I love science. I really do. But is it the most negative thing I involve myself in voluntarily?
“Do you ever think people will be able to speak to their pets?”
“Well, what doesn’t kill you makes you stronger!”
“Maybe as an exception, but there is no way that’s generally true.”
“Don’t worry, everything happens for a reason.”
“Sure, without accepting the assumption of causality, it’s all just chaos. Still, that doesn’t make it any more meaningful.”
“It’s ok, little Adam, Book* has gone on to a better place”
(*When I got my first fish, I didn’t know what to name it. My parents suggested I name it after something or someone I liked. Hence, Book.)
One can look at science as an occasional “maybe, but…” in a world of “no”. Unfettered, it’s not hard to see how “guilty until proven innocent” can turn into depressing cynicism (sorry, Book, there’s just no proof of a “fish heaven”). Falsifiability – being able to prove a theory is false – is crucial to scientific thinking. Another way to think of this: every test a theory passes makes it a stronger “maybe”, but as soon as a theory fails, it’s a “no”. After a theory has failed to fail a few reasonable tests, we tend to treat it as true. But there’s always a chance it could fail in a way you didn’t think of.
Humans thrive on acceptance and positivity. No one wants to be told no, they are wrong, or that they don’t understand. But as a scientist, it’s your job to tell your friends and colleagues “I don’t believe you, prove it” and likewise be told “no, I think you are wrong”. The constant rejection and skepticism can be emotionally draining.
Maybe this is why graduate students in STEM have such high diagnosed rates of depression. A recent article in Nature suggests the rate of diagnosis of anxiety and depression is six-times higher in graduate students than the general population. I’m otherwise not going to speculate on any connections between the culture of academia and clinical depression or anxiety but instead focus on how research can be emotionally taxing, and can negatively affect those who engage in it. (By the way, if any of this hits home, I encourage you to ask for help. Many people wait for a serious, catastrophic event before seeking help. It might be the hardest, but most important, and bravest thing you can do.)
On my worst days, it’s hard to look past the rejections and failures, and it may seem like science is an inherently depressing activity. As human beings with a senses of self, I would guess it’s impossible for anyone to avoid this feeling, at least occasionally. Yet this is not the fault of science itself, rather a symptom of being human, focusing on the wrong things, and deviating from the way one ought to look at science. This is not to put the blame entirely on the individual – I believe there is institutionalized pressure to act this way (we will discuss this later) – but I think there are ways to stay positive amidst the negativity.
To avoid this trap, I remind myself of one guiding principle. When my experiments aren’t working and it feels like everything is going off the rails, this principle helps me dissociate from the negativity return to my work with a healthy attitude:
Don’t be results-oriented
This may seem counter-intuitive. The point of science is to obtain results, but the specific outcome that these results give shouldn’t affect your value as a person who is a scientist. (To be clear, I think a scientist who produces a fantastic and exciting result should be celebrated, and some scientists will do better work than others, but one should find satisfaction in doing their job well, even if they don’t receive a Nobel Prize)
I think of it in a few ways…
“No” is just as important as “Yes”
Incorrect =/= Worthless. The Mythbusters have made incredibly satisfying careers out of saying “no”, while still being positive and loved by millions. They do this by giving their myths (theories) only exactly as much respect as they deserve, meaning they do not become emotionally attached to any one idea. The goal is not to find evidence that pushes a preferred narrative. The goal is to find out “under what circumstances could this theory be true?”
Most theories are wrong. That’s just how it is. You’ll probably find your initial theories fail most of the time. Likewise, most myths turn out to be exactly that – myth. But that doesn’t mean you won’t have fun failing, or that you get nothing useful out of the process. Most myths are based on something true, after all. And eventually, if you’re lucky, you might just prove something incredible is “plausible”.
Speaking of process…
Science is a process, not just a collection of results
When someone clears the Science category on Jeopardy, you don’t hear Alex Trebek say “wow, what an incredible scientist!”
“Doing science” is using a set of logical tools to learn something about our world. If I wanted a piece of art to hang on the wall, I wouldn’t buy a puzzle. As a scientist, you are not an art collector, you are a puzzle builder.
In this analogy I am treating your theory as the puzzle and each experiment as a piece. When a piece doesn’t fit into the puzzle, it doesn’t mean you are bad at puzzles or the piece is garbage – it may just belong to another puzzle. Each piece you discover is important, and should be treated as such.
Of course it’s valid to have a preconceived idea of what you want to learn and to push in that direction. Without working in a specific direction, you’re doing a random walk and could be wasting a lot of time. But if you discard “negative results” or results that don’t relate to your original research question, you are throwing out puzzle pieces that may be useful to someone else, but more importantly, turning the time you spent on that piece into wasted time.
Unfortunately it seems like this narrative is incompatible with the publish-or-perish reality of academia. As it stands, it is uncommon to publish “null results”, or, papers that do not confirm a hypothesis. Additionally, many researcher’s careers are determined by the number of publications that they produce each year. This means that if your study did not lead to a positive result, the failure is exactly equal to a professional failure. You’ve effectively wasted the time you spent on that work and have nothing to show for it. This means tonnes of good data may never see the light of day. Might as well have not come in to the lab.
Not only can the “only positive results are good results” and “more is better” mentality of academia be detrimental to the mental health of researchers, but one can argue it may be diluting the quality of research.
I’m lucky. I’ve worked with a supervisor who has made it clear from day one, that my mental health and work-life balance is of the utmost importance. He has also made it clear that very good, important science can happen when you chase a strange result that doesn’t fit into your puzzle. But we also do not work in an ultra-competitive field that is bloated with thousands and thousands of researchers.
I am lucky, but there are many graduate students and researchers who are not in this comfortable position. I think that if the push for funding and publishing forces one to stray from being creative, exploratory, and open, then science is in serious danger of becoming a soul crushing monster.
The broad-strokes solution, I guess, is for everyone to agree to chill and keep a sane work-life balance that prioritizes the right aspects of science. And the solution to overpopulation is to just spread everyone out. Obviously, we need to identify small, tangible problems and propose realistic, (hopefully simple) solutions.
This post is the first part of what I think will be a two-parts. So to conclude part one, I will list what I perceive to be problems with the way research is done today. But before I proceed with the list, remember the original goal here is to identify problems with the culture of research that make it an emotionally difficult activity. Some of these “problems” may be necessary aspects of how academia works. I don’t expect academia to be some group-hug love fest. But as you read the list, keep an open mind and consider how solving these problems may positively affect net scientific output as well.
- Careers are determined by publishing record – often skewed to volume of published work
- Null results are treated as less important and often unpublished, leading to wasted data and wasted time, both for the original researchers but also researchers who unknowingly attempt a similar experiment
- Highly competitive fields disincentivize exploratory work in exchange for laser-focused research narratives
- Good data can be expensive and hard to obtain but may not lead to a publishable result, yet there can be very little professional incentive to share it otherwise
In the next installment we will begin exploring some of these problems. In the mean-time, if you have comments opinions, I would love to chat in the comments or @arts_andscience or @AdamFortais on Twitter 🙂