write a research paper in 2 days

How to write a whole research paper in a week

Writing up a full research article in a single week? Maybe you think that’s impossible. Yet I have done it repeatedly, and so have students in my courses. This is an exceptionally joyful (even if demanding) experience: being so productive just feels great! You are not wasting any time, and a paper produced in one go is typically coherent and nice to read. Even if you are a slow writer, you can write a whole paper in a single week — if you follow my strategy. Read below about what you need to prepare and how to approach this project.

I wrote my first scientific research article in 7 days. It started as a desperate effort to stop my procrastination and “just do it”. But I was surprised what a positive experience it was: focused and efficient, I was making daily progress, feeling motivated and content. Finally, the fruits of my hard work were gaining shape — and they did it so quickly!

I realized it was highly effective to write up a paper like this: writing for the whole day, every day until the first draft was finished. My writing project was firmly present in my mind — I didn’t lose time catching up with what I have written in the last session. Since I was not doing anything else, my wandering mind settled in very fast, and I was getting into a routine. The daily progress was clearly visible and motivated me to continue. And the result was a coherent paper that was easy to revise.

Meanwhile, this paper-a-week approach is my favorite. That’s how I write my papers, and that’s what I teach to students. In on-site courses young scientists draft a whole paper in 5 days, writing one major section per day. At the beginning of the week, many participants have doubts. But at the end of the week, they are all excited to see how much they managed to write in just a single week.

If you would also like to try out this approach, then read on about the necessary preparations, the optimal setting, and a productive writing strategy.

If you would like to get support during the preparation, drafting and revising of your research article, check out my online course Write Up Your Paper .

Prepare well

• First, think about your audience and pick a suitable journal . This is an important step because the audience and journal determine the content & style of your paper. As a reference, pick two recent papers on a similar topic published in your target journal.
• Create a storyline for your paper. What is the main message you want to convey, and how are you going to present your results?
• Put together all the results that you need to present your story convincingly: collect the necessary data, finish analyses, and create figures and tables.
• Select and read the relevant background literature as well as studies you want to compare your work with. As you read, note down any point that comes to your mind as something to be mentioned in the Introduction or Discussion section.
• Draft a preliminary Abstract : it will help you keep the direction and not get distracted by secondary ideas as you write the individual sections.

Depending on how complete your results already are, you might need 2-4 weeks to finish all these preparations. To help you keep an overview, I created a checklist with detailed steps that you need to take before you attempt to write up your paper in a week. Subscribe to our Newsletter and get your copy of the checklist.

Reserve a whole week for writing

Now, writing a paper in a single week is a serious business. You can’t do it if you don’t focus solely on the writing and create good writing conditions. Therefore, I recommend the following settings:

• Find a place where you can write without distractions. I have written my first paper over the Easter holidays when there was nobody in the office. You might choose to write at home or in a library. Though if possible, the best is to go for a retreat: removing yourself from your everyday settings immensely helps focus on the writing.
• Cancel (all) social obligations for the week. While it’s crucial to relax in the evening, you want to avoid disturbances associated with social events. Anything that makes your thoughts drift away from your work because it requires planning, exchanging of messages with others, or simply because it’s too exciting is better left for some other week. On the other hand, a quiet meeting with a good friend over a glass of wine or beer might be just the perfect way to unwind and rest after a productive, yet exhausting day of writing.
• Get support from the partner, family or friends — if possible. It’s best when you don’t need to run errands, cook and clean during this week. If you live alone, you can probably easily arrange yourself for undisturbed work. If you live with other people, ask them for consideration and support.

What I described above are the *ideal* conditions for undisturbed writing. But don’t give up if you can’t create such conditions for yourself. Work with what is possible — maybe it will take you 7-8 instead of 5-6 days but that’s still a great result, right?

Do you need to revise & polish your manuscript or thesis but don’t know where to begin?

Get your Revision Checklist

Click here for an efficient step-by-step revision of your scientific texts.

Maybe you think that you can never ever draft a research article in a single week. Because you write so slowly, producing only few paragraphs per day. Well — I agree that if you don’t optimize your writing strategy, it would be hard to impossible to write up a whole paper in a week.

• Separate the processes of writing and revising. That’s the most important principle. Resist the urge to revise as you write the first draft. Moreover, don’t interrupt your writing to look up missing information. Work with placeholders instead. This allows you to get into the state of flow and proceed much faster than you can imagine.
• Start your writing day with 10 minutes of freewriting . Write without stopping about anything that comes to your mind. This helps you to warm up for writing, clear your head of any unrelated thoughts, and get into the mood of writing without editing.
• Take regular power breaks. I recommend to follow the Pomodoro technique : write for 25 minutes and then take a 5-minute break. After 3-4 such sessions take a longer break of 0.5-1 hour. During the breaks get up, walk a bit, stretch, look around, and breathe deeply. These breaks help you sustain high focus and productivity throughout the whole day.
• Eat and sleep well. What you are doing is similar to a professional athlete. So take care of your brain and body, and they will serve you well.
• Reward yourself. Every day celebrate the progress you have made. You have full right to be proud of you!

Write the individual sections in a reasonable order

If you have written a research paper before, you have probably realized that starting with the Introduction and finishing with the Discussion is not the ideal order in which to tackle the individual sections. Instead, I recommend the following procedure:

• Start with the Methods section. This is the easiest section to write, so it’s great as a warm-up, to get into writing without the need to think (and procrastinate ;)) too much. Look at your figures and tables: what methods did you use to create them? Then describe your methods, one after another.
• Results section: Writing the Methods section refreshes your memory about the research you have done. So writing the Results section next should not be too hard: Take one display object (figure or table) after another, and describe the results they contain. While you do so, you will come across points that need to be discussed in the Discussion section. Note them down so you don’t forget them.
• Introduction : When your results are fresh in your mind, you are in a great position to write the Introduction — because the Introduction should contain selected information that gives the reader context for your research project and allows them to understand your results and their implications.
• Discussion : When you have taken notes while writing the Results section, the Discussion section should be quite easy to draft. Don’t worry too early about the order in which you want to discuss the individual points. Write one paragraph for each point , and then see how you can logically arrange them.
• Abstract and title : On the last day, revise the preliminary Abstract or write a new one. You could also take a break of a few days before tackling the Abstract, to gain clarity and distance. Generate multiple titles (I recommend 6-10), so that you and your co-authors can choose the most appropriate one.

Just do it!

Once you have written the whole draft, let it sit for a week or two, and then revise it. Follow my tips for efficient revising and get your revision checklist that will guide you step-by-step through the whole process.

Now I am curious about your experience: Have you ever written up an academic article quickly? How did you do it? Please, share with us your tips & strategies!

Do you need to revise & polish your manuscript or thesis but don’t know where to begin? Is your text a mess and you don't know how to improve it?

Click here for an efficient step-by-step revision of your scientific texts. You will be guided through each step with concrete tips for execution.

7 thoughts on “ How to write a whole research paper in a week ”

Thank for your guide and suggestion. It gives to me very precious ways how to write a article. Now I am writing a article related to Buddhist studies. Thank you so much.

You are welcome!

excellent! it helped me a lot! wish you all best

Hi Parham, I’m happy to hear that!

I have never written any paper before. As I am from very old school.

But my writing skill is actually very good. Your help is definitely going to help me as this has inspired me alot. Will let you know, once done. I really like the outline that you have given. Basically you have made it so easy for me .

Hope fully will be in touch with you soon.

Thanks and ki d Regards, Shehla

Dear Shehla, that sounds great! I’m looking forward to hearing about your paper!

Comments are closed.

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Princeton Correspondents on Undergraduate Research

How to Write a Paper in Two Days: A Timeline

Last week, Yuem wrote about keeping track of his progress on his senior thesis —a project with distant deadlines. As an underclassman, I usually face shorter-term deadlines for class essays and problem sets, and these require a similar, but condensed approach.

This post has real-life inspiration. Next Thursday, I have a paper due for my philosophy class on Nietzsche. Weekdays are busy with problem sets and assignments. I do not expect myself to start consolidating material for the paper till this weekend, which leaves me plenty of time to plan an effective essay.

Here’s the schedule I successfully used last time, when I was looking at parts of Nietzsche’s Thus Spoke Zarathustra and the Gay Science.  Granted, the whole process I’m proposing is longer than just two days, but I promise if you use the pre-writing steps I suggest, you’ll be able to do the actual writing in a much shorter period of time!

5 Days before Due Date: Finish the core readings!

I spent about half of my weekend finishing the readings for the class that I had not been able to finish in time for lecture. Surprisingly few people realize how helpful this is. In a paper-based class, certain prompts will lend themselves to specific readings. You can write a decent paper–maybe even get a “good grade”– by reading only what is absolutely necessary for a paper, but it will fall far short of your potential. You are surrounded by world-class facilities and faculty–don’t waste your time on something sub-par. The best part about writing a paper is finding unexpected connections, after all.

4 Days before Due Date: Summarize the readings.

After I finished reading and highlighting parts of the books, I sat down with a notebook and wrote down the gist of each section using what I had previously marked in the books. I used to do this as I read, but found it to take a long time to finish the process. Now, I read in whatever small bursts of time I have, and revisit my books to quickly take notes in one go using what I have highlighted. Now, I had a short summary of the assigned works in front of me as a map of what to reference.

3 Days before Due Date: Finalize essay topic and write an outline.

I narrowed my essay topics down to two, and drafted points I had in mind for each one. I did some outside research as well, and chose the topic I felt better prepared with. I started to construct an outline by selecting relevant quotes (using my summary of notes) and finally had a blocked version of evidence for different points in the paper. At this point, I started to work around the pieces of evidence I had written down and formulate logical arguments and transitions.

2 Days before Due Date: Talk to my professor, revise outline, and start writing!

By this point, I realized what crucial questions I had for my professor. I ran through some of the main points I was going to make in the paper and discovered that a few of them were faulty. I adapted accordingly and started to write!

Writing an eight page paper in two days was surprisingly easy with a well-developed outline. Do yourself a favor and spend the bulk of your time in the “planning” stage of an essay: reading, summarizing, outlining, and discussing ideas with classmates and professors. The actual writing process will be a matter of a few hours spent at your computer transferring thoughts from outline to paper in a format that flows well. Have a friend or two help you edit your paper, and you will emerge feeling rewarded.

— Vidushi Sharma, Humanities Correspondent

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How to Write a Research Paper in a Day: Step-by-Step Guide

Julie Peterson

As all other students, you put a lot of effort into studying and writing homework assignments. You do your best to complete every single project on time. Unfortunately, that’s not always possible.

Research papers are long-term assignments. Your professors advise you to start early, and you try to do that. However, you have to think about tests and other assignments. Plus, you can’t stay in the library forever when you should also work on your social life.

Sooner or later, every student ends up in the same situation: the deadline is too close and the research paper is nowhere near finished. There are two usual reasons that lead to that scenario:

1) You forgot all about this project. You were too occupied with studying and classes. You didn’t set a reminder on your calendar, and your teacher just reminded you that the deadline is tomorrow .                

2) You kept procrastinating. The topic seemed simple enough, so you thought you had enough time. The day before the deadline, you’re facing the harsh reality: a research paper is more complex than it seems.

1. First Thing’s First: Calm Down!

What’s the first thing you do when you realize you have very little time to complete a whole research paper? Panic! It’s the usual reaction. You start saying to yourself:

• “There’s no way I can do this!”
• “It’s just impossible.”
• “Oh my God, what am I gonna do?”

That’s the wrong approach to have. Panic will block you from achieving your full potential. The first thing you need to do is relax . You forgot about that paper. Now, you’re left with a tight deadline. That’s okay. You still have time and you can still do something about it.

Close your eyes. Take a deep breath. Then, repeat to yourself:

• “I can do this. I will research and write whole day. I’ll get it done by tomorrow.”

That positive self-talk will prepare your mind for the challenge that follows. Eat something nice, make yourself some coffee and get to work. If necessary, take a 20-minute power nap before you proceed with the following steps.

2. Use the Pomodoro Technique

When you have to stay focused on a challenging task, it’s important to have a system. The Pomodoro Technique is a pretty effective method that helps you do more work in less time. It’s based on a simple principle:

• You work for 25 minutes straight, with no distractions.
• After the work session, you take a 5-minute break.

It sounds pretty simple, but it works. Twenty five minutes doesn’t seem like a long time. Your mind can stay focused on the task at hand without much effort. After the short break, you’ll be able to get back to work.

If you start writing the paper without such system, the task will seem overwhelming. With the Pomodoro Technique, you’re giving yourself small steps towards the ultimate goal.

You can use a browser extension like Strict Workflow to keep track of your working and resting session. It’s great because it blocks your access to distracting websites during the working session. When you give yourself a break of 5 minutes, you can check what’s new on Twitter.  

3. Start With Brainstorming

Before you get to work, you’ll need to get an idea. How do you want this paper to look like? Go through a brief brainstorming stage, so you’ll form an outline to guide you to the process of research and writing.

• Your teacher gave you a prompt for the research paper. Focus on it. What ideas do you get?
• Make a list of a few possible topics. The brainstorming stage doesn’t need much thinking. You just write whatever comes to your mind.
• Now, do a preliminary research on those topics. It shouldn’t take much time. Give 5 minutes to each idea you have. What topic gives you the greatest foundation for research? That’s what you should focus on.
• First, form your thesis statement. It’s something you will prove throughout the research paper. The preliminary research provided you with enough resources. Keep in mind that professors don’t like broad thesis statement. If, for example, the prompt was related to World War 2, you’ll have to narrow it down. You can opt for a specific event during the war, or even explore the Italian uniforms. Whatever it is, you need to make it very specific.
• Think of at least 3-4 subtopics. When you focus on the main topic, what questions do you have? You’ll want to answer those questions through the subtopics. That will be the body of your research paper.
• Finally, the outline should include a conclusion, which will sum up the claims and connect the loose ends.

4. Now, Onto the Research!

Here is an important piece of advice: don’t research as you write. When you’re working on a serious research paper, you need to explore many resources that will help you get ideas and form opinions. This should be a separate stage. Since you have only one day to write this paper, you can give yourself 2 hours for the research. Here are few tips to consider:

• Use Google Scholar instead of the usual Google search engine. It gives you access to high-quality scientific and academic sources. Only authoritative sources will make the paper look serious and well-researched.
• Keep track of all online sources you collect. You will need to reference them. Otherwise, you’ll be guilty of plagiarism. You can create a private Pinterest board, where you’ll collect all materials you plan to use. As for the referencing, you can use a free citation generator , which will save you a lot of time.
• Take notes! You can’t expect to remember everything you read and all ideas you get during this stage. If necessary, update the outline and make it more detailed.

5. Write It!

Finally, you’ve come down to the writing part. You might want to take a break before this stage. Have another cup of coffee and an energizing meal.

• Again: relax! You have an outline with good ideas. You have enough resources to work with. At this stage, you should just bring everything together, and that won’t take more than 4 hours.
• You don’t have to start with the introduction. Many students find it easier to write the thesis and develop the arguments first. Then, it’s easier to explain what the paper is about in the introductory part.
• Don’t think much about the style and grammar at first. This is your first draft, which will go through changes later on. Focus on expressing your ideas in a logical way.
• Support your arguments with quotes from the resources you have. They will add strength to the claims.
• Use simple, clear language. Don’t try to make a good impression by writing endless sentences and using words you just found in the dictionary. You don’t need complex style to show you know what you’re writing about.
• Don’t leave the references last. Cite the sources as you go!
• Keep up with the Pomodoro method while you write. If you feel exhausted and you need a longer break, take a power nap and you’ll continue later.

6. Don’t Forget the Editing

You’re almost done, but it’s not time to celebrate just yet. When you finish writing the research paper, it’s important to take a break. You must be hungry, so get something to eat. Try not to think about the paper for at least one hour. When you go back to it, the mistakes will be more obvious.

SEE: Top 6 Editing Tools for College Students

• Get rid of sentences and paragraphs that are not directly related to the thesis statement and subtopics.
• Add more information when you notice gaps in the logical flow.
• Pay attention to the citations. You have to format them in accordance with the required referencing style.
• Proofread! Once you’re done fixing the major aspects of the paper, you can do the last reading. At this point, focus on the grammar, spelling, and punctuation.

Now, you can congratulate yourself. You made it! You wrote an entire research paper in a single day. It’s not smart to procrastinate until the last day. However, it’s not impossible to write a paper in such a short timeframe. Now, have a good sleep. You deserve it.    

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How To Write A Research Paper

Step-By-Step Tutorial With Examples + FREE Template

By: Derek Jansen (MBA) | Expert Reviewer: Dr Eunice Rautenbach | March 2024

For many students, crafting a strong research paper from scratch can feel like a daunting task – and rightly so! In this post, we’ll unpack what a research paper is, what it needs to do , and how to write one – in three easy steps. 🙂 

Overview: Writing A Research Paper

What (exactly) is a research paper.

• How to write a research paper
• Stage 1 : Topic & literature search
• Stage 2 : Structure & outline
• Stage 3 : Iterative writing
• Key takeaways

Let’s start by asking the most important question, “ What is a research paper? ”.

Simply put, a research paper is a scholarly written work where the writer (that’s you!) answers a specific question (this is called a research question ) through evidence-based arguments . Evidence-based is the keyword here. In other words, a research paper is different from an essay or other writing assignments that draw from the writer’s personal opinions or experiences. With a research paper, it’s all about building your arguments based on evidence (we’ll talk more about that evidence a little later).

Now, it’s worth noting that there are many different types of research papers , including analytical papers (the type I just described), argumentative papers, and interpretative papers. Here, we’ll focus on analytical papers , as these are some of the most common – but if you’re keen to learn about other types of research papers, be sure to check out the rest of the blog .

With that basic foundation laid, let’s get down to business and look at how to write a research paper .

Overview: The 3-Stage Process

While there are, of course, many potential approaches you can take to write a research paper, there are typically three stages to the writing process. So, in this tutorial, we’ll present a straightforward three-step process that we use when working with students at Grad Coach.

These three steps are:

• Finding a research topic and reviewing the existing literature
• Developing a provisional structure and outline for your paper, and
• Writing up your initial draft and then refining it iteratively

Let’s dig into each of these.

Need a helping hand?

Step 1: Find a topic and review the literature

As we mentioned earlier, in a research paper, you, as the researcher, will try to answer a question . More specifically, that’s called a research question , and it sets the direction of your entire paper. What’s important to understand though is that you’ll need to answer that research question with the help of high-quality sources – for example, journal articles, government reports, case studies, and so on. We’ll circle back to this in a minute.

The first stage of the research process is deciding on what your research question will be and then reviewing the existing literature (in other words, past studies and papers) to see what they say about that specific research question. In some cases, your professor may provide you with a predetermined research question (or set of questions). However, in many cases, you’ll need to find your own research question within a certain topic area.

Finding a strong research question hinges on identifying a meaningful research gap – in other words, an area that’s lacking in existing research. There’s a lot to unpack here, so if you wanna learn more, check out the plain-language explainer video below.

Once you’ve figured out which question (or questions) you’ll attempt to answer in your research paper, you’ll need to do a deep dive into the existing literature – this is called a “ literature search ”. Again, there are many ways to go about this, but your most likely starting point will be Google Scholar .

If you’re new to Google Scholar, think of it as Google for the academic world. You can start by simply entering a few different keywords that are relevant to your research question and it will then present a host of articles for you to review. What you want to pay close attention to here is the number of citations for each paper – the more citations a paper has, the more credible it is (generally speaking – there are some exceptions, of course).

Ideally, what you’re looking for are well-cited papers that are highly relevant to your topic. That said, keep in mind that citations are a cumulative metric , so older papers will often have more citations than newer papers – just because they’ve been around for longer. So, don’t fixate on this metric in isolation – relevance and recency are also very important.

Beyond Google Scholar, you’ll also definitely want to check out academic databases and aggregators such as Science Direct, PubMed, JStor and so on. These will often overlap with the results that you find in Google Scholar, but they can also reveal some hidden gems – so, be sure to check them out.

Once you’ve worked your way through all the literature, you’ll want to catalogue all this information in some sort of spreadsheet so that you can easily recall who said what, when and within what context. If you’d like, we’ve got a free literature spreadsheet that helps you do exactly that.

Step 2: Develop a structure and outline

With your research question pinned down and your literature digested and catalogued, it’s time to move on to planning your actual research paper .

It might sound obvious, but it’s really important to have some sort of rough outline in place before you start writing your paper. So often, we see students eagerly rushing into the writing phase, only to land up with a disjointed research paper that rambles on in multiple

Now, the secret here is to not get caught up in the fine details . Realistically, all you need at this stage is a bullet-point list that describes (in broad strokes) what you’ll discuss and in what order. It’s also useful to remember that you’re not glued to this outline – in all likelihood, you’ll chop and change some sections once you start writing, and that’s perfectly okay. What’s important is that you have some sort of roadmap in place from the start.

At this stage you might be wondering, “ But how should I structure my research paper? ”. Well, there’s no one-size-fits-all solution here, but in general, a research paper will consist of a few relatively standardised components:

• Introduction
• Literature review
• Methodology

Let’s take a look at each of these.

First up is the introduction section . As the name suggests, the purpose of the introduction is to set the scene for your research paper. There are usually (at least) four ingredients that go into this section – these are the background to the topic, the research problem and resultant research question , and the justification or rationale. If you’re interested, the video below unpacks the introduction section in more detail. 

The next section of your research paper will typically be your literature review . Remember all that literature you worked through earlier? Well, this is where you’ll present your interpretation of all that content . You’ll do this by writing about recent trends, developments, and arguments within the literature – but more specifically, those that are relevant to your research question . The literature review can oftentimes seem a little daunting, even to seasoned researchers, so be sure to check out our extensive collection of literature review content here .

