phd research memes

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• CAREER COLUMN
• 12 May 2021

The 100 memes that immortalize my PhD defence

• Sophie Dufour-Beauséjour 0

Sophie Dufour-Beauséjour works as a policy analyst for the Government of Canada’s Climate Change Preparedness in the North Program.

You can also search for this author in PubMed   Google Scholar

I finished my PhD on sea-ice dynamics in Nunavik, an Inuit territory in the Canadian Arctic, during the pandemic. My defence took place on 30 October 2020, over Zoom.

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doi: https://doi.org/10.1038/d41586-021-01273-8

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• 40+ Hilarious research memes that will make you smile

Şeyma Beyazçiçek

Researches are part of our lives, especially if you are a forever learner. While doing research, we have been through similar difficulties or experienced the same feelings. In order to show these common points, internet memes come to our aid!

In this blog, you will see excellent any kind of material, such as UX research memes, clinical research memes, psychology research memes, and research paper memes. If you want to take a break and enjoy your time, you should definitely take a look at our 40 hilarious Research memes that will make you laugh :  

• 1. Tip of the iceberg

#1 Research meme - Source: Facebook - High Impact PhD

In the background of each research, there are nights, days, weeks, and even months spent time and effort for the research. So, the paper itself is just a little concrete form of all the effort and work. 

2. There is no destination!

#2 Research meme - Source: Make a meme

Researches are like living. There is no destination, but it is a journey! As you read and see, you will realize the limitless world of knowledge. 

3. But it sounds cool, isn’t it?

#3 Research meme - Source: Quick meme

When we need to do research, the first thing to do is to google it, right? We seem to have no better option as the first step in our era. 

4. Don’t want to check🫣

#4 Research meme - Source: Ah See it

Before submitting the paper, reading it might feel like it is not good enough. If you do not want to feel like that, all you need to do is submit it without the last check. 🤗

• 5. Memes matter🤨

#5 Research meme - Source: Reddit

When it comes to doing Research about anything not related to the Research topic, everything seems to be worth reading and learning. Especially if it is a meme!

6. They are always one step ahead!

#6 Research meme - Source: Facebook- High Impact PhD Memes

It is undeniable that applied research with sensational findings always gathers more attention and funding. Basic research is always doomed to lose spotlights. 😏

7. Vs the reality

#7 Research meme - Source: Pinterest

When you tell people that you are doing psych research, everybody imagines something different. However, the reality is completely different from their picture. But calm down; at least we know that you are drowning among the papers.

8. Don’t want to be THAT person

#8 Research meme - Source: Illinois

If you are the person who made somebody do psych Research or made them into psychology, you should definitely question yourself and your actions. 👀 

9. None can say the opposite!

#9 Research meme - Source: Giphy

If one has never done any research, s/he can assume that you begin a research, develop, and finish it. Nevertheless, of course, the process is way much more complicated than that! 

• 10. Welcome to the Research-lover club🫶

#10 Research meme - Source: Imgflip

If you are into research, any topic will be a duty for you. A new phone? A holiday plan? A trip abroad? Considered it done because the necessary research is done!

11. Me trying not to be a square

#11 Research meme - Source: Facebook- High Impact PhD Memes 

When you attempt to try a new research method for the first time, you might feel the anxiety of not knowing what you are doing. But as you do, it gets better, we promise. 

12. That’s the only smart thing to do 😎

#12 Research meme - Source: Meme-arsenal

Before making an important decision, no matter what, you should definitely do your research because it is how cool people act! 

13. UX Research is everything!

#13 Research meme - Source: Playbook UX

If you are a UX designer, you can share this meme with confidence. The picture given above summarizes the importance of UX research very well. 

14. Watch me, then 😈

#14 Research meme - Source: Pinterest

Yes, probably it is not a paper that can be written the night before; we know that. But if there is no other option left, it is possible turning into a writing machine. ⌨️

• 15. It is a serious job🧐

#15 Research meme - Source: Memes

While doing research, the most significant part is to collect data related to your topic in your most serious mood. It is essential but hard to keep this mood for a long time. 

16. Am I just perfect or bad at self-feedback?

#16 Research meme - Source: Tumblr

It seems like it is easier to find somebody else’s errors or criticize it. But when it comes to ours, our mistakes come suddenly invisible. Science needs to explain this!

17. I want to break free🎶

#17 Research meme - Source: McGill

While working on our research papers, we know that you do not completely feel free and work as you wish. Practicum supervisors are like a limit for research. 

18. Above the clouds☁️

#18 Research meme - Source: Imgflip

While doing the research, there is always a crowd of tabs that we cannot dare close. But, when we complete the research, it is the most satisfying feeling to close all the tabs finally.

19. So am I…

#19 Research meme - Source: Make a meme

This process is challenging both physically and psychologically, for sure. So, finishing a research paper might feel like someone who survived a battle scene. 

• 20. Look, I am famous!

#20 Research meme - Source: Twitter-High Impact PhD Memes

It is a really really satisfactory feeling to see your work online! Also, reading your work from someone else’s perspective is quite fun. 

21. It is hard to keep your energy stable 📉

#21 Research meme - Source: Meme-arsenal

At the beginning of the semester, we have big energy and motivation to start our paper. However, at the end of the semester, it is hard to feel the same enthusiasm and energy.  

22. Why would they?😭

#22 Research meme

Yes, we know that the question is optional, but still, it hurts us… When the respondents skip the question, we feel the rejection of the bone. 💔

23. So, what a medical researcher does?

#23 Research meme - Source: Mosio

When you tell people that you are a medical researcher, everybody might assume or imagine your work differently. This meme given above is a good illustration of the situation. 

24. The hardest part is done 👍

#24 Research meme - Source: Quick meme

Sometimes, it is hard to understand the topic or instructions of the research. When you understand it, it gets easier. However, when you complete your research and realize that you did wrong from the beginning, it is like a nightmare!

