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Abstract Generator

Get your abstract written – skip the headache., writefull's abstract generator gives you an abstract based on your paper's content., paste in the body of your text and click 'generate abstract' . here's an example from hindawi., frequently asked questions about the abstract generator.

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What are the Abstract Generator's key features?

Title is Here

Your abstract is here

• Abstract Generator

Abstract generator lets you create an abstract for the research paper by using advanced AI technology.

This online abstract maker generates a title and precise overview of the given content with one click.

It generates an accurate article abstract by combining the most relevant and important phrases from the content of the article.

How to write an abstract for a research paper?

Here’s how you can generate the abstract of your content in the below easy steps:

• Type or copy-paste your text into the given input field.
• Alternatively, upload a file from the local storage of your system.
• Verify the reCAPTCHA.
• Click on the Generate button.
• Copy the results and paste them wherever you want in real-time.

Features of Our Online Abstract Generator

Free for all.

Our abstract generator APA is completely free for everyone. You don’t have to purchase any subscription to abstract research papers and articles.

Files Uploading

To get rid of typing or pasting long text into the input box, you can use this feature.

This will allow you to upload TXT, DOC, and PDF files from the local storage without any hurdles.

Create Abstract and Title

This abstract creator online makes it easy for you to generate a title and precis overview of the given text with one click.

It takes the important key phrases from the content and combines them to create an accurate abstract with advanced AI.

Click to Copy

You can use this feature of our online abstract maker to copy the result text in real-time and paste it wherever you want without any hassle.

Download File

This feature lets you download the abstracted text in DOC format for future use just within a single click.

No Signup/Registration

This free text abstraction tool requires no signup or registration process to use it. Simply go the Editpad.org , search for the Abstract Generator, open it, and enter your text to create an abstract of any text within seconds.

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Free Abstract Generator

Make an abstract for your paper in 4 steps:

• Choose between a simple and an advanced option
• Paste the text or add the details
• Click “Generate”
• Check and copy the result

Your abstract may be:

• ⭐️ The Tool’s Benefits
• 🤔 Why Use Our Tool?

📝 What Is an Abstract?

• ✍️ How to Write It
• ✨ Abstract Example

🔗 References

⭐️ abstract generator: the benefits.

🤔 Why Use Online Abstract Generator?

Having trouble writing an abstract? You’re not alone.

Crafting an abstract can be problematic, especially when dealing with voluminous work. After all, converting a 100-page academic paper into 150 words is not an easy task. And this is where an abstract maker can help you immensely.

The amount of time you’ll save by relying on a machine to do the work for you is huge. Not to mention the result will be entirely error-free. No logical, grammatical, or other mistakes will spoil your piece.

Sounds interesting? Then, keep reading to learn more about abstracts and our generator.

An abstract is a brief summary of a work. Usually, it's a single paragraph containing 150 to 250 words. It describes all the key points and elements of an article, essay, or work of any other format.

Keep in mind that an abstract merely describes a text. It shouldn’t be an evaluation or an attempt to defend the paper. Instead, it’s just an overview.

Structure of an Abstract

An abstract is not a simple summary. It has a specific structure and should contain the following elements:

• The main issue . Describe the problem you are trying to solve with your research.
• The background . Include everything the reader needs to know before delving into your text.
• The goal . Don’t forget to describe the reasons behind your work.
• The methods . Tell the readers how exactly you performed your research.
• The results . What did you discover? If no particular result comes to mind, you can list your arguments here instead.
• The implications . Show the reader how significant your work is.

Remember that an abstract is separate from the rest of the paper. For the reader to get the complete picture of your research, your abstract must include everything listed above.

✍️ How to Write an Abstract

It can be tempting to go and write an abstract right away. But make sure to finish the planning of your work first. You want to write your abstract about your piece's contents, not build the contents around your abstract.

To make the writing process easier, divide it into 5 manageable steps:

• Check the requirements. First off, you need to know how much you are allowed to write. An average abstract is about 150-250 words long, but there is often a strict limit. Make sure to stay within it!
• Establish the goal and the problems of the research. The reader needs to know what your paper will be about right from the get-go. That’s why you need to formulate your thesis and showcase it first.
• Establish the methods. Tell the reader how you did your research. Don’t go in too deep: simply describe the methods without unnecessary details.
• Describe the results. Write a couple of sentences about the outcome of your investigation.
• Write a conclusion. Address the issue you established in the second step. You might also want to mention your work’s limitations regarding your research samples or methods. Try to give the reader a clear understanding of your goal and how you achieved it.

Want to make the process even easier? Use our abstract tool! Online generators like ours will help you craft an excellent paragraph in a matter of seconds.

Abstract Writing Tips

Finally, we want to help you make your abstract truly amazing. Check out our best tips below:

• It's best to get to the point immediately and without adding any filler or unnecessary details.
• The less specific your abstract is, the better.
• Check out some examples before you start writing. Sometimes the best way to learn something is to watch how everyone else does it.
• Avoid long sentences or bizarre vocabulary to make an abstract paragraph as concise as possible.
• It’s a great idea to single out some keywords from your outline and put them into your abstract.
• Don't forget about formatting. Any serious academic work has its requirements. Make sure you check them before writing your piece.

Following these simple tips will make you a master of abstract writing.

✨ Free Abstract Sample

As an example, check out this abstract of the article “Bioeffcacy of Mentha piperita essential oil against dengue fever mosquito” by Sarita Kumar:

The Mentha balsamea, or peppermint plant, is a result of cross-breeding between spearmint and water mint. These plants are most commonly used in the area of repelling insects. The following research revolves around peppermint oil insect repellent and its development. As a part of an experiment, we obtained 25 grams of fresh peppermint and, after grinding it, put it in a glass jar with olive oil. The jar was then left for two days in a warm temperate. Next, the oil was strained with a cheesecloth, gathered, and diluted at 70%. It then got separated into three different spray bottles. The test was to put the spray sample into a jar with mosquitoes and equate the result to the same test with a commercial repellant. Thus, we challenged the stereotype of synthetic repellents being more efficient than their analogs made from natural materials.

That will be the end of our guide on abstract writing. Thank you for reading, and make sure to try out our abstract writer tool to get the best results!

❓ Abstract Generator FAQ

❓ how do you write an abstract for a research paper.

You may use an abstract tool and make the writing process entirely automatic. If you can’t use it, write an abstract yourself by describing the following:

• The main problem.
• Background information.
• The end goal.
• Description of methods you used.
• The results of the research.

❓ What are the 5 parts of an abstract?

Parts of an abstract depend on the contents and limitations of your research. The 5 main elements are:

• The introduction
• Research significance
• Method description

❓ What makes a good abstract in a research paper?

A good abstract is one that:

• Meets all the requirements.
• Establishes the problem and main issues of the research.
• Describes the methods you used during the analysis.
• Showcases results of the study.
• Provides a clear conclusion.

❓ How long should my abstract be?

An average abstract is about 150-250 words long. You may often get strict limits that can go above or beyond these numbers. Your supervisor should provide the exact requirements for abstract length. So, make sure to double-check them.

Updated: Jun 18th, 2024

• Writing an Abstract: George Mason University
• Writing an Abstract for Your Research Paper: University of Wisconsin - Madison
• Writing an Abstract: Australian National University
• The Abstract: The University of Toronto

Abstract Generator

0 Sentence 0 Words

AI Abstract Generator

Creating abstracts can be a challenging task that demands a meticulous approach. It involves carefully dissecting your entire paper and scrutinizing each section to ensure that the vital points are adequately covered while avoiding unnecessary details.

However, despite their difficulties, abstracts play an exceptionally significant role. If your goal is to get your work published, mastering the art of abstract writing becomes essential. Additionally, many academic assignments necessitate the inclusion of an abstract, making it a crucial component of the overall scholarly development process.

What is an Abstract?

An abstract is a summary of a document, highlighting the full text's main ideas, key points, methodology, results, and conclusions. Its purpose is to quickly understand the document's content without reading the entire text. Abstracts are commonly used in academia and research to help readers assess the relevance and significance of a work.

What are the various structures of an Abstract?

Abstracts can have two main structures:

Structured Abstract:

It follows a specific format with sections like background/objective, methods, results, and conclusion.

Unstructured Abstract:

This format allows more flexibility and is often used in humanities and social sciences.

Both structures serve the purpose of providing a concise overview of the document's main content and findings.

How SpinBot's AI Abstract Generator Tool works?

To use SpinBot's AI Abstract Generator APA, follow the steps below:

Copy and paste the content or upload the document you want to generate an abstract from.

For more accuracy click on Advance Summarize

Remember that SpinBot's Free AI Abstract Generator APA utilizes advanced natural language processing techniques to generate abstracts, but it is always a good idea to review and refine the generated abstract to ensure it accurately represents the original document's content and meets your specific requirements.

Who are the users of SpinBot's Ai Abstract Generator?

SpinBot's AI Abstract Generator is a versatile tool that caters to a wide range of users seeking to create concise and informative abstracts. They include:

SpinBot's AI Abstract Generator assists students in creating well-structured abstracts for their academic assignments, research papers, and projects.

 ... Read More

It supports teachers in guiding students to develop clear and concise abstracts, enhancing their understanding of abstract writing conventions and facilitating effective communication.

Researchers

Researchers can generate informative abstracts for their studies, enabling them to quickly and accurately summarize their research and share key insights.

It provides bloggers with a convenient tool to create engaging abstracts for their blog posts, captivating readers and giving them a preview of the content.

News Writers and Columnists

SpinBot's AI Abstract Generator helps news writers and columnists craft compelling abstracts for articles, ensuring readers can quickly grasp the main points.

It supports podcasters in creating concise and attention-grabbing abstracts for their episodes, enticing listeners, and summarizing the topics covered.

