As a student, it was easy for me to fall in love with the idea of life as an academic: being able to think about and discuss interesting ideas with smart colleagues, having almost unlimited freedom over when and how and where you do your work, and working on important problems that could lead to substantial changes in how we assess and treat mental disorders. But just as in any other line of work, it’s in the day-to-day work where these things happen. So in order to find long-term fulfilment and success in academia, it is worthwhile to develop skills in the Core activities that appear over and over again. But how do you find the time and energy to do so with an already full schedule? By exploring the ways in which these activities are enjoyable.

But liking the idea of being a novelist is not enough; you have to like the actual work of novel-writing if you’re going to be good at it […] - Paul Graham, How to Do What You Love

Core processes

Reading

I appreciate reading when it nurtures my curiosity, when it develops my taste for good research and writing, and when it provides answers to questions I have.

Reading to nurture curiosity

I try to read things that challenge my current view of the world, and research from other fields than my own. Sometimes I encounter new insights that are directly applicable to my own work, and almost always there is new information that I can use to challenge and develop my own ideas. You can use cross-pollination to enrich your work with ideas from other fields.

Reading to develop taste

Reading gives me a sense of the field, where things are currently and where they may be heading. What’s the current dominant paradigms and theories? Who are the thought leaders, the individuals/groups currently doing the best work? Why is someone’s writing appealing, why is this particular article convincing? Actively developing your taste in your field of work will help you select projects.

Reading to answer questions

A sustainable way to keep up with the research literature is to read with a goal in mind. I might read something to write a detailed critique in an introduction or use as inspiration for a study of my own. Other times I read research from an adjacent field to remix into your my research, perhaps a new statistical method or theoretical approach.

Writing

Writing is the medium of research. All the common academic activities are done through writing: seminars, manuscripts, grant proposals, lectures, collaboration efforts…

I used to not enjoy it and see writing purely as a means to an end, but more recently I’ve come to appreciate writing itself. One annoying thing after reading articles with good writing is that your writing will never match those standards, but persistent effort will lead you to do work in line with your taste.

Writing to sharpen my thinking

When you write about a subject you see your own gaps in knowledge. What seemed brilliant and fully thought out in your head will fall apart once you put it in writing, and this is good!

Writing to generate ideas

Writing is also what makes it possible to gain new insights and connect ideas to each other.

Writing to convince and collaborate

Writing is the way through which most collaboration happens. Being able to communicate well in text means more influence and success, most directly through a higher acceptance rate of your articles and grant proposals, but also in reducing the risk of being misunderstood by collaborators and slowing down a project’s progress. If you write simply you cannot hide lack of ideas behind complicated words.

Analyses

The statistical analysis is the sharp tip of the empirical research process. It’s what everything boils down to, where you get to see if the brilliant idea held up or not. Lack of time or expertise to do statistical analyses is also the most common bottleneck in my research environment, so it’s a particularly valuable process to invest time in.

The students who ultimately succeed in learning R are not the ones who force themselves to memorize functions or do a bunch of coding drills. They’re the ones who accept they will feel stupid and that most of the rules will at first seem totally arbitrary, and who understand that they will gain great power if they just keep going. - Adam Mastroianni in You’ll Forget Most of What You Learn. What Should You Do About That

Analyses to get deep knowledge of the research process

By performing statistical analyses on a set of data, you dive deep into the intricacies, possibilities and limitations of the research process. It’s at the stage of analyses you encounter the design flaws that change which research questions can be answered, and identify the impact of compromises done during the active project phase. This knowledge is extremely valuable when planning future projects and is hard to come by without hands-on work with data.

I often find that it is the individual(s) performing the statistical analyses who end up with the most intimate knowledge of the data and possibilities of future scientific work in the project.

Analyses to improve the research-to-admin ratio

Since doing statistical analyses in a project is a high-demand activity, you can often reduce your burden of tedious admin tasks if you develop this skill. This will help you in the long term since you spend more time thinking about the actual research, and less time with the day-to-day practicalities.

Analyses to become a valuable collaborator

Your skills are always needed, which means you can use them to collaborate on interesting projects and develop valuable relationships with collaborators.

Tactics

By now you might agree that there are interesting and valuable aspects of reading, writing, and doing analyses. Unfortunately, this inspiration is rarely enough to change deeply ingrained habits. Subtle or slow progress in research feels frustrating and unrewarding. There may be few or no clear indications of steady progress and tasks to be ticked off. This is less stimulating than answering email, sitting in on an interesting seminar, arranging the project tasks just so in your software of choice, et cetera.

The activities are also inherently difficult. But confusion or resistance when writing are not inherently bad, they are part of the process.

Always create things

It’s easy for me to get stuck in consumption. If I just read one more article I might have enough material to write the discussion section, if I watch one more tutorial I might be able to do the analyses needed for our next project.

By continuously working on your own projects, you create things and take accountability rather than passively consuming content. At the very least, the article I read should have generated a one-sentence summary written in my own words. Ideally I also have notes about my reflections and impressions of the article, why I find it convincing or not. One or two examples of how I might cite the article are included in the note if the article is directly applicable to my own research.

Having a habit of always creating things helps me reinforce what I just learned, and it also makes it easier to get started on the big projects. If example citations for twenty different articles on a certain topic are already written, the first step of writing an introduction means arranging those citations in a way that makes sense rather than staring at a blank page.

Schedule for depth and stillness

High-quality work in any of the core activities never happen in the midst of a frenzied workday, between email inboxes and meetings, at least not for me. I need to carve out chunks of time where I have a reasonable chance of making progress on difficult and complicated work.

You need space and calm to play with ideas, otherwise project-related tasks that seem urgent swamp my schedule. For me it’s in the mornings 9-11. It doesn’t sound like enough, but two good hours Monday-Friday will add up to a lot of writing and reading. This time is when I do my best cognitive work, and I protect it fiercely to focus on deep work.

It’s also helpful because this means I restrict the time I work on a manuscript, for example. Rather than working 10 hours non-stop and then losing interest, I often stop despite having more ideas and things to say. I am then eager to get back into the groove tomorrow morning using the Pomodoro technique.

Analyses I can do anytime because I find those tasks more easy to get into no matter the time of day.

Explore/Exploit

Explore early and try out many different parts and roles. Once you find what you enjoy, go deep. It’s better to develop deep expertise in few areas than knowing a little bit of everything, at least in our context.

Nurturing a vision

Things in academia take time, so embrace slow productivity rather than hectic day-to-day activity.

• What sort of researcher would I like to become?
  • Idea machine & study design
  • Project management
  • High-quality writing
  • Feedback and revision
  • Statistical wizard
  • Collaboration master
• What areas of research am I interested in?
  • How am I going to achieve competence in those areas?
  • Why are those areas interesting?
• How am I going to continue growing and expanding my horizons?
• How will I balance the long-term goals with the short-term realities of the situation I find myself in?

Collaborate

Positivity, contribution, and aligned ambitions are traits of great scientific collaborators. Having colleagues that you enjoy working with will go a long way in creating an appreciation for the academic work.