• 25. No kid, just no.

#25 Research meme - Source: Memes happen

Yes, Wikipedia is also a source of information. But when the data is taken as copy and paste, it is an unacceptable mistake that a professional never ever does!

26. It is worthy ✨

#26 Research Meme

Looking at your final work and being able to be proud of the paper feels like a real victory! Is the paper good? Yes. Am I okay? Doesn’t matter. 🤝

27. Hard to tell🤔

#27 Research meme - Source: Make a meme

Both quantitive research and qualitative research have pros. But it is like a dilemma to make a decision between these two. 

28. But I googled it 😏

#28 Research meme - Source: Quick meme

Yes, it is not possible to do our research in libraries. Instead, we google our questions and topics. Still, it is research, isn’t it?😇

29. Do not confuse me, please🙏

#29 Research meme - Source: Twitter - Iopsyche Memes

Sometimes, our research does not give us what we want. However, we can turn these opposite ideas into the next work. Looking on the bright side is our job! 

• 30. Which one are you?

#30 Research meme - Source: 9GAG

If you want to be the muscled dog, take your job seriously. Otherwise, you will be the weak dog if you do not work like a professional! 

31. 🥁Drum rolls🥁

#31 Research meme - Source: Memes happen

Imagine that you have already prepared the 15 pages of your research, and your PI tells you to start over. The pain🤡

32. It is time to be serious

#32 Research meme - Source: Cheezburger

Yes, the research is important. There should not be any spelling errors. But memes never allow spelling eros. Check it once, twice, three times, four times, five times….

33. That critical decision

#33 Research meme - Source: Meme-arsenal

It is essential to read the important papers related to the topic. But when it takes too much time and delays the time of starting your own research, it might feel anxious.😶

34. Let’s calm down

#34 Research meme - Source: Joey deVilla

One cannot deny that Google is a source of information today. But still, simply scrolling through pages on Google does not give you a good research paper. 

• 35. Let your confidence speak!

#35 Research meme - Source: Giphy

When you are well-equipped for a topic that you have done your research before, and you witness that someone is talking totally wrong about it, you can let your self-confidence speak!

36. A product without UX Research?!

#36 Research meme - Source: Twitter - Doug Collins

The importance of UX research can be fully understood when a product is launched without UX research. 

37. Let’s make it spicy🪩

#37 Research meme - Source: LinkedIn

If your cries for help are ignored, all you need to do is to name the docs in a fun way, just like the example given above. 😊

38. The moment of confusion

#38 Research meme - Source: Memes

When you think about too much of your research, it starts to seem wrong and correct at the same time. So, not to feel burn-out, avoid thinking about too much. 

39. Social media and research?

#39 Research meme - Source: Ah See It 

Digital culture has changed many things. When we witness someone on social media mention their research, it does not sound reassuring, right? 

• 40. It is what it is

#40 Research meme - Source: Make a meme

I have not slept, and I have not eaten properly lately. I am also not socializing in these last days. But it does not matter because I finished my research. 👍 

In this post, we have collected funny research paper memes, UX research memes, funny clinical research memes, or research memes in gif forms to make you smile. Memes are an excellent form of common feelings, and if these memes were able to help you have a great time, we are even happier than you! 

Şeyma is a content writer at forms.app. She loves art and traveling. She is passionate about reading and writing. Şeyma has expertise in surveys, survey questions, giveaways, statistics, and online forms.

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If You've Ever Struggled With A PhD, You're Going To Find These 41 Memes Hilarious

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27 Hilarious Peer Review Memes for Academics and Researchers 🤓🔬

Welcome to our latest blog post! If you’re part of the academic or research community, you know that the peer review process, while essential, can be a rollercoaster of emotions. That’s why we’ve compiled a collection of 27 side-splitting peer review memes that perfectly capture the ups, downs, and quirky moments of academic life . From the endless cycle of revisions to the mysterious vanishing reviewer, these memes offer a light-hearted look at the challenges and idiosyncrasies we all face in the world of research. So, take a break from your scholarly endeavors, and let’s dive into some academic humor that’s sure to bring a smile to your face! 📚😂

Top 27 Hilarious Peer Review Memes:

“Finding a Minor Error” : A scientist triumphantly holding a magnifying glass over a stack of research papers, with the caption: “When you spot a minor error in a well-written paper .”

“Reviewer 2 Strikes Again” : A trio of superheroes labeled “Reviewer 1,” “Reviewer 3,” and a villain labeled “Reviewer 2,” with the caption: “The never-ending battle in peer review.”

“Endless Revisions” : A researcher sitting at a computer , surrounded by piles of crumpled paper and coffee cups , with a calendar showing months passing by. Caption: “Just one more revision they said.”

“The Waiting Game” : A skeleton sitting at a computer with an inbox still waiting for peer review feedback, captioned: “Still waiting for the reviewers’ comments.”

“The Optimistic Author” : An author submitting a paper with stars in their eyes , dreaming of acceptance. Next panel shows them receiving revision requests, with a caption: “Reality hits hard.”

“Citation Overload” : An overstuffed sandwich with each layer labeled as a different citation, captioned: “When reviewers ask for more citations.”

“Lost in Translation” : A researcher looking confused at a screen showing review comments that are vague and contradictory, captioned: “Trying to decipher reviewer feedback.”

“Data Juggling” : A scientist juggling multiple charts and graphs, with the caption: “When reviewers ask for additional data analysis.”

“The Perfect Match” : Two researchers finding each other on a dating app, only to realize they are reviewer and author of a contentious paper, captioned: “When your peer review is too close to home.”

“The Methodology Maze” : An image of a researcher looking perplexed at a complex maze, with each turn labeled with different research methods. Caption: “Navigating the methodology section as per reviewer’s suggestions.”