What are the features of SpinBot's AI Abstract Generator?

Besides its impressive speed, SpinBot's Abstract Creator offers the advantage of being highly accessible. It has been optimized for mobile and desktop usage, allowing users to access the tool from anywhere. Furthermore, the AI abstract generator has the following features:

Generates Abstracts Instantly

SpinBot's AI Abstract Generator allows users to generate abstracts instantly, eliminating the need for time-consuming manual summarization and accelerating the abstract creation process, saving valuable time and effort.

Increases Productivity

By automating the abstract generation process, SpinBot's AI Abstract Generator boosts productivity, enabling users to quickly create high-quality abstracts and focus their time and energy on other important tasks.

Uses AI & ML Technology

Powered by advanced AI and ML technologies, the tool ensures accurate analysis and extraction of key information, resulting in well-crafted abstracts that effectively summarize the content.

Protects Data Privacy

SpinBot prioritizes data privacy and security. The AI Abstract Generator provides a secure platform where users can generate abstracts without worrying about their confidential or sensitive information being compromised or stored.

Remains Free to Use

SpinBot's AI Abstract Generator is available for free, offering accessibility to all users without any cost involved. Users can take advantage of its features and generate abstracts without any financial barriers or restrictions.

How users can create Abstracts for research papers?

Here is a step-by-step guide to writing an abstract:

Step 1: Draft your research paper

Begin by writing your paper, saving the abstract for the end so you can accurately summarize the findings.

Step 2: Review abstract requirements

Familiarize yourself with any specific requirements, such as length or style, if you're writing for publication or a work project.

Step 3: Tailor the abstract to your target audience

Take into account your audience and the intended publication. Adapt the language and level of detail accordingly.

Step 4: Introduce the problem

Start by explaining the problem your research addresses or aims to solve, including the main claim or argument and the scope of your study.

Step 5: Outline your research methods

Describe the methods you employed in your study, including the research conducted, variables considered, and approach taken. Support your assertions with evidence.

Step 6: Highlight the research findings

Share the general findings and answers derived from your study. If necessary, highlight the most significant results.

Step 7: Summarize

Conclude your summary by discussing the meaning of your findings and emphasizing the paper's importance. In the case of an informative abstract, also address the implications of your work.

By following these steps, you can effectively write an abstract that provides a concise and informative overview of your research paper.

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What not to say in an abstract?

It is important to avoid providing excessive background information, detailed methodology, extensive citations, subjective statements, personal opinions, or ambiguous language in an abstract. The abstract should focus on conveying the key findings, main arguments, and implications of the research concisely and objectively.

What are the 4 C's of abstract writing?

The 4 C's of abstract writing are clarity, conciseness, completeness, and coherence. Clarity ensures that the abstract is easy to understand, conciseness involves presenting information succinctly, completeness includes covering all key aspects, and coherence ensures that the abstract flows logically and cohesively.

Why is writing an abstract so hard?

Writing an abstract can be challenging due to the inherent difficulty of condensing a complex and detailed content into a concise and coherent summary. It requires careful selection of information, balancing brevity with clarity, and effectively capturing the essence of the work while maintaining its relevance and significance.

What tense should be used in an abstract?

The present tense is commonly used in abstracts to describe the research findings, methodology, and conclusions. However, the specific tense usage may vary depending on the field or journal guidelines. It is recommended to consult the specific guidelines or conventions of the target publication for precise tense usage.

What is the first step in writing an abstract?

The first step in writing an abstract is thoroughly reading and understanding the entire document. Familiarize yourself with the research question, objectives, methodology, major findings, and conclusions. These steps help you identify the key elements that must be included in the abstract and ensure a comprehensive and accurate summary.

What are other tools by SpinBot?

Apart from the free abstract generator, SpinBot offers several other useful tools. These include the Article Rewriter, which helps paraphrase and rewrite text; the Grammar Checker, which identifies grammar and spelling errors; and the Word Counter, which provides accurate word and character counts for text.

Abstract Generator

This Abstract Generator is basically a guideline for writing abstracts. We have also written an article on how to write abstracts. Go through the post and use our tools to create properly formatted abstracts. Note: An abstract should be between 100 - 250 words.

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Abstract Generator

Table of Contents

Free Abstract Generator

Prepostseo’s Abstract Generator is an online tool that uses AI technology to help you automatically generate abstracts for your thesis, articles, or research papers. Our abstract maker uses accurate AI and language models to collect the most important phrases from a given content, to generate accurate abstracts.

How to Write Abstract By the Free AI Abstract Generator?

Below are the steps to generate abstracts with the help of our AI abstract maker tool:

Type or paste your writing into the input box of our AI abstract maker.

Simply, hit the “ Generate ” button.

The tool will write the abstract in the output box of the tool.

Finally, “ Copy ” or “ Download ” your abstract.

Best AI Abstract Generator: Online & Free

Here is your abstract

If you want to create beautiful abstracts and drastically improve the quality of your research, you've come to the right place. Meet our new mind-blowing AI abstract generator! It will create a fantastic piece of text that incorporates every critical aspect of your research.

• ️🤖 How to Use the Tool
• ️💡 Why Use the Abstract Generator?
• ️🔬 What Is an Abstract?
• ️✅ Abstract Types
• ️✍️ How to Write an Abstract
• ️📝 Abstract Example for Free
• ️❓ AI Abstract Generator FAQ
• ️🔗 References

🤖 How to Use Our Abstract Generator Online

• Paste your text into the empty field.
• Fill in all 5 advanced fields if necessary.
• Press “Generate.”
• An AI bot will generate an abstract for you!

💡 Why Use Our AI Abstract Generator?

Our generator is one of the best study tools you can find online. Here are its most notable advantages:

🔬 What Is an Abstract?

An abstract is a paragraph that gives readers a general synopsis of your research's contents and structure. It should include your thesis , main points, methodology, and findings. An abstract is usually 150-200 words in length.

It serves the following purposes:

• Helps to navigate your arguments.
• Allows readers to grasp the main idea from your text quickly.
• Aids in remembering key points from your paper.

✅ Abstract Types

Abstracts come in two general types: informative and descriptive . They differ in terms of components and styles because they have separate goals.

• A descriptive abstract indicates what information is included in your research. It doesn't provide study findings or conclusions. Some view it as an outline of the work rather than a synopsis. Typically, descriptive abstracts are brief, with 100 words or less.
• An informative abstract combines the material provided in a descriptive one (goal, methods, and scope) with the research's findings and conclusions. An informative abstract is usually around 10% of the work in length.

✍️ How to Write an Abstract

Now that you know what abstracts are, it's time to learn how to write them . Just follow our handy step-by-step guide below!

1. Define the Purpose of Your Research

The first step to writing an abstract is clearly outlining your research's general objective and purpose. To do it, answer the following question: What theoretical or practical issue does your study address, and which topic do you want to investigate?

It's better to avoid providing extensive background. Instead, give a brief answer to why your topic is essential. Also, don’t forget to explain all the technical words and terms if you plan to use them in your research.

2. Review the Requirements

You may receive specific requirements from your instructor about the length or style of your project. Neglecting them can result in failing your assignment. That's why it's best to review all the requirements before writing an abstract.

3. Explain the Problem and the Methods

This step requires you to outline a particular issue that your research focuses on and aims to resolve.

• Determine the focus of your study as well as your main arguments.
• Additionally, explain the methodology that you’ve used to make your arguments.
• Don’t forget to mention the evidence that proves your point.

4. Summarize the Findings

Every abstract requires a summary of the research's key findings. If you can’t cover everything, emphasize only the most significant points. Try to draw attention to those aspects that will help the reader understand your conclusions.

5. Conclude

The final step is to conclude your abstract. You can do it by addressing the significance of your findings and the role of your entire research. Note that you will need to write a summary for both types of abstracts, yet only the informative abstract will require you to discuss the effects of your work.

📝 Abstract Example for Free

We've prepared an example of a good abstract made with the help of our online generator. Feel free to use it to boost your inspiration.

Supplies and reserves affect the company's performance, so the choice of methods for controlling the inventory is a critical topic in modern management.

This research aims to study the possibilities of implementing the most effective inventory management system at the enterprise.

This work presents the results of quantitative and qualitative studies of the existing methods of inventory management. The data obtained made it possible to identify the advantages and disadvantages of various methods. Additionally, this research provides recommendations for using different inventory management systems, such as ERP and GSRP.

We hope that you've enjoyed our guide! To get an even better result, try our free abstract generator online. It will help you save time and enhance your academic writing skills. Good luck!

We also recommend using our conclusion generator and research question maker .

❓ AI Abstract Generator FAQ

❓ is there an abstract generator.

You can try out different apps on the internet, but our tool is definitely the best. StudyCorgi’s abstract generator is 100% free and unlimited. Besides, you can use it on any device. Try it out!

❓ How do I create an abstract online?

You can create an abstract using our abstract generator online. To do it, simply fill in all empty fields and press “Generate.” After creating your abstract, you can copy it and polish it however you like. This is how you make a perfect abstract online!

❓ Can AI write an abstract for me?

Our generator's AI can make an abstract for any subject or topic. It has a machine-learning system and can generate abstracts like a real human writer. You can use abstracts made by our app however you want—there are no copyright restrictions!

❓ Is 150 words good for an abstract?

The answer depends on the length of your research paper and the abstract type. For example, if you need to create a descriptive abstract, then 150 words is too lengthy. If your abstract is informative, then its length should be around 150-200 words.

