sample abstract for a research paper

Writing an Abstract for Your Research Paper

Definition and Purpose of Abstracts

An abstract is a short summary of your (published or unpublished) research paper, usually about a paragraph (c. 6-7 sentences, 150-250 words) long. A well-written abstract serves multiple purposes:

• an abstract lets readers get the gist or essence of your paper or article quickly, in order to decide whether to read the full paper;
• an abstract prepares readers to follow the detailed information, analyses, and arguments in your full paper;
• and, later, an abstract helps readers remember key points from your paper.

It’s also worth remembering that search engines and bibliographic databases use abstracts, as well as the title, to identify key terms for indexing your published paper. So what you include in your abstract and in your title are crucial for helping other researchers find your paper or article.

If you are writing an abstract for a course paper, your professor may give you specific guidelines for what to include and how to organize your abstract. Similarly, academic journals often have specific requirements for abstracts. So in addition to following the advice on this page, you should be sure to look for and follow any guidelines from the course or journal you’re writing for.

The Contents of an Abstract

Abstracts contain most of the following kinds of information in brief form. The body of your paper will, of course, develop and explain these ideas much more fully. As you will see in the samples below, the proportion of your abstract that you devote to each kind of information—and the sequence of that information—will vary, depending on the nature and genre of the paper that you are summarizing in your abstract. And in some cases, some of this information is implied, rather than stated explicitly. The Publication Manual of the American Psychological Association , which is widely used in the social sciences, gives specific guidelines for what to include in the abstract for different kinds of papers—for empirical studies, literature reviews or meta-analyses, theoretical papers, methodological papers, and case studies.

Here are the typical kinds of information found in most abstracts:

• the context or background information for your research; the general topic under study; the specific topic of your research
• the central questions or statement of the problem your research addresses
• what’s already known about this question, what previous research has done or shown
• the main reason(s) , the exigency, the rationale , the goals for your research—Why is it important to address these questions? Are you, for example, examining a new topic? Why is that topic worth examining? Are you filling a gap in previous research? Applying new methods to take a fresh look at existing ideas or data? Resolving a dispute within the literature in your field? . . .
• your research and/or analytical methods
• your main findings , results , or arguments
• the significance or implications of your findings or arguments.

Your abstract should be intelligible on its own, without a reader’s having to read your entire paper. And in an abstract, you usually do not cite references—most of your abstract will describe what you have studied in your research and what you have found and what you argue in your paper. In the body of your paper, you will cite the specific literature that informs your research.

When to Write Your Abstract

Although you might be tempted to write your abstract first because it will appear as the very first part of your paper, it’s a good idea to wait to write your abstract until after you’ve drafted your full paper, so that you know what you’re summarizing.

What follows are some sample abstracts in published papers or articles, all written by faculty at UW-Madison who come from a variety of disciplines. We have annotated these samples to help you see the work that these authors are doing within their abstracts.

Choosing Verb Tenses within Your Abstract

The social science sample (Sample 1) below uses the present tense to describe general facts and interpretations that have been and are currently true, including the prevailing explanation for the social phenomenon under study. That abstract also uses the present tense to describe the methods, the findings, the arguments, and the implications of the findings from their new research study. The authors use the past tense to describe previous research.

The humanities sample (Sample 2) below uses the past tense to describe completed events in the past (the texts created in the pulp fiction industry in the 1970s and 80s) and uses the present tense to describe what is happening in those texts, to explain the significance or meaning of those texts, and to describe the arguments presented in the article.

The science samples (Samples 3 and 4) below use the past tense to describe what previous research studies have done and the research the authors have conducted, the methods they have followed, and what they have found. In their rationale or justification for their research (what remains to be done), they use the present tense. They also use the present tense to introduce their study (in Sample 3, “Here we report . . .”) and to explain the significance of their study (In Sample 3, This reprogramming . . . “provides a scalable cell source for. . .”).

Sample Abstract 1

From the social sciences.

Reporting new findings about the reasons for increasing economic homogamy among spouses

Gonalons-Pons, Pilar, and Christine R. Schwartz. “Trends in Economic Homogamy: Changes in Assortative Mating or the Division of Labor in Marriage?” Demography , vol. 54, no. 3, 2017, pp. 985-1005.

Sample Abstract 2

From the humanities.

Analyzing underground pulp fiction publications in Tanzania, this article makes an argument about the cultural significance of those publications

Emily Callaci. “Street Textuality: Socialism, Masculinity, and Urban Belonging in Tanzania’s Pulp Fiction Publishing Industry, 1975-1985.” Comparative Studies in Society and History , vol. 59, no. 1, 2017, pp. 183-210.

Sample Abstract/Summary 3

From the sciences.

Reporting a new method for reprogramming adult mouse fibroblasts into induced cardiac progenitor cells

Lalit, Pratik A., Max R. Salick, Daryl O. Nelson, Jayne M. Squirrell, Christina M. Shafer, Neel G. Patel, Imaan Saeed, Eric G. Schmuck, Yogananda S. Markandeya, Rachel Wong, Martin R. Lea, Kevin W. Eliceiri, Timothy A. Hacker, Wendy C. Crone, Michael Kyba, Daniel J. Garry, Ron Stewart, James A. Thomson, Karen M. Downs, Gary E. Lyons, and Timothy J. Kamp. “Lineage Reprogramming of Fibroblasts into Proliferative Induced Cardiac Progenitor Cells by Defined Factors.” Cell Stem Cell , vol. 18, 2016, pp. 354-367.

Sample Abstract 4, a Structured Abstract

Reporting results about the effectiveness of antibiotic therapy in managing acute bacterial sinusitis, from a rigorously controlled study

Note: This journal requires authors to organize their abstract into four specific sections, with strict word limits. Because the headings for this structured abstract are self-explanatory, we have chosen not to add annotations to this sample abstract.

Wald, Ellen R., David Nash, and Jens Eickhoff. “Effectiveness of Amoxicillin/Clavulanate Potassium in the Treatment of Acute Bacterial Sinusitis in Children.” Pediatrics , vol. 124, no. 1, 2009, pp. 9-15.

“OBJECTIVE: The role of antibiotic therapy in managing acute bacterial sinusitis (ABS) in children is controversial. The purpose of this study was to determine the effectiveness of high-dose amoxicillin/potassium clavulanate in the treatment of children diagnosed with ABS.

METHODS : This was a randomized, double-blind, placebo-controlled study. Children 1 to 10 years of age with a clinical presentation compatible with ABS were eligible for participation. Patients were stratified according to age (<6 or ≥6 years) and clinical severity and randomly assigned to receive either amoxicillin (90 mg/kg) with potassium clavulanate (6.4 mg/kg) or placebo. A symptom survey was performed on days 0, 1, 2, 3, 5, 7, 10, 20, and 30. Patients were examined on day 14. Children’s conditions were rated as cured, improved, or failed according to scoring rules.

RESULTS: Two thousand one hundred thirty-five children with respiratory complaints were screened for enrollment; 139 (6.5%) had ABS. Fifty-eight patients were enrolled, and 56 were randomly assigned. The mean age was 6630 months. Fifty (89%) patients presented with persistent symptoms, and 6 (11%) presented with nonpersistent symptoms. In 24 (43%) children, the illness was classified as mild, whereas in the remaining 32 (57%) children it was severe. Of the 28 children who received the antibiotic, 14 (50%) were cured, 4 (14%) were improved, 4(14%) experienced treatment failure, and 6 (21%) withdrew. Of the 28children who received placebo, 4 (14%) were cured, 5 (18%) improved, and 19 (68%) experienced treatment failure. Children receiving the antibiotic were more likely to be cured (50% vs 14%) and less likely to have treatment failure (14% vs 68%) than children receiving the placebo.

CONCLUSIONS : ABS is a common complication of viral upper respiratory infections. Amoxicillin/potassium clavulanate results in significantly more cures and fewer failures than placebo, according to parental report of time to resolution.” (9)

Some Excellent Advice about Writing Abstracts for Basic Science Research Papers, by Professor Adriano Aguzzi from the Institute of Neuropathology at the University of Zurich:

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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.

Prevent plagiarism. Run a free check.

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 August 26, 2024, from https://www.scribbr.com/apa-style/apa-abstract/

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How to Write an Abstract (With Examples)

By Sarah Oakley

Table of Contents

What is an abstract in a paper, how long should an abstract be, 5 steps for writing an abstract, examples of an abstract, how prowritingaid can help you write an abstract.

If you are writing a scientific research paper or a book proposal, you need to know how to write an abstract, which summarizes the contents of the paper or book.

When researchers are looking for peer-reviewed papers to use in their studies, the first place they will check is the abstract to see if it applies to their work. Therefore, your abstract is one of the most important parts of your entire paper.

In this article, we’ll explain what an abstract is, what it should include, and how to write one.

An abstract is a concise summary of the details within a report. Some abstracts give more details than others, but the main things you’ll be talking about are why you conducted the research, what you did, and what the results show.

When a reader is deciding whether to read your paper completely, they will first look at the abstract. You need to be concise in your abstract and give the reader the most important information so they can determine if they want to read the whole paper.

Remember that an abstract is the last thing you’ll want to write for the research paper because it directly references parts of the report. If you haven’t written the report, you won’t know what to include in your abstract.

If you are writing a paper for a journal or an assignment, the publication or academic institution might have specific formatting rules for how long your abstract should be. However, if they don’t, most abstracts are between 150 and 300 words long.

A short word count means your writing has to be precise and without filler words or phrases. Once you’ve written a first draft, you can always use an editing tool, such as ProWritingAid, to identify areas where you can reduce words and increase readability.

If your abstract is over the word limit, and you’ve edited it but still can’t figure out how to reduce it further, your abstract might include some things that aren’t needed. Here’s a list of three elements you can remove from your abstract:

Discussion : You don’t need to go into detail about the findings of your research because your reader will find your discussion within the paper.

Definition of terms : Your readers are interested the field you are writing about, so they are likely to understand the terms you are using. If not, they can always look them up. Your readers do not expect you to give a definition of terms in your abstract.

References and citations : You can mention there have been studies that support or have inspired your research, but you do not need to give details as the reader will find them in your bibliography.

Good writing = better grades

ProWritingAid will help you improve the style, strength, and clarity of all your assignments.

If you’ve never written an abstract before, and you’re wondering how to write an abstract, we’ve got some steps for you to follow. It’s best to start with planning your abstract, so we’ve outlined the details you need to include in your plan before you write.

Remember to consider your audience when you’re planning and writing your abstract. They are likely to skim read your abstract, so you want to be sure your abstract delivers all the information they’re expecting to see at key points.

1. What Should an Abstract Include?

Abstracts have a lot of information to cover in a short number of words, so it’s important to know what to include. There are three elements that need to be present in your abstract:

Your context is the background for where your research sits within your field of study. You should briefly mention any previous scientific papers or experiments that have led to your hypothesis and how research develops in those studies.

Your hypothesis is your prediction of what your study will show. As you are writing your abstract after you have conducted your research, you should still include your hypothesis in your abstract because it shows the motivation for your paper.

Throughout your abstract, you also need to include keywords and phrases that will help researchers to find your article in the databases they’re searching. Make sure the keywords are specific to your field of study and the subject you’re reporting on, otherwise your article might not reach the relevant audience.

2. Can You Use First Person in an Abstract?

You might think that first person is too informal for a research paper, but it’s not. Historically, writers of academic reports avoided writing in first person to uphold the formality standards of the time. However, first person is more accepted in research papers in modern times.

If you’re still unsure whether to write in first person for your abstract, refer to any style guide rules imposed by the journal you’re writing for or your teachers if you are writing an assignment.