With the introduction and lit review out of the way, the next section of your paper is the research methodology . In a nutshell, the methodology section should describe to your reader what you did (beyond just reviewing the existing literature) to answer your research question. For example, what data did you collect, how did you collect that data, how did you analyse that data and so on? For each choice, you’ll also need to justify why you chose to do it that way, and what the strengths and weaknesses of your approach were.

Now, it’s worth mentioning that for some research papers, this aspect of the project may be a lot simpler . For example, you may only need to draw on secondary sources (in other words, existing data sets). In some cases, you may just be asked to draw your conclusions from the literature search itself (in other words, there may be no data analysis at all). But, if you are required to collect and analyse data, you’ll need to pay a lot of attention to the methodology section. The video below provides an example of what the methodology section might look like.

By this stage of your paper, you will have explained what your research question is, what the existing literature has to say about that question, and how you analysed additional data to try to answer your question. So, the natural next step is to present your analysis of that data . This section is usually called the “results” or “analysis” section and this is where you’ll showcase your findings.

Depending on your school’s requirements, you may need to present and interpret the data in one section – or you might split the presentation and the interpretation into two sections. In the latter case, your “results” section will just describe the data, and the “discussion” is where you’ll interpret that data and explicitly link your analysis back to your research question. If you’re not sure which approach to take, check in with your professor or take a look at past papers to see what the norms are for your programme.

Alright – once you’ve presented and discussed your results, it’s time to wrap it up . This usually takes the form of the “ conclusion ” section. In the conclusion, you’ll need to highlight the key takeaways from your study and close the loop by explicitly answering your research question. Again, the exact requirements here will vary depending on your programme (and you may not even need a conclusion section at all) – so be sure to check with your professor if you’re unsure.

Step 3: Write and refine

Finally, it’s time to get writing. All too often though, students hit a brick wall right about here… So, how do you avoid this happening to you?

Well, there’s a lot to be said when it comes to writing a research paper (or any sort of academic piece), but we’ll share three practical tips to help you get started.

First and foremost , it’s essential to approach your writing as an iterative process. In other words, you need to start with a really messy first draft and then polish it over multiple rounds of editing. Don’t waste your time trying to write a perfect research paper in one go. Instead, take the pressure off yourself by adopting an iterative approach.

Secondly , it’s important to always lean towards critical writing , rather than descriptive writing. What does this mean? Well, at the simplest level, descriptive writing focuses on the “ what ”, while critical writing digs into the “ so what ” – in other words, the implications . If you’re not familiar with these two types of writing, don’t worry! You can find a plain-language explanation here.

Last but not least, you’ll need to get your referencing right. Specifically, you’ll need to provide credible, correctly formatted citations for the statements you make. We see students making referencing mistakes all the time and it costs them dearly. The good news is that you can easily avoid this by using a simple reference manager . If you don’t have one, check out our video about Mendeley, an easy (and free) reference management tool that you can start using today.

Recap: Key Takeaways

We’ve covered a lot of ground here. To recap, the three steps to writing a high-quality research paper are:

• To choose a research question and review the literature
• To plan your paper structure and draft an outline
• To take an iterative approach to writing, focusing on critical writing and strong referencing

Remember, this is just a b ig-picture overview of the research paper development process and there’s a lot more nuance to unpack. So, be sure to grab a copy of our free research paper template to learn more about how to write a research paper.

Can you help me with a full paper template for this Abstract:

Background: Energy and sports drinks have gained popularity among diverse demographic groups, including adolescents, athletes, workers, and college students. While often used interchangeably, these beverages serve distinct purposes, with energy drinks aiming to boost energy and cognitive performance, and sports drinks designed to prevent dehydration and replenish electrolytes and carbohydrates lost during physical exertion.

Objective: To assess the nutritional quality of energy and sports drinks in Egypt.

Material and Methods: A cross-sectional study assessed the nutrient contents, including energy, sugar, electrolytes, vitamins, and caffeine, of sports and energy drinks available in major supermarkets in Cairo, Alexandria, and Giza, Egypt. Data collection involved photographing all relevant product labels and recording nutritional information. Descriptive statistics and appropriate statistical tests were employed to analyze and compare the nutritional values of energy and sports drinks.

Results: The study analyzed 38 sports drinks and 42 energy drinks. Sports drinks were significantly more expensive than energy drinks, with higher net content and elevated magnesium, potassium, and vitamin C. Energy drinks contained higher concentrations of caffeine, sugars, and vitamins B2, B3, and B6.

Conclusion: Significant nutritional differences exist between sports and energy drinks, reflecting their intended uses. However, these beverages’ high sugar content and calorie loads raise health concerns. Proper labeling, public awareness, and responsible marketing are essential to guide safe consumption practices in Egypt.

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How to Write a Research Paper: the LEAP approach (+cheat sheet)

In this article I will show you how to write a research paper using the four LEAP writing steps. The LEAP academic writing approach is a step-by-step method for turning research results into a published paper .

The LEAP writing approach has been the cornerstone of the 70 + research papers that I have authored and the 3700+ citations these paper have accumulated within 9 years since the completion of my PhD. I hope the LEAP approach will help you just as much as it has helped me to make an real, tangible impact with my research.

What is the LEAP research paper writing approach?

I designed the LEAP writing approach not only for merely writing the papers. My goal with the writing system was to show young scientists how to first think about research results and then how to efficiently write each section of the research paper.

In other words, you will see how to write a research paper by first analyzing the results and then building a logical, persuasive arguments. In this way, instead of being afraid of writing research paper, you will be able to rely on the paper writing process to help you with what is the most demanding task in getting published – thinking.

The four research paper writing steps according to the LEAP approach:

I will show each of these steps in detail. And you will be able to download the LEAP cheat sheet for using with every paper you write.

But before I tell you how to efficiently write a research paper, I want to show you what is the problem with the way scientists typically write a research paper and why the LEAP approach is more efficient.

How scientists typically write a research paper (and why it isn’t efficient)

Writing a research paper can be tough, especially for a young scientist. Your reasoning needs to be persuasive and thorough enough to convince readers of your arguments. The description has to be derived from research evidence, from prior art, and from your own judgment. This is a tough feat to accomplish.

The figure below shows the sequence of the different parts of a typical research paper. Depending on the scientific journal, some sections might be merged or nonexistent, but the general outline of a research paper will remain very similar.

Here is the problem: Most people make the mistake of writing in this same sequence.

While the structure of scientific articles is designed to help the reader follow the research, it does little to help the scientist write the paper. This is because the layout of research articles starts with the broad (introduction) and narrows down to the specifics (results). See in the figure below how the research paper is structured in terms of the breath of information that each section entails.

How to write a research paper according to the LEAP approach

For a scientist, it is much easier to start writing a research paper with laying out the facts in the narrow sections (i.e. results), step back to describe them (i.e. write the discussion), and step back again to explain the broader picture in the introduction.

For example, it might feel intimidating to start writing a research paper by explaining your research’s global significance in the introduction, while it is easy to plot the figures in the results. When plotting the results, there is not much room for wiggle: the results are what they are.

Starting to write a research papers from the results is also more fun because you finally get to see and understand the complete picture of the research that you have worked on.

Most importantly, following the LEAP approach will help you first make sense of the results yourself and then clearly communicate them to the readers. That is because the sequence of writing allows you to slowly understand the meaning of the results and then develop arguments for presenting to your readers.

I have personally been able to write and submit a research article in three short days using this method.

Step 1: Lay Out the Facts

You have worked long hours on a research project that has produced results and are no doubt curious to determine what they exactly mean. There is no better way to do this than by preparing figures, graphics and tables. This is what the first LEAP step is focused on – diving into the results.

How to p repare charts and tables for a research paper

Your first task is to try out different ways of visually demonstrating the research results. In many fields, the central items of a journal paper will be charts that are based on the data generated during research. In other fields, these might be conceptual diagrams, microscopy images, schematics and a number of other types of scientific graphics which should visually communicate the research study and its results to the readers. If you have reasonably small number of data points, data tables might be useful as well.

Tips for preparing charts and tables

• Try multiple chart types but in the finished paper only use the one that best conveys the message you want to present to the readers
• Follow the eight chart design progressions for selecting and refining a data chart for your paper: https://peerrecognized.com/chart-progressions
• Prepare scientific graphics and visualizations for your paper using the scientific graphic design cheat sheet: https://peerrecognized.com/tools-for-creating-scientific-illustrations/

How to describe the results of your research

Now that you have your data charts, graphics and tables laid out in front of you – describe what you see in them. Seek to answer the question: What have I found?  Your statements should progress in a logical sequence and be backed by the visual information. Since, at this point, you are simply explaining what everyone should be able to see for themselves, you can use a declarative tone: The figure X demonstrates that…

Tips for describing the research results :

• Answer the question: “ What have I found? “
• Use declarative tone since you are simply describing observations

Step 2: Explain the results

The core aspect of your research paper is not actually the results; it is the explanation of their meaning. In the second LEAP step, you will do some heavy lifting by guiding the readers through the results using logic backed by previous scientific research.

How to define the Message of a research paper

To define the central message of your research paper, imagine how you would explain your research to a colleague in 20 seconds . If you succeed in effectively communicating your paper’s message, a reader should be able to recount your findings in a similarly concise way even a year after reading it. This clarity will increase the chances that someone uses the knowledge you generated, which in turn raises the likelihood of citations to your research paper. 

Tips for defining the paper’s central message :

• Write the paper’s core message in a single sentence or two bullet points
• Write the core message in the header of the research paper manuscript

How to write the Discussion section of a research paper

In the discussion section you have to demonstrate why your research paper is worthy of publishing. In other words, you must now answer the all-important So what? question . How well you do so will ultimately define the success of your research paper.

Here are three steps to get started with writing the discussion section:

• Write bullet points of the things that convey the central message of the research article (these may evolve into subheadings later on).
• Make a list with the arguments or observations that support each idea.
• Finally, expand on each point to make full sentences and paragraphs.

Tips for writing the discussion section:

• What is the meaning of the results?
• Was the hypothesis confirmed?
• Write bullet points that support the core message
• List logical arguments for each bullet point, group them into sections
• Instead of repeating research timeline, use a presentation sequence that best supports your logic
• Convert arguments to full paragraphs; be confident but do not overhype
• Refer to both supportive and contradicting research papers for maximum credibility

How to write the Conclusions of a research paper

Since some readers might just skim through your research paper and turn directly to the conclusions, it is a good idea to make conclusion a standalone piece. In the first few sentences of the conclusions, briefly summarize the methodology and try to avoid using abbreviations (if you do, explain what they mean).

After this introduction, summarize the findings from the discussion section. Either paragraph style or bullet-point style conclusions can be used. I prefer the bullet-point style because it clearly separates the different conclusions and provides an easy-to-digest overview for the casual browser. It also forces me to be more succinct.

Tips for writing the conclusion section :

• Summarize the key findings, starting with the most important one
• Make conclusions standalone (short summary, avoid abbreviations)
• Add an optional take-home message and suggest future research in the last paragraph

How to refine the Objective of a research paper

The objective is a short, clear statement defining the paper’s research goals. It can be included either in the final paragraph of the introduction, or as a separate subsection after the introduction. Avoid writing long paragraphs with in-depth reasoning, references, and explanation of methodology since these belong in other sections. The paper’s objective can often be written in a single crisp sentence.

Tips for writing the objective section :

• The objective should ask the question that is answered by the central message of the research paper
• The research objective should be clear long before writing a paper. At this point, you are simply refining it to make sure it is addressed in the body of the paper.

How to write the Methodology section of your research paper

When writing the methodology section, aim for a depth of explanation that will allow readers to reproduce the study . This means that if you are using a novel method, you will have to describe it thoroughly. If, on the other hand, you applied a standardized method, or used an approach from another paper, it will be enough to briefly describe it with reference to the detailed original source.

Remember to also detail the research population, mention how you ensured representative sampling, and elaborate on what statistical methods you used to analyze the results.

Tips for writing the methodology section :

• Include enough detail to allow reproducing the research
• Provide references if the methods are known
• Create a methodology flow chart to add clarity
• Describe the research population, sampling methodology, statistical methods for result analysis
• Describe what methodology, test methods, materials, and sample groups were used in the research.

Step 3: Advertize the research

Step 3 of the LEAP writing approach is designed to entice the casual browser into reading your research paper. This advertising can be done with an informative title, an intriguing abstract, as well as a thorough explanation of the underlying need for doing the research within the introduction.

How to write the Introduction of a research paper

The introduction section should leave no doubt in the mind of the reader that what you are doing is important and that this work could push scientific knowledge forward. To do this convincingly, you will need to have a good knowledge of what is state-of-the-art in your field. You also need be able to see the bigger picture in order to demonstrate the potential impacts of your research work.

Think of the introduction as a funnel, going from wide to narrow, as shown in the figure below:

• Start with a brief context to explain what do we already know,
• Follow with the motivation for the research study and explain why should we care about it,
• Explain the research gap you are going to bridge within this research paper,
• Describe the approach you will take to solve the problem.

Tips for writing the introduction section :

• Follow the Context – Motivation – Research gap – Approach funnel for writing the introduction
• Explain how others tried and how you plan to solve the research problem
• Do a thorough literature review before writing the introduction
• Start writing the introduction by using your own words, then add references from the literature

How to prepare the Abstract of a research paper

The abstract acts as your paper’s elevator pitch and is therefore best written only after the main text is finished. In this one short paragraph you must convince someone to take on the time-consuming task of reading your whole research article. So, make the paper easy to read, intriguing, and self-explanatory; avoid jargon and abbreviations.

How to structure the abstract of a research paper:

• The abstract is a single paragraph that follows this structure:
• Problem: why did we research this
• Methodology: typically starts with the words “Here we…” that signal the start of own contribution.
• Results: what we found from the research.
• Conclusions: show why are the findings important

How to compose a research paper Title

The title is the ultimate summary of a research paper. It must therefore entice someone looking for information to click on a link to it and continue reading the article. A title is also used for indexing purposes in scientific databases, so a representative and optimized title will play large role in determining if your research paper appears in search results at all.

Tips for coming up with a research paper title:

• Capture curiosity of potential readers using a clear and descriptive title
• Include broad terms that are often searched
• Add details that uniquely identify the researched subject of your research paper
• Avoid jargon and abbreviations
• Use keywords as title extension (instead of duplicating the words) to increase the chance of appearing in search results

How to prepare Highlights and Graphical Abstract

Highlights are three to five short bullet-point style statements that convey the core findings of the research paper. Notice that the focus is on the findings, not on the process of getting there.

A graphical abstract placed next to the textual abstract visually summarizes the entire research paper in a single, easy-to-follow figure. I show how to create a graphical abstract in my book Research Data Visualization and Scientific Graphics.

Tips for preparing highlights and graphical abstract:

• In highlights show core findings of the research paper (instead of what you did in the study).
• In graphical abstract show take-home message or methodology of the research paper. Learn more about creating a graphical abstract in this article.

Step 4: Prepare for submission

Sometimes it seems that nuclear fusion will stop on the star closest to us (read: the sun will stop to shine) before a submitted manuscript is published in a scientific journal. The publication process routinely takes a long time, and after submitting the manuscript you have very little control over what happens. To increase the chances of a quick publication, you must do your homework before submitting the manuscript. In the fourth LEAP step, you make sure that your research paper is published in the most appropriate journal as quickly and painlessly as possible.

How to select a scientific Journal for your research paper

The best way to find a journal for your research paper is it to review which journals you used while preparing your manuscript. This source listing should provide some assurance that your own research paper, once published, will be among similar articles and, thus, among your field’s trusted sources.

After this initial selection of hand-full of scientific journals, consider the following six parameters for selecting the most appropriate journal for your research paper (read this article to review each step in detail):

• Scope and publishing history
• Ranking and Recognition
• Publishing time
• Acceptance rate
• Content requirements
• Access and Fees

How to select a journal for your research paper:

• Use the six parameters to select the most appropriate scientific journal for your research paper
• Use the following tools for journal selection: https://peerrecognized.com/journals
• Follow the journal’s “Authors guide” formatting requirements

How to Edit you manuscript

No one can write a finished research paper on their first attempt. Before submitting, make sure to take a break from your work for a couple of days, or even weeks. Try not to think about the manuscript during this time. Once it has faded from your memory, it is time to return and edit. The pause will allow you to read the manuscript from a fresh perspective and make edits as necessary.

I have summarized the most useful research paper editing tools in this article.

Tips for editing a research paper:

• Take time away from the research paper to forget about it; then returning to edit,
• Start by editing the content: structure, headings, paragraphs, logic, figures
• Continue by editing the grammar and language; perform a thorough language check using academic writing tools
• Read the entire paper out loud and correct what sounds weird

How to write a compelling Cover Letter for your paper

Begin the cover letter by stating the paper’s title and the type of paper you are submitting (review paper, research paper, short communication). Next, concisely explain why your study was performed, what was done, and what the key findings are. State why the results are important and what impact they might have in the field. Make sure you mention how your approach and findings relate to the scope of the journal in order to show why the article would be of interest to the journal’s readers.

I wrote a separate article that explains what to include in a cover letter here. You can also download a cover letter template from the article.

Tips for writing a cover letter:

• Explain how the findings of your research relate to journal’s scope
• Tell what impact the research results will have
• Show why the research paper will interest the journal’s audience
• Add any legal statements as required in journal’s guide for authors

How to Answer the Reviewers

Reviewers will often ask for new experiments, extended discussion, additional details on the experimental setup, and so forth. In principle, your primary winning tactic will be to agree with the reviewers and follow their suggestions whenever possible. After all, you must earn their blessing in order to get your paper published.

Be sure to answer each review query and stick to the point. In the response to the reviewers document write exactly where in the paper you have made any changes. In the paper itself, highlight the changes using a different color. This way the reviewers are less likely to re-read the entire article and suggest new edits.

In cases when you don’t agree with the reviewers, it makes sense to answer more thoroughly. Reviewers are scientifically minded people and so, with enough logical and supported argument, they will eventually be willing to see things your way.

Tips for answering the reviewers:

• Agree with most review comments, but if you don’t, thoroughly explain why
• Highlight changes in the manuscript
• Do not take the comments personally and cool down before answering

The LEAP research paper writing cheat sheet

Imagine that you are back in grad school and preparing to take an exam on the topic: “How to write a research paper”. As an exemplary student, you would, most naturally, create a cheat sheet summarizing the subject… Well, I did it for you.

This one-page summary of the LEAP research paper writing technique will remind you of the key research paper writing steps. Print it out and stick it to a wall in your office so that you can review it whenever you are writing a new research paper.

Now that we have gone through the four LEAP research paper writing steps, I hope you have a good idea of how to write a research paper. It can be an enjoyable process and once you get the hang of it, the four LEAP writing steps should even help you think about and interpret the research results. This process should enable you to write a well-structured, concise, and compelling research paper.

Have fund with writing your next research paper. I hope it will turn out great!

Learn writing papers that get cited

The LEAP writing approach is a blueprint for writing research papers. But to be efficient and write papers that get cited, you need more than that.

My name is Martins Zaumanis and in my interactive course Research Paper Writing Masterclass I will show you how to  visualize  your research results,  frame a message  that convinces your readers, and write  each section  of the paper. Step-by-step.

And of course – you will learn to respond the infamous  Reviewer No.2.

Hey! My name is Martins Zaumanis and I am a materials scientist in Switzerland ( Google Scholar ). As the first person in my family with a PhD, I have first-hand experience of the challenges starting scientists face in academia. With this blog, I want to help young researchers succeed in academia. I call the blog “Peer Recognized”, because peer recognition is what lifts academic careers and pushes science forward.

Besides this blog, I have written the Peer Recognized book series and created the Peer Recognized Academy offering interactive online courses.

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• How to write a research paper

Last updated

11 January 2024

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With proper planning, knowledge, and framework, completing a research paper can be a fulfilling and exciting experience. 

Though it might initially sound slightly intimidating, this guide will help you embrace the challenge. 

By documenting your findings, you can inspire others and make a difference in your field. Here's how you can make your research paper unique and comprehensive.

• What is a research paper?

Research papers allow you to demonstrate your knowledge and understanding of a particular topic. These papers are usually lengthier and more detailed than typical essays, requiring deeper insight into the chosen topic.

To write a research paper, you must first choose a topic that interests you and is relevant to the field of study. Once you’ve selected your topic, gathering as many relevant resources as possible, including books, scholarly articles, credible websites, and other academic materials, is essential. You must then read and analyze these sources, summarizing their key points and identifying gaps in the current research.

You can formulate your ideas and opinions once you thoroughly understand the existing research. To get there might involve conducting original research, gathering data, or analyzing existing data sets. It could also involve presenting an original argument or interpretation of the existing research.

Writing a successful research paper involves presenting your findings clearly and engagingly, which might involve using charts, graphs, or other visual aids to present your data and using concise language to explain your findings. You must also ensure your paper adheres to relevant academic formatting guidelines, including proper citations and references.

Overall, writing a research paper requires a significant amount of time, effort, and attention to detail. However, it is also an enriching experience that allows you to delve deeply into a subject that interests you and contribute to the existing body of knowledge in your chosen field.

• How long should a research paper be?

Research papers are deep dives into a topic. Therefore, they tend to be longer pieces of work than essays or opinion pieces. 

However, a suitable length depends on the complexity of the topic and your level of expertise. For instance, are you a first-year college student or an experienced professional? 

Also, remember that the best research papers provide valuable information for the benefit of others. Therefore, the quality of information matters most, not necessarily the length. Being concise is valuable.

Following these best practice steps will help keep your process simple and productive:

1. Gaining a deep understanding of any expectations

Before diving into your intended topic or beginning the research phase, take some time to orient yourself. Suppose there’s a specific topic assigned to you. In that case, it’s essential to deeply understand the question and organize your planning and approach in response. Pay attention to the key requirements and ensure you align your writing accordingly. 