“Infinite Edits Loop” : A flowchart looping endlessly between “Submit Revision” and “Receive More Edits”. Caption: “The never-ending cycle of peer review.”

“Reviewer’s Crystal Ball” : A mystic crystal ball with the words “Future Studies” inside it. Caption: “When reviewers expect you to predict and address future research outcomes.”

“The Jargon Jungle” : A researcher hacking through a dense jungle, where each plant is labeled with complex scientific jargon. Caption: “Trying to simplify language as suggested by reviewers.”

“Expectation vs. Reality: Results Section” : Two panels; the first showing a neat, straightforward graph (Expectation), and the second showing a messy, complicated graph (Reality). Caption: “What reviewers expect vs. what you have.”

“The Ghost Reviewer” : A ghost hovering over a computer, ignoring the email reminders. Caption: “The mysterious case of the disappearing reviewer.”

“Conference Call Confusion” : A group of confused researchers on a video call, with speech bubbles of contradictory comments. Caption: “When every reviewer has a different opinion.”

“The Lengthy Literature Review” : A researcher buried under a mountain of books and papers. Caption: “When reviewers ask for a ‘brief’ literature review update.”

“Graphs Galore” : A researcher surrounded by an overwhelming number of graphs and charts, looking bewildered. Caption: “When one reviewer asks for more data visualization.”

“The Keyword Conundrum” : A researcher looking at a thesaurus with a confused expression, surrounded by a cloud of keywords. Caption: “When reviewers suggest using ‘more specific’ keywords.”

“Revision Rollercoaster” : A rollercoaster ride with highs labeled “Acceptance” and lows labeled “Major Revisions.” Caption: “The emotional rollercoaster of manuscript revisions.”

“The Citation Detective” : A detective with a magnifying glass inspecting a citation, with the caption: “When reviewers question every single reference.”

“Reviewer Roulette” : A roulette wheel with sections labeled as different reviewer personalities (e.g., “The Nitpicker,” “The Over-Enthusiast,” “The Ghost”). Caption: “Spinning the wheel to see what kind of reviewer you’ll get this time .”

“Conference Deadline Panic” : A researcher frantically typing on a laptop with a calendar showing a looming conference date . Caption: “Trying to incorporate last-minute review comments before the conference deadline.”

“The Abstract Abyss” : A researcher staring into a swirling vortex labeled “Abstract.” Caption: “When you have to summarize years of work in 250 words.”

“Data Dive” : An image of a diver surrounded by a sea of data points and graphs. Caption: “Exploring the depths of data analysis after reviewer feedback.”

“The Overzealous Editor” : A cartoon of an editor with a giant red pen , crossing out huge sections of a manuscript. Caption: “When the editor gets a little too enthusiastic with revisions.”

“Peer Review Poker” : Researchers sitting around a poker table, holding cards with different sections of a manuscript. Caption: “Bluffing your way through the peer review process.”

And there you have it – 27 hilariously relatable peer review memes that every academic and researcher will understand and appreciate. Whether you’ve faced the enigmatic Reviewer 2, endured the endless revisions, or navigated the complex maze of methodology, these memes are a humorous reminder that you’re not alone in this journey. Share these with your colleagues to spread some laughter in your lab or library . Remember, a little humor goes a long way in making the rigorous journey of research a bit more enjoyable. Stay tuned for more academic insights and light-hearted content! 🌟📉

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Top PhD memes of 2021 (Updated)

The era is of the internet. People are passing their time on the internet, blog, Instagram, Facebook, and Twitter. Memes are evolved recently. It is a pictorial representation of a joke. And people love memes.

Our social media is flooded with jokes, memes and gifs. Here in the present article, we have enlisted some of the meme material related to PhD. PhD is a very serious business, still, some of the memes are incredible and describe some of the common problems everyone faces during their PhD time.

See this What a PhD student feel on Friday when everyone is planning to party!

This meme is best understood by those who are still struggling to write their research paper.

A cold-blooded insult to a PhD student.

This story is for those who have actually mastered a skill to describe their research like no one other did do it.

This one is actually exciting.

Another next level of insult to us (PhDs).

This happens to everyone. By reading a few papers we think we know everything.

Dr. Tushar Chauhan is a Scientist, Blogger and Scientific-writer. He has completed PhD in Genetics. Dr. Chauhan is a PhD coach and tutor.

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Scientific Publishing Is a Joke

An XKCD comic—and its many remixes—perfectly captures the absurdity of academic research.

A real scientific advance, like a successful date, needs both preparation and serendipity. As a tired, single medical student, I used to feel lucky when I managed two good dates in a row. But career scientists must continually create this kind of magic. Universities judge their research faculty not so much by the quality of their discoveries as by the number of papers they’ve placed in scholarly journals, and how prestigious those journals happen to be. Scientists joke (and complain) that this relentless pressure to pad their résumés often leads to flawed or unoriginal publications. So when Randall Munroe, the creator of the long-running webcomic XKCD , laid out this problem in a perfect cartoon last week, it captured the attention of scientists—and inspired many to create versions specific to their own disciplines. Together, these became a global, interdisciplinary conversation about the nature of modern research practices.

The cartoon is, like most XKCD comics, a simple back-and-white line drawing with a nerdy punch line. It depicts a taxonomy of the 12 “Types of Scientific Paper,” presented in a grid. “The immune system is at it again,” one paper’s title reads. “My colleague is wrong and I can finally prove it,” declares another. The gag reveals how research literature, when stripped of its jargon, is just as susceptible to repetition, triviality, pandering, and pettiness as other forms of communication. The cartoon’s childlike simplicity, though, seemed to offer cover for scientists to critique and celebrate their work at the same time.