3. Abstract Structure

Some scientific journals have strict rules on how to structure an abstract, so it’s best to check those first. If you don’t have any style rules to follow, try using the IMRaD structure, which stands for Introduction, Methodology, Results, and Discussion.

Following the IMRaD structure, start with an introduction. The amount of background information you should include depends on your specific research area. Adding a broad overview gives you less room to include other details. Remember to include your hypothesis in this section.

The next part of your abstract should cover your methodology. Try to include the following details if they apply to your study:

What type of research was conducted?

How were the test subjects sampled?

What were the sample sizes?

What was done to each group?

How long was the experiment?

How was data recorded and interpreted?

Following the methodology, include a sentence or two about the results, which is where your reader will determine if your research supports or contradicts their own investigations.

The results are also where most people will want to find out what your outcomes were, even if they are just mildly interested in your research area. You should be specific about all the details but as concise as possible.

The last few sentences are your conclusion. It needs to explain how your findings affect the context and whether your hypothesis was correct. Include the primary take-home message, additional findings of importance, and perspective. Also explain whether there is scope for further research into the subject of your report.

Your conclusion should be honest and give the reader the ultimate message that your research shows. Readers trust the conclusion, so make sure you’re not fabricating the results of your research. Some readers won’t read your entire paper, but this section will tell them if it’s worth them referencing it in their own study.

4. How to Start an Abstract

The first line of your abstract should give your reader the context of your report by providing background information. You can use this sentence to imply the motivation for your research.

You don’t need to use a hook phrase or device in your first sentence to grab the reader’s attention. Your reader will look to establish relevance quickly, so readability and clarity are more important than trying to persuade the reader to read on.

5. How to Format an Abstract

Most abstracts use the same formatting rules, which help the reader identify the abstract so they know where to look for it.

Here’s a list of formatting guidelines for writing an abstract:

Stick to one paragraph

Use block formatting with no indentation at the beginning

Put your abstract straight after the title and acknowledgements pages

Use present or past tense, not future tense

There are two primary types of abstract you could write for your paper—descriptive and informative.

An informative abstract is the most common, and they follow the structure mentioned previously. They are longer than descriptive abstracts because they cover more details.

Descriptive abstracts differ from informative abstracts, as they don’t include as much discussion or detail. The word count for a descriptive abstract is between 50 and 150 words.

Here is an example of an informative abstract:

A growing trend exists for authors to employ a more informal writing style that uses “we” in academic writing to acknowledge one’s stance and engagement. However, few studies have compared the ways in which the first-person pronoun “we” is used in the abstracts and conclusions of empirical papers. To address this lacuna in the literature, this study conducted a systematic corpus analysis of the use of “we” in the abstracts and conclusions of 400 articles collected from eight leading electrical and electronic (EE) engineering journals. The abstracts and conclusions were extracted to form two subcorpora, and an integrated framework was applied to analyze and seek to explain how we-clusters and we-collocations were employed. Results revealed whether authors’ use of first-person pronouns partially depends on a journal policy. The trend of using “we” showed that a yearly increase occurred in the frequency of “we” in EE journal papers, as well as the existence of three “we-use” types in the article conclusions and abstracts: exclusive, inclusive, and ambiguous. Other possible “we-use” alternatives such as “I” and other personal pronouns were used very rarely—if at all—in either section. These findings also suggest that the present tense was used more in article abstracts, but the present perfect tense was the most preferred tense in article conclusions. Both research and pedagogical implications are proffered and critically discussed.

Wang, S., Tseng, W.-T., & Johanson, R. (2021). To We or Not to We: Corpus-Based Research on First-Person Pronoun Use in Abstracts and Conclusions. SAGE Open, 11(2).

Here is an example of a descriptive abstract:

From the 1850s to the present, considerable criminological attention has focused on the development of theoretically-significant systems for classifying crime. This article reviews and attempts to evaluate a number of these efforts, and we conclude that further work on this basic task is needed. The latter part of the article explicates a conceptual foundation for a crime pattern classification system, and offers a preliminary taxonomy of crime.

Farr, K. A., & Gibbons, D. C. (1990). Observations on the Development of Crime Categories. International Journal of Offender Therapy and Comparative Criminology, 34(3), 223–237.

If you want to ensure your abstract is grammatically correct and easy to read, you can use ProWritingAid to edit it. The software integrates with Microsoft Word, Google Docs, and most web browsers, so you can make the most of it wherever you’re writing your paper.

Before you edit with ProWritingAid, make sure the suggestions you are seeing are relevant for your document by changing the document type to “Abstract” within the Academic writing style section.

You can use the Readability report to check your abstract for places to improve the clarity of your writing. Some suggestions might show you where to remove words, which is great if you’re over your word count.

We hope the five steps and examples we’ve provided help you write a great abstract for your research paper.

Sarah Oakley

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Home » Research Paper Abstract – Writing Guide and Examples

Research Paper Abstract – Writing Guide and Examples

Table of Contents

Research Paper Abstract

Research Paper Abstract is a brief summary of a research pape r that describes the study’s purpose, methods, findings, and conclusions . It is often the first section of the paper that readers encounter, and its purpose is to provide a concise and accurate overview of the paper’s content. The typical length of an abstract is usually around 150-250 words, and it should be written in a concise and clear manner.

Research Paper Abstract Structure

The structure of a research paper abstract usually includes the following elements:

• Background or Introduction: Briefly describe the problem or research question that the study addresses.
• Methods : Explain the methodology used to conduct the study, including the participants, materials, and procedures.
• Results : Summarize the main findings of the study, including statistical analyses and key outcomes.
• Conclusions : Discuss the implications of the study’s findings and their significance for the field, as well as any limitations or future directions for research.
• Keywords : List a few keywords that describe the main topics or themes of the research.

How to Write Research Paper Abstract

Here are the steps to follow when writing a research paper abstract:

• Start by reading your paper: Before you write an abstract, you should have a complete understanding of your paper. Read through the paper carefully, making sure you understand the purpose, methods, results, and conclusions.
• Identify the key components : Identify the key components of your paper, such as the research question, methods used, results obtained, and conclusion reached.
• Write a draft: Write a draft of your abstract, using concise and clear language. Make sure to include all the important information, but keep it short and to the point. A good rule of thumb is to keep your abstract between 150-250 words.
• Use clear and concise language : Use clear and concise language to explain the purpose of your study, the methods used, the results obtained, and the conclusions drawn.
• Emphasize your findings: Emphasize your findings in the abstract, highlighting the key results and the significance of your study.
• Revise and edit: Once you have a draft, revise and edit it to ensure that it is clear, concise, and free from errors.
• Check the formatting: Finally, check the formatting of your abstract to make sure it meets the requirements of the journal or conference where you plan to submit it.

Research Paper Abstract Examples

Research Paper Abstract Examples could be following:

Title : “The Effectiveness of Cognitive-Behavioral Therapy for Treating Anxiety Disorders: A Meta-Analysis”

Abstract : This meta-analysis examines the effectiveness of cognitive-behavioral therapy (CBT) in treating anxiety disorders. Through the analysis of 20 randomized controlled trials, we found that CBT is a highly effective treatment for anxiety disorders, with large effect sizes across a range of anxiety disorders, including generalized anxiety disorder, panic disorder, and social anxiety disorder. Our findings support the use of CBT as a first-line treatment for anxiety disorders and highlight the importance of further research to identify the mechanisms underlying its effectiveness.

Title : “Exploring the Role of Parental Involvement in Children’s Education: A Qualitative Study”

Abstract : This qualitative study explores the role of parental involvement in children’s education. Through in-depth interviews with 20 parents of children in elementary school, we found that parental involvement takes many forms, including volunteering in the classroom, helping with homework, and communicating with teachers. We also found that parental involvement is influenced by a range of factors, including parent and child characteristics, school culture, and socio-economic status. Our findings suggest that schools and educators should prioritize building strong partnerships with parents to support children’s academic success.

Title : “The Impact of Exercise on Cognitive Function in Older Adults: A Systematic Review and Meta-Analysis”

Abstract : This paper presents a systematic review and meta-analysis of the existing literature on the impact of exercise on cognitive function in older adults. Through the analysis of 25 randomized controlled trials, we found that exercise is associated with significant improvements in cognitive function, particularly in the domains of executive function and attention. Our findings highlight the potential of exercise as a non-pharmacological intervention to support cognitive health in older adults.

When to Write Research Paper Abstract

The abstract of a research paper should typically be written after you have completed the main body of the paper. This is because the abstract is intended to provide a brief summary of the key points and findings of the research, and you can’t do that until you have completed the research and written about it in detail.

Once you have completed your research paper, you can begin writing your abstract. It is important to remember that the abstract should be a concise summary of your research paper, and should be written in a way that is easy to understand for readers who may not have expertise in your specific area of research.

Purpose of Research Paper Abstract

The purpose of a research paper abstract is to provide a concise summary of the key points and findings of a research paper. It is typically a brief paragraph or two that appears at the beginning of the paper, before the introduction, and is intended to give readers a quick overview of the paper’s content.

The abstract should include a brief statement of the research problem, the methods used to investigate the problem, the key results and findings, and the main conclusions and implications of the research. It should be written in a clear and concise manner, avoiding jargon and technical language, and should be understandable to a broad audience.

The abstract serves as a way to quickly and easily communicate the main points of a research paper to potential readers, such as academics, researchers, and students, who may be looking for information on a particular topic. It can also help researchers determine whether a paper is relevant to their own research interests and whether they should read the full paper.

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Researcher, Academic Writer, Web developer

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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.

You can have a thorough understanding of abstracts using SciSpace ChatPDF which makes your abstract analysis part easier.

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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How to Write an Abstract | Steps & Examples

Published on 1 March 2019 by Shona McCombes . Revised on 10 October 2022 by Eoghan Ryan.

An abstract is a short summary of a longer work (such as a dissertation or research paper ). The abstract concisely reports the aims and outcomes of your research, so that readers know exactly what your paper is about.

Although the structure may vary slightly depending on your discipline, your abstract should describe the purpose of your work, the methods you’ve used, and the conclusions you’ve drawn.

One common way to structure your abstract is to use the IMRaD structure. This stands for:

• Introduction

Abstracts are usually around 100–300 words, but there’s often a strict word limit, so make sure to check the relevant requirements.

In a dissertation or thesis , include the abstract on a separate page, after the title page and acknowledgements but before the table of contents .

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Table of contents

Abstract example, when to write an abstract, step 1: introduction, step 2: methods, step 3: results, step 4: discussion, tips for writing an abstract, frequently asked questions about abstracts.

Hover over the different parts of the abstract to see how it is constructed.

This paper examines the role of silent movies as a mode of shared experience in the UK during the early twentieth century. At this time, high immigration rates resulted in a significant percentage of non-English-speaking citizens. These immigrants faced numerous economic and social obstacles, including exclusion from public entertainment and modes of discourse (newspapers, theater, radio).

Incorporating evidence from reviews, personal correspondence, and diaries, this study demonstrates that silent films were an affordable and inclusive source of entertainment. It argues for the accessible economic and representational nature of early cinema. These concerns are particularly evident in the low price of admission and in the democratic nature of the actors’ exaggerated gestures, which allowed the plots and action to be easily grasped by a diverse audience despite language barriers.

Keywords: silent movies, immigration, public discourse, entertainment, early cinema, language barriers.

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You will almost always have to include an abstract when:

• Completing a thesis or dissertation
• Submitting a research paper to an academic journal
• Writing a book proposal
• Applying for research grants

It’s easiest to write your abstract last, because it’s a summary of the work you’ve already done. Your abstract should:

• Be a self-contained text, not an excerpt from your paper
• Be fully understandable on its own
• Reflect the structure of your larger work

Start by clearly defining the purpose of your research. What practical or theoretical problem does the research respond to, or what research question did you aim to answer?