This preparation step entails

Deeply understanding the task or assignment

Being clear about the expected format and length

Familiarizing yourself with the citation and referencing requirements 

Understanding any defined limits for your research contribution

Where applicable, speaking to your professor or research supervisor for further clarification

2. Choose your research topic

Select a research topic that aligns with both your interests and available resources. Ideally, focus on a field where you possess significant experience and analytical skills. In crafting your research paper, it's crucial to go beyond summarizing existing data and contribute fresh insights to the chosen area.

Consider narrowing your focus to a specific aspect of the topic. For example, if exploring the link between technology and mental health, delve into how social media use during the pandemic impacts the well-being of college students. Conducting interviews and surveys with students could provide firsthand data and unique perspectives, adding substantial value to the existing knowledge.

When finalizing your topic, adhere to legal and ethical norms in the relevant area (this ensures the integrity of your research, protects participants' rights, upholds intellectual property standards, and ensures transparency and accountability). Following these principles not only maintains the credibility of your work but also builds trust within your academic or professional community.

For instance, in writing about medical research, consider legal and ethical norms , including patient confidentiality laws and informed consent requirements. Similarly, if analyzing user data on social media platforms, be mindful of data privacy regulations, ensuring compliance with laws governing personal information collection and use. Aligning with legal and ethical standards not only avoids potential issues but also underscores the responsible conduct of your research.

3. Gather preliminary research

Once you’ve landed on your topic, it’s time to explore it further. You’ll want to discover more about available resources and existing research relevant to your assignment at this stage. 

This exploratory phase is vital as you may discover issues with your original idea or realize you have insufficient resources to explore the topic effectively. This key bit of groundwork allows you to redirect your research topic in a different, more feasible, or more relevant direction if necessary. 

Spending ample time at this stage ensures you gather everything you need, learn as much as you can about the topic, and discover gaps where the topic has yet to be sufficiently covered, offering an opportunity to research it further. 

4. Define your research question

To produce a well-structured and focused paper, it is imperative to formulate a clear and precise research question that will guide your work. Your research question must be informed by the existing literature and tailored to the scope and objectives of your project. By refining your focus, you can produce a thoughtful and engaging paper that effectively communicates your ideas to your readers.

5. Write a thesis statement

A thesis statement is a one-to-two-sentence summary of your research paper's main argument or direction. It serves as an overall guide to summarize the overall intent of the research paper for you and anyone wanting to know more about the research.

A strong thesis statement is:

Concise and clear: Explain your case in simple sentences (avoid covering multiple ideas). It might help to think of this section as an elevator pitch.

Specific: Ensure that there is no ambiguity in your statement and that your summary covers the points argued in the paper.

Debatable: A thesis statement puts forward a specific argument––it is not merely a statement but a debatable point that can be analyzed and discussed.

Here are three thesis statement examples from different disciplines:

Psychology thesis example: "We're studying adults aged 25-40 to see if taking short breaks for mindfulness can help with stress. Our goal is to find practical ways to manage anxiety better."

Environmental science thesis example: "This research paper looks into how having more city parks might make the air cleaner and keep people healthier. I want to find out if more green spaces means breathing fewer carcinogens in big cities."

UX research thesis example: "This study focuses on improving mobile banking for older adults using ethnographic research, eye-tracking analysis, and interactive prototyping. We investigate the usefulness of eye-tracking analysis with older individuals, aiming to spark debate and offer fresh perspectives on UX design and digital inclusivity for the aging population."

6. Conduct in-depth research

A research paper doesn’t just include research that you’ve uncovered from other papers and studies but your fresh insights, too. You will seek to become an expert on your topic––understanding the nuances in the current leading theories. You will analyze existing research and add your thinking and discoveries.  It's crucial to conduct well-designed research that is rigorous, robust, and based on reliable sources. Suppose a research paper lacks evidence or is biased. In that case, it won't benefit the academic community or the general public. Therefore, examining the topic thoroughly and furthering its understanding through high-quality research is essential. That usually means conducting new research. Depending on the area under investigation, you may conduct surveys, interviews, diary studies , or observational research to uncover new insights or bolster current claims.

7. Determine supporting evidence

Not every piece of research you’ve discovered will be relevant to your research paper. It’s important to categorize the most meaningful evidence to include alongside your discoveries. It's important to include evidence that doesn't support your claims to avoid exclusion bias and ensure a fair research paper.

8. Write a research paper outline

Before diving in and writing the whole paper, start with an outline. It will help you to see if more research is needed, and it will provide a framework by which to write a more compelling paper. Your supervisor may even request an outline to approve before beginning to write the first draft of the full paper. An outline will include your topic, thesis statement, key headings, short summaries of the research, and your arguments.

9. Write your first draft

Once you feel confident about your outline and sources, it’s time to write your first draft. While penning a long piece of content can be intimidating, if you’ve laid the groundwork, you will have a structure to help you move steadily through each section. To keep up motivation and inspiration, it’s often best to keep the pace quick. Stopping for long periods can interrupt your flow and make jumping back in harder than writing when things are fresh in your mind.

10. Cite your sources correctly

It's always a good practice to give credit where it's due, and the same goes for citing any works that have influenced your paper. Building your arguments on credible references adds value and authenticity to your research. In the formatting guidelines section, you’ll find an overview of different citation styles (MLA, CMOS, or APA), which will help you meet any publishing or academic requirements and strengthen your paper's credibility. It is essential to follow the guidelines provided by your school or the publication you are submitting to ensure the accuracy and relevance of your citations.

11. Ensure your work is original

It is crucial to ensure the originality of your paper, as plagiarism can lead to serious consequences. To avoid plagiarism, you should use proper paraphrasing and quoting techniques. Paraphrasing is rewriting a text in your own words while maintaining the original meaning. Quoting involves directly citing the source. Giving credit to the original author or source is essential whenever you borrow their ideas or words. You can also use plagiarism detection tools such as Scribbr or Grammarly to check the originality of your paper. These tools compare your draft writing to a vast database of online sources. If you find any accidental plagiarism, you should correct it immediately by rephrasing or citing the source.

12. Revise, edit, and proofread

One of the essential qualities of excellent writers is their ability to understand the importance of editing and proofreading. Even though it's tempting to call it a day once you've finished your writing, editing your work can significantly improve its quality. It's natural to overlook the weaker areas when you've just finished writing a paper. Therefore, it's best to take a break of a day or two, or even up to a week, to refresh your mind. This way, you can return to your work with a new perspective. After some breathing room, you can spot any inconsistencies, spelling and grammar errors, typos, or missing citations and correct them. 

• The best research paper format 

The format of your research paper should align with the requirements set forth by your college, school, or target publication. 

There is no one “best” format, per se. Depending on the stated requirements, you may need to include the following elements:

Title page: The title page of a research paper typically includes the title, author's name, and institutional affiliation and may include additional information such as a course name or instructor's name. 

Table of contents: Include a table of contents to make it easy for readers to find specific sections of your paper.

Abstract: The abstract is a summary of the purpose of the paper.

Methods : In this section, describe the research methods used. This may include collecting data , conducting interviews, or doing field research .

Results: Summarize the conclusions you drew from your research in this section.

Discussion: In this section, discuss the implications of your research . Be sure to mention any significant limitations to your approach and suggest areas for further research.

Tables, charts, and illustrations: Use tables, charts, and illustrations to help convey your research findings and make them easier to understand.

Works cited or reference page: Include a works cited or reference page to give credit to the sources that you used to conduct your research.

Bibliography: Provide a list of all the sources you consulted while conducting your research.

Dedication and acknowledgments : Optionally, you may include a dedication and acknowledgments section to thank individuals who helped you with your research.

• General style and formatting guidelines

Formatting your research paper means you can submit it to your college, journal, or other publications in compliance with their criteria.

Research papers tend to follow the American Psychological Association (APA), Modern Language Association (MLA), or Chicago Manual of Style (CMOS) guidelines.

Here’s how each style guide is typically used:

Chicago Manual of Style (CMOS):

CMOS is a versatile style guide used for various types of writing. It's known for its flexibility and use in the humanities. CMOS provides guidelines for citations, formatting, and overall writing style. It allows for both footnotes and in-text citations, giving writers options based on their preferences or publication requirements.

American Psychological Association (APA):

APA is common in the social sciences. It’s hailed for its clarity and emphasis on precision. It has specific rules for citing sources, creating references, and formatting papers. APA style uses in-text citations with an accompanying reference list. It's designed to convey information efficiently and is widely used in academic and scientific writing.

Modern Language Association (MLA):

MLA is widely used in the humanities, especially literature and language studies. It emphasizes the author-page format for in-text citations and provides guidelines for creating a "Works Cited" page. MLA is known for its focus on the author's name and the literary works cited. It’s frequently used in disciplines that prioritize literary analysis and critical thinking.

To confirm you're using the latest style guide, check the official website or publisher's site for updates, consult academic resources, and verify the guide's publication date. Online platforms and educational resources may also provide summaries and alerts about any revisions or additions to the style guide.

Citing sources

When working on your research paper, it's important to cite the sources you used properly. Your citation style will guide you through this process. Generally, there are three parts to citing sources in your research paper: 

First, provide a brief citation in the body of your essay. This is also known as a parenthetical or in-text citation. 

Second, include a full citation in the Reference list at the end of your paper. Different types of citations include in-text citations, footnotes, and reference lists. 

In-text citations include the author's surname and the date of the citation. 

Footnotes appear at the bottom of each page of your research paper. They may also be summarized within a reference list at the end of the paper. 

A reference list includes all of the research used within the paper at the end of the document. It should include the author, date, paper title, and publisher listed in the order that aligns with your citation style.

10 research paper writing tips:

Following some best practices is essential to writing a research paper that contributes to your field of study and creates a positive impact.

These tactics will help you structure your argument effectively and ensure your work benefits others:

Clear and precise language:  Ensure your language is unambiguous. Use academic language appropriately, but keep it simple. Also, provide clear takeaways for your audience.

Effective idea separation:  Organize the vast amount of information and sources in your paper with paragraphs and titles. Create easily digestible sections for your readers to navigate through.

Compelling intro:  Craft an engaging introduction that captures your reader's interest. Hook your audience and motivate them to continue reading.

Thorough revision and editing:  Take the time to review and edit your paper comprehensively. Use tools like Grammarly to detect and correct small, overlooked errors.

Thesis precision:  Develop a clear and concise thesis statement that guides your paper. Ensure that your thesis aligns with your research's overall purpose and contribution.

Logical flow of ideas:  Maintain a logical progression throughout the paper. Use transitions effectively to connect different sections and maintain coherence.

Critical evaluation of sources:  Evaluate and critically assess the relevance and reliability of your sources. Ensure that your research is based on credible and up-to-date information.

Thematic consistency:  Maintain a consistent theme throughout the paper. Ensure that all sections contribute cohesively to the overall argument.

Relevant supporting evidence:  Provide concise and relevant evidence to support your arguments. Avoid unnecessary details that may distract from the main points.

Embrace counterarguments:  Acknowledge and address opposing views to strengthen your position. Show that you have considered alternative arguments in your field.

7 research tips 

If you want your paper to not only be well-written but also contribute to the progress of human knowledge, consider these tips to take your paper to the next level:

Selecting the appropriate topic: The topic you select should align with your area of expertise, comply with the requirements of your project, and have sufficient resources for a comprehensive investigation.

Use academic databases: Academic databases such as PubMed, Google Scholar, and JSTOR offer a wealth of research papers that can help you discover everything you need to know about your chosen topic.

Critically evaluate sources: It is important not to accept research findings at face value. Instead, it is crucial to critically analyze the information to avoid jumping to conclusions or overlooking important details. A well-written research paper requires a critical analysis with thorough reasoning to support claims.

Diversify your sources: Expand your research horizons by exploring a variety of sources beyond the standard databases. Utilize books, conference proceedings, and interviews to gather diverse perspectives and enrich your understanding of the topic.

Take detailed notes: Detailed note-taking is crucial during research and can help you form the outline and body of your paper.

Stay up on trends: Keep abreast of the latest developments in your field by regularly checking for recent publications. Subscribe to newsletters, follow relevant journals, and attend conferences to stay informed about emerging trends and advancements. 

Engage in peer review: Seek feedback from peers or mentors to ensure the rigor and validity of your research . Peer review helps identify potential weaknesses in your methodology and strengthens the overall credibility of your findings.

• The real-world impact of research papers

Writing a research paper is more than an academic or business exercise. The experience provides an opportunity to explore a subject in-depth, broaden one's understanding, and arrive at meaningful conclusions. With careful planning, dedication, and hard work, writing a research paper can be a fulfilling and enriching experience contributing to advancing knowledge.

How do I publish my research paper? 

Many academics wish to publish their research papers. While challenging, your paper might get traction if it covers new and well-written information. To publish your research paper, find a target publication, thoroughly read their guidelines, format your paper accordingly, and send it to them per their instructions. You may need to include a cover letter, too. After submission, your paper may be peer-reviewed by experts to assess its legitimacy, quality, originality, and methodology. Following review, you will be informed by the publication whether they have accepted or rejected your paper. 

What is a good opening sentence for a research paper? 

Beginning your research paper with a compelling introduction can ensure readers are interested in going further. A relevant quote, a compelling statistic, or a bold argument can start the paper and hook your reader. Remember, though, that the most important aspect of a research paper is the quality of the information––not necessarily your ability to storytell, so ensure anything you write aligns with your goals.

Research paper vs. a research proposal—what’s the difference?

While some may confuse research papers and proposals, they are different documents. 

A research proposal comes before a research paper. It is a detailed document that outlines an intended area of exploration. It includes the research topic, methodology, timeline, sources, and potential conclusions. Research proposals are often required when seeking approval to conduct research. 

A research paper is a summary of research findings. A research paper follows a structured format to present those findings and construct an argument or conclusion.

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How to Write a Research Paper

Use the links below to jump directly to any section of this guide:

Research Paper Fundamentals

How to choose a topic or question, how to create a working hypothesis or thesis, common research paper methodologies, how to gather and organize evidence , how to write an outline for your research paper, how to write a rough draft, how to revise your draft, how to produce a final draft, resources for teachers .

It is not fair to say that no one writes anymore. Just about everyone writes text messages, brief emails, or social media posts every single day. Yet, most people don't have a lot of practice with the formal, organized writing required for a good academic research paper. This guide contains links to a variety of resources that can help demystify the process. Some of these resources are intended for teachers; they contain exercises, activities, and teaching strategies. Other resources are intended for direct use by students who are struggling to write papers, or are looking for tips to make the process go more smoothly.

The resources in this section are designed to help students understand the different types of research papers, the general research process, and how to manage their time. Below, you'll find links from university writing centers, the trusted Purdue Online Writing Lab, and more.

What is an Academic Research Paper?

"Genre and the Research Paper" (Purdue OWL)

There are different types of research papers. Different types of scholarly questions will lend themselves to one format or another. This is a brief introduction to the two main genres of research paper: analytic and argumentative. 

"7 Most Popular Types of Research Papers" (Personal-writer.com)

This resource discusses formats that high school students commonly encounter, such as the compare and contrast essay and the definitional essay. Please note that the inclusion of this link is not an endorsement of this company's paid service.

How to Prepare and Plan Out Writing a Research Paper

Teachers can give their students a step-by-step guide like these to help them understand the different steps of the research paper process. These guides can be combined with the time management tools in the next subsection to help students come up with customized calendars for completing their papers.

"Ten Steps for Writing Research Papers" (American University)  

This resource from American University is a comprehensive guide to the research paper writing process, and includes examples of proper research questions and thesis topics.

"Steps in Writing a Research Paper" (SUNY Empire State College)

This guide breaks the research paper process into 11 steps. Each "step" links to a separate page, which describes the work entailed in completing it.

How to Manage Time Effectively

The links below will help students determine how much time is necessary to complete a paper. If your sources are not available online or at your local library, you'll need to leave extra time for the Interlibrary Loan process. Remember that, even if you do not need to consult secondary sources, you'll still need to leave yourself ample time to organize your thoughts.

"Research Paper Planner: Timeline" (Baylor University)

This interactive resource from Baylor University creates a suggested writing schedule based on how much time a student has to work on the assignment.

"Research Paper Planner" (UCLA)

UCLA's library offers this step-by-step guide to the research paper writing process, which also includes a suggested planning calendar.

There's a reason teachers spend a long time talking about choosing a good topic. Without a good topic and a well-formulated research question, it is almost impossible to write a clear and organized paper. The resources below will help you generate ideas and formulate precise questions.

"How to Select a Research Topic" (Univ. of Michigan-Flint)

This resource is designed for college students who are struggling to come up with an appropriate topic. A student who uses this resource and still feels unsure about his or her topic should consult the course instructor for further personalized assistance.

"25 Interesting Research Paper Topics to Get You Started" (Kibin)

This resource, which is probably most appropriate for high school students, provides a list of specific topics to help get students started. It is broken into subsections, such as "paper topics on local issues."

"Writing a Good Research Question" (Grand Canyon University)

This introduction to research questions includes some embedded videos, as well as links to scholarly articles on research questions. This resource would be most appropriate for teachers who are planning lessons on research paper fundamentals.

"How to Write a Research Question the Right Way" (Kibin)

This student-focused resource provides more detail on writing research questions. The language is accessible, and there are embedded videos and examples of good and bad questions.

It is important to have a rough hypothesis or thesis in mind at the beginning of the research process. People who have a sense of what they want to say will have an easier time sorting through scholarly sources and other information. The key, of course, is not to become too wedded to the draft hypothesis or thesis. Just about every working thesis gets changed during the research process.

CrashCourse Video: "Sociology Research Methods" (YouTube)

Although this video is tailored to sociology students, it is applicable to students in a variety of social science disciplines. This video does a good job demonstrating the connection between the brainstorming that goes into selecting a research question and the formulation of a working hypothesis.

"How to Write a Thesis Statement for an Analytical Essay" (YouTube)

Students writing analytical essays will not develop the same type of working hypothesis as students who are writing research papers in other disciplines. For these students, developing the working thesis may happen as a part of the rough draft (see the relevant section below). 

"Research Hypothesis" (Oakland Univ.)

This resource provides some examples of hypotheses in social science disciplines like Political Science and Criminal Justice. These sample hypotheses may also be useful for students in other soft social sciences and humanities disciplines like History.

When grading a research paper, instructors look for a consistent methodology. This section will help you understand different methodological approaches used in research papers. Students will get the most out of these resources if they use them to help prepare for conversations with teachers or discussions in class.

"Types of Research Designs" (USC)

A "research design," used for complex papers, is related to the paper's method. This resource contains introductions to a variety of popular research designs in the social sciences. Although it is not the most intuitive site to read, the information here is very valuable. 

"Major Research Methods" (YouTube)

Although this video is a bit on the dry side, it provides a comprehensive overview of the major research methodologies in a format that might be more accessible to students who have struggled with textbooks or other written resources.

"Humanities Research Strategies" (USC)

This is a portal where students can learn about four methodological approaches for humanities papers: Historical Methodologies, Textual Criticism, Conceptual Analysis, and the Synoptic method.

"Selected Major Social Science Research Methods: Overview" (National Academies Press)

This appendix from the book  Using Science as Evidence in Public Policy , printed by National Academies Press, introduces some methods used in social science papers.

"Organizing Your Social Sciences Research Paper: 6. The Methodology" (USC)

This resource from the University of Southern California's library contains tips for writing a methodology section in a research paper.

How to Determine the Best Methodology for You

Anyone who is new to writing research papers should be sure to select a method in consultation with their instructor. These resources can be used to help prepare for that discussion. They may also be used on their own by more advanced students.

"Choosing Appropriate Research Methodologies" (Palgrave Study Skills)

This friendly and approachable resource from Palgrave Macmillan can be used by students who are just starting to think about appropriate methodologies.

"How to Choose Your Research Methods" (NFER (UK))

This is another approachable resource students can use to help narrow down the most appropriate methods for their research projects.

The resources in this section introduce the process of gathering scholarly sources and collecting evidence. You'll find a range of material here, from introductory guides to advanced explications best suited to college students. Please consult the LitCharts  How to Do Academic Research guide for a more comprehensive list of resources devoted to finding scholarly literature.

Google Scholar

Students who have access to library websites with detailed research guides should start there, but people who do not have access to those resources can begin their search for secondary literature here.

"Gathering Appropriate Information" (Texas Gateway)

This resource from the Texas Gateway for online resources introduces students to the research process, and contains interactive exercises. The level of complexity is suitable for middle school, high school, and introductory college classrooms.

"An Overview of Quantitative and Qualitative Data Collection Methods" (NSF)

This PDF from the National Science Foundation goes into detail about best practices and pitfalls in data collection across multiple types of methodologies.

"Social Science Methods for Data Collection and Analysis" (Swiss FIT)

This resource is appropriate for advanced undergraduates or teachers looking to create lessons on research design and data collection. It covers techniques for gathering data via interviews, observations, and other methods.

"Collecting Data by In-depth Interviewing" (Leeds Univ.)

This resource contains enough information about conducting interviews to make it useful for teachers who want to create a lesson plan, but is also accessible enough for college juniors or seniors to make use of it on their own.

There is no "one size fits all" outlining technique. Some students might devote all their energy and attention to the outline in order to avoid the paper. Other students may benefit from being made to sit down and organize their thoughts into a lengthy sentence outline. The resources in this section include strategies and templates for multiple types of outlines. 

"Topic vs. Sentence Outlines" (UC Berkeley)

This resource introduces two basic approaches to outlining: the shorter topic-based approach, and the longer, more detailed sentence-based approach. This resource also contains videos on how to develop paper paragraphs from the sentence-based outline.

