpret these three elements in the context of scientific projects, suggesting a so-called TOP model (Figure). Projects are particularly well suited for you if they manage to completely engage you, drawing on your talents, your passions and your goals. Epilepsy genetics of the future will be multifaceted with many different niches and subfields that might allow a broad range of scientists with different backgrounds and motivations to contribute. Touching upon diverse fields such as genetics, neuroscience, social sciences, public health, etc., researchers with “cross-over skill sets” will be crucial. The age of the lonely genius researcher hiding out in his secret lab to eventually emerge with a Nobel-prize winning flash of inspiration is over, if it has ever existed. The science of the future will be network science and “chance favors the connected mind”.