You can include some brief context on the social or academic relevance of your topic, but don’t go into detailed background information. If your abstract uses specialised terms that would be unfamiliar to the average academic reader or that have various different meanings, give a concise definition.

After identifying the problem, state the objective of your research. Use verbs like “investigate,” “test,” “analyse,” or “evaluate” to describe exactly what you set out to do.

This part of the abstract can be written in the present or past simple tense  but should never refer to the future, as the research is already complete.

• This study will investigate the relationship between coffee consumption and productivity.
• This study investigates the relationship between coffee consumption and productivity.

Next, indicate the research methods that you used to answer your question. This part should be a straightforward description of what you did in one or two sentences. It is usually written in the past simple tense, as it refers to completed actions.

• Structured interviews will be conducted with 25 participants.
• Structured interviews were conducted with 25 participants.

Don’t evaluate validity or obstacles here — the goal is not to give an account of the methodology’s strengths and weaknesses, but to give the reader a quick insight into the overall approach and procedures you used.

Next, summarise the main research results . This part of the abstract can be in the present or past simple tense.

• Our analysis has shown a strong correlation between coffee consumption and productivity.
• Our analysis shows a strong correlation between coffee consumption and productivity.
• Our analysis showed a strong correlation between coffee consumption and productivity.

Depending on how long and complex your research is, you may not be able to include all results here. Try to highlight only the most important findings that will allow the reader to understand your conclusions.

Finally, you should discuss the main conclusions of your research : what is your answer to the problem or question? The reader should finish with a clear understanding of the central point that your research has proved or argued. Conclusions are usually written in the present simple tense.

• We concluded that coffee consumption increases productivity.
• We conclude that coffee consumption increases productivity.

If there are important limitations to your research (for example, related to your sample size or methods), you should mention them briefly in the abstract. This allows the reader to accurately assess the credibility and generalisability of your research.

If your aim was to solve a practical problem, your discussion might include recommendations for implementation. If relevant, you can briefly make suggestions for further research.

If your paper will be published, you might have to add a list of keywords at the end of the abstract. These keywords should reference the most important elements of the research to help potential readers find your paper during their own literature searches.

Be aware that some publication manuals, such as APA Style , have specific formatting requirements for these keywords.

It can be a real challenge to condense your whole work into just a couple of hundred words, but the abstract will be the first (and sometimes only) part that people read, so it’s important to get it right. These strategies can help you get started.

Read other abstracts

The best way to learn the conventions of writing an abstract in your discipline is to read other people’s. You probably already read lots of journal article abstracts while conducting your literature review —try using them as a framework for structure and style.

You can also find lots of dissertation abstract examples in thesis and dissertation databases .

Reverse outline

Not all abstracts will contain precisely the same elements. For longer works, you can write your abstract through a process of reverse outlining.

For each chapter or section, list keywords and draft one to two sentences that summarise the central point or argument. This will give you a framework of your abstract’s structure. Next, revise the sentences to make connections and show how the argument develops.

Write clearly and concisely

A good abstract is short but impactful, so make sure every word counts. Each sentence should clearly communicate one main point.

To keep your abstract or summary short and clear:

• Avoid passive sentences: Passive constructions are often unnecessarily long. You can easily make them shorter and clearer by using the active voice.
• Avoid long sentences: Substitute longer expressions for concise expressions or single words (e.g., “In order to” for “To”).
• Avoid obscure jargon: The abstract should be understandable to readers who are not familiar with your topic.
• Avoid repetition and filler words: Replace nouns with pronouns when possible and eliminate unnecessary words.
• Avoid detailed descriptions: An abstract is not expected to provide detailed definitions, background information, or discussions of other scholars’ work. Instead, include this information in the body of your thesis or paper.

If you’re struggling to edit down to the required length, you can get help from expert editors with Scribbr’s professional proofreading services .

Check your formatting

If you are writing a thesis or dissertation or submitting to a journal, there are often specific formatting requirements for the abstract—make sure to check the guidelines and format your work correctly. For APA research papers you can follow the APA abstract format .

Checklist: Abstract

The word count is within the required length, or a maximum of one page.

The abstract appears after the title page and acknowledgements and before the table of contents .

I have clearly stated my research problem and objectives.

I have briefly described my methodology .

I have summarized the most important results .

I have stated my main conclusions .

I have mentioned any important limitations and recommendations.

The abstract can be understood by someone without prior knowledge of the topic.

You've written a great abstract! Use the other checklists to continue improving your thesis or dissertation.

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 summarises the contents of your paper.

An abstract for a thesis or dissertation is usually around 150–300 words. There’s often a strict word limit, so make sure to check your university’s requirements.

The abstract is the very last thing you write. You should only write it after your research is complete, so that you can accurately summarize the entirety of your thesis or paper.

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.

The abstract appears on its own page, after the title page and acknowledgements but before the table of contents .

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How to write an abstract

What is an abstract?

General format of an abstract, the content of an abstract, abstract example, abstract style guides, frequently asked questions about writing an abstract, related articles.

An abstract is a summary of the main contents of a paper.

The abstract is the first glimpse that readers get of the content of a research paper. It can influence the popularity of a paper, as a well-written one will attract readers, and a poorly-written one will drive them away.

➡️ Different types of papers may require distinct abstract styles. Visit our guide on the different types of research papers to learn more.

Tip: Always wait until you’ve written your entire paper before you write the abstract.

Before you actually start writing an abstract, make sure to follow these steps:

• Read other papers : find papers with similar topics, or similar methodologies, simply to have an idea of how others have written their abstracts. Notice which points they decided to include, and how in depth they described them.
• Double check the journal requirements : always make sure to review the journal guidelines to format your paper accordingly. Usually, they also specify abstract's formats.
• Write the abstract after you finish writing the paper : you can only write an abstract once you finish writing the whole paper. This way you can include all important aspects, such as scope, methodology, and conclusion.

➡️ Read more about  what is a research methodology?

The general format of an abstract includes the following features:

• Between 150-300 words .
• An independent page , after the title page and before the table of contents.
• Concise summary including the aim of the research, methodology , and conclusion .
• Keywords describing the content.

As mentioned before, an abstract is a text that summarizes the main points of a research. Here is a break down of each element that should be included in an abstract:

• Purpose : every abstract should start by describing the main purpose or aim of the research.
• Methods : as a second point, the methodology carried out should be explained.
• Results : then, a concise summary of the results should be included.
• Conclusion : finally, a short outline of the general outcome of the research should be given.
• Keywords : along with the abstract, specific words and phrases related to the topics discussed in the research should be added. These words are usually around five, but the number can vary depending on the journal's guidelines.

This abstract, taken from ScienceDirect , illustrates the ideal structure of an abstract. It has 155 words, it's concise, and it clearly shows the division of elements necessary to write a successful abstract.

This paper explores the implicit assumption in the growing body of literature that social media usage is fundamentally different in business-to-business (B2B) companies than in the extant business-to-consumer (B2C) literature. Sashi's (2012) customer engagement cycle is utilized to compare organizational practices in relation to social media marketing in B2B, B2C, Mixed B2B/B2C and B2B2C business models. Utilizing 449 responses to an exploratory panel based survey instrument, we clearly identify differences in social media usage and its perceived importance as a communications channel. In particular we identify distinct differences in the relationship between social media importance and the perceived effectiveness of social media marketing across business models. Our results indicate that B2B social media usage is distinct from B2C, Mixed and B2B2C business model approaches. Specifically B2B organizational members perceive social media to have a lower overall effectiveness as a channel and identify it as less important for relationship oriented usage than other business models.

The exact format of an abstract depends on the citation style you implement. Whether it’s a well-known style (like APA, IEEE, etc.) or a journal's style, each format has its own guidelines, so make sure you know which style you are using before writing your abstract.

APA is one of the most commonly used styles to format an abstract. Therefore, we created a guide with exact instructions on how to write an abstract in APA style, and a template to download:

📕 APA abstract page: format and template

Additionally, you will find below an IEEE and ASA abstract guide by Purdue Online Writing Lab :

📗 IEEE General Format - Abstract

📘 ASA Manuscript Formatting - Abstract

No. You should always write an abstract once you finish writing the whole paper. This way you can include all important aspects of the paper, such as scope, methodology, and conclusion.

The length of an abstract depends on the formatting style of the paper. For example, APA style calls for 150 to 250 words. Generally, you need between 150-300 words.

No. An abstract has an independent section after the title page and before the table of contents, and should not be included in the table of contents.

Take a look at APA abstract page: format and template for exact details on how to format an abstract in APA style.

You can access any paper through Google Scholar or any other search engine; pick a paper and read the abstract. Abstracts are always freely available to read.

How to Write an Abstract in Research Papers (with Examples)

An abstract in research papers is a keyword-rich summary usually not exceeding 200-350 words. It can be considered the “face” of research papers because it creates an initial impression on the readers. While searching databases (such as PubMed) for research papers, a title is usually the first selection criterion for readers. If the title matches their search criteria, then the readers read the abstract, which sets the tone of the paper. Titles and abstracts are often the only freely available parts of research papers on journal websites. The pdf versions of full articles need to be purchased. Journal reviewers are often provided with only the title and abstract before they agree to review the complete paper. [ 1]  

Abstracts in research papers provide readers with a quick insight into what the paper is about to help them decide whether they want to read it further or not. Abstracts are the main selling points of articles and therefore should be carefully drafted, accurately highlighting the important aspects. [ 2]  

This article will help you identify the important components and provide tips on how to write an abstract in research papers effectively

What is an Abstract?  

An abstract in research papers can be defined as a synopsis of the paper. It should be clear, direct, self-contained, specific, unbiased, and concise. These summaries are published along with the complete research paper and are also submitted to conferences for consideration for presentation.  

Abstracts are of four types and journals can follow any of these formats: [ 2]  

• Structured  
• Unstructured  
• Descriptive  
• Informative  

Structured abstracts are used by most journals because they are more organized and have clear sections, usually including introduction/background; objective; design, settings, and participants (or materials and methods); outcomes and measures; results; and conclusion. These headings may differ based on the journal or the type of paper. Clinical trial abstracts should include the essential items mentioned in the CONSORT (Consolidated Standards Of Reporting Trials) guidelines.  

Figure 1. Structured abstract example [3] 

Unstructured abstracts are common in social science, humanities, and physical science journals. They usually have one paragraph and no specific structure or subheadings. These abstracts are commonly used for research papers that don’t report original work and therefore have a more flexible and narrative style.  

Figure 2. Unstructured abstract example [3] 

Descriptive abstracts are short (75–150 words) and provide an outline with only the most important points of research papers. They are used for shorter articles such as case reports, reviews, and opinions where space is at a premium, and rarely for original investigations. These abstracts don’t present the results but mainly list the topics covered.  

Here’s a sample abstract . [ 4]  

“Design of a Radio-Based System for Distribution Automation”  

A new survey by the Maryland Public Utilities Commission suggests that utilities have not effectively explained to consumers the benefits of smart meters. The two-year study of 86,000 consumers concludes that the long-term benefits of smart meters will not be realized until consumers understand the benefits of shifting some of their power usage to off-peak hours in response to the data they receive from their meters. The study presents recommendations for utilities and municipal governments to improve customer understanding of how to use the smart meters effectively.  

Keywords: smart meters, distribution systems, load, customer attitudes, power consumption, utilities  

Informative abstracts (structured or unstructured) give a complete detailed summary, including the main results, of the research paper and may or may not have subsections.   