"Types of Outlines and Samples" (Purdue OWL)

The Purdue Online Writing Lab's guide is a slightly less detailed discussion of different types of outlines. It contains several sample outlines.

"Writing An Outline" (Austin C.C.)

This resource from a community college contains sample outlines from an American history class that students can use as models.

"How to Structure an Outline for a College Paper" (YouTube)

This brief (sub-2 minute) video from the ExpertVillage YouTube channel provides a model of outline writing for students who are struggling with the idea.

"Outlining" (Harvard)

This is a good resource to consult after completing a draft outline. It offers suggestions for making sure your outline avoids things like unnecessary repetition.

As with outlines, rough drafts can take on many different forms. These resources introduce teachers and students to the various approaches to writing a rough draft. This section also includes resources that will help you cite your sources appropriately according to the MLA, Chicago, and APA style manuals.

"Creating a Rough Draft for a Research Paper" (Univ. of Minnesota)

This resource is useful for teachers in particular, as it provides some suggested exercises to help students with writing a basic rough draft. 

Rough Draft Assignment (Duke of Definition)

This sample assignment, with a brief list of tips, was developed by a high school teacher who runs a very successful and well-reviewed page of educational resources.

"Creating the First Draft of Your Research Paper" (Concordia Univ.)

This resource will be helpful for perfectionists or procrastinators, as it opens by discussing the problem of avoiding writing. It also provides a short list of suggestions meant to get students writing.

Using Proper Citations

There is no such thing as a rough draft of a scholarly citation. These links to the three major citation guides will ensure that your citations follow the correct format. Please consult the LitCharts How to Cite Your Sources guide for more resources.

Chicago Manual of Style Citation Guide

Some call  The Chicago Manual of Style , which was first published in 1906, "the editors' Bible." The manual is now in its 17th edition, and is popular in the social sciences, historical journals, and some other fields in the humanities.

APA Citation Guide

According to the American Psychological Association, this guide was developed to aid reading comprehension, clarity of communication, and to reduce bias in language in the social and behavioral sciences. Its first full edition was published in 1952, and it is now in its sixth edition.

MLA Citation Guide

The Modern Language Association style is used most commonly within the liberal arts and humanities. The  MLA Style Manual and Guide to Scholarly Publishing  was first published in 1985 and (as of 2008) is in its third edition.

Any professional scholar will tell you that the best research papers are made in the revision stage. No matter how strong your research question or working thesis, it is not possible to write a truly outstanding paper without devoting energy to revision. These resources provide examples of revision exercises for the classroom, as well as tips for students working independently.

"The Art of Revision" (Univ. of Arizona)

This resource provides a wealth of information and suggestions for both students and teachers. There is a list of suggested exercises that teachers might use in class, along with a revision checklist that is useful for teachers and students alike.

"Script for Workshop on Revision" (Vanderbilt University)

Vanderbilt's guide for leading a 50-minute revision workshop can serve as a model for teachers who wish to guide students through the revision process during classtime. 

"Revising Your Paper" (Univ. of Washington)

This detailed handout was designed for students who are beginning the revision process. It discusses different approaches and methods for revision, and also includes a detailed list of things students should look for while they revise.

"Revising Drafts" (UNC Writing Center)

This resource is designed for students and suggests things to look for during the revision process. It provides steps for the process and has a FAQ for students who have questions about why it is important to revise.

Conferencing with Writing Tutors and Instructors

No writer is so good that he or she can't benefit from meeting with instructors or peer tutors. These resources from university writing, learning, and communication centers provide suggestions for how to get the most out of these one-on-one meetings.

"Getting Feedback" (UNC Writing Center)

This very helpful resource talks about how to ask for feedback during the entire writing process. It contains possible questions that students might ask when developing an outline, during the revision process, and after the final draft has been graded.

"Prepare for Your Tutoring Session" (Otis College of Art and Design)

This guide from a university's student learning center contains a lot of helpful tips for getting the most out of working with a writing tutor.

"The Importance of Asking Your Professor" (Univ. of Waterloo)

This article from the university's Writing and Communication Centre's blog contains some suggestions for how and when to get help from professors and Teaching Assistants.

Once you've revised your first draft, you're well on your way to handing in a polished paper. These resources—each of them produced by writing professionals at colleges and universities—outline the steps required in order to produce a final draft. You'll find proofreading tips and checklists in text and video form.

"Developing a Final Draft of a Research Paper" (Univ. of Minnesota)

While this resource contains suggestions for revision, it also features a couple of helpful checklists for the last stages of completing a final draft.

Basic Final Draft Tips and Checklist (Univ. of Maryland-University College)

This short and accessible resource, part of UMUC's very thorough online guide to writing and research, contains a very basic checklist for students who are getting ready to turn in their final drafts.

Final Draft Checklist (Everett C.C.)

This is another accessible final draft checklist, appropriate for both high school and college students. It suggests reading your essay aloud at least once.

"How to Proofread Your Final Draft" (YouTube)

This video (approximately 5 minutes), produced by Eastern Washington University, gives students tips on proofreading final drafts.

"Proofreading Tips" (Georgia Southern-Armstrong)

This guide will help students learn how to spot common errors in their papers. It suggests focusing on content and editing for grammar and mechanics.

This final set of resources is intended specifically for high school and college instructors. It provides links to unit plans and classroom exercises that can help improve students' research and writing skills. You'll find resources that give an overview of the process, along with activities that focus on how to begin and how to carry out research. 

"Research Paper Complete Resources Pack" (Teachers Pay Teachers)

This packet of assignments, rubrics, and other resources is designed for high school students. The resources in this packet are aligned to Common Core standards.

"Research Paper—Complete Unit" (Teachers Pay Teachers)

This packet of assignments, notes, PowerPoints, and other resources has a 4/4 rating with over 700 ratings. It is designed for high school teachers, but might also be useful to college instructors who work with freshmen.

"Teaching Students to Write Good Papers" (Yale)

This resource from Yale's Center for Teaching and Learning is designed for college instructors, and it includes links to appropriate activities and exercises.

"Research Paper Writing: An Overview" (CUNY Brooklyn)

CUNY Brooklyn offers this complete lesson plan for introducing students to research papers. It includes an accompanying set of PowerPoint slides.

"Lesson Plan: How to Begin Writing a Research Paper" (San Jose State Univ.)

This lesson plan is designed for students in the health sciences, so teachers will have to modify it for their own needs. It includes a breakdown of the brainstorming, topic selection, and research question process. 

"Quantitative Techniques for Social Science Research" (Univ. of Pittsburgh)

This is a set of PowerPoint slides that can be used to introduce students to a variety of quantitative methods used in the social sciences.

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Writing your research paper

How to start your research paper [step-by-step guide]

All research papers have pretty much the same structure. If you can write one type of research paper, you can write another. Learn the steps to start and complete your research paper in our guide.

How to write a problem statement

What is a problem statement and how do you write one? This guide answers all your questions and includes an example of a problem statement.

How to write a research paper outline

Structuring the outline of your research paper early on is important. Read on to learn how to structure a research paper outline and to see examples, including an outline template.

How to write a research proposal

What is a research proposal and what should you use it for? This step-by-step guide teaches you how to structure and write a research proposal.

How to write an abstract

Not sure how to write an abstract for your paper? Clear your doubts with this guide, follow our tips, and start writing your abstract!

What are the different types of research papers?

Learn all you need to know about research papers, what differentiates a research paper from a thesis, and what types of research papers there are.

What is a research paper?

Are you confused about what a research paper actually is and what differentiates it from a thesis? Clarify it once and for all with our guide.

What is an appendix in a paper

Not sure what an appendix in a paper is? This guides defines what an appendix is and how to format one.

What is the abstract of a paper?

Not sure what the abstract of a paper is? Learn the definition of an abstract and how to format one in this guide with resources.

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• Research paper

How to Write a Research Paper | A Beginner's Guide

A research paper is a piece of academic writing that provides analysis, interpretation, and argument based on in-depth independent research.

Research papers are similar to academic essays , but they are usually longer and more detailed assignments, designed to assess not only your writing skills but also your skills in scholarly research. Writing a research paper requires you to demonstrate a strong knowledge of your topic, engage with a variety of sources, and make an original contribution to the debate.

This step-by-step guide takes you through the entire writing process, from understanding your assignment to proofreading your final draft.

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Table of contents

Understand the assignment, choose a research paper topic, conduct preliminary research, develop a thesis statement, create a research paper outline, write a first draft of the research paper, write the introduction, write a compelling body of text, write the conclusion, the second draft, the revision process, research paper checklist, free lecture slides.

Completing a research paper successfully means accomplishing the specific tasks set out for you. Before you start, make sure you thoroughly understanding the assignment task sheet:

• Read it carefully, looking for anything confusing you might need to clarify with your professor.
• Identify the assignment goal, deadline, length specifications, formatting, and submission method.
• Make a bulleted list of the key points, then go back and cross completed items off as you’re writing.

Carefully consider your timeframe and word limit: be realistic, and plan enough time to research, write, and edit.

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There are many ways to generate an idea for a research paper, from brainstorming with pen and paper to talking it through with a fellow student or professor.

You can try free writing, which involves taking a broad topic and writing continuously for two or three minutes to identify absolutely anything relevant that could be interesting.

You can also gain inspiration from other research. The discussion or recommendations sections of research papers often include ideas for other specific topics that require further examination.

Once you have a broad subject area, narrow it down to choose a topic that interests you, m eets the criteria of your assignment, and i s possible to research. Aim for ideas that are both original and specific:

• A paper following the chronology of World War II would not be original or specific enough.
• A paper on the experience of Danish citizens living close to the German border during World War II would be specific and could be original enough.

Note any discussions that seem important to the topic, and try to find an issue that you can focus your paper around. Use a variety of sources , including journals, books, and reliable websites, to ensure you do not miss anything glaring.

Do not only verify the ideas you have in mind, but look for sources that contradict your point of view.

• Is there anything people seem to overlook in the sources you research?
• Are there any heated debates you can address?
• Do you have a unique take on your topic?
• Have there been some recent developments that build on the extant research?

In this stage, you might find it helpful to formulate some research questions to help guide you. To write research questions, try to finish the following sentence: “I want to know how/what/why…”

A thesis statement is a statement of your central argument — it establishes the purpose and position of your paper. If you started with a research question, the thesis statement should answer it. It should also show what evidence and reasoning you’ll use to support that answer.

The thesis statement should be concise, contentious, and coherent. That means it should briefly summarize your argument in a sentence or two, make a claim that requires further evidence or analysis, and make a coherent point that relates to every part of the paper.

You will probably revise and refine the thesis statement as you do more research, but it can serve as a guide throughout the writing process. Every paragraph should aim to support and develop this central claim.

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A research paper outline is essentially a list of the key topics, arguments, and evidence you want to include, divided into sections with headings so that you know roughly what the paper will look like before you start writing.

A structure outline can help make the writing process much more efficient, so it’s worth dedicating some time to create one.

Your first draft won’t be perfect — you can polish later on. Your priorities at this stage are as follows:

• Maintaining forward momentum — write now, perfect later.
• Paying attention to clear organization and logical ordering of paragraphs and sentences, which will help when you come to the second draft.
• Expressing your ideas as clearly as possible, so you know what you were trying to say when you come back to the text.

You do not need to start by writing the introduction. Begin where it feels most natural for you — some prefer to finish the most difficult sections first, while others choose to start with the easiest part. If you created an outline, use it as a map while you work.

Do not delete large sections of text. If you begin to dislike something you have written or find it doesn’t quite fit, move it to a different document, but don’t lose it completely — you never know if it might come in useful later.

Paragraph structure

Paragraphs are the basic building blocks of research papers. Each one should focus on a single claim or idea that helps to establish the overall argument or purpose of the paper.

Example paragraph

George Orwell’s 1946 essay “Politics and the English Language” has had an enduring impact on thought about the relationship between politics and language. This impact is particularly obvious in light of the various critical review articles that have recently referenced the essay. For example, consider Mark Falcoff’s 2009 article in The National Review Online, “The Perversion of Language; or, Orwell Revisited,” in which he analyzes several common words (“activist,” “civil-rights leader,” “diversity,” and more). Falcoff’s close analysis of the ambiguity built into political language intentionally mirrors Orwell’s own point-by-point analysis of the political language of his day. Even 63 years after its publication, Orwell’s essay is emulated by contemporary thinkers.

Citing sources

It’s also important to keep track of citations at this stage to avoid accidental plagiarism . Each time you use a source, make sure to take note of where the information came from.

You can use our free citation generators to automatically create citations and save your reference list as you go.

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The research paper introduction should address three questions: What, why, and how? After finishing the introduction, the reader should know what the paper is about, why it is worth reading, and how you’ll build your arguments.

What? Be specific about the topic of the paper, introduce the background, and define key terms or concepts.

Why? This is the most important, but also the most difficult, part of the introduction. Try to provide brief answers to the following questions: What new material or insight are you offering? What important issues does your essay help define or answer?

How? To let the reader know what to expect from the rest of the paper, the introduction should include a “map” of what will be discussed, briefly presenting the key elements of the paper in chronological order.

The major struggle faced by most writers is how to organize the information presented in the paper, which is one reason an outline is so useful. However, remember that the outline is only a guide and, when writing, you can be flexible with the order in which the information and arguments are presented.

One way to stay on track is to use your thesis statement and topic sentences . Check:

• topic sentences against the thesis statement;
• topic sentences against each other, for similarities and logical ordering;
• and each sentence against the topic sentence of that paragraph.

Be aware of paragraphs that seem to cover the same things. If two paragraphs discuss something similar, they must approach that topic in different ways. Aim to create smooth transitions between sentences, paragraphs, and sections.

The research paper conclusion is designed to help your reader out of the paper’s argument, giving them a sense of finality.

Trace the course of the paper, emphasizing how it all comes together to prove your thesis statement. Give the paper a sense of finality by making sure the reader understands how you’ve settled the issues raised in the introduction.

You might also discuss the more general consequences of the argument, outline what the paper offers to future students of the topic, and suggest any questions the paper’s argument raises but cannot or does not try to answer.

You should not :

• Offer new arguments or essential information
• Take up any more space than necessary
• Begin with stock phrases that signal you are ending the paper (e.g. “In conclusion”)

There are four main considerations when it comes to the second draft.

• Check how your vision of the paper lines up with the first draft and, more importantly, that your paper still answers the assignment.
• Identify any assumptions that might require (more substantial) justification, keeping your reader’s perspective foremost in mind. Remove these points if you cannot substantiate them further.
• Be open to rearranging your ideas. Check whether any sections feel out of place and whether your ideas could be better organized.
• If you find that old ideas do not fit as well as you anticipated, you should cut them out or condense them. You might also find that new and well-suited ideas occurred to you during the writing of the first draft — now is the time to make them part of the paper.

The goal during the revision and proofreading process is to ensure you have completed all the necessary tasks and that the paper is as well-articulated as possible. You can speed up the proofreading process by using the AI proofreader .

Global concerns

• Confirm that your paper completes every task specified in your assignment sheet.
• Check for logical organization and flow of paragraphs.
• Check paragraphs against the introduction and thesis statement.

Fine-grained details

Check the content of each paragraph, making sure that:

• each sentence helps support the topic sentence.
• no unnecessary or irrelevant information is present.
• all technical terms your audience might not know are identified.

Next, think about sentence structure , grammatical errors, and formatting . Check that you have correctly used transition words and phrases to show the connections between your ideas. Look for typos, cut unnecessary words, and check for consistency in aspects such as heading formatting and spellings .

Finally, you need to make sure your paper is correctly formatted according to the rules of the citation style you are using. For example, you might need to include an MLA heading  or create an APA title page .

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Checklist: Research paper

I have followed all instructions in the assignment sheet.

My introduction presents my topic in an engaging way and provides necessary background information.

My introduction presents a clear, focused research problem and/or thesis statement .

My paper is logically organized using paragraphs and (if relevant) section headings .

Each paragraph is clearly focused on one central idea, expressed in a clear topic sentence .

Each paragraph is relevant to my research problem or thesis statement.

I have used appropriate transitions  to clarify the connections between sections, paragraphs, and sentences.

My conclusion provides a concise answer to the research question or emphasizes how the thesis has been supported.

My conclusion shows how my research has contributed to knowledge or understanding of my topic.

My conclusion does not present any new points or information essential to my argument.

I have provided an in-text citation every time I refer to ideas or information from a source.

I have included a reference list at the end of my paper, consistently formatted according to a specific citation style .

I have thoroughly revised my paper and addressed any feedback from my professor or supervisor.

I have followed all formatting guidelines (page numbers, headers, spacing, etc.).

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Home > Hacks How to Write a 10 and 20 page Paper in One Night

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Hacks How to Write a 10 and 20 page Paper in One Night

Updated: June 19, 2024

Published: April 19, 2020

It’s the night before a big paper is due. For whatever reason, you find yourself needing to write an entire research paper in a very short amount of time. While procrastination isn’t ideal, extenuating circumstances may have caused your timeline to get pushed back. So, here you are, looking for how to write a 10-page paper or how to write a 20-page paper in one night.

It goes without saying the best way to write a paper is to give yourself enough time to outline, draft, and edit. Yet, it’s still possible to write in less time. Take heed of these best tips and tricks to organize your thoughts and get your thesis on paper as fast as possible.

Photo by  Adolfo Félix  on  Unsplash

How to prepare before you write, 1. create a schedule to maximize your time.

You’ve likely already spent time panicking. Once you calm yourself of the anxiety of having to finish a 10- or 20-page paper in one night, organize your plan of attack. First, you should designate an area free of distractions so that you can focus. Aside from a few breaks and snacks, it’s best to set up a comfortable place to write. Give yourself some time to outline and find/cite research . Once you know how you’re going to approach the subject, then you can start drafting.

2. Determine your Main Topic

If you’ve been given a prompt, then your topic is clear. However, sometimes you have the freedom to choose what your research will be about. In this case, it’s smartest to choose a topic that you are already knowledgeable about. That way, you will save yourself key time that would have otherwise been spent on research. If you don’t feel strongly about any particular topic, then at least try to pick one that has a lot of information available.

3. Perform Research

Start looking up sources to cite that support your thesis, or main argument. As you research, be sure to take notes. One of the best ways to do this is to use a word processor like Google Docs or Microsoft Word to copy and paste URLs. For each source, it would be best to copy/paste one main sentence that covers its point.

Then, you can write brief notes in your own words that summarize what you have read from that source. While you are performing research, you can start to put together an outline, or the flow of how you will present your ideas broken down by topic and argument.

4. Outline 3-5 subtopics

Once you’ve chosen your topic, then try to pull 3-5 subtopics from it. Each sub-topic should be juicy enough to be able to write a lot about it. The subtopics are your supporting paragraphs which fill the body of the research paper. They should basically be mini essays within themselves.

Writing in One Night

Writing a long research paper in one night isn’t ideal, but it is doable. Some of the best ways to get it done is to follow these 5 tips:

1. Plan and Outline

Take those few extra moments to plan and outline your paper. While it may feel like a waste of valuable time, it is going to help you stay on track. When you have an outline and you get to the middle of your paper, you won’t feel lost as to how to continue. An outline will be useful to you like a map is on a journey.

2. Use Specialized Search

Take advantage of search tools that are designed for scholars. For example, a few of these include: Google Scholar and Elsevier .

3. Leverage Tools

There are citation management tools that will help you find sources for your topic. Mendeley is just one of them. You can type parts of your paper into the tool and find quotes of value. Be sure to cite everything you use to avoid plagiarism .

4. Proofread and Edit

Once you complete writing 10 to 20 pages, you may feel like throwing in the towel and going to sleep for a few hours. However, it is crucial to power through and proofread your paper. If you have anyone available who can read your paper over, that would be best because it’s hard to catch mistakes when you’ve been looking at the same thing for so long. But, if no one is available, try to read your paper back to yourself out loud. This way, you may be able to catch typos better.

5. Check Formatting

Every research paper needs to adhere to a particular format guideline. Whether it’s APA, MLA, or another standard formatting practice, be sure to double check that your layout adheres to the guidelines.

Photo by  Christin Hume  on  Unsplash

When to start writing.

If you have yet to find yourself trying to write a paper at the last minute and all the notes above are scaring you out of procrastination, then that’s a good start! Perhaps you were recently assigned a research paper. In this case, the best way to tackle the project is to do the following:

Start Early

Get started right away. Even if it means just performing early research or writing an outline, starting early is going to save you from having to write a paper in one night down the line. When you start early, you benefit greatly because you can: leverage peers for ideas, take the necessary time to edit and rewrite, and you lower your risk of picking a topic with too little information and having to change topics at the last minute.

Writing in Stages

Starting early also affords you the opportunity to write in stages. You can think of writing as a cycle when you write in stages. First, you can create your outline. Then, you can write the introduction, edit it, and rewrite anything you may need to before moving on to the next piece (or the first body paragraph, in this case).

Use a Timeline

Create a timeline for your writing in stages. If you start four weeks in advance, for example, you have time to do all of the following:

• Fully understand the assignment and ask any questions
• Start to read and document sources
• Create notecards and cite books for sources
• Write a summary of what you’ve discovered so far that will be used in some of your paper
• Create 3-5 subtopics and outline points you want to explore
• Look for more sources on your subtopics
• Start writing summaries on each subtopic
• Write some analysis of your findings
• Start to piece together the research paper based on your notes and outline (almost like completing a puzzle)
• Edit and proofread / ask for feedback

The Writing Process

The actual writing process is a little different for everyone, but this is a general overview for how to write a 20-page paper, or one that is shorter.