Updated: Jun 5th, 2024

🔗 References

• Writing an Abstract for Your Research Paper: University of Wisconsin – Madison
• Writing an Abstract: The University of Melbourne
• Organizing Your Social Sciences Research Paper: The Abstract: University of Southern California
• Abstract Samples: Michigan State University
• Writing an Abstract: George Madison University

Free Abstract Generator for Research Papers

• 🚀 Meet Our Abstract Generator

📃 What Is an Abstract?

• ✍️ How to Write an Abstract
• 🫣 7 Mistakes You Should Avoid

🔗 References

🚀 meet our abstract generator for research papers.

The abstract provides a brief overview of the research assignment. So, this part gives a general assessment of the work and encourages the reader to explore it further. Almost every student dealt with the difficult task of condensing their research results into several hundred words. But that’s not a problem anymore!

We used artificial intelligence to make a tool that will make your academic life more enjoyable . You can get an excellent example of an abstract specifically for your research paper in minutes. To do this, you need to specify the reason for the research, the problems, and the goals. Also, we recommend mentioning the methodology and your findings to ensure the outcome is accurate. After that, the AI abstract maker will do the rest for you!

Key Reasons to Use Our Online Abstract Generator

Students juggle various assignments and obligations. Research papers are among the most challenging tasks they have to complete. What makes them so difficult is the sheer volume of information and study involved. Dealing with large amounts of material often leaves students drained and incapable of summarizing their work correctly.

Our abstract generator for research papers makes this process more straightforward thanks to several factors:

Abstracts provide short summaries of larger works, including research papers and dissertations. Readers scan them to decide whether or not they wish to continue reading the rest of the paper. In about 150–200 words, you should state the problem and provide the research goal, results, implications, and used methods.

One should write research abstracts only after the rest of the work is ironed out and ready. While this part of research may seem insignificant, students should take the time to write the abstract well. Doing so lets them identify any flaws in the research methodology and results.

Types of Research Paper Abstracts

Many students believe that abstracts come only in one type. In reality, there are several versions of summaries used in academic circles.

• Critical Abstract . These are the most extensive abstracts, at around 450 words. Unlike other entries on this list, they encourage deep analysis: for example, a discussion about the validity or reliability of their studies. It’s mostly used in social science research .
• Descriptive Abstract . This format is quite similar to informative abstracts but much shorter. On average, this type is only 100 words long and covers the main focus of the studies. Descriptive summaries offer no conclusions or recommendations for further research.
• Highlight Abstract . Students rarely get to use this type, as its primary goal is to get the reader’s attention. Highlight abstracts don’t helpfully summarize papers . Instead, they concentrate on the unique parts of the research, such as its results and conclusions.
• Informative Abstract . This is the most common type used by researchers and writers. It provides primary information about research concepts, methodology, findings, and recommendations. Sometimes, informative research abstracts have keywords listed at the bottom, but this practice is mainly reserved for professional publications.

✍️ How to Write an Abstract in 5 Steps

Despite the incredible versatility of our abstract generator, it’s still important to learn how to make abstracts on your own. We’ve dedicated this part of the guide to the five steps of writing these summaries. So, these instructions will help you create an abstract for any academic paper.

• Write the paper . To create an abstract, you first need a research paper. Create an outline of the study detailing the problem and methods you’ll use to address it. Explain the research methodology, state what information can be extracted from it, and show how the findings apply to the overall field of study.
• Review paper requirements . Once you’re done with the draft, review the criteria provided by the educational institution. Use the supporting documents with instructions, as they can clarify the requirements for the work's style, formatting, and length. Different disciplines require specific styles, so read this information carefully.
• Consider the audience . When working on an abstract, it’s crucial to identify who will be reading it afterward. For example, students often adjust their language to reach the general public and not only their respective professors.
• Write the abstract . Now, write the abstract based on the provided requirements. Use the body of the research to summarize the problem, explain the methods used in the paper , and show what their results were. Finish the summary by telling why your findings are valuable to the study field and what can be done in further research.
• Iron it out . Like with all writing pieces, it's essential to review the abstract and check if it has all the necessary components. The text should be easy to follow, cover all points, and be informative. As the abstract creates the first impression, make it a good one.

Abstract Formats: MLA & APA Styles

Abstract types aren’t the only things students should look out for. In academic settings, several formatting styles detail how the text should look on paper. The majority of US colleges use two popular methods: MLA and APA . Here, we discuss how abstracts look in each of them.

• Abstracts have their own page directly after the title or cover pages.
• In the APA style, the first line on the page is the word “Abstract” in the center without quotation marks.
• The following line in APA abstracts summarizes the critical points of the research. It introduces the main topic, questions, methodology, findings, and conclusions.
• Use double spaces and make the abstract under 250 words.
• Include keywords after the summary in APA format to help people find the work in various databases.
• Start with a sentence that contains the thesis statement and reason for readers to care about the research.
• Use short and simple sentences with precise words and phrases, as the abstract needs to be easy-to-understand.
• Use transitional words and phrases to make the writing flow and connect ideas more efficiently.
• Edit the abstract until it is 5-7 sentences long or under 250 words.
• Avoid using footnotes and citations.

🫣 7 Mistakes You Should Avoid When Writing an Abstract

Writing abstracts is a pretty straightforward process. But it doesn’t mean that everybody is immune from making mistakes, especially after spending days toiling away on a research paper.

There are seven common errors everybody should check before submitting an abstract.

• Making it too long . A summary should concisely describe the whole paper. Avoid repetition and details that have little to do with the research.
• Using chopped-up sentences . Ensure that your paper contains only complete sentences. It makes the work more professional and easier to comprehend.
• Adding too much technical jargon . Keep things simple so that anyone reading the abstract understands what it’s about. It will also make more people check out your paper.
• Not correcting the text . Sometimes, students want to finish a work without editing it too much. Take the time and comb the document for errors and factual mistakes.
• Failing to explain the significance of the research . The first couple of sentences should give readers a clear understanding of why the study is essential.
• Using the wrong tense . It’s recommended that abstracts be written in the past tense. Some academic institutions won’t accept papers with improperly written abstracts.
• Too many adjectives and hyperboles . You aren’t writing a 19th-century novel but an academic paper. The work should reflect that, so avoid using too many literary devices .

We hope you’ve found this article interesting and helpful in your academic pursuits. We also suggest taking a look at our guide for creating an excellent research paper . If you have any more questions about the art of writing abstracts, check out the FAQ section below.

❓ Research Abstract Generator – FAQ

• It’s written for the right audience.
• It's in the past tense and third person.
• Stands alone on the page.
• Has keywords and critical references.
• Reason for writing it and the importance of the research.
• Problematics the work attempts to solve.
• Methodology behind the study.
• Results backed by specific data.
• Practical and theoretical applications of the findings.

Updated: Oct 25th, 2023

• What Exactly is an Abstract? – Regents of the University of Michigan
• Abstract and Keywords Guide. – American Psychological Association
• Writing an Abstract. – The University of Melbourne
• Six Steps to Write an Abstract. – The University of Alabama
• How To Write an Abstract in 7 Steps (With an Example). – Indeed
• MLA Formatting: How Do I Do: An Abstract. – Warner Pacific University Library
• Abstracts. – The Writing Center, University of North Carolina at Chapel Hill
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This article offers an excellent generator for students to craft compelling abstracts. Also, you can explore our guide and tips on writing an abstract for research papers. Learn how to streamline the abstract-writing process and ensure your work gets the attention it deserves.

Research Paper Abstract Generator

Writing the abstract for your research paper, dissertation, or book chapter is usually one of the final steps before you submit your work. It’s also the activity that many students and researchers find most difficult. A strong abstract must be clear, succinct and informative, but how do you decide what to include?

Structuring your abstract

Many journals require the abstract to be structured according to

whereas the abstract for your dissertation or chapter may just be a short narrative paragraph. Either way, the abstract should contain key information from the study and be easy to read. Creating an abstract is as much an art as a science.

Happily, Scholarcy can help by identifying exactly the right information to include in your abstract.

Abstract in numbers

4 steps to generate an abstract with scholarcy, upload your article.

Simply upload your article to Scholarcy Library to generate a summary flashcard that outlines your research and contains the information needed to create your abstract.

View Scholarcy Highlights

The Scholarcy Highlights tab contains 5-7 bullet points comprising the background to the study, the key findings, and the conclusion.

View Scholarcy Summary

If your paper contains standard IMRaD sections, then the Scholarcy Summary will automatically be structured to follow these headings and will include any study objectives that you have written.

And the Study subjects and participants tab extracts key information about study participants, interventions, and quantitative results. Perfect for your abstract!

Try Smart Synopsis

Alternatively, for your dissertation or book chapter, you can use our Smart Synopses tool to create a more naturally flowing, narrative abstract.

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Generate accurate APA citations for free

• Knowledge Base
• APA Style 7th edition
• How to write and format an APA abstract

APA Abstract (2020) | Formatting, Length, and Keywords

Published on November 6, 2020 by Raimo Streefkerk . Revised on January 17, 2024.

An APA abstract is a comprehensive summary of your paper in which you briefly address the research problem , hypotheses , methods , results , and implications of your research. It’s placed on a separate page right after the title page and is usually no longer than 250 words.

Most professional papers that are submitted for publication require an abstract. Student papers typically don’t need an abstract, unless instructed otherwise.

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Table of contents

How to format the abstract, how to write an apa abstract, which keywords to use, frequently asked questions, apa abstract example.

Formatting instructions

Follow these five steps to format your abstract in APA Style:

• Insert a running head (for a professional paper—not needed for a student paper) and page number.
• Set page margins to 1 inch (2.54 cm).
• Write “Abstract” (bold and centered) at the top of the page.
• Do not indent the first line.
• Double-space the text.
• Use a legible font like Times New Roman (12 pt.).
• Limit the length to 250 words.
• Indent the first line 0.5 inches.
• Write the label “Keywords:” (italicized).
• Write keywords in lowercase letters.
• Separate keywords with commas.
• Do not use a period after the keywords.