The concept was intuitive—and infinitely remixable. Within a couple of days, the sociologist Kieran Healy had created a version of the grid for his field; its entries included “This seems very weird and bad but it’s perfectly rational when you’re poor,” and “I take a SOCIOLOGICAL approach, unlike SOME people.” Epidemiologists got on board too—“We don’t really have a clue what we’re doing: but here are some models!” Statisticians , perhaps unsurprisingly, also geeked out: “A new robust variance estimator that nobody needs.” (I don’t get it either.) You couldn’t keep the biologists away from the fun (“New microscope!! Yours is now obsolete”), and—in their usual fashion—the science journalists soon followed (“Readers love animals”). A doctoral student cobbled together a website to help users generate their own versions. We reached Peak Meme with the creation of a meta-meme outlining a taxonomy of academic-paper memes. At that point, the writer and internet activist Cory Doctorow lauded the collective project of producing these jokes as “an act of wry, insightful auto-ethnography—self-criticism wrapped in humor that tells a story.”

Put another way: The joke was on target. “The meme hits the right nerve,” says Vinay Prasad, an associate epidemiology professor and a prominent critic of medical research . “Many papers serve no purpose, advance no agenda, may not be correct, make no sense, and are poorly read. But they are required for promotion.” The scholarly literature in many fields is riddled with extraneous work; indeed, I’ve always been intrigued by the idea that this sorry outcome was more or less inevitable, given the incentives at play. Take a bunch of clever, ambitious people and tell them to get as many papers published as possible while still technically passing muster through peer review … and what do you think is going to happen? Of course the system gets gamed: The results from one experiment get sliced up into a dozen papers, statistics are massaged to produce more interesting results, and conclusions become exaggerated . The most prolific authors have found a way to publish more than one scientific paper a week. Those who can’t keep up might hire a paper mill to do (or fake) the work on their behalf.

In medicine, at least, the urgency of COVID-19 only made it easier to publish a lot of articles very quickly. The most prestigious journals— The New England Journal of Medicine , the Journal of the American Medical Association , and The Lancet —have traditionally reserved their limited space for large, expensive clinical trials. During the pandemic, though, they started rapidly accepting reports that described just a handful of patients. More than a few CVs were beefed up along the way. Scientists desperate to stay relevant began to shoehorn COVID-19 into otherwise unrelated research, says Saurabh Jha, an associate radiology professor and a deputy editor of the journal Academic Radiology .

A staggering 200,000 COVID-19 papers have already been published, of which just a tiny proportion will ever be read or put into practice. To be fair, it’s hard to know in advance which data will prove most useful during an unprecedented health crisis. But pandemic publishing has only served to exacerbate some well-established bad habits, Michael Johansen, a family-medicine physician and researcher who has criticized many studies as being of minimal value, told me. “COVID publications appear to be representative of the literature at large: a few really important papers and a whole bunch of stuff that isn’t or shouldn’t be read,” he said. Peer-reviewed results confirming that our vaccines really work, for example, could lead to millions of lives being saved. Data coming out of the United Kingdom’s nationwide RECOVERY trial have provided strong evidence for now-standard treatments such as dexamethasone. But that weird case report? Another modeling study trying to predict the unpredictable? They’re good for a news cycle, maybe, but not for real medical care. And some lousy studies have even undermined the treatment of COVID-19 patients ( hydroxychloroquine has entered the chat).

I should pause here to acknowledge that I’m a hypocrite. “Some thoughts on how everyone else is bad at research” is listed as one of the facetious article types in the original XKCD comic, yet here I am rehashing the same idea, with an internet-culture angle. Unfortunately, because The Atlantic isn’t included in scientific databases, publishing this piece will do nothing to advance my academic career. “Everyone recognizes it’s a hamster-in-a-wheel situation, and we are all hamsters,” says Anirban Maitra, a physician and scientific director at MD Anderson Cancer Center. (He created a version of the “12 Types” meme for my own beloved field: “A random pathology paper with the phrase ‘artificial intelligence’ in the title.”) Maitra has built a successful career by running in the publication wheel—his own bibliography now includes more than 300 publications —but he says he has no idea how to fix the system’s flaws. In fact, none of the scientists I talked with could think of a realistic solution. If science has become a punch line, then we haven’t yet figured out how to get rid of the setup.

While the XKCD comic can be read as critical of the scientific enterprise, part of its viral appeal is that it also conveys the joy that scientists feel in nerding out about their favorite topics. (“Hey, I found a trove of old records! They don’t turn out to be particularly useful, but still, cool!”) Publication metrics have become a sad stand-in for quality in academia, but maybe there’s a lesson in the fact that even a webcomic can arouse so much passion and collaboration across the scientific community. Surely there’s a better way to cultivate knowledge than today’s endless grid of black-and-white papers.

• #Gari-Token
• #Ever-SAFUV2
• #Funny-Meme
• #Options-Jedi
• #Real-Ou-Fake
• #Ansh-Verma
• #Digibyte-Memes
• #Dean-Norris-Smile
• #Abikukutv9
• #Middle-Finger
• #pokketninja
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• #Bubble-Chat-Meme
• #Akshay-Kumar
• #Mandela-Catalogue
• #Jammu-And-Kashmir
• #Peter-Knetter
• #memesdaily
• #Bad-Quality
• #Plz-Help-Me-Meme
• #Pouce-Bleu
• #sheeeeeesh
• #Daniel-Og-Simen
• #megastarmie
• #Memes2022-Funny
• #Meme-Goreng
• #Viral-Memes
• #Tyra-Banks
• #Pet-The-Meme
• #textbubble
• #Thats-Meme
• #realisation
• #realization
• #remorseful
• #sympathies
• #Linke-Soep
• #Berk-Music
• #Tran-Nhat-Ha
• #Head-Pat-Nhat-Ha
• #Alina-Sanchez
• #What-Is-Love
• #animatedtext
• #Chumi-Shumi-Meme
• #007-David007-Y-T
• #Fit-Lovers
• #What-Da-Cat-Doin
• #Serious-Face
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Impact memes: PhDs HuMor(e)