• Start with a Thesis: Your thesis is one sentence that clearly and concisely explains what you are going to prove with research.
• Include a Menu Sentence: At the end of your introduction, you will briefly outline your subtopics in what is often referred to as a “menu sentence.” This allows the reader to understand what they can expect to learn about as they continue to read your paper.
• Create a Detailed Introduction: Your introduction should be detailed enough so that someone with little to no knowledge about your subject matter can understand what the paper is about.
• Keep References: Be sure to write your references as you go along so that you basically can create your bibliography in the process of writing. Again, this is where a tool like Mendeley may be useful.
• Write First: Write first and edit later. You want to get all your ideas down on the page before you start judging or editing the writing.
• Save Often: Create the draft on a cloud platform that is automatically saved (i.e. Google Docs in case your computer crashes) or email the work to yourself as you go.

The Breakdown of a 10-Page Paper

Sources to Consider Using

When writing your research paper and finding sources, it’s best to use a mix of sources. This may include:

• Internet: The Internet is filled with limitless possibilities. When you use the Internet, it’s best to find credible and trustworthy sources to avoid using fake news as a source. That’s why tools like Google Scholar can be so helpful.
• Textbooks: It’s more likely than not that you’ll be able to use your class textbook as a source for the research you are conducting.
• Books: Additionally, other books outside of those you read within your class will prove useful in any research paper.

Final Steps: Editing and Formatting

Once you’ve written all your ideas on the page, it’s time to edit. It cannot be stressed enough that editing is pivotal before submission. This is especially true if you’ve been writing under immense pressure.

Writing a 10- or 20-page research paper in one night is not easy, so there are bound to be mistakes and typos. The best way to catch these mistakes is to follow these tips:

• Take a break before you edit so you can come back to the page with somewhat fresh eyes and a clearer head
• Read it out loud to edit and catch mistakes because sometimes your brain will override typos or missing words to make sense of what it is reading
• If possible, ask someone else to look it over
• Consider using footnotes or block quotes
• Format according to how your university asks – MLA or APA, etc.

The Bottom Line

Life throws curveballs your way without warning. Whether you are holding yourself accountable for procrastinating or something out of your control came up, you may find yourself needing to write a big research paper in one night. It’s not the best-case scenario, but with the right tools and tricks up your sleeve, you can surely get it done!

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Tips for writing a research paper in one or two days?

I have one research paper left this semester, and although it's not due till April 16th, I really wanna finish it early, ideally by the end of the month.

I have my topic in mind and have grabbed a few sources to use already, though I have yet to actually start it. I'm just not sure how people manage to write uni papers so quickly. What are some tips for organizing and writing a 1750+ word paper in only a few days?

Thanks in advance!

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How to Write a Research Proposal: (with Examples & Templates)

Table of Contents

Before conducting a study, a research proposal should be created that outlines researchers’ plans and methodology and is submitted to the concerned evaluating organization or person. Creating a research proposal is an important step to ensure that researchers are on track and are moving forward as intended. A research proposal can be defined as a detailed plan or blueprint for the proposed research that you intend to undertake. It provides readers with a snapshot of your project by describing what you will investigate, why it is needed, and how you will conduct the research.  

Your research proposal should aim to explain to the readers why your research is relevant and original, that you understand the context and current scenario in the field, have the appropriate resources to conduct the research, and that the research is feasible given the usual constraints.  

This article will describe in detail the purpose and typical structure of a research proposal , along with examples and templates to help you ace this step in your research journey.  

What is a Research Proposal ?  

A research proposal¹ ,²  can be defined as a formal report that describes your proposed research, its objectives, methodology, implications, and other important details. Research proposals are the framework of your research and are used to obtain approvals or grants to conduct the study from various committees or organizations. Consequently, research proposals should convince readers of your study’s credibility, accuracy, achievability, practicality, and reproducibility.   

With research proposals , researchers usually aim to persuade the readers, funding agencies, educational institutions, and supervisors to approve the proposal. To achieve this, the report should be well structured with the objectives written in clear, understandable language devoid of jargon. A well-organized research proposal conveys to the readers or evaluators that the writer has thought out the research plan meticulously and has the resources to ensure timely completion.  

Purpose of Research Proposals  

A research proposal is a sales pitch and therefore should be detailed enough to convince your readers, who could be supervisors, ethics committees, universities, etc., that what you’re proposing has merit and is feasible . Research proposals can help students discuss their dissertation with their faculty or fulfill course requirements and also help researchers obtain funding. A well-structured proposal instills confidence among readers about your ability to conduct and complete the study as proposed.  

Research proposals can be written for several reasons:³  

• To describe the importance of research in the specific topic  
• Address any potential challenges you may encounter  
• Showcase knowledge in the field and your ability to conduct a study  
• Apply for a role at a research institute  
• Convince a research supervisor or university that your research can satisfy the requirements of a degree program  
• Highlight the importance of your research to organizations that may sponsor your project  
• Identify implications of your project and how it can benefit the audience  

What Goes in a Research Proposal?    

Research proposals should aim to answer the three basic questions—what, why, and how.  

The What question should be answered by describing the specific subject being researched. It should typically include the objectives, the cohort details, and the location or setting.  

The Why question should be answered by describing the existing scenario of the subject, listing unanswered questions, identifying gaps in the existing research, and describing how your study can address these gaps, along with the implications and significance.  

The How question should be answered by describing the proposed research methodology, data analysis tools expected to be used, and other details to describe your proposed methodology.   

Research Proposal Example  

Here is a research proposal sample template (with examples) from the University of Rochester Medical Center. 4 The sections in all research proposals are essentially the same although different terminology and other specific sections may be used depending on the subject.  

Structure of a Research Proposal  

If you want to know how to make a research proposal impactful, include the following components:¹  

1. Introduction  

This section provides a background of the study, including the research topic, what is already known about it and the gaps, and the significance of the proposed research.  

2. Literature review  

This section contains descriptions of all the previous relevant studies pertaining to the research topic. Every study cited should be described in a few sentences, starting with the general studies to the more specific ones. This section builds on the understanding gained by readers in the Introduction section and supports it by citing relevant prior literature, indicating to readers that you have thoroughly researched your subject.  

3. Objectives  

Once the background and gaps in the research topic have been established, authors must now state the aims of the research clearly. Hypotheses should be mentioned here. This section further helps readers understand what your study’s specific goals are.  

4. Research design and methodology  

Here, authors should clearly describe the methods they intend to use to achieve their proposed objectives. Important components of this section include the population and sample size, data collection and analysis methods and duration, statistical analysis software, measures to avoid bias (randomization, blinding), etc.  

5. Ethical considerations  

This refers to the protection of participants’ rights, such as the right to privacy, right to confidentiality, etc. Researchers need to obtain informed consent and institutional review approval by the required authorities and mention this clearly for transparency.  

6. Budget/funding  

Researchers should prepare their budget and include all expected expenditures. An additional allowance for contingencies such as delays should also be factored in.  

7. Appendices  

This section typically includes information that supports the research proposal and may include informed consent forms, questionnaires, participant information, measurement tools, etc.  

8. Citations  

Important Tips for Writing a Research Proposal  

Writing a research proposal begins much before the actual task of writing. Planning the research proposal structure and content is an important stage, which if done efficiently, can help you seamlessly transition into the writing stage. 3,5  

The Planning Stage  

• Manage your time efficiently. Plan to have the draft version ready at least two weeks before your deadline and the final version at least two to three days before the deadline.
• What is the primary objective of your research?  
• Will your research address any existing gap?  
• What is the impact of your proposed research?  
• Do people outside your field find your research applicable in other areas?  
• If your research is unsuccessful, would there still be other useful research outcomes?  

  The Writing Stage  

• Create an outline with main section headings that are typically used.  
• Focus only on writing and getting your points across without worrying about the format of the research proposal , grammar, punctuation, etc. These can be fixed during the subsequent passes. Add details to each section heading you created in the beginning.   
• Ensure your sentences are concise and use plain language. A research proposal usually contains about 2,000 to 4,000 words or four to seven pages.  
• Don’t use too many technical terms and abbreviations assuming that the readers would know them. Define the abbreviations and technical terms.  
• Ensure that the entire content is readable. Avoid using long paragraphs because they affect the continuity in reading. Break them into shorter paragraphs and introduce some white space for readability.  
• Focus on only the major research issues and cite sources accordingly. Don’t include generic information or their sources in the literature review.  
• Proofread your final document to ensure there are no grammatical errors so readers can enjoy a seamless, uninterrupted read.  
• Use academic, scholarly language because it brings formality into a document.  
• Ensure that your title is created using the keywords in the document and is neither too long and specific nor too short and general.  
• Cite all sources appropriately to avoid plagiarism.  
• Make sure that you follow guidelines, if provided. This includes rules as simple as using a specific font or a hyphen or en dash between numerical ranges.  
• Ensure that you’ve answered all questions requested by the evaluating authority.  

Key Takeaways   

Here’s a summary of the main points about research proposals discussed in the previous sections:  

• A research proposal is a document that outlines the details of a proposed study and is created by researchers to submit to evaluators who could be research institutions, universities, faculty, etc.  
• Research proposals are usually about 2,000-4,000 words long, but this depends on the evaluating authority’s guidelines.  
• A good research proposal ensures that you’ve done your background research and assessed the feasibility of the research.  
• Research proposals have the following main sections—introduction, literature review, objectives, methodology, ethical considerations, and budget.  

Frequently Asked Questions  

Q1. How is a research proposal evaluated?  

A1. In general, most evaluators, including universities, broadly use the following criteria to evaluate research proposals . 6  

• Significance —Does the research address any important subject or issue, which may or may not be specific to the evaluator or university?  
• Content and design —Is the proposed methodology appropriate to answer the research question? Are the objectives clear and well aligned with the proposed methodology?  
• Sample size and selection —Is the target population or cohort size clearly mentioned? Is the sampling process used to select participants randomized, appropriate, and free of bias?  
• Timing —Are the proposed data collection dates mentioned clearly? Is the project feasible given the specified resources and timeline?  
• Data management and dissemination —Who will have access to the data? What is the plan for data analysis?  

Q2. What is the difference between the Introduction and Literature Review sections in a research proposal ?  

A2. The Introduction or Background section in a research proposal sets the context of the study by describing the current scenario of the subject and identifying the gaps and need for the research. A Literature Review, on the other hand, provides references to all prior relevant literature to help corroborate the gaps identified and the research need.  

Q3. How long should a research proposal be?  

A3. Research proposal lengths vary with the evaluating authority like universities or committees and also the subject. Here’s a table that lists the typical research proposal lengths for a few universities.  

Q4. What are the common mistakes to avoid in a research proposal ?  

A4. Here are a few common mistakes that you must avoid while writing a research proposal . 7  

• No clear objectives: Objectives should be clear, specific, and measurable for the easy understanding among readers.  
• Incomplete or unconvincing background research: Background research usually includes a review of the current scenario of the particular industry and also a review of the previous literature on the subject. This helps readers understand your reasons for undertaking this research because you identified gaps in the existing research.  
• Overlooking project feasibility: The project scope and estimates should be realistic considering the resources and time available.   
• Neglecting the impact and significance of the study: In a research proposal , readers and evaluators look for the implications or significance of your research and how it contributes to the existing research. This information should always be included.  
• Unstructured format of a research proposal : A well-structured document gives confidence to evaluators that you have read the guidelines carefully and are well organized in your approach, consequently affirming that you will be able to undertake the research as mentioned in your proposal.  
• Ineffective writing style: The language used should be formal and grammatically correct. If required, editors could be consulted, including AI-based tools such as Paperpal , to refine the research proposal structure and language.  

Thus, a research proposal is an essential document that can help you promote your research and secure funds and grants for conducting your research. Consequently, it should be well written in clear language and include all essential details to convince the evaluators of your ability to conduct the research as proposed.  

This article has described all the important components of a research proposal and has also provided tips to improve your writing style. We hope all these tips will help you write a well-structured research proposal to ensure receipt of grants or any other purpose.  

References  

• Sudheesh K, Duggappa DR, Nethra SS. How to write a research proposal? Indian J Anaesth. 2016;60(9):631-634. Accessed July 15, 2024. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5037942/  
• Writing research proposals. Harvard College Office of Undergraduate Research and Fellowships. Harvard University. Accessed July 14, 2024. https://uraf.harvard.edu/apply-opportunities/app-components/essays/research-proposals  
• What is a research proposal? Plus how to write one. Indeed website. Accessed July 17, 2024. https://www.indeed.com/career-advice/career-development/research-proposal  
• Research proposal template. University of Rochester Medical Center. Accessed July 16, 2024. https://www.urmc.rochester.edu/MediaLibraries/URMCMedia/pediatrics/research/documents/Research-proposal-Template.pdf  
• Tips for successful proposal writing. Johns Hopkins University. Accessed July 17, 2024. https://research.jhu.edu/wp-content/uploads/2018/09/Tips-for-Successful-Proposal-Writing.pdf  
• Formal review of research proposals. Cornell University. Accessed July 18, 2024. https://irp.dpb.cornell.edu/surveys/survey-assessment-review-group/research-proposals  
• 7 Mistakes you must avoid in your research proposal. Aveksana (via LinkedIn). Accessed July 17, 2024. https://www.linkedin.com/pulse/7-mistakes-you-must-avoid-your-research-proposal-aveksana-cmtwf/  

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Get accurate academic translations, rewriting support, grammar checks, vocabulary suggestions, and generative AI assistance that delivers human precision at machine speed. Try for free or upgrade to Paperpal Prime starting at US$19 a month to access premium features, including consistency, plagiarism, and 30+ submission readiness checks to help you succeed.  

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How to overcome anxiety over writing papers?

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Alice! Health Promotion. "How to overcome anxiety over writing papers?." Go Ask Alice!, Columbia University, 24 Jun. 2022, https://goaskalice.columbia.edu/answered-questions/how-overcome-anxiety-over-writing-papers. Accessed 30, Jul. 2024.

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Alice! Health Promotion. (2022, June 24). How to overcome anxiety over writing papers?. Go Ask Alice!, https://goaskalice.columbia.edu/answered-questions/how-overcome-anxiety-over-writing-papers.

Dear Alice,

I have terrible anxiety about writing papers. Because of this, I put them off, need to ask for extensions, and then have more anxiety about completing the assignment. In addition, when I start writing, I find it difficult to keep going, especially because I hit what may seem to others as small roadblocks, like uncertainty about citation format. I don’t experience nearly as much stress about other types of work (e.g., studying for and taking exams). What can I do to get over or at least cope reasonably with this fear?

Dear Reader,

Just thinking about writing anxiety made this answer more difficult to compose. You see, writing anxiety and writer’s block are concerns for both students and professionals of all ages and academic levels. In fact, even the most seasoned writers experience anxiety or writer’s block now and then. Fortunately, writing is a complex process that, with practice and patience, may be improved. Read on for some strategies for overcoming the roadblock you’re experiencing.

Writing anxiety comes in multiple forms such as an inability to form an idea, a physical struggle to manifest words on the paper, or a fear of not meeting expectations that hinders your progress. The four main causes of writer’s block include psychological, motivational, cognitive, and behavioral reasons. Psychological causes often include mood or stressors that affect cognitive processing. Motivation-related blocks often arise from a fear of failure. Similarly, those categorized as cognitive causes stem from perfectionism and obsession with details, much like you described in your uncertainty when formatting citations. Lastly, the most common cause of writing anxiety is behavioral changes such as procrastination. Procrastination may lead to a domino effect in which more work doesn’t get done and the pile-up becomes overwhelming. Writer’s block is different for everyone not only in its cause but also in its manifestation and how long it lasts. For some, it may occur for a few minutes and for others it may take decades to overcome, but it’s good to know that it’s possible.

It’s worth noting that more and more research has been dedicated to understanding the psychology behind writer’s block in order to help conquer it. Multiple studies have concluded that writer’s block is most effectively combated by giving the brain a break. This period of time is called the incubation period and could include activities such as going on a walk, playing a word game, or getting a full night’s sleep. When done for an appropriate amount of time, these mental breaks could help writers to think more creatively and find inspiration. Fortunately, writing anxiety is typically a product of a writer’s habits, and habits are changeable! You’ve already made a great first step by identifying a few things that don’t work for you — procrastination and obtaining deadline extensions provide you little or no relief. Now, the next step is to try out or adopt some new habits. To help relieve the anxiety and fear you feel about writing papers, implementing any of the following strategies may be useful:

• Stay on top of your reading assignments and do your best to attend classes — that way you won’t have to cram or teach yourself course material before writing your papers.
• Prior to writing, brainstorm ideas. Create a chart or write down topics of interest to refer back to while writing.
• Follow the guidelines your professor talked about in class or included in a syllabus or grading rubric. If you’re not sure about the guidelines, ask for clarification early.
• Start writing even before you envision your entire argument. Getting words down on paper may help you come up with the rest of your writing assignment. Try free writing or diagramming to inspire ideas.
• Compose different parts of your paper in whatever order feels easy. You’re not required to write in sequential order, as long as the final product is well-organized. Some find it helpful to start with the sections that come naturally and move toward the more challenging parts.
• Avoid stopping and editing each sentence as you write. This will slow you down. Instead, consider writing your paper in several whole drafts, and take breaks between editing. Remind yourself that the first draft is low-pressure and exploratory.
• Write your paper in several sittings rather than trying to crank it out in one marathon session. Attempting to write a paper in one sitting may overwhelm you, thereby distracting you from your task.
• Avoid distractions by turning off your internet and cellphone or writing a draft by hand.
• Get feedback from others. Many schools offer writing support services such as helping you develop and structure ideas, find research, connect thoughts, strengthen your understanding of grammar, and much more.
• Seek out additional support. If you’re wondering if your writing block is related to a learning disability, you can check to see if your school as an office of disability services that provides support to students. 

You can also reach out to instructors or a tutor to help implement these strategies for combating writing anxiety. Remember that writing anxiety is common — and you’re certainly not alone. However, if you continue to experience these feelings and need additional support, you might find it helpful to reach out to a mental health professional.

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How do i implement time management strategies and avoid procrastination, what are some tools for managing stress, what should i do if my classmates seem to breeze through coursework while i struggle, how can i find a therapist.

• Introduction
• Conclusions
• Article Information

a Inclusion criteria for tau pathology: low/medium or high tau indicated by standardized uptake value ratio >1.10 or positive visual read assessed by 18 F-flortaucipir positron emission tomography (PET) imaging.

b Inclusion criteria for amyloid pathology (≥37 Centiloids) assessed with 18 F-florbetapir or 18 F-florbetaben PET.

c Inclusion criteria for Mini-Mental State Examination: score of 20 to 28.

d Phosphorylated tau 181 (P-tau181) screening criterion was not implemented for the entire trial duration (eMethods in Supplement 3 ).

e Exclusion criteria for MRI include presence of amyloid-related imaging abnormalities of edema/effusion, >4 cerebral microhemorrhages, >1 area of superficial siderosis, and any intracerebral hemorrhage >1 cm or severe white matter disease.

f Summary of other screen failure can be found in eTable 3 in Supplement 3 (lists reason if ≥20 participants).

g Stratified by baseline tau categorization and enrolling sites.

h One additional death occurred after treatment completion and in the follow-up period.

i Alzheimer disease progression to a degree prompting study discontinuation, per investigator judgment.

j Treatment completion criteria: amyloid plaque level of 11 Centiloids on any single scan or 11 to <25 Centiloids on 2 consecutive scans.

k Participants who met treatment completion criteria are included in discontinuation and completion numbers.

l Percentage calculated as No./total No. of participants with a PET scan at visit: n = 761 at 24 wk, n = 672 at 52 wk, and n = 620 at 76 wk. Corresponding number of participants and percentages for the low/medium tau population were 20.3% (n = 106) at 24 wk, 51.9% (n = 241) at 52 wk, and 73.5% (n = 321) at 76 wk.

A, 35.1% slowing (95% CI, 19.90%-50.23%) of clinical progression. B, 22.3% slowing (95% CI, 11.38%-33.15%) of clinical progression. C, 36.0% slowing (95% CI, 20.76%-51.15%) of clinical progression. D, 28.9% slowing (95% CI, 18.41%-39.44%) of clinical progression. iADRS data were analyzed using the natural cubic spline model with 2 degrees of freedom (NCS2) and CDR-SB data were analyzed with mixed models for repeated measures (MMRM). For MMRM analyses, 95% CIs for least-squares mean changes were calculated with the normal approximation method. For the Alzheimer Disease Cooperative Study—Instrumental Activities of Daily Living, 13-item cognitive subscale of the Alzheimer Disease Assessment Scale, and CDR-SB clinical assessments analyzed with NCS2, see eFigure 1 (low/medium tau population) and eFigure 2 (combined population) in Supplement 3 and Table 2. For all clinical assessments analyzed with MMRM, see eFigure 3 (low/medium tau population) and 4 (combined population) in Supplement 3 and Table 2. P  < .001 for all 76 week time points.

Biomarker data shown were analyzed using mixed models for repeated measures (MMRM). For MMRM analyses, 95% CIs for the least-squares mean changes were calculated with the normal approximation method. P  < .001 for all time points in panels A-D. B, P value is from Fisher exact test comparing the percent amyloid negative by treatment groups at each visit. E and F, The analysis was conducted using a Cox proportional hazards model. There were 163 events among 573 participants in the placebo group and 100 events among 555 participants in the donanemab group in the low/medium tau population and 288 events among 844 participants in the placebo group and 186 events among 805 participants in the donanemab group in the combined population. CDR-G indicates Clinical Dementia Rating Global Score.