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The abstract is a self-contained piece of text that informs the reader what your research is about. It’s best to write the abstract after you’re finished with the rest of your paper.

The questions below may help structure your abstract. Try answering them in one to three sentences each.

• What is the problem? Outline the objective, research questions , and/or hypotheses .
• What has been done? Explain your research methods .
• What did you discover? Summarize the key findings and conclusions .
• What do the findings mean? Summarize the discussion and recommendations .

Check out our guide on how to write an abstract for more guidance and an annotated example.

Guide: writing an abstract

At the end of the abstract, you may include a few keywords that will be used for indexing if your paper is published on a database. Listing your keywords will help other researchers find your work.

Choosing relevant keywords is essential. Try to identify keywords that address your topic, method, or population. APA recommends including three to five keywords.

An abstract is a concise summary of an academic text (such as a journal article or dissertation ). It serves two main purposes:

• To help potential readers determine the relevance of your paper for their own research.
• To communicate your key findings to those who don’t have time to read the whole paper.

Abstracts are often indexed along with keywords on academic databases, so they make your work more easily findable. Since the abstract is the first thing any reader sees, it’s important that it clearly and accurately summarizes the contents of your paper.

An APA abstract is around 150–250 words long. However, always check your target journal’s guidelines and don’t exceed the specified word count.

In an APA Style paper , the abstract is placed on a separate page after the title page (page 2).

Avoid citing sources in your abstract . There are two reasons for this:

• The abstract should focus on your original research, not on the work of others.
• The abstract should be self-contained and fully understandable without reference to other sources.

There are some circumstances where you might need to mention other sources in an abstract: for example, if your research responds directly to another study or focuses on the work of a single theorist. In general, though, don’t include citations unless absolutely necessary.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Streefkerk, R. (2024, January 17). APA Abstract (2020) | Formatting, Length, and Keywords. Scribbr. Retrieved June 25, 2024, from https://www.scribbr.com/apa-style/apa-abstract/

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Best Abstract Generator: Generate Abstracts For Research Papers 

In the ever-evolving landscape of academic research, AI-powered tools are revolutionising the art of abstract writing. Abstrazer, Scholarcy, WriteFull, and ChatGPT are leading the charge, offering students and researchers efficient ways to condense extensive research into concise summaries.

Harnessing advanced AI algorithms, these tools ensure clarity, grammatical accuracy, and relevance, catering to a diverse range of academic needs. Which of these tools are best for you? Let’s find out.

Best Online Abstract Generator Tool

Abstrazer offers students and researchers a unique platform to automatically generate abstracts for their research papers, cutting down the arduous process of abstract writing.

Given the specific requirements of abstracts, which typically hover between 150 to 250 words, this tool ensures conciseness without omitting key information.

The strength of Abstrazer lies in its advanced AI technology, which streamlines the abstract generation process.

If you’re grappling with summarizing your paper’s key findings and methods, Abstrazer provides a concise summary by eliminating unnecessary details and highlighting only the pivotal points.

It’s been designed to cater to a wide range of users, ensuring a well-structured abstract irrespective of the academic paper’s complexity.

What sets Abstrazer apart is its versatility. For instance, if one’s specific requirement revolves around APA formatting, the abstract generator utilizes advanced AI feature ensures accurate formatting with spot-on language edits.

This online abstract maker is especially handy when the task of abstract creation seems daunting. With a few inputs, Abstrazer simplifies the process of creating compelling abstracts that resonate with the intended audience.

Additionally, this AI-based tool is also available within various academic platforms through plugins, making it a handy tool on both mobile and desktop interfaces.

For those aiming for error-free, high-quality abstracts, Abstrazer is the go-to tool. It promises efficiency, saving precious time and effort, while still ensuring the final output gives the reader an apt snapshot of the research, making the academic journey a tad easier.

Scholarcy, an online abstract generator, offers a solution for students and researchers grappling with the challenge of abstract writing.

With the increasing demand for a tool to create concise summaries, this AI-powered abstract generator has risen to the occasion. While writing an abstract can be challenging, this tool simplifies the process of creating engaging and compelling abstracts for your research paper.

To use this tool, simply upload your academic paper. Within seconds, Scholarcy automatically generates an abstract that’s well-structured and caters to a wide range of users.

Its AI-based technology reads the entire paper, from introduction to conclusion, and provides a concise summary, highlighting key findings and key points without unnecessary details. The resulting abstract is typically between 150 to 250 words, making it apt for publication guidelines.

What makes Scholarcy stand out is its advanced AI technology. This abstract generator APA utilizes advanced algorithms to ensure abstracts are grammatically correct and error-free.

The abstract generator is a versatile tool, ideal for:

• Literature reviews
• Academic articles

For those with specific requirements, Scholarcy offers language edits to ensure conciseness and accuracy. Additionally, the abstract creator offers plugins for both mobile and desktop, making it accessible to a vast audience.

This free abstract generator saves time and effort, eliminating the struggle to write abstracts manually. 

One notable feature is the daily quota for free abstract generation, ensuring users can create abstracts without any cost. However, for those requiring more, premium options are also available within the platform. 

Writefull is an AI-powered tool designed to aid researchers in creating well-structured abstracts for their academic papers.

It’s no secret that generating an abstract can be challenging; after all, summarizing months or even years of research into a concise summary isn’t easy.

This is where the Writefull’s abstract generator steps in, simplifying the process of creating compelling abstracts by using advanced AI technology.

The online abstract maker allows you to paste content from your research paper – from the introduction to the conclusion – and automatically generates an abstract, honing in on the key points and findings of your work.

The beauty of this tool is its ability to produce high-quality abstracts without any cost. The abstract generator online not only ensures accurate and concise summaries but also saves time and effort, especially for students and researchers who have a tight daily quota or are on tight deadlines.

In addition to abstract writing, Writefull also offers a title generator to help craft the perfect headline for your research paper. The tool caters to a wide range of users, providing a concise summary while removing unnecessary details, ensuring grammatical accuracy and an error-free result.

But Writefull’s features don’t end there. This versatile tool also offers:

• Paraphrasing option
• Aids in language edits, and
• An ‘Academizer’ feature that turns informal text into formal academic language. 

Fascinatingly, the abstract generator APA utilizes advanced AI to distinguish content generated by AI from original text, ensuring the authenticity of your work.

Moreover, the platform is accessible both on mobile and desktop and even offers plugins for instant access. For those who prioritize conciseness and accuracy, Writefull is the go-to solution, ready to serve specific requirements and create engaging abstracts within seconds.

ChatGPT, developed by OpenAI, is a potent abstract generator that, when used right, can provide a high-quality abstract tailored to your academic paper.

Its development process is grounded on extensive datasets, which allows the tool to create abstracts that are not only coherent but original.

This AI-powered abstract generator is a versatile tool that can cater to a wide range of users, from students trying to generate an abstract for their thesis to seasoned researchers working on extensive literature reviews.

One of the unique features of ChatGPT is its ability to generate abstracts based on specific prompts provided by the user.

With just a few clicks, ChatGPT automatically generates an abstract, streamlining the abstract writing process and ensuring conciseness. Users have found it helpful, especially when dealing with specific requirements for their abstracts, which often must be between 150 to 250 words.

This AI-based tool ensures the elimination of unnecessary details, highlighting only the key points that give the reader a well-structured summary of the research.

It’s like having an AI writing assistant that helps you write abstracts efficiently.

While ChatGPT simplifies the process of creating abstracts, it’s essential to note that this AI tool should supplement and not replace the expertise of the researcher. It saves time and effort, but the output should always be reviewed for grammatical accuracy and relevance.

In an ever-evolving academic landscape, the introduction of tools like ChatGPT, powered by advanced AI, is a testament to how technology can assist students and researchers in producing error-free, compelling abstracts for their work.

Wrapping Up: Generate An Abstract From A Research Paper Easily

Navigating the realm of academic research, tools like Abstrazer, Scholarcy, WriteFull, and ChatGPT are leveraging advanced AI to simplify abstract creation. Each offers unique features, from automatic abstract generation to specific formatting like APA.

Designed to cater to various users, from students to seasoned researchers, these platforms streamline the abstract-writing process, ensuring concise and coherent summaries. They highlight the potential of AI in academic writing, merging efficiency with quality.

Dr Andrew Stapleton has a Masters and PhD in Chemistry from the UK and Australia. He has many years of research experience and has worked as a Postdoctoral Fellow and Associate at a number of Universities. Although having secured funding for his own research, he left academia to help others with his YouTube channel all about the inner workings of academia and how to make it work for you.

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• How to Write an Abstract

Expedite peer review, increase search-ability, and set the tone for your study

The abstract is your chance to let your readers know what they can expect from your article. Learn how to write a clear, and concise abstract that will keep your audience reading.

How your abstract impacts editorial evaluation and future readership

After the title , the abstract is the second-most-read part of your article. A good abstract can help to expedite peer review and, if your article is accepted for publication, it’s an important tool for readers to find and evaluate your work. Editors use your abstract when they first assess your article. Prospective reviewers see it when they decide whether to accept an invitation to review. Once published, the abstract gets indexed in PubMed and Google Scholar , as well as library systems and other popular databases. Like the title, your abstract influences keyword search results. Readers will use it to decide whether to read the rest of your article. Other researchers will use it to evaluate your work for inclusion in systematic reviews and meta-analysis. It should be a concise standalone piece that accurately represents your research. 

What to include in an abstract

The main challenge you’ll face when writing your abstract is keeping it concise AND fitting in all the information you need. Depending on your subject area the journal may require a structured abstract following specific headings. A structured abstract helps your readers understand your study more easily. If your journal doesn’t require a structured abstract it’s still a good idea to follow a similar format, just present the abstract as one paragraph without headings. 