Figure 3. Informative abstract example [5] 

Purpose of Abstracts in Research    

Abstracts in research have two main purposes—selection and indexing. [ 6,7]  

• Selection : Abstracts allow interested readers to quickly decide the relevance of a paper to gauge if they should read it completely.   
• Indexing : Most academic journal databases accessed through libraries enable you to search abstracts, allowing for quick retrieval of relevant articles and avoiding unnecessary search results. Therefore, abstracts must necessarily include the keywords that researchers may use to search for articles.  

Thus, a well-written, keyword-rich abstract can p ique readers’ interest and curiosity and help them decide whether they want to read the complete paper. It can also direct readers to articles of potential clinical and research interest during an online search.  

Contents of Abstracts in Research  

Abstracts in research papers summarize the main points of an article and are broadly categorized into four or five sections. Here are some details on how to write an abstract .   

Introduction/Background and/or Objectives  

This section should provide the following information:  

• What is already known about the subject?  
• What is not known about the subject or what does the study aim to investigate?  

The hypothesis or research question and objectives should be mentioned here. The Background sets the context for the rest of the paper and its length should be short so that the word count could be saved for the Results or other information directly pertaining to the study. The objective should be written in present or past simple tense.  

Examples:  

The antidepressant efficacy of desvenlafaxine (DV) has been established in 8-week, randomized controlled trials. The present study examined the continued efficacy of DV across 6 months of maintenance treatment . [ 1]  

Objective: To describe gastric and breast cancer risk estimates for individuals with CDH1 variants.  

Design, Setting, and Participants (or Materials and Methods)  

This section should provide information on the processes used and should be written in past simple tense because the process is already completed.  

A few important questions to be answered include:  

• What was the research design and setting?  
• What was the sample size and how were the participants sampled?  
• What treatments did the participants receive?  
• What were the data collection and data analysis dates?  
• What was the primary outcome measure?  

Hazard ratios (HRs) were estimated for each cancer type and used to calculate cumulative risks and risks per decade of life up to age 80 years.  

This section, written in either present or past simple tense, should be the longest and should describe the main findings of the study. Here’s an example of how descriptive the sentences should be:  

Avoid: Response rates differed significantly between diabetic and nondiabetic patients.  

Better: The response rate was higher in nondiabetic than in diabetic patients (49% vs 30%, respectively; P<0.01).  

This section should include the following information:  

• Total number of patients (included, excluded [exclusion criteria])  
• Primary and secondary outcomes, expressed in words, and supported by numerical data  
• Data on adverse outcomes  

Example: [ 8]  

In total, 10.9% of students were reported to have favorable study skills. The minimum score was found for preparation for examination domain. Also, a significantly positive correlation was observed between students’ study skills and their Grade Point Average (GPA) of previous term (P=0.001, r=0.269) and satisfaction with study skills (P=0.001, r=0.493).  

Conclusions  

Here, authors should mention the importance of their findings and also the practical and theoretical implications, which would benefit readers referring to this paper for their own research. Present simple tense should be used here.  

Examples: [ 1,8]  

The 9.3% prevalence of bipolar spectrum disorders in students at an arts university is substantially higher than general population estimates. These findings strengthen the oft-expressed hypothesis linking creativity with affective psychopathology.  

The findings indicated that students’ study skills need to be improved. Given the significant relationship between study skills and GPA, as an index of academic achievement, and satisfaction, it is necessary to promote the students’ study skills. These skills are suggested to be reinforced, with more emphasis on weaker domains.  

When to Write an Abstract  

In addition to knowing how to write an abstract , you should also know when to write an abstract . It’s best to write abstracts once the paper is completed because this would make it easier for authors to extract relevant parts from every section.  

Abstracts are usually required for: [ 7]    

• submitting articles to journals  
• applying for research grants   
• writing book proposals  
• completing and submitting dissertations  
• submitting proposals for conference papers  

Mostly, the author of the entire work writes the abstract (the first author, in works with multiple authors). However, there are professional abstracting services that hire writers to draft abstracts of other people’s work.   

How to Write an Abstract (Step-by-Step Process)  

Here are some key steps on how to write an abstract in research papers: [ 9]  

• Write the abstract after you’ve finished writing your paper.  
• Select the major objectives/hypotheses and conclusions from your Introduction and Conclusion sections.  
• Select key sentences from your Methods section.  
• Identify the major results from the Results section.  
• Paraphrase or re-write the sentences selected in steps 2, 3, and 4 in your own words into one or two paragraphs in the following sequence: Introduction/Objective, Methods, Results, and Conclusions. The headings may differ among journals, but the content remains the same.  
• Ensure that this draft does not contain: a.   new information that is not present in the paper b.   undefined abbreviations c.   a discussion of previous literature or reference citations d.   unnecessary details about the methods used  
• Remove all extra information and connect your sentences to ensure that the information flows well, preferably in the following order: purpose; basic study design, methodology and techniques used; major findings; summary of your interpretations, conclusions, and implications. Use section headings for structured abstracts.  
• Ensure consistency between the information presented in the abstract and the paper.  
• Check to see if the final abstract meets the guidelines of the target journal (word limit, type of abstract, recommended subheadings, etc.) and if all the required information has been included.  

Choosing Keywords for Abstracts  

Keywords [ 2] are the important and repeatedly used words and phrases in research papers and can help indexers and search engines find papers relevant to your requirements. Easy retrieval would help in reaching a wider audience and eventually gain more citations. In the fields of medicine and health, keywords should preferably be chosen from the Medical Subject Headings (MeSH) list of the US National Library of Medicine because they are used for indexing. These keywords need to be different from the words in the main title (automatically used for indexing) but can be variants of the terms/phrases used in the title, abstract, and the main text. Keywords should represent the content of your manuscript and be specific to your subject area.  

Basic tips for authors [ 10,11]  

• Read through your paper and highlight key terms or phrases that are most relevant and frequently used in your field, to ensure familiarity.  
• Several journals provide instructions about the length (eg, 3 words in a keyword) and maximum number of keywords allowed and other related rules. Create a list of keywords based on these instructions and include specific phrases containing 2 to 4 words. A longer string of words would yield generic results irrelevant to your field.  
• Use abbreviations, acronyms, and initializations if these would be more familiar.  
• Search with your keywords to ensure the results fit with your article and assess how helpful they would be to readers.  
• Narrow down your keywords to about five to ten, to ensure accuracy.  
• Finalize your list based on the maximum number allowed.  

  Few examples: [ 12]  

Important Tips for Writing an Abstract  

Here are a few tips on how to write an abstract to ensure that your abstract is complete, concise, and accurate. [ 1,2]  

• Write the abstract last.  
• Follow journal-specific formatting guidelines or Instructions to Authors strictly to ensure acceptance for publication.  
• Proofread the final draft meticulously to avoid grammatical or typographical errors.  
• Ensure that the terms or data mentioned in the abstract are consistent with the main text.  
• Include appropriate keywords at the end.

Do not include:  

• New information  
• Text citations to references  
• Citations to tables and figures  
• Generic statements  
• Abbreviations unless necessary, like a trial or study name  

Key Takeaways    

Here’s a quick snapshot of all the important aspects of how to write an abstract . [2]

• An abstract in research is a summary of the paper and describes only the main aspects. Typically, abstracts are about 200-350 words long.  
• Abstracts are of four types—structured, unstructured, descriptive, and informative.  
• Abstracts should be simple, clear, concise, independent, and unbiased (present both favorable and adverse outcomes).  
• They should adhere to the prescribed journal format, including word limits, section headings, number of keywords, fonts used, etc.  
• The terminology should be consistent with the main text.   
• Although the section heading names may differ for journals, every abstract should include a background and objective, analysis methods, primary results, and conclusions.  
• Nonstandard abbreviations, references, and URLs shouldn’t be included.  
• Only relevant and specific keywords should be used to ensure focused searches and higher citation frequency.  
• Abstracts should be written last after completing the main paper.  

Frequently Asked Questions   

Q1. Do all journals have different guidelines for abstracts?  

A1. Yes, all journals have their own specific guidelines for writing abstracts; a few examples are given in the following table. [ 6,13,14,15]  

Q2. What are the common mistakes to avoid when writing an abstract?  

A2. Listed below are a few mistakes that authors may make inadvertently while writing abstracts.  

• Copying sentences from the paper verbatim  

An abstract is a summary, which should be created by paraphrasing your own work or writing in your own words. Extracting sentences from every section and combining them into one paragraph cannot be considered summarizing.  

• Not adhering to the formatting guidelines  

Journals have special instructions for writing abstracts, such as word limits and section headings. These should be followed strictly to avoid rejections.  

• Not including the right amount of details in every section  

Both too little and too much information could discourage readers. For instance, if the Background has very little information, the readers may not get sufficient context to appreciate your research. Similarly, incomplete information in the Methods and a text-heavy Results section without supporting numerical data may affect the credibility of your research.  

• Including citations, standard abbreviations, and detailed measurements  

Typically, abstracts shouldn’t include these elements—citations, URLs, and abbreviations. Only nonstandard abbreviations are allowed or those that would be more familiar to readers than the expansions.  

• Including new information  

Abstracts should strictly include only the same information mentioned in the main text. Any new information should first be added to the text and then to the abstract only if necessary or if permitted by the word limit.  

• Not including keywords  

Keywords are essential for indexing and searching and should be included to increase the frequency of retrieval and citation.  

Q3. What is the difference between abstracts in research papers and conference abstracts? [16]  

A3. The table summarizes the main differences between research and conference abstracts.  

  Thus, abstracts are essential “trailers” that can market your research to a wide audience. The better and more complete the abstract the more are the chances of your paper being read and cited. By following our checklist and ensuring that all key elements are included, you can create a well-structured abstract that summarizes your paper accurately.  

References  

• Andrade C. How to write a good abstract for a scientific paper or conference presentation. Indian J Psychiatry . 2011; 53(2):172-175. Accessed June 14, 2024. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3136027/  
• Tullu MS. Writing the title and abstract for a research paper: Being concise, precise, and meticulous is the key. 2019; 13(Suppl 1): S12-S17. Accessed June 14, 2024. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6398294/  
• Zawia J. Writing an Academic Paper? Get to know Abstracts vs. Structured Abstracts. Medium. Published October 16, 2023. Accessed June 16, 2024. https://medium.com/@jamala.zawia/writing-an-academic-paper-get-to-know-abstracts-vs-structured-abstracts-11ed86888367  
• Markel M and Selber S. Technical Communication, 12 th edition. 2018; pp. 482. Bedford/St Martin’s.  
• Abstracts. Arkansas State University. Accessed June 17, 2024. https://www.astate.edu/a/global-initiatives/online/a-state-online-services/online-writing-center/resources/How%20to%20Write%20an%20Abstract1.pdf  
• AMA Manual of Style. 11 th edition. Oxford University Press.  
• Writing an Abstract. The University of Melbourne. Accessed June 16, 2024. https://services.unimelb.edu.au/__data/assets/pdf_file/0007/471274/Writing_an_Abstract_Update_051112.pdf  
• 10 Good Abstract Examples that will Kickstart Your Brain. Kibin Essay Writing Blog. Published April 5, 2017. Accessed June 17, 2024. https://www.kibin.com/essay-writing-blog/10-good-abstract-examples/  
• A 10-step guide to make your research paper abstract more effective. Editage Insights. Published October 16, 2013. Accessed June 17, 2024. https://www.editage.com/insights/a-10-step-guide-to-make-your-research-paper-abstract-more-effective  
• Using keywords to write your title and abstract. Taylor & Francis Author Services. Accessed June 15, 2024. https://authorservices.taylorandfrancis.com/publishing-your-research/writing-your-paper/using-keywords-to-write-title-and-abstract/  
• How to choose and use keywords in research papers. Paperpal by Editage blog. Published March 10, 2023. Accessed June 17, 2024. https://paperpal.com/blog/researcher-resources/phd-pointers/how-to-choose-and-use-keywords-in-research-papers  
• Title, abstract and keywords. Springer. Accessed June 16, 2024. https://www.springer.com/it/authors-editors/authorandreviewertutorials/writing-a-journal-manuscript/title-abstract-and-keywords/10285522  
• Abstract and keywords guide. APA Style, 7 th edition. Accessed June 18, 2024. https://apastyle.apa.org/instructional-aids/abstract-keywords-guide.pdf  
• Abstract guidelines. American Society for Microbiology. Accessed June 18, 2024. https://asm.org/events/asm-microbe/present/abstract-guidelines  
• Guidelines for conference abstracts. The Lancet. Accessed June 16, 2024. https://www.thelancet.com/pb/assets/raw/Lancet/pdfs/Abstract_Guidelines_2013.pdf  
• Is a conference abstract the same as a paper abstract? Global Conference Alliance, Inc. Accessed June 18, 2024. https://globalconference.ca/is-a-conference-abstract-the-same-as-a-paper-abstract/  

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Writing an abstract - a six point checklist (with samples)

Posted in: abstract , dissertations

The abstract is a vital part of any research paper. It is the shop front for your work, and the first stop for your reader. It should provide a clear and succinct summary of your study, and encourage your readers to read more. An effective abstract, therefore should answer the following questions:

• Why did you do this study or project?
• What did you do and how?
• What did you find?
• What do your findings mean?