Trial protocol

Statistical analysis plan

Nonauthor collaborators

Data sharing statement

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Sims JR , Zimmer JA , Evans CD, et al. Donanemab in Early Symptomatic Alzheimer Disease : The TRAILBLAZER-ALZ 2 Randomized Clinical Trial . JAMA. 2023;330(6):512–527. doi:10.1001/jama.2023.13239

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Donanemab in Early Symptomatic Alzheimer Disease : The TRAILBLAZER-ALZ 2 Randomized Clinical Trial

• 1 Eli Lilly and Company, Indianapolis, Indiana
• 2 Boston Center for Memory and Boston University Alzheimer’s Disease Center, Boston, Massachusetts
• 3 Department of Neurology and Department of Psychiatry, Alpert Medical School of Brown University, Providence, Rhode Island
• 4 Butler Hospital, Providence, Rhode Island
• 5 Department of Neurology, Indiana University School of Medicine, Indianapolis
• 6 Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden; Memory Clinic, Skåne University Hospital, Lund, Sweden
• 7 Scottish Brain Sciences, Edinburgh, United Kingdom
• Editorial Donanemab for Alzheimer Disease—Who Benefits and Who Is Harmed? Jennifer J. Manly, PhD; Kacie D. Deters, PhD JAMA
• Editorial Amyloid-Targeting Monoclonal Antibodies for Alzheimer Disease Gil D. Rabinovici, MD; Renaud La Joie, PhD JAMA
• Editorial Novel Alzheimer Disease Treatments and Reconsideration of US Pharmaceutical Reimbursement Policy Meredith B. Rosenthal, PhD JAMA
• Editorial Ushering in a New Era of Alzheimer Disease Therapy Eric W. Widera, MD; Sharon A. Brangman, MD; Nathaniel A. Chin, MD JAMA
• Viewpoint Role of Registries in Medicare Coverage of New Alzheimer Disease Drugs Ilina C. Odouard, MPH; Mariana P. Socal, MD, PhD; Gerard F. Anderson, PhD JAMA
• Medical News & Perspectives Who Should Get the New Alzheimer Disease Drug? Rita Rubin, MA JAMA
• Comment & Response Use of Donanemab in Early Symptomatic Alzheimer Disease—Reply Cynthia D. Evans, PhD; John R. Sims, MD JAMA
• Comment & Response Use of Donanemab in Early Symptomatic Alzheimer Disease Nunzio Pomara, MD; Bruno Pietro Imbimbo, PhD JAMA
• Viewpoint Risks of Harm in Alzheimer Disease by Amyloid Lowering Madhav Thambisetty, MD, PhD; Robert Howard, MD JAMA
• Medical News in Brief FDA Greenlights Second Alzheimer Drug, Donanemab Emily Harris JAMA

Question   Does donanemab, a monoclonal antibody designed to clear brain amyloid plaque, provide clinical benefit in early symptomatic Alzheimer disease?

Findings   In this randomized clinical trial that included 1736 participants with early symptomatic Alzheimer disease and amyloid and tau pathology, the least-squares mean change in the integrated Alzheimer Disease Rating Scale score (range, 0-144; lower score indicates greater impairment) at 76 weeks was −6.02 in the donanemab group and −9.27 in the placebo group for the low/medium tau population and −10.19 in the donanemab group and −13.11 in the placebo group in the combined study population, both of which were significant differences.

Meaning   Among participants with early symptomatic Alzheimer disease and amyloid and tau pathology, donanemab treatment significantly slowed clinical progression at 76 weeks.

Importance   There are limited efficacious treatments for Alzheimer disease.

Objective   To assess efficacy and adverse events of donanemab, an antibody designed to clear brain amyloid plaque.

Design, Setting, and Participants   Multicenter (277 medical research centers/hospitals in 8 countries), randomized, double-blind, placebo-controlled, 18-month phase 3 trial that enrolled 1736 participants with early symptomatic Alzheimer disease (mild cognitive impairment/mild dementia) with amyloid and low/medium or high tau pathology based on positron emission tomography imaging from June 2020 to November 2021 (last patient visit for primary outcome in April 2023).

Interventions   Participants were randomized in a 1:1 ratio to receive donanemab (n = 860) or placebo (n = 876) intravenously every 4 weeks for 72 weeks. Participants in the donanemab group were switched to receive placebo in a blinded manner if dose completion criteria were met.

Main Outcomes and Measures   The primary outcome was change in integrated Alzheimer Disease Rating Scale (iADRS) score from baseline to 76 weeks (range, 0-144; lower scores indicate greater impairment). There were 24 gated outcomes (primary, secondary, and exploratory), including the secondary outcome of change in the sum of boxes of the Clinical Dementia Rating Scale (CDR-SB) score (range, 0-18; higher scores indicate greater impairment). Statistical testing allocated α of .04 to testing low/medium tau population outcomes, with the remainder (.01) for combined population outcomes.

Results   Among 1736 randomized participants (mean age, 73.0 years; 996 [57.4%] women; 1182 [68.1%] with low/medium tau pathology and 552 [31.8%] with high tau pathology), 1320 (76%) completed the trial. Of the 24 gated outcomes, 23 were statistically significant. The least-squares mean (LSM) change in iADRS score at 76 weeks was −6.02 (95% CI, −7.01 to −5.03) in the donanemab group and −9.27 (95% CI, −10.23 to −8.31) in the placebo group (difference, 3.25 [95% CI, 1.88-4.62]; P  < .001) in the low/medium tau population and −10.2 (95% CI, −11.22 to −9.16) with donanemab and −13.1 (95% CI, −14.10 to −12.13) with placebo (difference, 2.92 [95% CI, 1.51-4.33]; P  < .001) in the combined population. LSM change in CDR-SB score at 76 weeks was 1.20 (95% CI, 1.00-1.41) with donanemab and 1.88 (95% CI, 1.68-2.08) with placebo (difference, −0.67 [95% CI, −0.95 to −0.40]; P  < .001) in the low/medium tau population and 1.72 (95% CI, 1.53-1.91) with donanemab and 2.42 (95% CI, 2.24-2.60) with placebo (difference, −0.7 [95% CI, −0.95 to −0.45]; P  < .001) in the combined population. Amyloid-related imaging abnormalities of edema or effusion occurred in 205 participants (24.0%; 52 symptomatic) in the donanemab group and 18 (2.1%; 0 symptomatic during study) in the placebo group and infusion-related reactions occurred in 74 participants (8.7%) with donanemab and 4 (0.5%) with placebo. Three deaths in the donanemab group and 1 in the placebo group were considered treatment related.

Conclusions and Relevance   Among participants with early symptomatic Alzheimer disease and amyloid and tau pathology, donanemab significantly slowed clinical progression at 76 weeks in those with low/medium tau and in the combined low/medium and high tau pathology population.

Trial Registration   ClinicalTrials.gov Identifier: NCT04437511

Deposition of β-amyloid in the brain is an early event in Alzheimer disease that leads to neurofibrillary tangles composed of tau protein and other characteristic brain changes referred to as the amyloid cascade . 1 , 2 Abnormal β-amyloid is a key pathological hallmark of Alzheimer disease defined by the 2018 National Institute on Aging and the Alzheimer’s Association Research Framework 3 and is one of the major targets in Alzheimer disease research and drug development.

Over the past decade, considerable advances occurred in testing the amyloid cascade hypothesis in Alzheimer disease clinical trials. Numerous amyloid-targeting therapy trials failed to show appreciable slowing of clinical disease progression 4 - 7 ; however, aducanumab, lecanemab, and donanemab recently showed promising amyloid plaque clearance, potentially benefitting patients. 8 - 10

Donanemab is an immunoglobulin G1 monoclonal antibody directed against insoluble, modified, N-terminal truncated form of β-amyloid present only in brain amyloid plaques. Donanemab binds to N-terminal truncated form of β-amyloid and aids plaque removal through microglial-mediated phagocytosis. 11 In the phase 2 TRAILBLAZER-ALZ trial of donanemab vs placebo, the primary outcome was met, as measured by the integrated Alzheimer Disease Rating Scale (iADRS), an integrated assessment of cognition and daily function. 9 Adverse events of interest included amyloid-related imaging abnormalities and infusion-related reactions. 9 To confirm and expand results from TRAILBLAZER-ALZ, we report results from TRAILBLAZER-ALZ 2, a global phase 3 randomized clinical trial that assessed donanemab efficacy and adverse events in a larger group of participants with low/medium tau pathology (the population studied in the phase 2 trial) and in a combined population including those with high tau pathology, a population hypothesized to be more difficult to treat due to more advanced disease.

TRAILBLAZER-ALZ 2 was a 76-week, phase 3, randomized, double-blind, parallel, multicenter, placebo-controlled trial with participants screened at 277 sites in 8 countries (eTable 1 in Supplement 3 ). Enrollment began June 19, 2020, and ended November 5, 2021, and database lock/unblinding (double-blind phase) occurred on April 28, 2023. The trial was originally designed as a phase 2 trial but was subsequently amended to a larger phase 3 trial in February 2021 in an effort to confirm and expand the results of the previous TRAILBLAZER-ALZ trial. The trial was conducted according to the Declaration of Helsinki, the International Conference on Harmonization Good Clinical Practice Guideline, and local regulatory requirements. An independent ethics committee/institutional review board at each site approved the study protocol ( Supplement 1 ), which is provided alongside the statistical analysis plan ( Supplement 2 ). Participants and study partners provided written consent. An independent data and safety monitoring board provided trial oversight.

The trial included participants aged 60 to 85 years with early symptomatic Alzheimer disease (mild cognitive impairment [MCI] 12 or Alzheimer disease with mild dementia). 3 P-tau181 screening was removed in an early protocol amendment (eMethods in Supplement 3 ). Eligible participants had screening Mini-Mental State Examination (MMSE) scores of 20 to 28, amyloid pathology (≥37 Centiloids) assessed with 18 F-florbetapir 13 or 18 F-florbetaben 14 positron emission tomography (PET), and presence of tau pathology assessed by 18 F-flortaucipir PET imaging with central image evaluation. 13 , 15 Tau PET scans were categorized as low/medium or high tau by visual and quantitative reads as previously described 16 - 20 ( Supplements 1 and 2 ). Screening procedures also included magnetic resonance imaging (MRI), and key exclusion criteria included presence of amyloid-related imaging abnormalities of edema/effusion, more than 4 cerebral microhemorrhages, more than 1 area of superficial siderosis, and any intracerebral hemorrhage greater than 1 cm or severe white matter disease on MRI. For all eligibility criteria, see Supplement 1 . Demographic information, including race and ethnicity, was collected to potentially understand any differences in disease course, treatment effects, or adverse events. The participants self-reported race and ethnicity based on fixed categories.

Eligible participants were randomly assigned in a 1:1 ratio ( Figure 1 ) by a computer-generated sequence using interactive web response systems, with stratification by baseline tau categorization and enrolling sites; the randomization block size was 4. Randomized participants received either donanemab (700 mg for the first 3 doses and 1400 mg thereafter) or placebo, administered intravenously every 4 weeks for up to 72 weeks. If amyloid plaque level (assessed at 24 weeks and 52 weeks) was less than 11 Centiloids on any single PET scan or less than 25 but greater than or equal to 11 Centiloids on 2 consecutive PET scans (TRAILBLAZER-ALZ cutoffs 9 ), donanemab was switched to placebo in a blinded procedure. Final adverse events and efficacy assessments were performed at 76 weeks. Amyloid-related imaging abnormality monitoring occurred with scheduled MRIs at 4, 12, 24, 52, and 76 weeks and unscheduled MRIs at investigator discretion. Any participant with detected amyloid-related imaging abnormalities had imaging every 4 to 6 weeks until resolution or stabilization. Amyloid-related imaging abnormality management and treatment interruption guidelines (eTable 2 in Supplement 3 ) depended on severity and symptoms. If infusions were held, investigators were advised to await resolution of amyloid-related imaging abnormalities of edema/effusion on radiographic imaging and stabilization of amyloid-related imaging abnormalities of microhemorrhages and hemosiderin deposits before resuming infusions. Permanent discontinuation was advised for macrohemorrhages. Investigators made final amyloid-related imaging abnormality management decisions.

The primary outcome was change in the iADRS score from baseline to 76 weeks in either the low/medium tau population or combined (low/medium and high tau) population. The iADRS is an integrated assessment of cognition and daily function from the 13-item cognitive subscale of the Alzheimer Disease Assessment Scale (ADAS-Cog 13 ) and Alzheimer Disease Cooperative Study—Instrumental Activities of Daily Living (ADCS-iADL), measuring global disease severity across the Alzheimer disease continuum as a single summary score. The iADRS is validated and captures clinical progression from MCI due to Alzheimer disease through moderate dementia due to Alzheimer disease, and treatment effects have been demonstrated across MCI and Alzheimer disease with mild dementia. 6 , 9 , 21 - 27 The possible scores on the iADRS range from 0 to 144 (lower scores indicate greater impairment), and the meaningful within-patient change (MWPC) is a change of 5 points for those with Alzheimer disease with MCI and 9 points for those with Alzheimer disease with mild dementia. The MWPC, or minimal clinically important difference (MCID) as in Supplement 1 and 2 , is a threshold for outcome scores (either patient-reported or physician-measured) above which a patient or physician would consider the change meaningful. 28

Prespecified secondary outcomes included changes from baseline to 76 weeks by sum of boxes of the Clinical Dementia Rating Scale (CDR-SB), the ADAS-Cog 13 , the ADCS-iADL, and MMSE in the low/medium tau or combined population. Amyloid plaque reduction at 76 weeks, percentage of participants reaching amyloid clearance (<24.1 Centiloids measured by amyloid PET 9 , 29 ) at 24 weeks and 76 weeks, tau PET 1 (frontal cortical regions) change, volumetric MRI (vMRI; whole brain, hippocampus, and ventricles) change, and adverse events were additional secondary outcomes. Supplement 1 provides a complete listing and methodology of adverse events assessments. Amyloid-related imaging abnormalities of edema/effusion, amyloid-related imaging abnormalities of microhemorrhages and hemosiderin deposits, and infusion-related reactions were adverse events of special interest because they were considered class effects or observed in previous trials. 9 , 30 - 32 Secondary outcomes related to pharmacokinetics and antidrug antibodies were also prespecified and are planned for subsequent studies. Exploratory outcomes included change in plasma P-tau217 (C 2 N Diagnostics) at 76 weeks and time-based analyses: progression risk using the CDR Global score (CDR-G; progression defined as any increase from baseline in CDR-G at consecutive visits), participants with no progression at 1 year on the CDR-SB, and clinical progression delay (ie, months saved with treatment) on the iADRS and CDR-SB. Additional information about outcome measures, including score ranges and MWPCs, is provided in eMethods in Supplement 3 .

Prespecified primary and secondary outcomes were controlled for multiplicity (gated) at 76 weeks ( Supplement 2 and eMethods in Supplement 3 ) except for MMSE, changes in vMRI measurements, and adverse event assessments. Additional time points were gated for amyloid clearance and P-tau217. Nominal P values are reported for gated and nongated outcomes.

The trial was originally designed as a phase 2 trial with a plan to enroll 500 participants and assess CDR-SB as the primary outcome, but was subsequently amended to a phase 3 trial assessing the iADRS score as the primary outcome in February 2021 in an effort to confirm and expand the results of the TRAILBLAZER-ALZ trial. No unblinded data analysis of TRAILBLAZER-ALZ 2 was performed or used to inform design or analyses. Further details regarding major protocol or study adjustments are in eMethods in Supplement 3 and the trial protocol in Supplement 1 .

Revised study sample size and power calculations were based on the primary results from the TRAILBLAZER-ALZ trial, 9 where mean progression in the placebo and donanemab groups on iADRS was −10.06 and −6.86 (approximately 32% slowing of disease progression) over 76 weeks, respectively. Multiple longitudinal data sets were simulated and the natural cubic spline model with 2 degrees of freedom (NCS2) was fit to each sample to determine the power. The powering and sample size determination of the trial was based on the low/medium tau population. With a sample size of approximately 1000 randomized participants in the low/medium tau population and an assumed 30% discontinuation rate, the NCS model provided greater than 95% power to achieve statistical significance at a 2-sided α level of .05. The total planned enrollment (including both the low/medium and high tau populations) was 1800.

Most statistical analyses were done with SAS version 9.4 (SAS Institute). Some time-based progression analyses were analyzed with R Project version 4.3.0 (R Foundation).

The efficacy analyses were conducted by using the evaluable efficacy population (participants with a baseline and at least 1 postbaseline efficacy measurement based on randomized treatment). A prespecified gated testing scheme 33 , 34 was used to control for study-wise type I error rate at 2-sided α level of .05, with 80% of initial α spend (.04) for multiplicity control allocated to the low/medium tau population and 20% of initial α spend (.01) for multiplicity control allocated to the combined population (testing scheme in Supplement 2 ; eMethods in Supplement 3 also describes time-based analyses not described below).

Clinical outcomes (except for CDR-SB) were primarily analyzed using an NCS2 model. The protocol-specified week value for each participant was used as a continuous variable to create NCS basis functions with knot locations at 0 weeks, the median observation time, and 76 weeks. The model restricted baseline estimates to be the same for treatment and placebo groups. The baseline score and each scheduled postbaseline score were dependent variables in the model. The model’s independent variables included NCS basis expansion terms (2 terms), NCS basis expansion term × treatment interaction (2 terms), baseline age, concomitant acetylcholinesterase inhibitor and/or memantine use at baseline (yes/no), and randomization stratifying factors (pooled site and baseline tau category [baseline tau category in combined population only]). An unstructured variance covariance matrix was used to model the within-participant errors using restricted maximum likelihood. The Kenward-Roger approximation was used to estimate the denominator degrees of freedom.

The MMRM was used to primarily assess CDR-SB, plasma P-tau217, amyloid PET, and vMRI. The analysis model used change from baseline as the dependent variable. The model was adjusted for age, baseline value, visit as a categorical variable, treatment, baseline × visit interactions, treatment × visit interactions, concomitant acetylcholinesterase inhibitor/memantine use at baseline (CDR-SB only), and randomization stratifying factors of pooled site and, for combined population only, baseline tau category. For vMRI, only age and baseline brain volumes were covariates. The covariance matrix structure used was the same as NCS. Plasma P-tau 217 value was log 10 -transformed to meet the normality assumption.

Both the NCS2 and MMRM use the same protocol-specified time values for each participant in the analysis; the NCS2 model makes additional parametric assumptions for the shape of the longitudinal mean structure that can lead to increased efficiency.

The percent slowing relative to placebo was calculated by dividing the least-squares mean (LSM) change from baseline treatment differences at 76 weeks by the LSM change from baseline with placebo at 76 weeks and multiplying by 100.

ANCOVA analysis was conducted for tau PET standardized uptake value ratio (SUVR), with change from baseline to 76 weeks as the dependent variable and covariates of baseline tau SUVR, age, and, for the combined population, tau burden.

MMRM, NCS with 3 degrees of freedom model (NCS3), and bayesian disease progression model (DPM) were applied as sensitivity analyses for the primary outcome. DPM was applied to measure the proportion of disease progression in donanemab-treated participants relative to placebo-treated participants using a disease progression ratio, as previously described. 35 Details on sensitivity analyses for censoring after amyloid-related imaging abnormalities or infusion-related reactions, per-protocol analysis, and analysis of study completers are in eMethods in Supplement 3 . Details of subgroup analyses and time-based analyses are also described in eMethods in Supplement 3 .

Cox proportional hazard models were applied to CDR-G (gated), iADRS (nongated), and CDR-SB (nongated). Progression to next clinical stage was defined as any increase in CDR-G at 2 consecutive visits from baseline. MWPC was established as an iADRS change of greater than or equal to 5 for those with Alzheimer disease with MCI and greater than or equal to 9 points for those with Alzheimer disease with mild dementia and a CDR-SB change of greater than or equal to 1 point for those with Alzheimer disease with MCI and greater than or equal to 2 points for Alzheimer disease with mild dementia at 2 consecutive visits from baseline.

Analyses of the high tau population alone (ie, not combined with the low/medium tau population) for primary and secondary outcomes was performed post hoc.

Adverse events were evaluated in all participants exposed to study drug and were summarized according to event frequency by treatment assignment.

If less than 30% of the ADCS-iADL, 3 or fewer items of the ADAS-Cog 13, or 1 box of the CDR were missing, the total score for these assessments was imputed. If more items were missing than defined, the total score at that visit was considered missing ( Supplement 2 ). If either the ADCS-iADL or ADAS-Cog 13 scores were missing, the iADRS score was considered as missing. The missing data for NCS and MMRM analyses were handled by the likelihood-based mixed-effect model and the model parameters were estimated using restricted likelihood estimation incorporating all the observed data.

All presented primary, secondary, and exploratory outcomes were controlled for multiplicity (gated) in at least 1 population except for MMSE, vMRI measurements, and safety assessments. Of the 24 gated outcomes (eMethods in Supplement 3 ), 23 were statistically significant.

Of 8240 participants screened, 1736 were enrolled (mean age, 73.0 years; 996 [57.4%] women) and 76% completed the trial: 860 were assigned to receive donanemab and 876 were assigned to receive placebo ( Figure 1 ). Baseline characteristics are summarized by treatment groups in both low/medium tau (n = 1182) and combined populations (n = 1736) ( Table 1 ). As expected, the combined population had higher tau biomarkers at baseline due to the inclusion of participants with high tau pathology and showed greater impairment across baseline clinical assessments.

In the low/medium tau population, LSM change from baseline in the iADRS score at 76 weeks was −6.02 (95% CI, −7.01 to −5.03) in the donanemab group and −9.27 (95% CI, −10.23 to −8.31) in the placebo group (difference, 3.25 [95% CI, 1.88-4.62]; P  < .001), representing a 35.1% (95% CI, 19.90%-50.23%) slowing of disease progression ( Figure 2 , Table 2 ).