Background or Introduction – What is currently known? Start with a brief, 2 or 3 sentence, introduction to the research area. 

Objectives or Aims – What is the study and why did you do it? Clearly state the research question you’re trying to answer.

Methods – What did you do? Explain what you did and how you did it. Include important information about your methods, but avoid the low-level specifics. Some disciplines have specific requirements for abstract methods. 

• CONSORT for randomized trials.
• STROBE for observational studies
• PRISMA for systematic reviews and meta-analyses

Results – What did you find? Briefly give the key findings of your study. Include key numeric data (including confidence intervals or p values), where possible.

Conclusions – What did you conclude? Tell the reader why your findings matter, and what this could mean for the ‘bigger picture’ of this area of research. 

Writing tips

The main challenge you may find when writing your abstract is keeping it concise AND convering all the information you need to.

• Keep it concise and to the point. Most journals have a maximum word count, so check guidelines before you write the abstract to save time editing it later.
• Write for your audience. Are they specialists in your specific field? Are they cross-disciplinary? Are they non-specialists? If you’re writing for a general audience, or your research could be of interest to the public keep your language as straightforward as possible. If you’re writing in English, do remember that not all of your readers will necessarily be native English speakers.
• Focus on key results, conclusions and take home messages.
• Write your paper first, then create the abstract as a summary.
• Check the journal requirements before you write your abstract, eg. required subheadings.
• Include keywords or phrases to help readers search for your work in indexing databases like PubMed or Google Scholar.
• Double and triple check your abstract for spelling and grammar errors. These kind of errors can give potential reviewers the impression that your research isn’t sound, and can make it easier to find reviewers who accept the invitation to review your manuscript. Your abstract should be a taste of what is to come in the rest of your article.

Don’t

• Sensationalize your research.
• Speculate about where this research might lead in the future.
• Use abbreviations or acronyms (unless absolutely necessary or unless they’re widely known, eg. DNA).
• Repeat yourself unnecessarily, eg. “Methods: We used X technique. Results: Using X technique, we found…”
• Contradict anything in the rest of your manuscript.
• Include content that isn’t also covered in the main manuscript.
• Include citations or references.

Tip: How to edit your work

Editing is challenging, especially if you are acting as both a writer and an editor. Read our guidelines for advice on how to refine your work, including useful tips for setting your intentions, re-review, and consultation with colleagues.

• How to Write a Great Title
• How to Write Your Methods
• How to Report Statistics
• How to Write Discussions and Conclusions
• How to Edit Your Work

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FAQs about Using AI Abstract Generator

What is an abstract.

An abstract is a concise summary that provides an overview of the main points or key elements of a document, research paper, or article.

What makes a good abstract in a research paper?

A good abstract in a research paper should effectively convey the study's purpose, methodology, results, and conclusion concisely and clearly. It should provide a quick overview of the essential information.

Can ChatGPT create abstracts for documents?

ChatGPT can assist in creating abstracts for documents by summarizing text-based content. However, it has a character limit, and for longer documents, it's recommended to use specialized AI tools designed for document summarization.

Is there a free online AI tool that generates abstracts for articles?

Yes, there are free online AI tools that generate abstracts for articles. HiPDF's AI Abstract Generator is one such tool that allows users to create abstracts for articles and other written materials.

What is the best AI abstract generator?

Determining the best AI abstract generator depends on specific needs and preferences. HiPDF's AI Abstract Generator, ChatGPT, and other tools like Sharly AI are among the popular choices, each with unique features.

Is there an AI abstract generator that can craft abstracts for scanned PDFs?

Certainly! For effective abstract generation from scanned PDFs, consider tools equipped with OCR (Optical Character Recognition) and summarization capabilities. PDFelement is a reliable option, utilizing OCR to extract text from scanned documents accurately and then using AI to analyze the PDF for abstract generation. This ensures precise and meaningful abstracts from your scanned PDFs.

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Revolutionize Your Lab Work with the Brand-New AI Abstract Generator Tool!

Mindgrasp recently released apa abstract generator.

published 1/10/2023 by Mindgrasp

Big names like Chegg, ChatGPT, and Quizlet have taken loads off of students’ backs for years. We know how painful it is watching peers breeze through their homework plugging in each question and getting neat answers and examples of work.

Finally, researchers’ calls have been answered with an abstract summary generator. The tool for simplifying the scientific writing process is here and it’s powered by Artificial Intelligence. AI has come a long way and it’s normal to be skeptical of the new technology. We challenge you to synthesize your next report faster than Mindgrasp’s automatic abstract maker. Using state-of-the-art tech you’re able to create an abstract by pasting long text from your APA report, other online abstracts, research sources, and notes right into the software. Doing this cuts down on the countless hours spent combing through your own lab jargon to simplify and write an abstract. If you haven’t saved hours of time on your writing, we are willing to bet you couldn’t write a better summary quicker. No more stressing over plagiarism! With an abstract generator tool, you can get completely original outputs and stay on the right side of academic integrity. The text output is written at a professional academic writing level so there are also no worries a professor wouldn’t take this abstract generator’s APA citing seriously. Try out the advanced tools of the future! In just a few moments, you can save hours of work on your next report.

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Generate a Research Abstract from a Title

Wordblot has so many potential uses. Within academic writing, a common problem is generating the abstract. So give it a spin and enter a title to see if we can help you with an abstract.

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Free AI Abstract Generator: Abstrazer

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What this handout is about

This handout provides definitions and examples of the two main types of abstracts: descriptive and informative. It also provides guidelines for constructing an abstract and general tips for you to keep in mind when drafting. Finally, it includes a few examples of abstracts broken down into their component parts.

What is an abstract?

An abstract is a self-contained, short, and powerful statement that describes a larger work. Components vary according to discipline. An abstract of a social science or scientific work may contain the scope, purpose, results, and contents of the work. An abstract of a humanities work may contain the thesis, background, and conclusion of the larger work. An abstract is not a review, nor does it evaluate the work being abstracted. While it contains key words found in the larger work, the abstract is an original document rather than an excerpted passage.

Why write an abstract?

You may write an abstract for various reasons. The two most important are selection and indexing. Abstracts allow readers who may be interested in a longer work to quickly decide whether it is worth their time to read it. Also, many online databases use abstracts to index larger works. Therefore, abstracts should contain keywords and phrases that allow for easy searching.

Say you are beginning a research project on how Brazilian newspapers helped Brazil’s ultra-liberal president Luiz Ignácio da Silva wrest power from the traditional, conservative power base. A good first place to start your research is to search Dissertation Abstracts International for all dissertations that deal with the interaction between newspapers and politics. “Newspapers and politics” returned 569 hits. A more selective search of “newspapers and Brazil” returned 22 hits. That is still a fair number of dissertations. Titles can sometimes help winnow the field, but many titles are not very descriptive. For example, one dissertation is titled “Rhetoric and Riot in Rio de Janeiro.” It is unclear from the title what this dissertation has to do with newspapers in Brazil. One option would be to download or order the entire dissertation on the chance that it might speak specifically to the topic. A better option is to read the abstract. In this case, the abstract reveals the main focus of the dissertation:

This dissertation examines the role of newspaper editors in the political turmoil and strife that characterized late First Empire Rio de Janeiro (1827-1831). Newspaper editors and their journals helped change the political culture of late First Empire Rio de Janeiro by involving the people in the discussion of state. This change in political culture is apparent in Emperor Pedro I’s gradual loss of control over the mechanisms of power. As the newspapers became more numerous and powerful, the Emperor lost his legitimacy in the eyes of the people. To explore the role of the newspapers in the political events of the late First Empire, this dissertation analyzes all available newspapers published in Rio de Janeiro from 1827 to 1831. Newspapers and their editors were leading forces in the effort to remove power from the hands of the ruling elite and place it under the control of the people. In the process, newspapers helped change how politics operated in the constitutional monarchy of Brazil.

From this abstract you now know that although the dissertation has nothing to do with modern Brazilian politics, it does cover the role of newspapers in changing traditional mechanisms of power. After reading the abstract, you can make an informed judgment about whether the dissertation would be worthwhile to read.

Besides selection, the other main purpose of the abstract is for indexing. Most article databases in the online catalog of the library enable you to search abstracts. This allows for quick retrieval by users and limits the extraneous items recalled by a “full-text” search. However, for an abstract to be useful in an online retrieval system, it must incorporate the key terms that a potential researcher would use to search. For example, if you search Dissertation Abstracts International using the keywords “France” “revolution” and “politics,” the search engine would search through all the abstracts in the database that included those three words. Without an abstract, the search engine would be forced to search titles, which, as we have seen, may not be fruitful, or else search the full text. It’s likely that a lot more than 60 dissertations have been written with those three words somewhere in the body of the entire work. By incorporating keywords into the abstract, the author emphasizes the central topics of the work and gives prospective readers enough information to make an informed judgment about the applicability of the work.

When do people write abstracts?

• when submitting articles to journals, especially online journals
• when applying for research grants
• when writing a book proposal
• when completing the Ph.D. dissertation or M.A. thesis
• when writing a proposal for a conference paper
• when writing a proposal for a book chapter

Most often, the author of the entire work (or prospective work) writes the abstract. However, there are professional abstracting services that hire writers to draft abstracts of other people’s work. In a work with multiple authors, the first author usually writes the abstract. Undergraduates are sometimes asked to draft abstracts of books/articles for classmates who have not read the larger work.

Types of abstracts

There are two types of abstracts: descriptive and informative. They have different aims, so as a consequence they have different components and styles. There is also a third type called critical, but it is rarely used. If you want to find out more about writing a critique or a review of a work, see the UNC Writing Center handout on writing a literature review . If you are unsure which type of abstract you should write, ask your instructor (if the abstract is for a class) or read other abstracts in your field or in the journal where you are submitting your article.