So here's our run down of the key elements of a well-written abstract.

• Size - A succinct and well written abstract should be between approximately 100- 250 words.
• Background - An effective abstract usually includes some scene-setting information which might include what is already known about the subject, related to the paper in question (a few short sentences).
• Purpose  - The abstract should also set out the purpose of your research, in other words, what is not known about the subject and hence what the study intended to examine (or what the paper seeks to present).
• Methods - The methods section should contain enough information to enable the reader to understand what was done, and how. It should include brief details of the research design, sample size, duration of study, and so on.
• Results - The results section is the most important part of the abstract. This is because readers who skim an abstract do so to learn about the findings of the study. The results section should therefore contain as much detail about the findings as the journal word count permits.
• Conclusion - This section should contain the most important take-home message of the study, expressed in a few precisely worded sentences. Usually, the finding highlighted here relates to the primary outcomes of the study. However, other important or unexpected findings should also be mentioned. It is also customary, but not essential, to express an opinion about the theoretical or practical implications of the findings, or the importance of their findings for the field. Thus, the conclusions may contain three elements:
• The primary take-home message.
• Any additional findings of importance.
• Implications for future studies.

Example Abstract 2: Engineering Development and validation of a three-dimensional finite element model of the pelvic bone.

Abstract from: Dalstra, M., Huiskes, R. and Van Erning, L., 1995. Development and validation of a three-dimensional finite element model of the pelvic bone. Journal of biomechanical engineering, 117(3), pp.272-278.

And finally...  A word on abstract types and styles

Abstract types can differ according to subject discipline. You need to determine therefore which type of abstract you should include with your paper. Here are two of the most common types with examples.

Informative Abstract

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 researcher presents and explains all the main arguments and the important results and evidence in the paper. An informative abstract includes the information that can be found in a descriptive abstract [purpose, methods, scope] but it 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 usually no more than 300 words in length.

Descriptive Abstract A descriptive abstract indicates the type of information found in the work. It makes no judgements 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 only describes the work being summarised. Some researchers consider it an outline of the work, rather than a summary. Descriptive abstracts are usually very short, 100 words or less.

Adapted from Andrade C. How to write a good abstract for a scientific paper or conference presentation. Indian J Psychiatry. 2011 Apr;53(2):172-5. doi: 10.4103/0019-5545.82558. PMID: 21772657; PMCID: PMC3136027 .

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How to Write an Abstract APA Format

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

An APA abstract is a brief, comprehensive summary of the contents of an article, research paper, dissertation, or report.

It is written in accordance with the guidelines of the American Psychological Association (APA), which is a widely used format in social and behavioral sciences. 

An APA abstract summarizes, usually in one paragraph of between 150–250 words, the major aspects of a research paper or dissertation in a prescribed sequence that includes:

• The rationale: the overall purpose of the study, providing a clear context for the research undertaken.
• Information regarding the method and participants: including materials/instruments, design, procedure, and data analysis.
• Main findings or trends: effectively highlighting the key outcomes of the hypotheses.
• Interpretations and conclusion(s): solidify the implications of the research.
• Keywords related to the study: assist the paper’s discoverability in academic databases.

The abstract should stand alone, be “self-contained,” and make sense to the reader in isolation from the main article.

The purpose of the abstract is to give the reader a quick overview of the essential information before reading the entire article. The abstract is placed on its own page, directly after the title page and before the main body of the paper.

Although the abstract will appear as the very first part of your paper, it’s good practice to write your abstract after you’ve drafted your full paper, so that you know what you’re summarizing.

Note : This page reflects the latest version of the APA Publication Manual (i.e., APA 7), released in October 2019.

Structure of the Abstract

[NOTE: DO NOT separate the components of the abstract – it should be written as a single paragraph. This section is separated to illustrate the abstract’s structure.]

1) The Rationale

One or two sentences describing the overall purpose of the study and the research problem(s) you investigated. You are basically justifying why this study was conducted.

• What is the importance of the research?
• Why would a reader be interested in the larger work?
• For example, are you filling a gap in previous research or applying new methods to take a fresh look at existing ideas or data?
• Women who are diagnosed with breast cancer can experience an array of psychosocial difficulties; however, social support, particularly from a spouse, has been shown to have a protective function during this time. This study examined the ways in which a woman’s daily mood, pain, and fatigue, and her spouse’s marital satisfaction predict the woman’s report of partner support in the context of breast cancer.
• The current nursing shortage, high hospital nurse job dissatisfaction, and reports of uneven quality of hospital care are not uniquely American phenomena.
• Students with special educational needs and disabilities (SEND) are more likely to exhibit behavioral difficulties than their typically developing peers. The aim of this study was to identify specific risk factors that influence variability in behavior difficulties among individuals with SEND.

2) The Method

Information regarding the participants (number, and population). One or two sentences outlining the method, explaining what was done and how. The method is described in the present tense.

• Pretest data from a larger intervention study and multilevel modeling were used to examine the effects of women’s daily mood, pain, and fatigue and average levels of mood, pain, and fatigue on women’s report of social support received from her partner, as well as how the effects of mood interacted with partners’ marital satisfaction.
• This paper presents reports from 43,000 nurses from more than 700 hospitals in the United States, Canada, England, Scotland, and Germany in 1998–1999.
• The study sample comprised 4,228 students with SEND, aged 5–15, drawn from 305 primary and secondary schools across England. Explanatory variables were measured at the individual and school levels at baseline, along with a teacher-reported measure of behavior difficulties (assessed at baseline and the 18-month follow-up).

3) The Results

One or two sentences indicating the main findings or trends found as a result of your analysis. The results are described in the present or past tense.

• Results show that on days in which women reported higher levels of negative or positive mood, as well as on days they reported more pain and fatigue, they reported receiving more support. Women who, on average, reported higher levels of positive mood tended to report receiving more support than those who, on average, reported lower positive mood. However, average levels of negative mood were not associated with support. Higher average levels of fatigue but not pain were associated with higher support. Finally, women whose husbands reported higher levels of marital satisfaction reported receiving more partner support, but husbands’ marital satisfaction did not moderate the effect of women’s mood on support.
• Nurses in countries with distinctly different healthcare systems report similar shortcomings in their work environments and the quality of hospital care. While the competence of and relation between nurses and physicians appear satisfactory, core problems in work design and workforce management threaten the provision of care.
• Hierarchical linear modeling of data revealed that differences between schools accounted for between 13% (secondary) and 15.4% (primary) of the total variance in the development of students’ behavior difficulties, with the remainder attributable to individual differences. Statistically significant risk markers for these problems across both phases of education were being male, eligibility for free school meals, being identified as a bully, and lower academic achievement. Additional risk markers specific to each phase of education at the individual and school levels are also acknowledged.

4) The Conclusion / Implications

A brief summary of your conclusions and implications of the results, described in the present tense. Explain the results and why the study is important to the reader.

• For example, 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?

Implications of these findings are discussed relative to assisting couples during this difficult time in their lives.

• Resolving these issues, which are amenable to managerial intervention, is essential to preserving patient safety and care of consistently high quality.
• Behavior difficulties are affected by risks across multiple ecological levels. Addressing any one of these potential influences is therefore likely to contribute to the reduction in the problems displayed.

The above examples of abstracts are from the following papers:

Aiken, L. H., Clarke, S. P., Sloane, D. M., Sochalski, J. A., Busse, R., Clarke, H., … & Shamian, J. (2001). Nurses’ reports on hospital care in five countries . Health affairs, 20(3) , 43-53.

Boeding, S. E., Pukay-Martin, N. D., Baucom, D. H., Porter, L. S., Kirby, J. S., Gremore, T. M., & Keefe, F. J. (2014). Couples and breast cancer: Women’s mood and partners’ marital satisfaction predicting support perception . Journal of Family Psychology, 28(5) , 675.

Oldfield, J., Humphrey, N., & Hebron, J. (2017). Risk factors in the development of behavior difficulties among students with special educational needs and disabilities: A multilevel analysis . British journal of educational psychology, 87(2) , 146-169.

5) Keywords

APA style suggests including a list of keywords at the end of the abstract. This is particularly common in academic articles and helps other researchers find your work in databases.

Keywords in an abstract should be selected to help other researchers find your work when searching an online database. These keywords should effectively represent the main topics of your study. Here are some tips for choosing keywords:

Core Concepts: Identify the most important ideas or concepts in your paper. These often include your main research topic, the methods you’ve used, or the theories you’re discussing.

Specificity: Your keywords should be specific to your research. For example, suppose your paper is about the effects of climate change on bird migration patterns in a specific region. In that case, your keywords might include “climate change,” “bird migration,” and the region’s name.

Consistency with Paper: Make sure your keywords are consistent with the terms you’ve used in your paper. For example, if you use the term “adolescent” rather than “teen” in your paper, choose “adolescent” as your keyword, not “teen.”

Jargon and Acronyms: Avoid using too much-specialized jargon or acronyms in your keywords, as these might not be understood or used by all researchers in your field.

Synonyms: Consider including synonyms of your keywords to capture as many relevant searches as possible. For example, if your paper discusses “post-traumatic stress disorder,” you might include “PTSD” as a keyword.

Remember, keywords are a tool for others to find your work, so think about what terms other researchers might use when searching for papers on your topic.

The Abstract SHOULD NOT contain:

Lengthy background or contextual information: The abstract should focus on your research and findings, not general topic background.

Undefined jargon, abbreviations,  or acronyms: The abstract should be accessible to a wide audience, so avoid highly specialized terms without defining them.

Citations: Abstracts typically do not include citations, as they summarize original research.

Incomplete sentences or bulleted lists: The abstract should be a single, coherent paragraph written in complete sentences.

New information not covered in the paper: The abstract should only summarize the paper’s content.

Subjective comments or value judgments: Stick to objective descriptions of your research.

Excessive details on methods or procedures: Keep descriptions of methods brief and focused on main steps.

Speculative or inconclusive statements: The abstract should state the research’s clear findings, not hypotheses or possible interpretations.