• Published: 24 July 2020
• Volume 79 , pages 35973–35994, ( 2020 )

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• Concetta Papapicco   ORCID: orcid.org/0000-0003-3240-8740 1 &
• Giuseppe Mininni   ORCID: orcid.org/0000-0001-7896-6620 1  

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The era of User Generated Content (USG) on Social Networks has invested different areas of human experience, including one of the highest levels of education, i.e., the PhD grade. As regards the opportunity to “imitate” a virtual content, the phenomenon of Memes (Shifman, J Vis Cult 13(3):340–358, 56 ) is spreading. The present research aims at the understanding how the online functions and practices of humor signification are featured considering linguistic and visual aspects. In particular it has a twofold goals: a) analyzing which differences emerged in terms of functions and emotions between humor in PhD Memes on Facebook and Instagram by means of ‘diatextual’ analysis; b) performing a fine-grained qualitative analysis about rethorical aspects based on linguistic and visual elements of Phd Memes in order to contribute to the field of humor automatic detection. To satisfy these purposes, 70 memes about the PhD on Facebook and Instagram were collected and, then, analyzed in two levels: (1) the quanti-qualitative, aiming to detect the semi-automatic emotional involvement, expression of humor in “meme discourses”; (2) the semiotic analysis of meme images. The results highlight first of all typical cases of incongruences in automatic and diatextual analysis in coding the effective emotions; furthermore they also show the peculiar function of humor, mediated by communication through memes, which is mainly a kind of ‘emotional sharing’ consisting in the complaint against a complex and precarious career path; in addition some differences in relation to the type of social media (Facebook or Instagram) are reported.

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Papapicco, C., Mininni, G. Impact memes: PhDs HuMor(e). Multimed Tools Appl 79 , 35973–35994 (2020). https://doi.org/10.1007/s11042-020-09166-0

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Received : 16 January 2020

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Published : 24 July 2020

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DOI : https://doi.org/10.1007/s11042-020-09166-0

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Reviewer 2 Memes: A Humorous Take on Academic Publishing’s Harsh Critic

Reviewer 2 Memes: Adding Laughter to Academic Publishing's Peer Review Process

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Review process.

In the world of academic publishing, receiving feedback from reviewers is an essential part of the process. While most reviewers provide constructive criticism that helps authors improve their work, there is always that one reviewer who seems to have a bone to pick. Enter “Reviewer 2,” the bane of many authors’ existence. But while Reviewer 2 may be the source of frustration for some, it has also become the subject of countless memes.

For those unfamiliar with the term, “Reviewer 2” refers to the anonymous peer reviewer who provides feedback on an author’s manuscript. Reviewer 2 has become something of a legend in academic circles for their harsh, nitpicky, and sometimes nonsensical comments.

Despite the fact that Reviewer 2 is just one of many reviewers, their feedback often carries more weight than the others, leading to a sense of dread when authors receive their comments.

But rather than wallow in despair, some authors have turned to humor to cope with Reviewer 2’s critiques. Memes featuring Reviewer 2 have popped up on social media, depicting everything from a hapless victim at the mercy of a tyrannical Reviewer 2 to a defiant author standing up to the reviewer’s absurd comments.

One popular Reviewer 2 meme features a picture of Leonardo DiCaprio from the movie “The Revenant” with the caption, “I ain’t afraid of no Reviewer 2.” Another shows a person standing on the edge of a cliff with the caption, “Me, reading Reviewer 2’s comments.” The memes often play off the frustration and absurdity of Reviewer 2’s feedback, providing a lighthearted take on a serious issue.

While the memes may be amusing, they also highlight a larger issue in academic publishing. Reviewer 2’s nitpicky comments can sometimes distract from the bigger picture and make it harder for authors to focus on the actual content of their work.

Additionally, the anonymity of peer review can lead to reviewers making comments that they wouldn’t necessarily make if they were identified.

Despite the challenges posed by Reviewer 2 and the peer review process in general, it remains an important part of academic publishing.

The feedback provided by reviewers, even the overly critical ones, can help authors improve their work and ensure that published research is of the highest quality.

In conclusion, while Reviewer 2 may be the source of frustration for many authors, it has also become a source of humor and levity through the creation of memes.

These memes provide a lighthearted take on a serious issue and highlight some of the challenges of the peer review process. Ultimately, however, peer review remains an essential part of academic publishing, and authors must learn to navigate the process, Reviewer 2 and all.

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Recorded on February 21, 2024.

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[00:00:00] Erin Spain, MS: This is Breakthroughs, a podcast from Northwestern University Feinberg School of Medicine. I'm Erin Spain, host of the show. Northwestern University Feinberg School of Medicine is home to a team of premier faculty and staff biostatisticians, who are the driving force of data analytic innovation and excellence here. Today, we are talking with Dr. Denise Scholtens, a leader in biostatistics at Northwestern, about the growing importance of the field, and how she leverages her skills to collaborate on several projects in Maternal and Fetal Health. She is the Director of the Northwestern University Data Analysis and Coordinating Center, NUDACC, and Chief of Biostatistics in the Department of Preventive Medicine, as well as Professor of Preventive Medicine and Neurological Surgery. Welcome to the show.  

[00:01:02] Denise Scholtens, PhD: Thank you so much.  

[00:01:02] Erin Spain, MS: So you have said in the past that you were drawn to this field of biostatistics because you're interested in both math and medicine, but not interested in becoming a clinician. Tell me about your path into the field and to Northwestern.  