Descriptive abstracts

A descriptive abstract indicates the type of information found in the work. It makes no judgments about the work, nor does it provide results or conclusions of the research. It does incorporate key words found in the text and may include the purpose, methods, and scope of the research. Essentially, the descriptive abstract describes the work being abstracted. Some people consider it an outline of the work, rather than a summary. Descriptive abstracts are usually very short—100 words or less.

Informative abstracts

The majority of abstracts are informative. While they still do not critique or evaluate a work, they do more than describe it. A good informative abstract acts as a surrogate for the work itself. That is, the writer presents and explains all the main arguments and the important results and evidence in the complete article/paper/book. An informative abstract includes the information that can be found in a descriptive abstract (purpose, methods, scope) but also includes the results and conclusions of the research and the recommendations of the author. The length varies according to discipline, but an informative abstract is rarely more than 10% of the length of the entire work. In the case of a longer work, it may be much less.

Here are examples of a descriptive and an informative abstract of this handout on abstracts . Descriptive abstract:

The two most common abstract types—descriptive and informative—are described and examples of each are provided.

Informative abstract:

Abstracts present the essential elements of a longer work in a short and powerful statement. The purpose of an abstract is to provide prospective readers the opportunity to judge the relevance of the longer work to their projects. Abstracts also include the key terms found in the longer work and the purpose and methods of the research. Authors abstract various longer works, including book proposals, dissertations, and online journal articles. There are two main types of abstracts: descriptive and informative. A descriptive abstract briefly describes the longer work, while an informative abstract presents all the main arguments and important results. This handout provides examples of various types of abstracts and instructions on how to construct one.

Which type should I use?

Your best bet in this case is to ask your instructor or refer to the instructions provided by the publisher. You can also make a guess based on the length allowed; i.e., 100-120 words = descriptive; 250+ words = informative.

How do I write an abstract?

The format of your abstract will depend on the work being abstracted. An abstract of a scientific research paper will contain elements not found in an abstract of a literature article, and vice versa. However, all abstracts share several mandatory components, and there are also some optional parts that you can decide to include or not. When preparing to draft your abstract, keep the following key process elements in mind:

• Reason for writing: What is the importance of the research? Why would a reader be interested in the larger work?
• Problem: What problem does this work attempt to solve? What is the scope of the project? What is the main argument/thesis/claim?
• Methodology: An abstract of a scientific work may include specific models or approaches used in the larger study. Other abstracts may describe the types of evidence used in the research.
• Results: Again, an abstract of a scientific work may include specific data that indicates the results of the project. Other abstracts may discuss the findings in a more general way.
• Implications: What changes should be implemented as a result of the findings of the work? How does this work add to the body of knowledge on the topic?

(This list of elements is adapted with permission from Philip Koopman, “How to Write an Abstract.” )

All abstracts include:

• A full citation of the source, preceding the abstract.
• The most important information first.
• The same type and style of language found in the original, including technical language.
• Key words and phrases that quickly identify the content and focus of the work.
• Clear, concise, and powerful language.

Abstracts may include:

• The thesis of the work, usually in the first sentence.
• Background information that places the work in the larger body of literature.
• The same chronological structure as the original work.

How not to write an abstract:

• Do not refer extensively to other works.
• Do not add information not contained in the original work.
• Do not define terms.

If you are abstracting your own writing

When abstracting your own work, it may be difficult to condense a piece of writing that you have agonized over for weeks (or months, or even years) into a 250-word statement. There are some tricks that you could use to make it easier, however.

Reverse outlining:

This technique is commonly used when you are having trouble organizing your own writing. The process involves writing down the main idea of each paragraph on a separate piece of paper– see our short video . For the purposes of writing an abstract, try grouping the main ideas of each section of the paper into a single sentence. Practice grouping ideas using webbing or color coding .

For a scientific paper, you may have sections titled Purpose, Methods, Results, and Discussion. Each one of these sections will be longer than one paragraph, but each is grouped around a central idea. Use reverse outlining to discover the central idea in each section and then distill these ideas into one statement.

Cut and paste:

To create a first draft of an abstract of your own work, you can read through the entire paper and cut and paste sentences that capture key passages. This technique is useful for social science research with findings that cannot be encapsulated by neat numbers or concrete results. A well-written humanities draft will have a clear and direct thesis statement and informative topic sentences for paragraphs or sections. Isolate these sentences in a separate document and work on revising them into a unified paragraph.

If you are abstracting someone else’s writing

When abstracting something you have not written, you cannot summarize key ideas just by cutting and pasting. Instead, you must determine what a prospective reader would want to know about the work. There are a few techniques that will help you in this process:

Identify key terms:

Search through the entire document for key terms that identify the purpose, scope, and methods of the work. Pay close attention to the Introduction (or Purpose) and the Conclusion (or Discussion). These sections should contain all the main ideas and key terms in the paper. When writing the abstract, be sure to incorporate the key terms.

Highlight key phrases and sentences:

Instead of cutting and pasting the actual words, try highlighting sentences or phrases that appear to be central to the work. Then, in a separate document, rewrite the sentences and phrases in your own words.

Don’t look back:

After reading the entire work, put it aside and write a paragraph about the work without referring to it. In the first draft, you may not remember all the key terms or the results, but you will remember what the main point of the work was. Remember not to include any information you did not get from the work being abstracted.

Revise, revise, revise

No matter what type of abstract you are writing, or whether you are abstracting your own work or someone else’s, the most important step in writing an abstract is to revise early and often. When revising, delete all extraneous words and incorporate meaningful and powerful words. The idea is to be as clear and complete as possible in the shortest possible amount of space. The Word Count feature of Microsoft Word can help you keep track of how long your abstract is and help you hit your target length.

Example 1: Humanities abstract

Kenneth Tait Andrews, “‘Freedom is a constant struggle’: The dynamics and consequences of the Mississippi Civil Rights Movement, 1960-1984” Ph.D. State University of New York at Stony Brook, 1997 DAI-A 59/02, p. 620, Aug 1998

This dissertation examines the impacts of social movements through a multi-layered study of the Mississippi Civil Rights Movement from its peak in the early 1960s through the early 1980s. By examining this historically important case, I clarify the process by which movements transform social structures and the constraints movements face when they try to do so. The time period studied includes the expansion of voting rights and gains in black political power, the desegregation of public schools and the emergence of white-flight academies, and the rise and fall of federal anti-poverty programs. I use two major research strategies: (1) a quantitative analysis of county-level data and (2) three case studies. Data have been collected from archives, interviews, newspapers, and published reports. This dissertation challenges the argument that movements are inconsequential. Some view federal agencies, courts, political parties, or economic elites as the agents driving institutional change, but typically these groups acted in response to the leverage brought to bear by the civil rights movement. The Mississippi movement attempted to forge independent structures for sustaining challenges to local inequities and injustices. By propelling change in an array of local institutions, movement infrastructures had an enduring legacy in Mississippi.

Now let’s break down this abstract into its component parts to see how the author has distilled his entire dissertation into a ~200 word abstract.

What the dissertation does This dissertation examines the impacts of social movements through a multi-layered study of the Mississippi Civil Rights Movement from its peak in the early 1960s through the early 1980s. By examining this historically important case, I clarify the process by which movements transform social structures and the constraints movements face when they try to do so.

How the dissertation does it The time period studied in this dissertation includes the expansion of voting rights and gains in black political power, the desegregation of public schools and the emergence of white-flight academies, and the rise and fall of federal anti-poverty programs. I use two major research strategies: (1) a quantitative analysis of county-level data and (2) three case studies.

What materials are used Data have been collected from archives, interviews, newspapers, and published reports.

Conclusion This dissertation challenges the argument that movements are inconsequential. Some view federal agencies, courts, political parties, or economic elites as the agents driving institutional change, but typically these groups acted in response to movement demands and the leverage brought to bear by the civil rights movement. The Mississippi movement attempted to forge independent structures for sustaining challenges to local inequities and injustices. By propelling change in an array of local institutions, movement infrastructures had an enduring legacy in Mississippi.

Keywords social movements Civil Rights Movement Mississippi voting rights desegregation

Example 2: Science Abstract

Luis Lehner, “Gravitational radiation from black hole spacetimes” Ph.D. University of Pittsburgh, 1998 DAI-B 59/06, p. 2797, Dec 1998

The problem of detecting gravitational radiation is receiving considerable attention with the construction of new detectors in the United States, Europe, and Japan. The theoretical modeling of the wave forms that would be produced in particular systems will expedite the search for and analysis of detected signals. The characteristic formulation of GR is implemented to obtain an algorithm capable of evolving black holes in 3D asymptotically flat spacetimes. Using compactification techniques, future null infinity is included in the evolved region, which enables the unambiguous calculation of the radiation produced by some compact source. A module to calculate the waveforms is constructed and included in the evolution algorithm. This code is shown to be second-order convergent and to handle highly non-linear spacetimes. In particular, we have shown that the code can handle spacetimes whose radiation is equivalent to a galaxy converting its whole mass into gravitational radiation in one second. We further use the characteristic formulation to treat the region close to the singularity in black hole spacetimes. The code carefully excises a region surrounding the singularity and accurately evolves generic black hole spacetimes with apparently unlimited stability.

This science abstract covers much of the same ground as the humanities one, but it asks slightly different questions.

Why do this study The problem of detecting gravitational radiation is receiving considerable attention with the construction of new detectors in the United States, Europe, and Japan. The theoretical modeling of the wave forms that would be produced in particular systems will expedite the search and analysis of the detected signals.