• Any illustration, figure, table, or references to them . All visual aids, data, or extensive details should be included in the main body of your paper, not in the abstract. 
• Elliptical or incomplete sentences should be avoided in an abstract . The use of ellipses (…), which could indicate incomplete thoughts or omitted text, is not appropriate in an abstract.

APA Style for Abstracts

An APA abstract must be formatted as follows:

Include the running head aligned to the left at the top of the page (professional papers only) and page number. Note, student papers do not require a running head. On the first line, center the heading “Abstract” and bold (do not underlined or italicize). Do not indent the single abstract paragraph (which begins one line below the section title). Double-space the text. Use Times New Roman font in 12 pt. Set one-inch (or 2.54 cm) margins. If you include a “keywords” section at the end of the abstract, indent the first line and italicize the word “Keywords” while leaving the keywords themselves without any formatting.

Example APA Abstract Page

Download this example as a PDF

Further Information

• APA 7th Edition Abstract and Keywords Guide
• Example APA Abstract
• How to Write a Good Abstract for a Scientific Paper or Conference Presentation
• How to Write a Lab Report
• Writing an APA paper

How long should an APA abstract be?

An APA abstract should typically be between 150 to 250 words long. However, the exact length may vary depending on specific publication or assignment guidelines. It is crucial that it succinctly summarizes the essential elements of the work, including purpose, methods, findings, and conclusions.

Where does the abstract go in an APA paper?

In an APA formatted paper, the abstract is placed on its own page, directly after the title page and before the main body of the paper. It’s typically the second page of the document. It starts with the word “Abstract” (centered and not in bold) at the top of the page, followed by the text of the abstract itself.

What are the 4 C’s of abstract writing?

The 4 C’s of abstract writing are an approach to help you create a well-structured and informative abstract. They are:

Conciseness: An abstract should briefly summarize the key points of your study. Stick to the word limit (typically between 150-250 words for an APA abstract) and avoid unnecessary details.

Clarity: Your abstract should be easy to understand. Avoid jargon and complex sentences. Clearly explain the purpose, methods, results, and conclusions of your study.

Completeness: Even though it’s brief, the abstract should provide a complete overview of your study, including the purpose, methods, key findings, and your interpretation of the results.

Cohesion: The abstract should flow logically from one point to the next, maintaining a coherent narrative about your study. It’s not just a list of disjointed elements; it’s a brief story of your research from start to finish.

What is the abstract of a psychology paper?

An abstract in a psychology paper serves as a snapshot of the paper, allowing readers to quickly understand the purpose, methodology, results, and implications of the research without reading the entire paper. It is generally between 150-250 words long.

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How to Write an Abstract for a Research Paper | Examples

What is a research paper abstract?

Research paper abstracts summarize your study quickly and succinctly to journal editors and researchers and prompt them to read further. But with the ubiquity of online publication databases, writing a compelling abstract is even more important today than it was in the days of bound paper manuscripts.

Abstracts exist to “sell”  your work, and they could thus be compared to the “executive summary” of a business resume: an official briefing on what is most important about your research. Or the “gist” of your research. With the majority of academic transactions being conducted online, this means that you have even less time to impress readers–and increased competition in terms of other abstracts out there to read.

The APCI (Academic Publishing and Conferences International) notes that there are  12 questions or “points” considered in the selection process  for journals and conferences and stresses the importance of having an abstract that ticks all of these boxes. Because it is often the ONLY chance you have to convince readers to keep reading, it is important that you spend time and energy crafting an abstract that faithfully represents the central parts of your study and captivates your audience.

With that in mind, follow these suggestions when structuring and writing your abstract, and learn how exactly to put these ideas into a solid abstract that will captivate your target readers.

Before Writing Your Abstract

How long should an abstract be.

All abstracts are written with the same essential objective: to give a summary of your study. But there are two basic styles of abstract: descriptive and informative . Here is a brief delineation of the two:

Of the two types of abstracts, informative abstracts are much more common, and they are widely used for submission to journals and conferences. Informative abstracts apply to lengthier and more technical research and are common in the sciences, engineering, and psychology, while descriptive abstracts are more likely used in humanities and social science papers. The best method of determining which abstract type you need to use is to follow the instructions for journal submissions and to read as many other published articles in those journals as possible.

Research Abstract Guidelines and Requirements

As any article about research writing will tell you, authors must always closely follow the specific guidelines and requirements indicated in the Guide for Authors section of their target journal’s website. The same kind of adherence to conventions should be applied to journal publications, for consideration at a conference, and even when completing a class assignment.

Each publisher has particular demands when it comes to formatting and structure. Here are some common questions addressed in the journal guidelines:

• Is there a maximum or minimum word/character length?
• What are the style and formatting requirements?
• What is the appropriate abstract type?
• Are there any specific content or organization rules that apply?

There are of course other rules to consider when composing a research paper abstract. But if you follow the stated rules the first time you submit your manuscript, you can avoid your work being thrown in the “circular file” right off the bat.

Identify Your Target Readership

The main purpose of your abstract is to lead researchers to the full text of your research paper. In scientific journals, abstracts let readers decide whether the research discussed is relevant to their own interests or study. Abstracts also help readers understand your main argument quickly. Consider these questions as you write your abstract:

• Are other academics in your field the main target of your study?
• Will your study perhaps be useful to members of the general public?
• Do your study results include the wider implications presented in the abstract?

Outlining and Writing Your Abstract

What to include in an abstract.

Just as your  research paper title  should cover as much ground as possible in a few short words, your abstract must cover  all  parts of your study in order to fully explain your paper and research. Because it must accomplish this task in the space of only a few hundred words, it is important not to include ambiguous references or phrases that will confuse the reader or mislead them about the content and objectives of your research. Follow these  dos  and  don’ts  when it comes to what kind of writing to include:

• Avoid acronyms or abbreviations since these will need to be explained in order to make sense to the reader, which takes up valuable abstract space. Instead, explain these terms in the Introduction section of the main text.
• Only use references to people or other works if they are well-known. Otherwise, avoid referencing anything outside of your study in the abstract.
• Never include tables, figures, sources, or long quotations in your abstract; you will have plenty of time to present and refer to these in the body of your paper.

Use keywords in your abstract to focus your topic

A vital search tool is the research paper keywords section, which lists the most relevant terms directly underneath the abstract. Think of these keywords as the “tubes” that readers will seek and enter—via queries on databases and search engines—to ultimately land at their destination, which is your paper. Your abstract keywords should thus be words that are commonly used in searches but should also be highly relevant to your work and found in the text of your abstract. Include 5 to 10 important words or short phrases central to your research in both the abstract and the keywords section.

For example, if you are writing a paper on the prevalence of obesity among lower classes that crosses international boundaries, you should include terms like “obesity,” “prevalence,” “international,” “lower classes,” and “cross-cultural.” These are terms that should net a wide array of people interested in your topic of study. Look at our nine rules for choosing keywords for your research paper if you need more input on this.

Research Paper Abstract Structure

As mentioned above, the abstract (especially the informative abstract) acts as a surrogate or synopsis of your research paper, doing almost as much work as the thousands of words that follow it in the body of the main text. In the hard sciences and most social sciences, the abstract includes the following sections and organizational schema.

Each section is quite compact—only a single sentence or two, although there is room for expansion if one element or statement is particularly interesting or compelling. As the abstract is almost always one long paragraph, the individual sections should naturally merge into one another to create a holistic effect. Use the following as a checklist to ensure that you have included all of the necessary content in your abstract.

1) Identify your purpose and motivation

So your research is about rabies in Brazilian squirrels. Why is this important? You should start your abstract by explaining why people should care about this study—why is it significant to your field and perhaps to the wider world? And what is the exact purpose of your study; what are you trying to achieve? Start by answering the following questions:

• What made you decide to do this study or project?
• Why is this study important to your field or to the lay reader?
• Why should someone read your entire article?

In summary, the first section of your abstract should include the importance of the research and its impact on related research fields or on the wider scientific domain.

2) Explain the research problem you are addressing

Stating the research problem that your study addresses is the corollary to why your specific study is important and necessary. For instance, even if the issue of “rabies in Brazilian squirrels” is important, what is the problem—the “missing piece of the puzzle”—that your study helps resolve?

You can combine the problem with the motivation section, but from a perspective of organization and clarity, it is best to separate the two. Here are some precise questions to address:

• What is your research trying to better understand or what problem is it trying to solve?
• What is the scope of your study—does it try to explain something general or specific?
• What is your central claim or argument?

3) Discuss your research approach

Your specific study approach is detailed in the Methods and Materials section .  You have already established the importance of the research, your motivation for studying this issue, and the specific problem your paper addresses. Now you need to discuss  how  you solved or made progress on this problem—how you conducted your research. If your study includes your own work or that of your team, describe that here. If in your paper you reviewed the work of others, explain this here. Did you use analytic models? A simulation? A double-blind study? A case study? You are basically showing the reader the internal engine of your research machine and how it functioned in the study. Be sure to:

• Detail your research—include methods/type of the study, your variables, and the extent of the work
• Briefly present evidence to support your claim
• Highlight your most important sources

4) Briefly summarize your results

Here you will give an overview of the outcome of your study. Avoid using too many vague qualitative terms (e.g, “very,” “small,” or “tremendous”) and try to use at least some quantitative terms (i.e., percentages, figures, numbers). Save your qualitative language for the conclusion statement. Answer questions like these:

• What did your study yield in concrete terms (e.g., trends, figures, correlation between phenomena)?
• How did your results compare to your hypothesis? Was the study successful?
• Where there any highly unexpected outcomes or were they all largely predicted?

5) State your conclusion

In the last section of your abstract, you will give a statement about the implications and  limitations of the study . Be sure to connect this statement closely to your results and not the area of study in general. Are the results of this study going to shake up the scientific world? Will they impact how people see “Brazilian squirrels”? Or are the implications minor? Try not to boast about your study or present its impact as  too  far-reaching, as researchers and journals will tend to be skeptical of bold claims in scientific papers. Answer one of these questions:

• What are the exact effects of these results on my field? On the wider world?
• What other kind of study would yield further solutions to problems?
• What other information is needed to expand knowledge in this area?

After Completing the First Draft of Your Abstract

Revise your abstract.

The abstract, like any piece of academic writing, should be revised before being considered complete. Check it for  grammatical and spelling errors  and make sure it is formatted properly.

Get feedback from a peer

Getting a fresh set of eyes to review your abstract is a great way to find out whether you’ve summarized your research well. Find a reader who understands research papers but is not an expert in this field or is not affiliated with your study. Ask your reader to summarize what your study is about (including all key points of each section). This should tell you if you have communicated your key points clearly.

In addition to research peers, consider consulting with a professor or even a specialist or generalist writing center consultant about your abstract. Use any resource that helps you see your work from another perspective.

Consider getting professional editing and proofreading

While peer feedback is quite important to ensure the effectiveness of your abstract content, it may be a good idea to find an academic editor  to fix mistakes in grammar, spelling, mechanics, style, or formatting. The presence of basic errors in the abstract may not affect your content, but it might dissuade someone from reading your entire study. Wordvice provides English editing services that both correct objective errors and enhance the readability and impact of your work.

Additional Abstract Rules and Guidelines

Write your abstract after completing your paper.

Although the abstract goes at the beginning of your manuscript, it does not merely introduce your research topic (that is the job of the title), but rather summarizes your entire paper. Writing the abstract last will ensure that it is complete and consistent with the findings and statements in your paper.

Keep your content in the correct order

Both questions and answers should be organized in a standard and familiar way to make the content easier for readers to absorb. Ideally, it should mimic the overall format of your essay and the classic “introduction,” “body,” and “conclusion” form, even if the parts are not neatly divided as such.