In the combined population, LSM change from baseline in the iADRS score at 76 weeks was −10.19 (95% CI, −11.22 to −9.16) in the donanemab group and −13.11 (95% CI, −14.10 to −12.13) in the placebo group (difference, 2.92 [95% CI, 1.51-4.33]; P  < .001), representing a 22.3% (95% CI, 11.38%-33.15%) slowing of disease progression ( Figure 2 , Table 2 ).

In the low/medium tau population, the differences between treatment groups in the LSM change from baseline at 76 weeks was −0.67 (95% CI, −0.95 to −0.40) (36.0% [95% CI, 20.76%-51.15%] slowing of clinical progression) for CDR-SB, 1.83 (95% CI, 0.91-2.75) (39.9% [95% CI, 19.15%-60.58%] slowing of clinical progression) for ADCS-iADL, and −1.52 (95% CI, −2.25 to −0.79) (32.4% [95% CI, 16.55%-48.35%] slowing of clinical progression) for ADAS-Cog 13 ( Figure 2 , Table 2 ; eFigure 1 and 3 in Supplement 3 ).

In the combined population, the differences in the LSM change from baseline to 76 weeks between the donanemab and placebo groups were −0.70 (95% CI, −0.95 to −0.45) (28.9% [95% CI, 18.26%-39.53%] slowing of clinical progression) for CDR-SB, 1.70 (95% CI, 0.84-2.57) (27.8% [95% CI, 13.48%-42.13%] slowing of clinical progression) for ADCS-iADL, and −1.33 (95% CI, −2.09 to −0.57) (19.5% [95% CI, 8.23%-30.83%] slowing of clinical progression) for ADAS-Cog13 ( Figure 2 , Table 2 ; eFigures 2 and 4 in Supplement 3 ).

At 76 weeks, brain amyloid plaque level decreased by 88.0 Centiloids (95% CI, −90.20 to −85.87) with donanemab treatment and increased by 0.2 Centiloids (95% CI, −1.91 to 2.26) in the placebo group in the low/medium tau population; in the combined population, amyloid plaque level decreased by 87.0 Centiloids (95% CI, −88.90 to −85.17) with donanemab treatment and decreased by 0.67 Centiloids (95% CI, −2.45 to 1.11) in the placebo group ( Figure 3 A). The percentages of donanemab-treated participants in the low/medium tau population who reached amyloid clearance 29 , 38 were 34.2% (95% CI, 30.22%-38.34%) at 24 weeks and 80.1% (95% CI, 76.12%-83.62%) at 76 weeks compared with 0.2% (95% CI, 0.03%-1.02%) at 24 weeks and 0% (95% CI, 0.00%-0.81%) at 76 weeks of placebo-treated participants. In the combined population, amyloid clearance was reached in 29.7% (95% CI, 26.56%-33.04%) of participants at 24 weeks and 76.4% (95% CI, 72.87%-79.57%) at 76 weeks of donanemab-treated participants compared with 0.2% (95% CI, 0.07%-0.90%) at 24 weeks and 0.3% (95% CI, 0.08%-1.05%) at 76 weeks of placebo-treated participants ( Figure 3 B).

Evaluation of the LSM change from baseline to 76 weeks in frontal tau SUVR (cerebellar gray reference) did not show a significant difference in the low/medium tau or in the combined population (eFigure 5 in Supplement 3 ). The difference in LSM change in tau SUVR from placebo in the frontal lobe at 76 weeks was −0.0002 (95% CI, −0.01 to 0.01; P  = .97) in the low/medium tau population and −0.0041 (95% CI, −0.01 to 0.01; P  = .45) in the combined population.

For both the low/medium tau and combined populations, at 76 weeks, vMRI (a non-gated secondary outcome) showed a greater decrease in whole brain volume, a lesser decrease in the hippocampal volume, and a greater increase in ventricular volume in the donanemab group than in the placebo group (eFigure 6 in Supplement 3 ).

P-tau217 was significantly reduced from baseline with donanemab treatment compared with placebo in the low/medium tau and combined population. The difference in LSM change in tau SUVR (log 10 -based) vs placebo was −0.25 (95% CI, −0.28 to −0.22; P  < .001) in the low/medium tau population and −0.22 (95% CI −0.24 to −0.20; P  < .001) in the combined population at 76 weeks ( Figure 3 C and D).

There was a 38.6% (CDR-G hazard ratio, 0.61 [95% CI, 0.47-0.80]; P  < .001) lower risk of disease progression in the low/medium tau population and a 37.4% (CDR-G hazard ratio, 0.63 [95% CI, 0.51-0.77; P  < .001) lower risk of disease progression in the combined population with donanemab treatment compared with placebo over the 18-month trial ( Figure 3 E and F; see eFigure 7 in Supplement 3 for nongated disease progression analyses of iADRS and CDR-SB). Substantial decline in the low/medium tau population occurred in 100 (18%) donanemab-treated participants and 163 (28%) placebo-treated participants and, in the combined population, occurred in 186 (23%) donanemab-treated and 288 (34%) placebo-treated participants. In addition, in the low/medium tau population, an estimated 47% of participants were stable (showed no decline in CDR-SB from baseline) with donanemab at 1 year compared with 29% of participants receiving placebo ( P  < .001) (eTable 6 in Supplement 3 ). At 76 weeks, disease progression with donanemab treatment in the low/medium tau population was delayed by 4.36 months (95% CI, 1.87-6.85) on the iADRS and 7.53 months (95% CI, 5.69-9.36) on the CDR-SB.

Sensitivity analyses of the iADRS score (eFigure 8 in Supplement 3 ) using NCS3, MMRM, and DPM analyses, NCS2 in the completers and per protocol populations, and censoring change scores after amyloid-related imaging abnormalities edema/effusion and/or infusion-related reaction observations were consistent with the primary analysis (33.4%-39.6% slowing of clinical progression).

The findings as measured by iADRS and CDR-SB were generally consistent across baseline characteristic subgroups where the subgroup was sufficiently large (eFigure 9 in Supplement 3 ).

Analysis of the smaller (n = 552) high tau population alone (ie, not combined with the low/medium tau population) for all primary and secondary outcomes was completed post hoc. The difference between the donanemab and placebo groups in the LSM change from baseline at 76 weeks was 1.26 (95% CI, −1.77 to 4.28; P  = .42) for the iADRS score and −0.69 (95% CI −1.19 to −0.20; P  = .006) for the CDR-SB score. For additional assessments in the high tau population, see eTables 4, 5, and 10 and eFigures 10-13 in Supplement 3 .

The incidence of death was 1.9% in the donanemab group and 1.1% in the placebo group, while the incidence of serious adverse events was 17.4% in the donanemab group and 15.8% in the placebo group ( Table 3 ). In the donanemab group, 3 participants with serious amyloid-related imaging abnormalities subsequently died (2 APOE ε4 heterozygous carriers and one noncarrier; none were prescribed anticoagulant or anti-platelet medications; one resumed treatment after resolution of severe amyloid-related imaging abnormalities edema/effusion that was accompanied by severe amyloid-related imaging abnormalities microhemorrhages and hemosiderin deposits and one had superficial siderosis at baseline) (eTable 9 in Supplement 3 ). Treatment-emergent adverse events were reported by 759 of 853 participants (89.0%) receiving donanemab and 718 of 874 participants (82.2%) receiving placebo. Treatment discontinuation due to adverse events was reported in 112 participants receiving donanemab and 38 participants receiving placebo. The most common adverse events that led to treatment discontinuation were infusion-related reactions, either amyloid-related imaging abnormalities edema/effusion or microhemorrhages and hemosiderin deposits, and hypersensitivity (eTable 7 in Supplement 3 ).

Either amyloid-related imaging abnormalities of edema/effusion or microhemorrhages and hemosiderin deposits occurred in 314 participants (36.8%) receiving donanemab and 130 (14.9%) receiving placebo. Amyloid-related imaging abnormalities of edema/effusion, determined via MRI, occurred in 205 participants (24.0%) in the donanemab group and in 18 (2.1%) in the placebo group. Most amyloid-related imaging abnormalities of edema/effusion events were mild to moderate (see eTable 2 in Supplement 3 ) (n = 188 [93.1%] in the donanemab group; n = 17 [100%] in the placebo group). Symptomatic amyloid-related imaging abnormalities of edema/effusion were reported by 52 participants (6.1%) in the donanemab group (25.4% of those with amyloid-related imaging abnormalities of edema/effusion), with 45 participants (86.5%) having symptom resolution. Most cases (57.9%) of first amyloid-related imaging abnormalities of edema/effusion occurred after receiving up to 3 donanemab infusions. Serious amyloid-related imaging abnormalities of edema/effusion (see Table 3 ) occurred in 13 participants (1.5%) receiving donanemab. First events of amyloid-related imaging abnormalities of edema/effusion radiographically resolved in 198 (98.0%) donanemab-treated participants and 11 (64.7%) placebo-treated participants, with a mean amyloid-related imaging abnormalities of edema/effusion resolution time of 72.4 days for those receiving donanemab and 63.5 days for those receiving placebo. Edema/effusion were numerically less common among APOE ε4 noncarriers than carriers, with higher frequency among homozygotes than heterozygotes ( Table 3 ; further details in eTable 8 in Supplement 3 ).

The incidence of amyloid-related imaging abnormalities of microhemorrhages and hemosiderin deposits, determined via MRI, was higher in the donanemab group than the placebo group (268 participants [31.4%] vs 119 participants [13.6%]). Incidence of amyloid-related imaging abnormalities of microhemorrhages and hemosiderin deposits in the absence of amyloid-related imaging abnormalities of edema/effusion was not different between treatments (12.7% in the donanemab group vs 12.4% in the placebo group). The incidence of microhemorrhage and superficial siderosis was greater in the donanemab group than in the placebo group (microhemorrhage: 26.8% vs 12.5%; superficial siderosis: 15.7% vs 3.0%). Three intracerebral hemorrhages greater than 1 cm were recorded in the donanemab group and 2 were recorded in the placebo group ( Table 3 ).

Infusion-related reactions were reported by 74 participants (8.7%) in the donanemab group and 4 (0.5%) in the placebo group. Serious infusion-related reactions or hypersensitivity occurred in 3 participants (0.4%) in the donanemab group. Most infusion-related reactions were mild to moderate and occurred during or within 30 minutes of the end of the infusion and between the second and fifth infusion (73.6%). Anaphylactic reaction occurred in 3 participants (0.4%) in the donanemab group and were considered to be mild to moderate.

In this phase 3 trial, donanemab significantly slowed Alzheimer disease progression, based on the iADRS score, compared with placebo in the low/medium tau and combined tau populations and across secondary clinical outcomes of CDR-SB, ADAS-Cog 13 , and ADCS-iADL scores.

Donanemab treatment resulted in clinically meaningful benefit (considered to be >20% slowing of clinical progression 39 - 41 ) on the iADRS and CDR-SB scales for both the low/medium tau and combined populations, regardless of statistical model. Additional support for clinical relevance is the 38.6% risk reduction of disease progression as measured on the CDR-G score and the 4.4 to 7.5 months saved over the 18-month study (low/medium tau population). Furthermore, an estimated 47% of participants receiving donanemab had no change in the CDR-SB at 1 year (no disease progression), compared with 29% of participants receiving placebo.

This trial used a definition of a MWPC 28 based on any incremental change on the CDR-G scale (Alzheimer disease with MCI to mild Alzheimer disease or mild Alzheimer disease to moderate Alzheimer disease) or point changes of −5 on the iADRS and 1 on the CDR-SB for those with Alzheimer disease with MCI or −9 on the iADRS and 2 on the CDR-SB for those with Alzheimer disease with mild dementia at consecutive visits from baseline. In analyses assessing whether individual participants reached thresholds of clinically important progression over the course of the trial, donanemab resulted in significantly lower risk of meaningful change on the CDR-G as well as the prespecified nongated analyses of the iADRS and CDR-SB outcomes.

These clinical outcomes were achieved in 52% of low/medium tau participants completing donanemab treatment by 1 year, based on when a participant met amyloid clearance criteria. Limited-duration dosing was a distinct trial design feature reflecting donanemab binding specificity for amyloid plaque and implemented to decrease burden, cost, and potentially unnecessary treatments. 11 Early significant changes on both brain amyloid PET scans and P-tau217 blood test results suggest opportunities for clinical monitoring of therapy. Donanemab treatment resulted in significantly reduced brain amyloid plaque in participants at all time points assessed, with 80% (low/medium tau population) and 76% (combined population) of participants achieving amyloid clearance at 76 weeks. Clearance beyond 76 weeks, and associated Alzheimer disease biomarkers levels, are currently being studied in the ongoing extension phase. The lack of response in frontal tau-PET is inconsistent with the TRAILBLAZER-ALZ phase 2 results. 9 , 38 Additional regions have yet to be analyzed and reported. Factors resulting in this inconsistency will be examined. Changes in vMRI (including a greater decrease in whole brain volume in the donanemab group) were consistent with previous reports 9 , 42 and would benefit from further exploration.

The general belief is that treating Alzheimer disease at the earliest disease stage is likely to result in more clinically meaningful effects. 43 , 44 Post hoc evaluation in only high tau participants demonstrated no differences ( P < .05) on the primary outcome or on most secondary clinical outcomes in donanemab-treated compared with placebo-treated participants within the 18-month trial, with the exception of CDR-SB. Compared with significant differences in the low/medium tau population, this supports the hypothesis that a greater benefit from amyloid-lowering therapies may occur when initiated at an earlier disease stage.

Similar to other amyloid-lowering drugs, and the phase 2 TRAILBLAZER-ALZ trial, amyloid-related imaging abnormalities are an associated adverse event. When amyloid-related imaging abnormalities occur, they are mostly asymptomatic and resolve in approximately 10 weeks. When symptoms occur, they are usually mild, consisting of a headache or increase in confusion, but can have more severe symptoms such as seizures. In some instances, these events can be life-threatening and result in, or lead to, death. For 1.6% of participants in the donanemab treatment group, amyloid-related imaging abnormalities led to serious outcomes, such as hospitalization, and required supportive care and/or corticosteroid use. It is also important to note that 3 deaths in TRAILBLAZER-ALZ 2 occurred after serious amyloid-related imaging abnormalities. Further evaluation of the risks associated with serious and life-threatening amyloid-related imaging abnormalities will be important to identify the best approaches for managing risks and maximizing benefit, in addition to earlier treatment of the disease when less amyloid pathology is present and, theoretically, when amyloid-related imaging abnormalities risk is lower.

This study has several limitations. First, an inherent limitation to limited-duration dosing was variability in total donanemab doses received and/or duration of donanemab dosing. Second, data collection was for 76 weeks, limiting long-term understanding of donanemab; however, a study extension is ongoing. Third, the studied populations were primarily White (91.5%), which may limit generalizability to other populations due to a lack of racial and ethnic diversity. Fourth, although no related protocol amendments were necessary, this trial was conducted during the COVID-19 pandemic, and COVID-19 was the most commonly reported adverse event across treatment groups (see eMethods in Supplement 3 ). Fifth, direct comparison of results to other amyloid-targeting trials is not possible due to trial design differences such as stratification by baseline tau PET category. Sixth, amyloid-related imaging abnormality and infusion-related reaction occurrences may have caused participants and investigators to infer treatment assignment; attempts to minimize bias included blinding CDR raters to adverse event information and, based on sensitivity analyses, censoring change scores after the first observation of amyloid-related imaging abnormalities of edema/effusion and/or infusion-related reactions did not impact the results.

Among participants with early symptomatic Alzheimer disease and amyloid and tau pathology, donanemab significantly slowed clinical progression at 76 weeks in those with low/medium tau and in the combined low/medium and high tau pathology population.

Accepted for Publication: June 28, 2023.

Published Online: July 17, 2023. doi:10.1001/jama.2023.13239

Corresponding Author: John R. Sims, MD, Eli Lilly and Company, Lilly Corporate Center DC 1532, Indianapolis, IN 46285 ( [email protected] ).

Author Contributions: Dr Solomon had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Sims, Zimmer, Ardayfio, Sparks, Wessels, Wang, Collins, Salloway, Mintun, Skovronsky.

Acquisition, analysis, or interpretation of data: Sims, Zimmer, Evans, Lu, Ardayfio, Sparks, Wessels, Shcherbinin, Wang, Nery, Collins, Solomon, Apostolova, Hansson, Ritchie, Brooks, Mintun, Skovronsky.

Drafting of the manuscript: Sims, Evans, Ardayfio, Wang, Nery, Collins, Ritchie, Skovronsky.

Critical review of the manuscript for important intellectual content: Sims, Zimmer, Ardayfio, Wessels, Shcherbinin, Salloway, Apostolova, Ritchie, Mintun, Skovronsky.

Statistical analysis: Lu, Ardayfio, Sparks, Wang, Salloway, Skovronsky.

Obtained funding: Sims, Brooks, Mintun, Skovronsky.

Administrative, technical, or material support: Zimmer, Evans, Wessels, Shcherbinin, Collins, Salloway, Brooks, Mintun, Skovronsky.

Supervision: Sims, Wessels, Nery, Collins, Solomon, Brooks, Mintun, Skovronsky.

Other - imaging and biomarker analysis: Collins.

Other - suggested additional analyses: Apostolova.

Conflict of Interest Disclosures: Dr Sims reported being an employee of Eli Lilly and Company during the conduct of the study. Dr Zimmer reported receiving personal fees from and being a shareholder in Eli Lilly and Company during the conduct of the study. Dr Evans reported being an employee of and minority shareholder in Eli Lilly and Company during the conduct of the study. Dr Lu reported being an employee of and stockholder in Eli Lilly. Dr Ardayfio reported being an employee of and stockholder in Eli Lilly during the conduct of the study. Dr Wessels reported being a minor shareholder in Eli Lilly and Company outside the submitted work. Dr Shcherbinin reported being an employee of and stockholder in Eli Lilly and Company during the conduct of the study and Eli Lilly and Company having patents pending relevant to this research. Dr Nery reported being an employee of and shareholder in Eli Lilly and Company during the conduct of the study. Dr Collins reported being an employee of and stockholder in from Eli Lilly and Company during the conduct of the study. Dr Salloway reported receiving personal fees and grants from Biogen, Eli Lilly, Genentech, Avid, Roche, Eisai, Novartis, Acumen, NovoNordisk, and Prothena during the conduct of the study. Dr Apostolova reported receiving grants from NIA, Alzheimer Association, AVID Radiopharmaceuticals, Life Molecular Imaging, and Roche Diagnostics and personal fees from Eli Lilly, Biogen, Two Labs, IQVIA, Genentech, Siemens, Corium, GE Healthcare, Eisa, Roche Diagnostics, Alnylam, Alzheimer Association, and from the US Food And Drug Administration outside the submitted work. Dr Hansson reported personal fees from AC Immune, Amylyx, Alzpath, BioArtic, Biogen, Cerveau, Eisai, Eli Lilly, Fujirebio, Merk, Novartis, Novo Nordisk, Roche, Sanofi, and Siemens outside the submitted work. Dr Ritchie reported receiving personal fees from Actinogen, Biogen, Cogstate, Eisai, Eli Lilly, Janssen Cilag, Merck, Novo Nordisk, Roche Diagnostics, and Signant and being founder of and majority shareholder in Scottish Brain Sciences outside the submitted work. Dr Brooks reported being an employee of and shareholder in Eli Lilly and Company. Dr Mintun reported being an employee of and shareholder in Eli Lilly and Company and having a patent pending with Eli Lilly and Company. Dr Skovronsky reported being an employee of and shareholder in Eli Lilly and Company. No other disclosures were reported.

Funding/Support: This work was funded by Eli Lilly and Company.

Role of the Funder/Sponsor: Eli Lilly and Company was responsible for design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Group Information: The TRAILBLAZER-ALZ 2 Investigators appear listed in Supplement 4 .

Data Sharing Statement: See Supplement 5 .

Additional Contributions: We thank all the trial participants and their families and caregivers who participated in the TRAILBLAZER-ALZ 2 trial as well as the site staff, raters, and site investigators (see list in Supplement 4 ); members of the data and safety monitoring board; vendor partners including BioAgilitix, Clario, Clinical Trial Media, Cogstate, C 2 N Diagnostics, Invicro, IQVIA, Labcorp and Quanterix. The authors would like to thank the following salaried employees of Eli Lilly and Company for their contributions to TRAILBLAZER-ALZ 2, for which they received no additional compensation: Andrea Abram, MBA; Hrideep Antony, BS; Anupa Arora, MD; Theresa Bauer, BS; Jude Burger, MS; Yang Dai, MS; Russell A Delgiacco, MS; Marybeth Devine, BS; Dawn East, BS; Tim Edison, PharmD; Naohisa Hatekeyama, MS; Jeremy T Hemiup, MS, MBA; Stacy A Huckins, BS; Blaire Iris Kaufman, BS; Rashna Khanna, MD; Min Jung Kim, MS; Albert Lo, MD, PhD; Dedeepya Masarapu, B Pharm; Shoichiro Sato, MD, PhD; Adam Schaum, MAS; Linda Shurzinske, MS; Andrea L Speas, RNN, BSN; LisaAnn Trembath, MS; Giulia Tronchin, PhD; Melissa Veenhuizen, DVM, MS; Wen Xu, PhD; and Wei Zhou, MS. The authors would like to acknowledge Paula Hauck, PhD; Deirdre Hoban, PhD; and Carmen Deveau, PhD, salaried employees of Eli Lilly and Company, for project management support, and strategic scientific communication expertise, for which they received no additional compensation.