What the study does The characteristic formulation of GR is implemented to obtain an algorithm capable of evolving black holes in 3D asymptotically flat spacetimes. Using compactification techniques, future null infinity is included in the evolved region, which enables the unambiguous calculation of the radiation produced by some compact source. A module to calculate the waveforms is constructed and included in the evolution algorithm.

Results This code is shown to be second-order convergent and to handle highly non-linear spacetimes. In particular, we have shown that the code can handle spacetimes whose radiation is equivalent to a galaxy converting its whole mass into gravitational radiation in one second. We further use the characteristic formulation to treat the region close to the singularity in black hole spacetimes. The code carefully excises a region surrounding the singularity and accurately evolves generic black hole spacetimes with apparently unlimited stability.

Keywords gravitational radiation (GR) spacetimes black holes

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

Belcher, Wendy Laura. 2009. Writing Your Journal Article in Twelve Weeks: A Guide to Academic Publishing Success. Thousand Oaks, CA: Sage Press.

Koopman, Philip. 1997. “How to Write an Abstract.” Carnegie Mellon University. October 1997. http://users.ece.cmu.edu/~koopman/essays/abstract.html .

Lancaster, F.W. 2003. Indexing And Abstracting in Theory and Practice , 3rd ed. London: Facet Publishing.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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Abstract Writing: A Step-by-Step Guide With Tips & Examples

Table of Contents

Introduction

Abstracts of research papers have always played an essential role in describing your research concisely and clearly to researchers and editors of journals, enticing them to continue reading. However, with the widespread availability of scientific databases, the need to write a convincing abstract is more crucial now than during the time of paper-bound manuscripts.

Abstracts serve to "sell" your research and can be compared with your "executive outline" of a resume or, rather, a formal summary of the critical aspects of your work. Also, it can be the "gist" of your study. Since most educational research is done online, it's a sign that you have a shorter time for impressing your readers, and have more competition from other abstracts that are available to be read.

The APCI (Academic Publishing and Conferences International) articulates 12 issues or points considered during the final approval process for conferences & journals and emphasises the importance of writing an abstract that checks all these boxes (12 points). Since it's the only opportunity you have to captivate your readers, you must invest time and effort in creating an abstract that accurately reflects the critical points of your research.

With that in mind, let’s head over to understand and discover the core concept and guidelines to create a substantial abstract. Also, learn how to organise the ideas or plots into an effective abstract that will be awe-inspiring to the readers you want to reach.

What is Abstract? Definition and Overview

The word "Abstract' is derived from Latin abstractus meaning "drawn off." This etymological meaning also applies to art movements as well as music, like abstract expressionism. In this context, it refers to the revealing of the artist's intention.

Based on this, you can determine the meaning of an abstract: A condensed research summary. It must be self-contained and independent of the body of the research. However, it should outline the subject, the strategies used to study the problem, and the methods implemented to attain the outcomes. The specific elements of the study differ based on the area of study; however, together, it must be a succinct summary of the entire research paper.

Abstracts are typically written at the end of the paper, even though it serves as a prologue. In general, the abstract must be in a position to:

• Describe the paper.
• Identify the problem or the issue at hand.
• Explain to the reader the research process, the results you came up with, and what conclusion you've reached using these results.
• Include keywords to guide your strategy and the content.

Furthermore, the abstract you submit should not reflect upon any of  the following elements:

• Examine, analyse or defend the paper or your opinion.
• What you want to study, achieve or discover.
• Be redundant or irrelevant.

After reading an abstract, your audience should understand the reason - what the research was about in the first place, what the study has revealed and how it can be utilised or can be used to benefit others. You can understand the importance of abstract by knowing the fact that the abstract is the most frequently read portion of any research paper. In simpler terms, it should contain all the main points of the research paper.

What is the Purpose of an Abstract?

Abstracts are typically an essential requirement for research papers; however, it's not an obligation to preserve traditional reasons without any purpose. Abstracts allow readers to scan the text to determine whether it is relevant to their research or studies. The abstract allows other researchers to decide if your research paper can provide them with some additional information. A good abstract paves the interest of the audience to pore through your entire paper to find the content or context they're searching for.

Abstract writing is essential for indexing, as well. The Digital Repository of academic papers makes use of abstracts to index the entire content of academic research papers. Like meta descriptions in the regular Google outcomes, abstracts must include keywords that help researchers locate what they seek.

Types of Abstract

Informative and Descriptive are two kinds of abstracts often used in scientific writing.

A descriptive abstract gives readers an outline of the author's main points in their study. The reader can determine if they want to stick to the research work, based on their interest in the topic. An abstract that is descriptive is similar to the contents table of books, however, the format of an abstract depicts complete sentences encapsulated in one paragraph. It is unfortunate that the abstract can't be used as a substitute for reading a piece of writing because it's just an overview, which omits readers from getting an entire view. Also, it cannot be a way to fill in the gaps the reader may have after reading this kind of abstract since it does not contain crucial information needed to evaluate the article.

To conclude, a descriptive abstract is:

• A simple summary of the task, just summarises the work, but some researchers think it is much more of an outline
• Typically, the length is approximately 100 words. It is too short when compared to an informative abstract.
• A brief explanation but doesn't provide the reader with the complete information they need;
• An overview that omits conclusions and results

An informative abstract is a comprehensive outline of the research. There are times when people rely on the abstract as an information source. And the reason is why it is crucial to provide entire data of particular research. A well-written, informative abstract could be a good substitute for the remainder of the paper on its own.

A well-written abstract typically follows a particular style. The author begins by providing the identifying information, backed by citations and other identifiers of the papers. Then, the major elements are summarised to make the reader aware of the study. It is followed by the methodology and all-important findings from the study. The conclusion then presents study results and ends the abstract with a comprehensive summary.

In a nutshell, an informative abstract:

• Has a length that can vary, based on the subject, but is not longer than 300 words.
• Contains all the content-like methods and intentions
• Offers evidence and possible recommendations.

Informative Abstracts are more frequent than descriptive abstracts because of their extensive content and linkage to the topic specifically. You should select different types of abstracts to papers based on their length: informative abstracts for extended and more complex abstracts and descriptive ones for simpler and shorter research papers.

What are the Characteristics of a Good Abstract?

• A good abstract clearly defines the goals and purposes of the study.
• It should clearly describe the research methodology with a primary focus on data gathering, processing, and subsequent analysis.
• A good abstract should provide specific research findings.
• It presents the principal conclusions of the systematic study.
• It should be concise, clear, and relevant to the field of study.
• A well-designed abstract should be unifying and coherent.
• It is easy to grasp and free of technical jargon.
• It is written impartially and objectively.

What are the various sections of an ideal Abstract?

By now, you must have gained some concrete idea of the essential elements that your abstract needs to convey . Accordingly, the information is broken down into six key sections of the abstract, which include:

An Introduction or Background

Research methodology, objectives and goals, limitations.

Let's go over them in detail.

The introduction, also known as background, is the most concise part of your abstract. Ideally, it comprises a couple of sentences. Some researchers only write one sentence to introduce their abstract. The idea behind this is to guide readers through the key factors that led to your study.

It's understandable that this information might seem difficult to explain in a couple of sentences. For example, think about the following two questions like the background of your study:

• What is currently available about the subject with respect to the paper being discussed?
• What isn't understood about this issue? (This is the subject of your research)

While writing the abstract’s introduction, make sure that it is not lengthy. Because if it crosses the word limit, it may eat up the words meant to be used for providing other key information.

Research methodology is where you describe the theories and techniques you used in your research. It is recommended that you describe what you have done and the method you used to get your thorough investigation results. Certainly, it is the second-longest paragraph in the abstract.

In the research methodology section, it is essential to mention the kind of research you conducted; for instance, qualitative research or quantitative research (this will guide your research methodology too) . If you've conducted quantitative research, your abstract should contain information like the sample size, data collection method, sampling techniques, and duration of the study. Likewise, your abstract should reflect observational data, opinions, questionnaires (especially the non-numerical data) if you work on qualitative research.

The research objectives and goals speak about what you intend to accomplish with your research. The majority of research projects focus on the long-term effects of a project, and the goals focus on the immediate, short-term outcomes of the research. It is possible to summarise both in just multiple sentences.

In stating your objectives and goals, you give readers a picture of the scope of the study, its depth and the direction your research ultimately follows. Your readers can evaluate the results of your research against the goals and stated objectives to determine if you have achieved the goal of your research.

In the end, your readers are more attracted by the results you've obtained through your study. Therefore, you must take the time to explain each relevant result and explain how they impact your research. The results section exists as the longest in your abstract, and nothing should diminish its reach or quality.

One of the most important things you should adhere to is to spell out details and figures on the results of your research.

Instead of making a vague assertion such as, "We noticed that response rates varied greatly between respondents with high incomes and those with low incomes", Try these: "The response rate was higher for high-income respondents than those with lower incomes (59 30 percent vs. 30 percent in both cases; P<0.01)."

You're likely to encounter certain obstacles during your research. It could have been during data collection or even during conducting the sample . Whatever the issue, it's essential to inform your readers about them and their effects on the research.

Research limitations offer an opportunity to suggest further and deep research. If, for instance, you were forced to change for convenient sampling and snowball samples because of difficulties in reaching well-suited research participants, then you should mention this reason when you write your research abstract. In addition, a lack of prior studies on the subject could hinder your research.

Your conclusion should include the same number of sentences to wrap the abstract as the introduction. The majority of researchers offer an idea of the consequences of their research in this case.

Your conclusion should include three essential components:

• A significant take-home message.
• Corresponding important findings.
• The Interpretation.

Even though the conclusion of your abstract needs to be brief, it can have an enormous influence on the way that readers view your research. Therefore, make use of this section to reinforce the central message from your research. Be sure that your statements reflect the actual results and the methods you used to conduct your research.