Write the abstract from scratch

Because the abstract is a self-contained piece of writing viewed separately from the body of the paper, you should write it separately as well. Never copy and paste direct quotes from the paper and avoid paraphrasing sentences in the paper. Using new vocabulary and phrases will keep your abstract interesting and free of redundancies while conserving space.

Don’t include too many details in the abstract

Again, the density of your abstract makes it incompatible with including specific points other than possibly names or locations. You can make references to terms, but do not explain or define them in the abstract. Try to strike a balance between being specific to your study and presenting a relatively broad overview of your work.

Wordvice Resources

If you think your abstract is fine now but you need input on abstract writing or require English editing services (including paper editing ), then head over to the Wordvice academic resources page, where you will find many more articles, for example on writing the Results , Methods , and Discussion sections of your manuscript, on choosing a title for your paper , or on how to finalize your journal submission with a strong cover letter .    

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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How to write a good abstract for a scientific paper or conference presentation

Chittaranjan andrade.

Department of Psychopharmacology, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India

Abstracts of scientific papers are sometimes poorly written, often lack important information, and occasionally convey a biased picture. This paper provides detailed suggestions, with examples, for writing the background, methods, results, and conclusions sections of a good abstract. The primary target of this paper is the young researcher; however, authors with all levels of experience may find useful ideas in the paper.

INTRODUCTION

This paper is the third in a series on manuscript writing skills, published in the Indian Journal of Psychiatry . Earlier articles offered suggestions on how to write a good case report,[ 1 ] and how to read, write, or review a paper on randomized controlled trials.[ 2 , 3 ] The present paper examines how authors may write a good abstract when preparing their manuscript for a scientific journal or conference presentation. Although the primary target of this paper is the young researcher, it is likely that authors with all levels of experience will find at least a few ideas that may be useful in their future efforts.

The abstract of a paper is the only part of the paper that is published in conference proceedings. The abstract is the only part of the paper that a potential referee sees when he is invited by an editor to review a manuscript. The abstract is the only part of the paper that readers see when they search through electronic databases such as PubMed. Finally, most readers will acknowledge, with a chuckle, that when they leaf through the hard copy of a journal, they look at only the titles of the contained papers. If a title interests them, they glance through the abstract of that paper. Only a dedicated reader will peruse the contents of the paper, and then, most often only the introduction and discussion sections. Only a reader with a very specific interest in the subject of the paper, and a need to understand it thoroughly, will read the entire paper.

Thus, for the vast majority of readers, the paper does not exist beyond its abstract. For the referees, and the few readers who wish to read beyond the abstract, the abstract sets the tone for the rest of the paper. It is therefore the duty of the author to ensure that the abstract is properly representative of the entire paper. For this, the abstract must have some general qualities. These are listed in Table 1 .

General qualities of a good abstract

SECTIONS OF AN ABSTRACT

Although some journals still publish abstracts that are written as free-flowing paragraphs, most journals require abstracts to conform to a formal structure within a word count of, usually, 200–250 words. The usual sections defined in a structured abstract are the Background, Methods, Results, and Conclusions; other headings with similar meanings may be used (eg, Introduction in place of Background or Findings in place of Results). Some journals include additional sections, such as Objectives (between Background and Methods) and Limitations (at the end of the abstract). In the rest of this paper, issues related to the contents of each section will be examined in turn.

This section should be the shortest part of the abstract and should very briefly outline the following information:

• What is already known about the subject, related to the paper in question
• What is not known about the subject and hence what the study intended to examine (or what the paper seeks to present)

In most cases, the background can be framed in just 2–3 sentences, with each sentence describing a different aspect of the information referred to above; sometimes, even a single sentence may suffice. The purpose of the background, as the word itself indicates, is to provide the reader with a background to the study, and hence to smoothly lead into a description of the methods employed in the investigation.

Some authors publish papers the abstracts of which contain a lengthy background section. There are some situations, perhaps, where this may be justified. In most cases, however, a longer background section means that less space remains for the presentation of the results. This is unfortunate because the reader is interested in the paper because of its findings, and not because of its background.

A wide variety of acceptably composed backgrounds is provided in Table 2 ; most of these have been adapted from actual papers.[ 4 – 9 ] Readers may wish to compare the content in Table 2 with the original abstracts to see how the adaptations possibly improve on the originals. Note that, in the interest of brevity, unnecessary content is avoided. For instance, in Example 1 there is no need to state “The antidepressant efficacy of desvenlafaxine (DV), a dual-acting antidepressant drug , has been established…” (the unnecessary content is italicized).

Examples of the background section of an abstract

The methods section is usually the second-longest section in the abstract. It should contain enough information to enable the reader to understand what was done, and how. Table 3 lists important questions to which the methods section should provide brief answers.

Questions regarding which information should ideally be available in the methods section of an abstract

Carelessly written methods sections lack information about important issues such as sample size, numbers of patients in different groups, doses of medications, and duration of the study. Readers have only to flip through the pages of a randomly selected journal to realize how common such carelessness is.

Table 4 presents examples of the contents of accept-ably written methods sections, modified from actual publications.[ 10 , 11 ] Readers are invited to take special note of the first sentence of each example in Table 4 ; each is packed with detail, illustrating how to convey the maximum quantity of information with maximum economy of word count.

Examples of the methods section of an abstract

The results section is the most important part of the abstract and nothing should compromise its range and quality. This is because readers who peruse an abstract do so to learn about the findings of the study. The results section should therefore be the longest part of the abstract and should contain as much detail about the findings as the journal word count permits. For example, it is bad writing to state “Response rates differed significantly between diabetic and nondiabetic patients.” A better sentence is “The response rate was higher in nondiabetic than in diabetic patients (49% vs 30%, respectively; P <0.01).”

Important information that the results should present is indicated in Table 5 . Examples of acceptably written abstracts are presented in Table 6 ; one of these has been modified from an actual publication.[ 11 ] Note that the first example is rather narrative in style, whereas the second example is packed with data.

Information that the results section of the abstract should ideally present

Examples of the results section of an abstract

CONCLUSIONS

This section should contain the most important take-home message of the study, expressed in a few precisely worded sentences. Usually, the finding highlighted here relates to the primary outcome measure; however, other important or unexpected findings should also be mentioned. It is also customary, but not essential, for the authors to express an opinion about the theoretical or practical implications of the findings, or the importance of their findings for the field. Thus, the conclusions may contain three elements:

• The primary take-home message
• The additional findings of importance
• The perspective

Despite its necessary brevity, this section has the most impact on the average reader because readers generally trust authors and take their assertions at face value. For this reason, the conclusions should also be scrupulously honest; and authors should not claim more than their data demonstrate. Hypothetical examples of the conclusions section of an abstract are presented in Table 7 .

Examples of the conclusions section of an abstract

MISCELLANEOUS OBSERVATIONS

Citation of references anywhere within an abstract is almost invariably inappropriate. Other examples of unnecessary content in an abstract are listed in Table 8 .

Examples of unnecessary content in a abstract

It goes without saying that whatever is present in the abstract must also be present in the text. Likewise, whatever errors should not be made in the text should not appear in the abstract (eg, mistaking association for causality).

As already mentioned, the abstract is the only part of the paper that the vast majority of readers see. Therefore, it is critically important for authors to ensure that their enthusiasm or bias does not deceive the reader; unjustified speculations could be even more harmful. Misleading readers could harm the cause of science and have an adverse impact on patient care.[ 12 ] A recent study,[ 13 ] for example, concluded that venlafaxine use during the second trimester of pregnancy may increase the risk of neonates born small for gestational age. However, nowhere in the abstract did the authors mention that these conclusions were based on just 5 cases and 12 controls out of the total sample of 126 cases and 806 controls. There were several other serious limitations that rendered the authors’ conclusions tentative, at best; yet, nowhere in the abstract were these other limitations expressed.

As a parting note: Most journals provide clear instructions to authors on the formatting and contents of different parts of the manuscript. These instructions often include details on what the sections of an abstract should contain. Authors should tailor their abstracts to the specific requirements of the journal to which they plan to submit their manuscript. It could also be an excellent idea to model the abstract of the paper, sentence for sentence, on the abstract of an important paper on a similar subject and with similar methodology, published in the same journal for which the manuscript is slated.

Source of Support: Nil

Conflict of Interest: None declared.

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Writing an Abstract for a Research Paper: Guidelines, Examples, and Templates

There are six steps to writing a standard abstract. (1) Begin with a broad statement about your topic. Then, (2) state the problem or knowledge gap related to this topic that your study explores. After that, (3) describe what specific aspect of this problem you investigated, and (4) briefly explain how you went about doing this. After that, (5) describe the most meaningful outcome(s) of your study. Finally, (6) close your abstract by explaining the broad implication(s) of your findings.

In this article, I present step-by-step guidelines for writing an abstract for an academic paper. These guidelines are fo llowed by an example of a full abstract that follows these guidelines and a few fill-in-the-blank templates that you can use to write your own abstract.

Guidelines for Writing an Abstract

The basic structure of an abstract is illustrated below.

A standard abstract starts with a very general statement and becomes more specific with each sentence that follows until once again making a broad statement about the study’s implications at the end. Altogether, a standard abstract has six functions, which are described in detail below.

Start by making a broad statement about your topic.

The first sentence of your abstract should briefly describe a problem that is of interest to your readers. When writing this first sentence, you should think about who comprises your target audience and use terms that will appeal to this audience. If your opening sentence is too broad, it might lose the attention of potential readers because they will not know if your study is relevant to them.

Too broad : Maintaining an ideal workplace environment has a positive effect on employees.

The sentence above is so broad that it will not grab the reader’s attention. While it gives the reader some idea of the area of study, it doesn’t provide any details about the author’s topic within their research area. This can be fixed by inserting some keywords related to the topic (these are underlined in the revised example below).

Improved : Keeping the workplace environment at an ideal temperature positively affects the overall health of employees.

The revised sentence is much better, as it expresses two points about the research topic—namely, (i) what aspect of workplace environment was studied, (ii) what aspect of employees was observed. The mention of these aspects of the research will draw the attention of readers who are interested in them.

Describe the general problem that your paper addresses.

After describing your topic in the first sentence, you can then explain what aspect of this topic has motivated your research. Often, authors use this part of the abstract to describe the research gap that they identified and aimed to fill. These types of sentences are often characterized by the use of words such as “however,” “although,” “despite,” and so on.

However, a comprehensive understanding of how different workplace bullying experiences are associated with absenteeism is currently lacking.

The above example is typical of a sentence describing the problem that a study intends to tackle. The author has noticed that there is a gap in the research, and they briefly explain this gap here.

Although it has been established that quantity and quality of sleep can affect different types of task performance and personal health, the interactions between sleep habits and workplace behaviors have received very little attention.

The example above illustrates a case in which the author has accomplished two tasks with one sentence. The first part of the sentence (up until the comma) mentions the general topic that the research fits into, while the second part (after the comma) describes the general problem that the research addresses.

Express the specific problem investigated in your paper.

After describing the general problem that motivated your research, the next sentence should express the specific aspect of the problem that you investigated. Sentences of this type are often indicated by the use of phrases like “the purpose of this research is to,” “this paper is intended to,” or “this work aims to.”

Uninformative : However, a comprehensive understanding of how different workplace bullying experiences are associated with absenteeism is currently lacking. The present article aimed to provide new insights into the relationship between workplace bullying and absenteeism .

The second sentence in the above example is a mere rewording of the first sentence. As such, it adds nothing to the abstract. The second sentence should be more specific than the preceding one.