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• Open access
• Published: 24 July 2024

AI models collapse when trained on recursively generated data

• Ilia Shumailov 1   na1 ,
• Zakhar Shumaylov 2   na1 ,
• Yiren Zhao   ORCID: orcid.org/0000-0002-3727-7463 3 ,
• Nicolas Papernot 4 , 5 ,
• Ross Anderson   ORCID: orcid.org/0000-0001-8697-5682 6 , 7   na2 &
• Yarin Gal   ORCID: orcid.org/0000-0002-2733-2078 1  

Nature volume  631 ,  pages 755–759 ( 2024 ) Cite this article

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Stable diffusion revolutionized image creation from descriptive text. GPT-2 (ref.  1 ), GPT-3(.5) (ref.  2 ) and GPT-4 (ref.  3 ) demonstrated high performance across a variety of language tasks. ChatGPT introduced such language models to the public. It is now clear that generative artificial intelligence (AI) such as large language models (LLMs) is here to stay and will substantially change the ecosystem of online text and images. Here we consider what may happen to GPT-{ n } once LLMs contribute much of the text found online. We find that indiscriminate use of model-generated content in training causes irreversible defects in the resulting models, in which tails of the original content distribution disappear. We refer to this effect as ‘model collapse’ and show that it can occur in LLMs as well as in variational autoencoders (VAEs) and Gaussian mixture models (GMMs). We build theoretical intuition behind the phenomenon and portray its ubiquity among all learned generative models. We demonstrate that it must be taken seriously if we are to sustain the benefits of training from large-scale data scraped from the web. Indeed, the value of data collected about genuine human interactions with systems will be increasingly valuable in the presence of LLM-generated content in data crawled from the Internet.

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The development of LLMs is very involved and requires large quantities of training data. Yet, although current LLMs 2 , 4 , 5 , 6 , including GPT-3, were trained on predominantly human-generated text, this may change. If the training data of most future models are also scraped from the web, then they will inevitably train on data produced by their predecessors. In this paper, we investigate what happens when text produced by, for example, a version of GPT forms most of the training dataset of following models. What happens to GPT generations GPT-{ n } as n increases? We discover that indiscriminately learning from data produced by other models causes ‘model collapse’—a degenerative process whereby, over time, models forget the true underlying data distribution, even in the absence of a shift in the distribution over time. We give examples of model collapse for GMMs, VAEs and LLMs. We show that, over time, models start losing information about the true distribution, which first starts with tails disappearing, and learned behaviours converge over the generations to a point estimate with very small variance. Furthermore, we show that this process is inevitable, even for cases with almost ideal conditions for long-term learning, that is, no function estimation error. We also briefly mention two close concepts to model collapse from the existing literature: catastrophic forgetting arising in the framework of task-free continual learning 7 and data poisoning 8 , 9 maliciously leading to unintended behaviour. Neither is able to explain the phenomenon of model collapse fully, as the setting is fundamentally different, but they provide another perspective on the observed phenomenon and are discussed in more depth in the  Supplementary Materials . Finally, we discuss the broader implications of model collapse. We note that access to the original data distribution is crucial: in learning tasks in which the tails of the underlying distribution matter, one needs access to real human-produced data. In other words, the use of LLMs at scale to publish content on the Internet will pollute the collection of data to train their successors: data about human interactions with LLMs will be increasingly valuable.

What is model collapse?

Definition 2.1 (model collapse).

Model collapse is a degenerative process affecting generations of learned generative models, in which the data they generate end up polluting the training set of the next generation. Being trained on polluted data, they then mis-perceive reality. The process is depicted in Fig. 1a . We separate two special cases: early model collapse and late model collapse. In early model collapse, the model begins losing information about the tails of the distribution; in late model collapse, the model converges to a distribution that carries little resemblance to the original one, often with substantially reduced variance.

This process occurs owing to three specific sources of error compounding over generations and causing deviation from the original model:

Statistical approximation error. This is the primary type of error, which arises owing to the number of samples being finite, and disappears as the number of samples tends to infinity. This occurs because of a non-zero probability that information can get lost at every step of resampling.

Functional expressivity error. This is a secondary type of error, arising owing to limited function approximator expressiveness. In particular, neural networks are only universal approximators as their size goes to infinity. As a result, a neural network can introduce non-zero likelihood outside the support of the original distribution or zero likelihood inside the support of the original distribution. A simple example of the expressivity error is if we tried fitting a mixture of two Gaussians with a single Gaussian. Even if we have perfect information about the data distribution (that is, infinite number of samples), model errors will be inevitable. However, in the absence of the other two types of error, this can only occur at the first generation.

Functional approximation error. This is a secondary type of error, arising primarily from the limitations of learning procedures, for example, structural bias of stochastic gradient descent 10 , 11 or choice of objective 12 . This error can be viewed as one arising in the limit of infinite data and perfect expressivity at each generation.

Each of the above can cause model collapse to get worse or better. More approximation power can even be a double-edged sword—better expressiveness may counteract statistical noise, resulting in a good approximation of the true distribution, but it can equally compound the noise. More often than not, we get a cascading effect, in which individual inaccuracies combine to cause the overall error to grow. For example, overfitting the density model causes the model to extrapolate incorrectly and assigns high-density regions to low-density regions not covered in the training set support; these will then be sampled with arbitrary frequency. It is worth noting that other types of error exist. For example, computers have limited precision in practice. We now turn to mathematical intuition to explain how the above give rise to the errors observed, how different sources can compound and how we can quantify the average model divergence.

Theoretical intuition

Here we provide a theoretical intuition for the phenomenon of model collapse. We argue that the process of model collapse is universal among generative models that recursively train on data generated by previous generations. We quantify the sources of errors discussed in the previous section by examining two mathematical models, which prove to be simple enough to provide analytical expressions for quantities of interest, but also portray the phenomenon of model collapse: a discrete distribution in the absence of functional expressivity and approximation errors, and a multidimensional Gaussian approximation, portraying joint functional expressivity and statistical errors. We further illustrate the impact of all three jointly for a more complex setting of density estimation in Hilbert spaces in the Supplementary Materials .

The overall stochastic process we consider, which we call learning with generational data, is the following. The dataset at generation i is \({{\mathcal{D}}}_{i}\) , comprising independent and identically distributed random variables \({X}_{j}^{i}\) with distribution p i , j   ∈  {1,…,  M i } denotes the size of the dataset. Going from generation i to generation i  + 1, we aim to estimate the distribution of samples in \({{\mathcal{D}}}_{i}\) , with an approximation \({p}_{{\theta }_{i+1}}\) . This step is what we refer to as functional approximation, \({p}_{{\theta }_{i+1}}={{\mathcal{F}}}_{\theta }({p}_{i})\) . The dataset \({{\mathcal{D}}}_{i+1}\) is then generated by sampling from \({p}_{i+1}={\alpha }_{i}{p}_{{\theta }_{i+1}}+{\beta }_{i}{p}_{i}+{\gamma }_{i}{p}_{0}\) , with non-negative parameters α i ,  β i ,  γ i summing to 1, that is, they represent proportions of data used from different generations. This corresponds to a mixing of data coming from the original distribution ( γ i ), data used by the previous generation ( β i ) and data generated by the new model ( α i ). We refer to this as the sampling step. For the mathematical models to come, we consider α i  =  γ i  = 0, that is, data only from a single step are used, whereas numerical experiments are performed on more realistic choices of parameters.

Discrete distributions with exact approximation

In this subsection, we consider a discrete probability distribution in absence of functional approximation and expressivity errors, that is, \({\mathcal{F}}(p)=p\) . In this case, model collapse arises only because of statistical errors from the sampling step. At first, the tails (low-probability events) begin to disappear as a result of the low probability of sampling them and, over time, support of the distribution shrinks. Denoting the sample size as M , if we consider state i with probability \(q\le \frac{1}{M}\) , the expected number of samples with value i coming from those events will be less than 1. In practice, this would mean that we lose information about them. Considering more generally some state i with probability q , using standard conditional probability, we can show that the probability of losing information (that is, sampling no data at some generation) is equal to 1 −  q , implying that the distribution must converge to a delta function positioned at some state, with the probability of ending up at a certain state equal to the probability of sampling said state from the original distribution.

This can be shown directly by considering the process \({{\bf{X}}}^{i}\to {\mathcal{F}}\,\to \) \({p}_{i+1}\to {{\bf{X}}}^{i+1}\) as a Markov chain, as X i +1 only depends on X i . Furthermore, if all the \({X}_{j}^{i}\) have the same value, then at the next generation, the approximated distribution will be exactly a delta function and therefore all of \({X}_{j}^{i+1}\) will also have the same value. This implies that the Markov chain contains at least one absorbing state and therefore, with probability 1, it will converge to one of the absorbing states. This is a well-known fact, of which a proof is provided in the Supplementary Materials . For this chain, the only absorbing states are those corresponding to delta functions. As a result, as we follow the progress of model collapse, we are guaranteed to end up in a constant state, having lost all the information of the original distribution when the chain is absorbed. This argument also works in general owing to floating-point representations being discrete, making the Markov chain over the parameters of the model discrete. Thus, as long as the model parameterization allows for delta functions, we will get to it, because—owing to sampling errors—the only possible absorbing states are delta functions. On the basis of the discussion above, we see how both early model collapse, in which only the low-probability events get cut off, and late stage model collapse, in which the process begins to collapse into a single mode, must arise in the case of discrete distributions with perfect functional approximation.

Multidimensional Gaussian

Following the discussion about discrete distributions, we now present a more generic result, which can be shown in the Gaussian approximation setting, in which each generation is approximated using the unbiased estimates of the mean and the variance. A similar result holds more generally, which we detail in the  Supplementary Materials .

Theorem 3.1 (Gaussian model collapse)

Assume the original data are sampled from distribution \({{\mathcal{D}}}_{0}\) (not necessarily Gaussian), with non-zero sample variance. Assume X n are fit recursively using the unbiased sample mean and variance estimators from the previous generation, \({X}_{j}^{n}| {\mu }_{n},{\Sigma }_{n} \sim {\mathcal{N}}({\mu }_{n},{\Sigma }_{n})\) , with a fixed sample size. Then,

in which \({{\mathbb{W}}}_{2}\) denotes the Wasserstein-2 distance between the true distribution and its approximation at generation n .

In words, this implies that not only does the n th generation approximation diverge arbitrarily far from the original one but it also collapses to be zero variance as the number of generations increases, with probability 1. The results are very analogous to that seen in the discrete case, with this theorem illustrating the effect of late stage model collapse, in which the process begins to collapse to be zero variance. The early stage model collapse can also be seen and the interested reader is referred to the  Supplementary Materials for a more in-depth discussion.

Model collapse in language models

In this section, we evaluate the effect of model collapse on language models. We cover more interpretable machine learning models—VAEs and GMMs—in the  Supplementary Materials . Code is publically available in ref.  13 .

Model collapse is universal across various families of machine learning models. Yet, if small models such as GMMs and VAEs are normally trained from scratch, LLMs are different. They are so expensive to retrain from scratch that they are typically initialized with pre-trained models such as BERT 4 , RoBERTa 5 or GPT-2 (ref.  2 ), which are trained on large text corpora. They are then fine-tuned to various downstream tasks 14 .

Here we explore what happens with language models when they are sequentially fine-tuned with data generated by other models. We can easily replicate all experiments covered in this paper with larger language models in non-fine-tuning settings to demonstrate model collapse. Given that training a single moderately large model produces twice the American lifetime’s worth of CO 2 (ref.  15 ), we opted to not run such an experiment and instead focus on a more realistic setting for a proof of concept. Note that even the language experiments described in this paper took weeks to run. We evaluate the most common setting of training a language model—a fine-tuning setting for which each of the training cycles starts from a pre-trained model with recent data. The data here come from another fine-tuned pre-trained model. Because training is restricted to produce models that are close to the original pre-trained model, and data points generated by the models will generally produce very small gradients, the expectation here may be that the model should only change moderately after fine-tuning. We fine-tune the OPT-125m causal language model made available by Meta through Hugging Face 6 .

We fine-tune it on the wikitext2 dataset 16 . For data generation from the trained models, we use a five-way beam search. We block training sequences to be 64 tokens long; then, for each token sequence in the training set, we ask the model to predict the next 64 tokens. We go through all of the original training dataset and produce an artificial dataset of the same size. Because we go through all of the original dataset and predict all of the blocks, if the model had 0 error, it would produce the original wikitext2 dataset. Training for each generation starts with generation from the original training data. Each experiment is run five times and the results are shown as five separate runs with different randomness seeds. The original model fine-tuned with real wikitext2 data obtains 34 mean perplexity, from the zero-shot baseline of 115, that is, it successfully learns the task. Finally, to be as realistic as possible, we use the best-performing model on the original task, evaluated using the original wikitext2 validation set, as the base model for the subsequent generations, meaning that—in practice—observed model collapse can be even more pronounced. Here we consider two different settings:

Five epochs, no original training data. Here the model is trained for five epochs starting on the original dataset but with no original data retained for subsequent runs. The overall original task performance is presented in Fig. 1b . We find that training with generated data allows us to adapt to the underlying task, losing some performance, from 20 to 28 perplexity points.

Ten epochs, 10% of original training data preserved. Here the model is trained for ten epochs on the original dataset and with every new generation of training, a random 10% of the original data points is sampled. The overall original task performance is presented in Fig. 1c . We find that preservation of the original data allows for better model fine-tuning and leads to only minor degradation of performance.

Both training regimes lead to degraded performance in our models, yet we do find that learning with generated data is possible and models can successfully learn (some of) the underlying task. In particular, from Fig. 1 and their 3D versions in the  Supplementary Materials , we see that model collapse occurs, as the density of samples with low perplexity begins to accumulate over the generations. This in turn makes it likely that, over the generations, the sampled data will similarly collapse to a delta function.

a , Model collapse refers to a degenerative learning process in which models start forgetting improbable events over time, as the model becomes poisoned with its own projection of reality. Here data are assumed to be human-curated and start off clean; then model 0 is trained and data are sampled from it; at step n , data are added to the overall data from step n  − 1 and this combination is used to train model n . Data obtained with Monte Carlo sampling should ideally be statistically close to the original, provided that fitting and sampling procedures are perfect. This process depicts what happens in real life with the Internet: model-generated data become pervasive. b , c , Performance of OPT-125m models of different generations evaluated using the original wikitext2 test dataset. Shown on the left are the histograms of perplexities of each individual data training sequence produced by different generations as evaluated by the very first model trained with the real data. Over the generations, models tend to produce samples that the original model trained with real data is more likely to produce. At the same time, a much longer tail appears for later generations. Later generations start producing samples that would never be produced by the original model, that is, they start misperceiving reality based on errors introduced by their ancestors. The same plots are shown in 3D in the Supplementary Materials . On the right, average perplexity and its standard deviation are shown for each independent run. The x axis refers to the generation of the model. ‘Real’ refers to the ‘model 0’ trained on the original wikitext2 dataset; model 1 was trained on the data produced by model 0, model 2 was trained on data produced by model 1 and so on, with all generated datasets equal in size. We find that models trained on generated data are able to learn some of the original task, but with errors, as seen from the increase in perplexity.

It is important to note here that the observed behaviour is in line with the general intuition established in the section ‘Theoretical intuition’. To be precise, in all experiments, generational learning is only performed on a finite (usually small) number of generations, whereas claims of the section ‘Theoretical intuition’ are mostly presented in the limit of generations going to infinity. However, as seen from experiments on VAEs and GMMs in the  Supplementary Materials , convergence to delta functions and specific rates of such convergence are highly related to the specifics of the problem considered, and complete collapse may or may not occur, even after a small number of steps. This is further illustrated theoretically in the  Supplementary Materials , in which potentially notable divergence from the original model can occur even after a few generations.

Figure 1b,c on the left shows histograms of individual data-point perplexities generated by the models of different generations as is evaluated by the first model developed with real wikitext2 training data. Here, over the generations, models tend to produce more sequences that the original model would produce with the higher likelihood. The observed effect is similar to that described for VAEs and GMMs in the  Supplementary Materials , in which—over the generations—models started to produce samples that would be produced with higher probabilities by the original model. At the same time, we discover that generated data have much longer tails, suggesting that some of the data would never be produced by the original model—these are the errors that accumulate because of the learning with generational data.

Example of text outputs of an OPT-125m model affected by model collapse—models degrade over generations, for which each new generation is trained on data produced by the previous generation.

Input: some started before 1360 — was typically accomplished by a master mason and a small team of itinerant masons, supplemented by local parish labourers, according to Poyntz Wright. But other authors reject this model, suggesting instead that leading architects designed the parish church towers based on early examples of Perpendicular.

Gen 0: Revival architecture such as St. John’s Cathedral in London. The earliest surviving example of Perpendicular Revival architecture is found in the 18th @-@ century Church of Our Lady of Guernsey, which dates from the late 19th century. There are two types of perpendicular churches : those.

Gen 1: architecture such as St. Peter’s Basilica in Rome or St. Peter’s Basilica in Buenos Aires. There is no evidence that any of these buildings were built during the reign of Pope Innocent III, but it is possible that they may have been built during the reign of his successor, Pope Innocent.

Gen 5: ism, which had been translated into more than 100 languages including English, French, German, Italian, Spanish, Portuguese, Dutch, Swedish, Norwegian, Polish, Hungarian, Slovak, Lithuanian, Estonian, Finnish, Romanian, Bulgarian, Turkish, Croatian, Serbian, Ukrainian, Russian, Kazakh, Kyrgyz.

Gen 9: architecture. In addition to being home to some of the world’s largest populations of black @-@ tailed jackrabbits, white @-@ tailed jackrabbits, blue @-@ tailed jackrabbits, red @-@ tailed jackrabbits, yellow @-.

Ablation: Repetitions

We find that data generated by language models in our experiments end up containing a large number of repeating phrases, as in Example 1. The repeating problem has been observed in nearly all text-generation models 17 , 18 and, to rule this out as the cause of model collapse, we further provide numerical experiments when models are explicitly encouraged to produce non-repeating sequences with a repeating penalty of 2.0. We find that this causes the models to produce lower score continuations to avoid using repeats, which—as a result—causes the consequent models to perform even worse. Model perplexities shift across the generations towards more probable token sequences, as measured using the model trained on the original real data distribution. Further illustrations are provided in the  Supplementary Materials . In particular, enforcing this for the LLM experiments causes the perplexity to double compared with the original. Models remain as susceptible to model collapse, if not more.

The described process demonstrates that fine-tuning of language models does not curb the effects of model collapse and models that are being fine-tuned are also vulnerable. We find that, over the generations, models tend to produce more probable sequences from the original data and start introducing their own improbable sequences, that is, errors.

We now discuss the implications of model collapse on the underlying learning dynamics of LLMs. Long-term poisoning attacks on language models are not new. For example, we saw the creation of click, content and troll farms, a form of human ‘language models’, whose job is to misguide social networks and search algorithms. The negative effect that these poisoning attacks had on search results led to changes in search algorithms. For example, Google downgraded farmed articles 19 , putting more emphasis on content produced by trustworthy sources, such as education domains, whereas DuckDuckGo removed them altogether 20 . What is different with the arrival of LLMs is the scale at which such poisoning can happen once it is automated. Preserving the ability of LLMs to model low-probability events is essential to the fairness of their predictions: such events are often relevant to marginalized groups. Low-probability events are also vital to understand complex systems 21 .

Our evaluation suggests a ‘first mover advantage’ when it comes to training models such as LLMs. In our work, we demonstrate that training on samples from another generative model can induce a distribution shift, which—over time—causes model collapse. This in turn causes the model to mis-perceive the underlying learning task. To sustain learning over a long period of time, we need to make sure that access to the original data source is preserved and that further data not generated by LLMs remain available over time. The need to distinguish data generated by LLMs from other data raises questions about the provenance of content that is crawled from the Internet: it is unclear how content generated by LLMs can be tracked at scale. One option is community-wide coordination to ensure that different parties involved in LLM creation and deployment share the information needed to resolve questions of provenance. Otherwise, it may become increasingly difficult to train newer versions of LLMs without access to data that were crawled from the Internet before the mass adoption of the technology or direct access to data generated by humans at scale.

Data availability

Data generation code for GMM experiments is available in ref.  13 . Data used for VAE experiments are available in ref.  22 . Data used for LLM experiments are available in ref.  16 .

Code availability

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Acknowledgements

This paper is dedicated to the memory of Professor Ross J. Anderson, our colleague and friend, who contributed much to this and other works we have produced over the years. We thank A. Thudi, D. Glukhov, P. Zaika, and D. Barak for useful discussions and feedback.

Author information

These authors contributed equally: Ilia Shumailov, Zakhar Shumaylov

Deceased: Ross Anderson

Authors and Affiliations

OATML, Department of Computer Science, University of Oxford, Oxford, UK

Ilia Shumailov & Yarin Gal

Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK

Zakhar Shumaylov

Department of Electrical and Electronic Engineering, Imperial College London, London, UK

University of Toronto, Toronto, Ontario, Canada

Nicolas Papernot

Vector Institute, Toronto, Ontario, Canada

Department of Computer Science and Technology, University of Cambridge, Cambridge, UK

Ross Anderson

School of Informatics, University of Edinburgh, Edinburgh, UK

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Contributions

I.S. and Z.S. proposed and developed the idea, led the research and mathematical modelling and developed the GMM and VAE experiments. I.S. and Y.Z. developed the language-model experiments. N.P., Y.G. and R.A. supervised and guided the project. All authors contributed to writing of the manuscript. Y.G. is supported by a Turing AI Fellowship financed by the UK government’s Office for Artificial Intelligence, through UK Research and Innovation (grant reference EP/V030302/1) and delivered by the Alan Turing Institute.

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Correspondence to Ilia Shumailov , Zakhar Shumaylov or Yarin Gal .

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Shumailov, I., Shumaylov, Z., Zhao, Y. et al. AI models collapse when trained on recursively generated data. Nature 631 , 755–759 (2024). https://doi.org/10.1038/s41586-024-07566-y

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DOI : https://doi.org/10.1038/s41586-024-07566-y

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