Good Abstract Examples

Abstract example #1.

Children’s consumption behavior in response to food product placements in movies.

The abstract:

"Almost all research into the effects of brand placements on children has focused on the brand's attitudes or behavior intentions. Based on the significant differences between attitudes and behavioral intentions on one hand and actual behavior on the other hand, this study examines the impact of placements by brands on children's eating habits. Children aged 6-14 years old were shown an excerpt from the popular film Alvin and the Chipmunks and were shown places for the item Cheese Balls. Three different versions were developed with no placements, one with moderately frequent placements and the third with the highest frequency of placement. The results revealed that exposure to high-frequency places had a profound effect on snack consumption, however, there was no impact on consumer attitudes towards brands or products. The effects were not dependent on the age of the children. These findings are of major importance to researchers studying consumer behavior as well as nutrition experts as well as policy regulators."

Abstract Example #2

Social comparisons on social media: The impact of Facebook on young women’s body image concerns and mood. The abstract:

"The research conducted in this study investigated the effects of Facebook use on women's moods and body image if the effects are different from an internet-based fashion journal and if the appearance comparison tendencies moderate one or more of these effects. Participants who were female ( N = 112) were randomly allocated to spend 10 minutes exploring their Facebook account or a magazine's website or an appearance neutral control website prior to completing state assessments of body dissatisfaction, mood, and differences in appearance (weight-related and facial hair, face, and skin). Participants also completed a test of the tendency to compare appearances. The participants who used Facebook were reported to be more depressed than those who stayed on the control site. In addition, women who have the tendency to compare appearances reported more facial, hair and skin-related issues following Facebook exposure than when they were exposed to the control site. Due to its popularity it is imperative to conduct more research to understand the effect that Facebook affects the way people view themselves."

Abstract Example #3

The Relationship Between Cell Phone Use and Academic Performance in a Sample of U.S. College Students

"The cellphone is always present on campuses of colleges and is often utilised in situations in which learning takes place. The study examined the connection between the use of cell phones and the actual grades point average (GPA) after adjusting for predictors that are known to be a factor. In the end 536 students in the undergraduate program from 82 self-reported majors of an enormous, public institution were studied. Hierarchical analysis ( R 2 = .449) showed that use of mobile phones is significantly ( p < .001) and negative (b equal to -.164) connected to the actual college GPA, after taking into account factors such as demographics, self-efficacy in self-regulated learning, self-efficacy to improve academic performance, and the actual high school GPA that were all important predictors ( p < .05). Therefore, after adjusting for other known predictors increasing cell phone usage was associated with lower academic performance. While more research is required to determine the mechanisms behind these results, they suggest the need to educate teachers and students to the possible academic risks that are associated with high-frequency mobile phone usage."

Quick tips on writing a good abstract

There exists a common dilemma among early age researchers whether to write the abstract at first or last? However, it's recommended to compose your abstract when you've completed the research since you'll have all the information to give to your readers. You can, however, write a draft at the beginning of your research and add in any gaps later.

If you find abstract writing a herculean task, here are the few tips to help you with it:

1. Always develop a framework to support your abstract

Before writing, ensure you create a clear outline for your abstract. Divide it into sections and draw the primary and supporting elements in each one. You can include keywords and a few sentences that convey the essence of your message.

2. Review Other Abstracts

Abstracts are among the most frequently used research documents, and thousands of them were written in the past. Therefore, prior to writing yours, take a look at some examples from other abstracts. There are plenty of examples of abstracts for dissertations in the dissertation and thesis databases.

3. Avoid Jargon To the Maximum

When you write your abstract, focus on simplicity over formality. You should  write in simple language, and avoid excessive filler words or ambiguous sentences. Keep in mind that your abstract must be readable to those who aren't acquainted with your subject.

4. Focus on Your Research

It's a given fact that the abstract you write should be about your research and the findings you've made. It is not the right time to mention secondary and primary data sources unless it's absolutely required.

Conclusion: How to Structure an Interesting Abstract?

Abstracts are a short outline of your essay. However, it's among the most important, if not the most important. The process of writing an abstract is not straightforward. A few early-age researchers tend to begin by writing it, thinking they are doing it to "tease" the next step (the document itself). However, it is better to treat it as a spoiler.

The simple, concise style of the abstract lends itself to a well-written and well-investigated study. If your research paper doesn't provide definitive results, or the goal of your research is questioned, so will the abstract. Thus, only write your abstract after witnessing your findings and put your findings in the context of a larger scenario.

The process of writing an abstract can be daunting, but with these guidelines, you will succeed. The most efficient method of writing an excellent abstract is to centre the primary points of your abstract, including the research question and goals methods, as well as key results.

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What is the ideal length of an abstract?

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• 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

• Donanemab for Alzheimer Disease—Who Benefits and Who Is Harmed? JAMA Editorial August 8, 2023 Jennifer J. Manly, PhD; Kacie D. Deters, PhD
• Amyloid-Targeting Monoclonal Antibodies for Alzheimer Disease JAMA Editorial August 8, 2023 Gil D. Rabinovici, MD; Renaud La Joie, PhD
• Novel Alzheimer Disease Treatments and Reconsideration of US Pharmaceutical Reimbursement Policy JAMA Editorial August 8, 2023 Meredith B. Rosenthal, PhD
• Ushering in a New Era of Alzheimer Disease Therapy JAMA Editorial August 8, 2023 Eric W. Widera, MD; Sharon A. Brangman, MD; Nathaniel A. Chin, MD
• Role of Registries in Medicare Coverage of New Alzheimer Disease Drugs JAMA Viewpoint October 10, 2023 This Viewpoint discusses how the design of the Centers for Medicare & Medicaid Services (CMS) registry could impact Medicare’s ability to evaluate whether monoclonal antibodies are reasonable and necessary for patients with Alzheimer disease and help physicians understand when the drug is most beneficial. Ilina C. Odouard, MPH; Mariana P. Socal, MD, PhD; Gerard F. Anderson, PhD
• Who Should Get the New Alzheimer Disease Drug? JAMA Medical News & Perspectives October 17, 2023 This Medical News story examines the complexity of determining who to treat with lecanemab, the new Alzheimer disease drug. Rita Rubin, MA
• Use of Donanemab in Early Symptomatic Alzheimer Disease—Reply JAMA Comment & Response December 19, 2023 Cynthia D. Evans, PhD; John R. Sims, MD
• Use of Donanemab in Early Symptomatic Alzheimer Disease JAMA Comment & Response December 19, 2023 Nunzio Pomara, MD; Bruno Pietro Imbimbo, PhD
• Risks of Harm in Alzheimer Disease by Amyloid Lowering JAMA Viewpoint June 18, 2024 This Viewpoint discusses how data gaps in published research impede clinicians’ ability to clearly discuss the risks and benefits of amyloid-lowering drugs for treating Alzheimer disease. Madhav Thambisetty, MD, PhD; Robert Howard, MD

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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

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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Deconstructing the Testing Mode Effect: Analyzing the Difference Between Writing and No Writing on the Test

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The examination of the testing mode effect has received increased attention as higher education has shifted to remote testing during the Covid-19 pandemic. We argue that the testing mode effect should be broken into four distinct subparts: the ability to physically write on the test, the method of answer recording, the proctoring/testing environment, and the effect testing mode has on instructor question selection. This paper examines an area largely neglected by the literature surrounding the testing mode effect, the ability (or lack thereof) to write on the test. Using a normalization technique to control for student aptitude and instructor bias, we find that removing the ability of students to physically write on the test significantly lowers student performance. This finding holds across multiple question types classified by difficulty level, Bloom’s taxonomy, and on figure/graph-based questions, and has implications for testing in both face-to-face and online environments.

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Daniel M. Settlage, University of Arkansas-Fort Smith

Jim r. wollscheid, university of arkansas-fort smith.

College of Business and Industry-Professor of Economics

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Becoming Lyrical: Poems That Depict Our Reflective Journeys In Online Teaching

Online and blended learning over the years have brought great challenges and opportunities. At the beginning of this project, we asked: How do educators reflect on teaching online in particular? And how do we articulate our reflections in creative ways? With these questions in mind, the authors took on the challenge of the artistic expression of writing and reading poetry to reflect critically and creatively on our experiences of teaching online in higher education. By drawing connections between theory and our poetry we provide insight into our lessons learned from teaching online. We conclude with encouragement to use creative writing to foster a collective and reflective environment in higher education and for personal awareness and growth.

Author Biographies

Patrick kelly, university of calgary.

Patrick Kelly has has been an instructional designer in higher education for over 20 years and is always looking for something creative and fun to challenge myself. Oh, I am not a poet!

Cari Din, University of Calgary

Cari Din is an Associate Professor (Teaching) in the Faculty of Kinesiology, a Teaching Scholar, a Canadian Centre of Advanced Leadership Fellow in the Haskayne School of Business, and believes we are all profoundly creative. She loves hiking, her sons, and laughter!

Craig Ginn, University of Calgary

Craig Ginn is an Associate Professor (Teaching) at the University of Calgary in the Department of Classics and Religion and serves as the Director of the International Indigenous Studies Program.  Recent courses he has developed include  Religion in Popular Music  and  Indigenous Traditions and Worldviews.   

Robyn Mae Paul, University of Calgary

Robyn Paul is a PhD candidate in Mechanical Engineering at the University of Calgary. Her teaching and research integrates principles from ecofeminism to deconstruct the hidden curriculum of engineering education. She is passionate about student mental health and creating new narratives of engineering that centre social justice conversations.

Copyright (c) 2024 Patrick Kelly, Cari Din, Craig Ginn, Robyn Mae Paul

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