[00:01:17] Denise Scholtens, PhD: You're right. I have always been interested in both math and medicine. I knew I did not want to be involved in clinical care. Originally, fresh out of college, I was a math major and I taught high school math for a couple of years. I really enjoyed that, loved the kids, loved the teaching parts of things. Interestingly enough, my department chair at the time assigned me to teach probability and statistics to high school seniors. I had never taken a statistics course before, so I was about a week ahead of them in our classes and found that I just really enjoyed the discipline. So as much as I loved teaching, I did decide to go ahead and invest in this particular new area that I had found and I really enjoyed. So I wanted to figure out how I could engage in the field of statistics. Decided to see, you know, exactly how studying statistics could be applied to medicine. At the time, Google was brand new. So I literally typed in the two words math and medicine to see what would come up. And the discipline of biostatistics is what Google generated. And so here I am, I applied to grad school and it's been a great fit for me.  

[00:02:23] Erin Spain, MS: Oh, that's fantastic. So you went on to get a PhD, and then you came to Northwestern in 2004. And so tell me a little bit about the field then and how it's changed so dramatically since.  

[00:02:36] Denise Scholtens, PhD: So yes, I started here at Northwestern in 2004, just a few months after I had defended my thesis. At the time there was really an emerging field of study called bioinformatics. So I wrote my thesis in the space of genomics data analysis with what at the time was a brand new technology, microarrays. This was the first way we could measure gene transcription at a high throughput level. So I did my thesis work in that space. I studied at an institution with a lot of strengths and very classical statistics. So things that we think of in biostatistics like clinical trial design, observational study analysis, things like that. So I had really classic biostatistics training and then complimented that with sort of these emerging methods with these high dimensional data types. So I came to Northwestern here and I sort of felt like I lived in two worlds. I had sort of classic biostat clinical trials, which were certainly, you know, happening here. And, that work was thriving here at Northwestern, but I had this kind of new skillset, and I just didn't quite know how to bring the two together. That was obviously a long time ago, 20 years ago. Now we think of personalized medicine and genomic indicators for treatment and, you know, there's a whole variety of omics data variations on the theme that are closely integrated with clinical and population level health research. So there's no longer any confusion for me about how those two things come together. You know, they're two disciplines that very nicely complement each other. But yeah, I think that does speak to how the field has changed, you know, these sort of classic biostatistics methods are really nicely blended with a lot of high dimensional data types. And it's been fun to be a part of that.  

[00:04:17] Erin Spain, MS: There were only a handful of folks like you at Northwestern at the time. Tell me about now and the demand for folks with your skill set.  

[00:04:26] Denise Scholtens, PhD: When I came to Northwestern, I was one of a very small handful of biostatistics faculty. There were five of us. We were not even called a division of biostatistics. We were just here as the Department of Preventive Medicine. And a lot of the work we did was really very tightly integrated with the epidemiologists here in our department and we still do a lot of that for sure. There was also some work going on with the Cancer Center here at Northwestern. But yeah, a pretty small group of us, who has sort of a selected set of collaborations. You know, I contrast that now to our current division of biostatistics where we are over 20s, pushing 25, depending on exactly how you want to count. Hoping to bring a couple of new faculty on board this calendar year. We have a staff of about 25 statistical analysts. And database managers and programmers. So you know, when I came there were five faculty members and I think two master's level staff. We are now pushing, you know, pushing 50 people in our division here so it's a really thriving group.  

[00:05:26] Erin Spain, MS: in your opinion, what makes a good biostatistician? Do you have to have a little bit of a tough skin to be in this field?  

Denise Scholtens, PhD: I do think it's a unique person who wants to be a biostatistician. There are a variety of traits that can lead to success in this space. First of all, I think it's helpful to be wildly curious about somebody else's work. To be an excellent collaborative biostatistician, you have to be able to learn the language of another discipline. So some other clinical specialty or public health application. Another trait that makes a biostatistician successful is to be able to ask the right questions about data that will be collected or already have been collected. So understanding the subtleties there, the study design components that lead to why we have the data that we have. You know, a lot of our data, you could think of it in a simple flat file, right? Like a Microsoft Excel file with rows and columns. That certainly happens a lot, but there are a lot of incredibly innovative data types out there: wearables technology, imaging data, all kinds of high dimensional data. So I think a tenacity to understand all of the subtleties of those data and to be able to ask the right questions. And then I think for a biostatistician at a medical school like ours, being able to blend those two things, so understanding what the data are and what you have to work with and what you're heading toward, but then also facilitating the translation of those analytic findings for the audience that really wants to understand them. So for the clinicians, for the patients, for participants and the population that the findings would apply to.   

Erin Spain, MS: It must feel good, though, in those situations where you are able to help uncover something to improve a study or a trial.  

[00:07:07] Denise Scholtens, PhD: It really does. This is a job that's easy to get out of bed for in the morning. There's a lot of really good things that happen here. It's exciting to know that the work we do could impact clinical practice, could impact public health practice. I think in any job, you know, you can sometimes get bogged down by the amount of work or the difficulty of the work or the back and forth with team members. There's just sort of all of the day to day grind, but to be able to take a step back and remember the actual people who are affected by our own little niche in this world. It's an incredibly helpful and motivating practice that I often keep to remember exactly why I'm doing what I'm doing and who I'm doing it for.  

[00:07:50] Erin Spain, MS: Well, and another important part of your work is that you are a leader. You are leading the center, NUDACC, that you mentioned, Northwestern University Data Analysis and Coordinating Center. Now, this has been open for about five years. Tell me about the center and why it's so crucial to the future of the field.  

[00:08:08] Denise Scholtens, PhD: We specialize at NUDACC in large scale, multicenter prospective studies. So these are the clinical trials or the observational studies that often, most conclusively, lead to clinical or public health practice decision making. We focus specifically on multicenter work. Because it requires a lot of central coordination and we've specifically built up our NUDACC capacity to handle these multi center investigations where we have a centralized database, we have centralized and streamlined data quality assurance pipelines. We can help with central team leadership and organization for large scale networks. So we have specifically focused on those areas. There's a whole lot of project management and regulatory expertise that we have to complement our data analytics strengths as well. I think my favorite part of participating in these studies is we get involved at the very beginning. We are involved in executive level planning of these studies. We oversee all components of study design. We are intimately involved in the development of the data capture systems. And in the QA of it. We do all of this work on the front end so that we get all of the fun at the end with the statistics and can analyze data that we know are scientifically sound, are well collected, and can lead to, you know, really helpful scientific conclusions.  

[00:09:33] Erin Spain, MS: Tell me about that synergy between the clinicians and the other investigators that you're working with on these projects.  

[00:09:41] Denise Scholtens, PhD: It is always exciting, often entertaining. Huge range of scientific opinion and expertise and points of view, all of which are very valid and very well informed. All of the discussion that could go into designing and launching a study, it's just phenomenally interesting and trying to navigate all of that and help bring teams to consensus in terms of what is scientifically most relevant, what's going to be most impactful, what is possible given the logistical strengths. Taking all of these well informed, valid, scientific points of view and being a part of the team that helps integrate them all toward a cohesive study design and a well executed study. That's a unique part of the challenge that we face here at NUDACC, but an incredibly rewarding one. It's also such an honor and a gift to be able to work with such a uniformly gifted set of individuals. Just the clinical researchers who devote themselves to these kinds of studies are incredibly generous, incredibly thoughtful and have such care for their patients and the individuals that they serve, that to be able to sit with them and think about the next steps for a great study is a really unique privilege.  

[00:10:51] Erin Spain, MS: How unique is a center like this at a medical school?  

[00:10:55] Denise Scholtens, PhD: It's fairly unique to have a center like this at a medical school. Most of the premier medical research institutions do have some level of data coordinating center capacity. We're certainly working toward trying to be one of the nation's best, absolutely, and build up our capacity for doing so. I'm actually currently a part of a group of data coordinating centers where it's sort of a grassroots effort right now to organize ourselves and come up with, you know, some unified statements around the gaps that we see in our work, the challenges that we face strategizing together to improve our own work and to potentially contribute to each other's work. I think maybe the early beginnings of a new professional organization for data coordinating centers. We have a meeting coming up of about, I think it's 12 to 15 different institutions, academic research institutions, specifically medical schools that have centers like ours to try to talk through our common pain points and also celebrate our common victories.  

[00:11:51] Erin Spain, MS: I want to shift gears a little bit to talk about some of your research collaborations, many of which focus on maternal and fetal health and pregnancy. You're now involved with a study with folks at the Ohio State University that received a 14 million grant looking at the effectiveness of aspirin in the prevention of hypertensive disorders in pregnancy. Tell me about this work.  

[00:12:14] Denise Scholtens, PhD: Yes, this is called the aspirin study. I suppose not a very creative name, but a very appropriate one. What we'll be doing in this study is looking at two different doses of aspirin for trying to prevent maternal hypertensive disorders of pregnancy in women who are considered at high risk for these disorders. This is a huge study. Our goal is to enroll 10,742 participants. This will take place at 11 different centers across the nation. And yes, we at NUDACC will serve as the data coordinating center here, and we are partnering with the Ohio State University who will house the clinical coordinating center. So this study is designed to look at two different doses to see which is more effective at preventing hypertensive disorders of pregnancy. So that would include gestational hypertension and preeclampsia. What's really unique about this study and the reason that it is so large is that it is specifically funded to look at what's called a heterogeneity of treatment effect. What that is is a difference in the effectiveness of aspirin in preventing maternal hypertensive disorders, according to different subgroups of women. We'll specifically have sufficient statistical power to test for differences in treatment effectiveness. And we have some high priority subgroups that we'll be looking at. One is a self-identified race. There's been a noted disparity in maternal hypertensive disorders, for individuals who self identify according to different races. And so we will be powered to see if aspirin has comparable effectiveness and hopefully even better effectiveness for the groups who really need it, to bring those rates closer to equity which is, you know, certainly something we would very strongly desire to see. We'll also be able to look at subgroups of women according to obesity, according to maternal age at pregnancy, according to the start time of aspirin when aspirin use is initiated during pregnancy. So that's why the trial is so huge. For a statistician, the statisticians out there who might be listening, this is powered on a statistical interaction term, which doesn't happen very often. So it's exciting that the trial is funded in that way.  

[00:14:27] Erin Spain, MS: Tell me a little bit more about this and how your specific skills are going to be utilized in this study.  

[00:14:32] Denise Scholtens, PhD: Well, there are three biostatistics faculty here at Northwestern involved in this. So we're definitely dividing and conquering. Right now, we're planning this study and starting to stand it up. So we're developing our statistical analysis plans. We're developing the database. We are developing our randomization modules. So this is the piece of the study where participants are randomized to which dose of aspirin they're going to receive. Because of all of the subgroups that we're planning to study, we need to make especially sure that the assignments of which dose of aspirin are balanced within and across all of those subgroups. So we're going to be using some adaptive randomization techniques to ensure that that balance is there. So there's some fun statistical and computer programming innovation that will be applied to accomplish those things. So right now, there are usually two phases of a study that are really busy for us. That's starting to study up and that's where we are. And so yes, it is very busy for us right now. And then at the end, you know, in five years or so, once recruitment is over, then we analyze all the data,  

[00:15:36] Erin Spain, MS: Are there any guidelines out there right now about the use of aspirin in pregnancy. What do you hope that this could accomplish?  

 Prescribing aspirin use for the prevention of hypertension during pregnancy is not uncommon at all. That is actually fairly routinely done, but that it's not outcomes based in terms of which dosage is most effective. So 81 milligrams versus 162 milligrams. That's what we will be evaluating. And my understanding is that clinicians prescribe whatever they think is better, and I'm sure those opinions are very well informed but there is very little outcome based evidence for this in this particular population that we'll be studying. So that would be the goal here, would be to hopefully very conclusively say, depending on the rates of the hypertensive disorders that we see in our study, which of the two doses of aspirin is more effective. Importantly, we will also be tracking any side effects of taking aspirin. And so that's also very much often a part of the evaluation of You know, taking a, taking a drug, right, is how safe is it? So we'll be tracking that very closely as well. Another unique part of this study is that we will be looking at factors that help explain aspirin adherence. So we are going to recommend that participants take their dose of aspirin daily. We don't necessarily expect that's always going to happen, so we are going to measure how much of their prescribed dose they are actually taking and then look at, you know, factors that contribute to that. So be they, you know, social determinants of health or a variety of other things that we'll investigate to try to understand aspirin adherence, and then also model the way in which that adherence could have affected outcomes.  

Erin Spain, MS: This is not the first study that you've worked on involving maternal and fetal health. Tell me about your interest in this particular area, this particular field, and some of the other work that you've done.  

[00:17:31] Denise Scholtens, PhD: So I actually first got my start in data coordinating work through the HAPO study. HAPO stands for Hyperglycemia Adverse Pregnancy Outcome. That study was started here at Northwestern before I arrived. Actually recruitment to the study occurred between 2000 and 2006. Northwestern served as the central coordinating center for that study. It was an international study of 25,000 pregnant individuals who were recruited and then outcomes were evaluated both in moms and newborns. When I was about mid career here, all the babies that were born as a part of HAPO were early teenagers. And so we conducted a follow up study on the HAPO cohort. So that's really when I got involved. It was my first introduction to being a part of a coordinating center. As I got into it, though, I saw the beauty of digging into all of these details for a huge study like this and then saw these incredible resources that were accumulated through the conduct of such a large study. So the data from the study itself is, was of course, a huge resource. But then also we have all of these different samples that sit in a biorepository, right? So like usually blood sample collection is a big part of a study like this. So all these really fun ancillary studies could spin off of the HAPO study. So we did some genomics work. We did some metabolomics work. We've integrated the two and what's called integrated omics. So, you know, my work in this space really started in the HAPO study. And I have tremendously enjoyed integrating these high dimensional data types that have come from these really rich data resources that have all, you know, resulted because of this huge multicenter longitudinal study. So I kind of accidentally fell into the space of maternal and fetal health, to be honest. But I just became phenomenally interested in it and it's been a great place.  

[00:19:24] Erin Spain, MS: Would you say that this is also a population that hasn't always been studied very much in biomedical science?  

[00:19:32] Denise Scholtens, PhD: I think that that is true, for sure. There are some unique vulnerabilities, right, for a pregnant individual and for the fetus, right, and in that situation. You know, the vast majority of what we do is really only pertaining to the pregnant participant but, you know, there are certainly fetal outcomes, newborn outcomes. And so, I think conducting research in this particular population is a unique opportunity and there are components of it that need to be treated with special care given sort of this unique phase of human development and this unique phase of life.  

[00:20:03] Erin Spain, MS: So, as data generation just really continues to explode, and technology is advancing so fast, faster than ever, where do you see this field evolving, the field of biostatistics, where do you see it going in the next five to ten years?  

[00:20:19] Denise Scholtens, PhD: That's a great question. I think all I can really tell you is that I'm continually surprised by new data types. I think that we will see an emergence of a whole new kind of technology that we probably can't even envision five years from now. And I think that the fun part about being a biostatistician is seeing what's happening and then trying to wrap your mind around the possibilities and the actual nature of the data that are collected. You know, I think back to 2004 and this whole high throughput space just felt so big. You know, we could look at gene transcription across the genome using one technology. And we could only look at one dimension of it. Right now it just seems so basic. When I think about where the field has come over the past 20 years, it's just phenomenal. I think we're seeing a similar emergence of the scale and the type of data in the imaging space and in the wearable space, with EHR data, just. You know, all these different technologies for capturing, capturing things that we just never even conceived of before. I do hope that we continue to emphasize making meaningful and translatable conclusions from these data. So actionable conclusions that can impact the way that we care for others around us. I do hope that remains a guiding principle in all that we do.  

[00:21:39] Erin Spain, MS: Why is Northwestern Medicine and Northwestern Feinberg School of Medicine such a supportive environment to pursue this type of work?  

[00:21:47] Denise Scholtens, PhD: That's a wonderful question and one, honestly, that faculty candidates often ask me. When we bring faculty candidates in to visit here at Northwestern, they immediately pick up on the fact that we are a collaborative group of individuals who are for each other. Who want to see each other succeed, who are happy to share the things that we know and support each other's work, and support each other's research, and help strategize around the things that we want to accomplish. There is a strong culture here, at least in my department and in my division that I've really loved that continues to persist around really genuinely collaborating and genuinely sharing lessons learned and genuinely supporting each other as we move toward common goals. We've had some really strong, generous leadership who has helped us to get there and has helped create a culture where those are the guiding principles. In my leadership role is certainly something that I strive to maintain. Really hope that's true. I'm sure I don't do it perfectly but that's absolutely something I want to see accomplished here in the division and in NUDACC for sure.  

[00:22:50] Erin Spain, MS: Well, thank you so much for coming on the show and telling us about your path here to Northwestern and all of the exciting work that we can look forward to in the coming years.  

[00:22:59] Denise Scholtens, PhD: Thank you so much for having me. I've really enjoyed this.  

[00:23:01] Erin Spain, MS: You can listen to shows from the Northwestern Medicine Podcast Network to hear more about the latest developments in medical research, health care, and medical education. Leaders from across specialties speak to topics ranging from basic science to global health to simulation education. Learn more at feinberg. northwestern.edu/podcasts.