Improved : However, a comprehensive understanding of how different workplace bullying experiences are associated with absenteeism is currently lacking. The present article aimed to define various subtypes of workplace bullying and determine which subtypes tend to lead to absenteeism .

The second sentence of this passage is much more informative than in the previous example. This sentence lets the reader know exactly what they can expect from the full research article.

Explain how you attempted to resolve your study’s specific problem.

In this part of your abstract, you should attempt to describe your study’s methodology in one or two sentences. As such, you must be sure to include only the most important information about your method. At the same time, you must also be careful not to be too vague.

Too vague : We conducted multiple tests to examine changes in various factors related to well-being.

This description of the methodology is too vague. Instead of merely mentioning “tests” and “factors,” the author should note which specific tests were run and which factors were assessed.

Improved : Using data from BHIP completers, we conducted multiple one-way multivariate analyses of variance and follow-up univariate t-tests to examine changes in physical and mental health, stress, energy levels, social satisfaction, self-efficacy, and quality of life.

This sentence is very well-written. It packs a lot of specific information about the method into a single sentence. Also, it does not describe more details than are needed for an abstract.

Briefly tell the reader what you found by carrying out your study.

This is the most important part of the abstract—the other sentences in the abstract are there to explain why this one is relevant. When writing this sentence, imagine that someone has asked you, “What did you find in your research?” and that you need to answer them in one or two sentences.

Too vague : Consistently poor sleepers had more health risks and medical conditions than consistently optimal sleepers.

This sentence is okay, but it would be helpful to let the reader know which health risks and medical conditions were related to poor sleeping habits.

Improved : Consistently poor sleepers were more likely than consistently optimal sleepers to suffer from chronic abdominal pain, and they were at a higher risk for diabetes and heart disease.

This sentence is better, as the specific health conditions are named.

Finally, describe the major implication(s) of your study.

Most abstracts end with a short sentence that explains the main takeaway(s) that you want your audience to gain from reading your paper. Often, this sentence is addressed to people in power (e.g., employers, policymakers), and it recommends a course of action that such people should take based on the results.

Too broad : Employers may wish to make use of strategies that increase employee health.

This sentence is too broad to be useful. It does not give employers a starting point to implement a change.

Improved : Employers may wish to incorporate sleep education initiatives as part of their overall health and wellness strategies.

This sentence is better than the original, as it provides employers with a starting point—specifically, it invites employers to look up information on sleep education programs.

Abstract Example

The abstract produced here is from a paper published in Electronic Commerce Research and Applications . I have made slight alterations to the abstract so that this example fits the guidelines given in this article.

(1) Gamification can strengthen enjoyment and productivity in the workplace. (2) Despite this, research on gamification in the work context is still limited. (3) In this study, we investigated the effect of gamification on the workplace enjoyment and productivity of employees by comparing employees with leadership responsibilities to those without leadership responsibilities. (4) Work-related tasks were gamified using the habit-tracking game Habitica, and data from 114 employees were gathered using an online survey. (5) The results illustrated that employees without leadership responsibilities used work gamification as a trigger for self-motivation, whereas employees with leadership responsibilities used it to improve their health. (6) Work gamification positively affected work enjoyment for both types of employees and positively affected productivity for employees with leadership responsibilities. (7) Our results underline the importance of taking work-related variables into account when researching work gamification.

In Sentence (1), the author makes a broad statement about their topic. Notice how the nouns used (“gamification,” “enjoyment,” “productivity”) are quite general while still indicating the focus of the paper. The author uses Sentence (2) to very briefly state the problem that the research will address.

In Sentence (3), the author explains what specific aspects of the problem mentioned in Sentence (2) will be explored in the present work. Notice that the mention of leadership responsibilities makes Sentence (3) more specific than Sentence (2). Sentence (4) gets even more specific, naming the specific tools used to gather data and the number of participants.

Sentences (5) and (6) are similar, with each sentence describing one of the study’s main findings. Then, suddenly, the scope of the abstract becomes quite broad again in Sentence (7), which mentions “work-related variables” instead of a specific variable and “researching” instead of a specific kind of research.

Abstract Templates

Copy and paste any of the paragraphs below into a word processor. Then insert the appropriate information to produce an abstract for your research paper.

Template #1

Researchers have established that [Make a broad statement about your area of research.] . However, [Describe the knowledge gap that your paper addresses.] . The goal of this paper is to [Describe the purpose of your paper.] . The achieve this goal, we [Briefly explain your methodology.] . We found that [Indicate the main finding(s) of your study; you may need two sentences to do this.] . [Provide a broad implication of your results.] .

Template #2

It is well-understood that [Make a broad statement about your area of research.] . Despite this, [Describe the knowledge gap that your paper addresses.] . The current research aims to [Describe the purpose of your paper.] . To accomplish this, we [Briefly explain your methodology.] . It was discovered that [Indicate the main finding(s) of your study; you may need two sentences to do this.] . [Provide a broad implication of your results.] .

Template #3

Extensive research indicates that [Make a broad statement about your area of research.] . Nevertheless, [Describe the knowledge gap that your paper addresses.] . The present work is intended to [Describe the purpose of your paper.] . To this end, we [Briefly explain your methodology.] . The results revealed that [Indicate the main finding(s) of your study; you may need two sentences to do this.] . [Provide a broad implication of your results.] .

• How to Write an Abstract

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How to Write an Abstract

How to write an abstract for a conference, what is an abstract and why is it important, an abstract is a brief summary of your research or creative project, usually about a paragraph long (250-350 words), and is written when you are ready to present your research or included in a thesis or research publication..

For additional support in writing your abstract, you can contact the Office of URSA at [email protected]  or schedule a time to meet with a Writing and Research Consultant at the OSU Writing Center 

Main Components of an Abstract: 

The opening sentences should summarize your topic and describe what researchers already know, with reference to the literature. 

A brief discussion that clearly states the purpose of your research or creative project. This should give general background information on your work and allow people from different fields to understand what you are talking about. Use verbs like investigate, analyze, test, etc. to describe how you began your work. 

In this section you will be discussing the ways in which your research was performed and the type of tools or methodological techniques you used to conduct your research. 

This is where you describe the main findings of your research study and what you have learned. Try to include only the most important findings of your research that will allow the reader to understand your conclusions. If you have not completed the project, talk about your anticipated results and what you expect the outcomes of the study to be. 

Significance

This is the final section of your abstract where you summarize the work performed. This is where you also discuss the relevance of your work and how it advances your field and the scientific field in general.

• Your word count for a conference may be limited, so make your abstract as clear and concise as possible.
• Organize it by using good transition words found on the lef so the information flows well.
• Have your abstract proofread and receive feedback from your supervisor, advisor, peers, writing center, or other professors from different disciplines. 
• Double-check on the guidelines for your abstract and adhere to any formatting or word count requirements.
• Do not include bibliographic references or footnotes. 
• Avoid the overuse of technical terms or jargon. 

Feeling stuck? Visit the OSU ScholarsArchive for more abstract examples related to your field

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How To Write A Research Paper

Research Paper Abstract

How to Write an Abstract For a Research Paper with Examples

12 min read

Published on: Jan 19, 2024

Last updated on: Jul 23, 2024

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Struggling to encapsulate your extensive research into a concise abstract? Writing an abstract for a research paper can be intimidating, but it doesn't have to be! 

This blog is your guide to deciphering the abstract, understanding its purpose, and learning the art of writing your own.

We'll break down the abstract into clear, simple steps. We'll show you what it is, why it matters, and most importantly, how to write one that's clear, concise, and grabs your reader's attention. 

So, leave your confusion behind, and let's dive into it!

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What is an Abstract in a Paper?

An abstract in a research paper is a concise summary that provides an overview of the main points and key elements of the entire document. It is typically found at the beginning of academic papers, articles, or research reports. 

The abstract serves as a standalone piece that briefly communicates the purpose, methodology, results, and conclusions of the study.

Usually ranging from 150 to 250 words, an abstract provides readers with a quick overview of the entire text.

Purpose of Abstracts

Abstracts serve several essential purposes in academic and professional settings, and therefore the importance of abstracts in research can not be overlooked. The primary objectives of abstracts include:

• Concise Summary : Distills key elements for quick understanding.
• Quick Information Retrieval : Saves time by offering a snapshot of document relevance.
• Decision-Making Tool : Helps researchers choose studies aligning with their objectives.
• Communication of Research : Disseminates findings to diverse audiences effectively.
• Database Indexing : Facilitates efficient literature review in academic databases.
• Conference and Journal Submissions : Essential requirement for evaluating contributions' merit and relevance.

When to Write an Abstract?

We need to include an abstract when:

• Submitting research papers for publication.
• Sending research proposals for conferences or academic events.
• Completing theses, dissertations, or comprehensive reports.
• Drafting articles for scholarly journals.
• Presenting academic projects or detailed proposals.

Types of Abstract

There are 2 basic types of abstract writing:

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The Contents of an Abstract

An abstract typically includes the following components:

• Purpose/Objective : Clearly states the primary goal of the research or document.
• Methods/Approach : Briefly outline the methodology or approach used in the study.
• Results/Findings : Highlights the main outcomes or discoveries of the research.
• Conclusions/Implications : Summarize the key conclusions and their broader significance.

Another way to structure your abstract is to use the IMRaD structure. It stands for:

• Introduction : Introduces the research topic and the problem under investigation.
• Methods : Describes the research methods and experimental design employed.
• Results : Presents the main findings or outcomes of the study.
• Discussion : Analyzes the results, discusses their implications, and draws conclusions.

Adhering to the IMRaD structure ensures a logical flow in your abstract, making it comprehensible and informative for readers.

How to Write an Abstract in 5 Steps?

Let's take a look at the simple steps to write an abstract for a research paper: 

Step 1: Craft an Engaging Introduction 

Begin by clearly defining the purpose of your research. Identify the practical or theoretical problem your research addresses and state the research question you aim to answer. 

Provide brief context on the social or academic relevance of your topic without delving into detailed background information. If using specialized terms, offer concise definitions. 

Use verbs like "investigate," "analyze," or "evaluate" to describe your research objective. Write in the present or past simple tense, avoiding references to the future, as the research is already complete.

Step 2: Outline Your Methods Clearly

Outline the research methods and experimental design employed in your study. Refrain from evaluating the validity or challenges of your methodology. Provide a clear description of how you conducted your research, including any specific techniques, tools, or procedures used.

Be concise but offer enough detail for readers to understand the approach you took. Use the past simple tense to describe methods. 

Step 3: Present Your Results with Precision

Highlight the main findings or outcomes of your research. Summarize the data collected and present key results without interpretation. Use clear and specific language to convey the essential elements of your study.

This section of the abstract can use either present or past simple tense.

Step 4: Articulate a Thoughtful Discussion

Analyze the results and discuss their implications. Interpret the findings in the context of your research question and objectives. Explore the broader significance of your results and any potential applications or recommendations.

Include brief mentions of any significant limitations in your research, such as those related to sample size or methods. This provides readers with insights to assess the credibility and generalizability of your study.

Step 5: List Relevant Keywords

Conclude your abstract by listing keywords that capture the essential concepts and topics addressed in your research. These keywords assist in indexing and categorizing your work for easy retrieval in academic databases.

Abstract Examples

Below are some samples to help you understand how to write an effective abstract for a research paper: 

Sample Abstract 1

Abstract for a research paper humanities

Bago, B., Kovacs, M., Protzko, J., Nagy, T., Kekecs, Z., Palfi, B., Adamkovi, M., Adamus, S., Albalooshi, S., AlbayrakAydemir, N., Alfian, I., Alper, S., Solas, S. A., Alves, S. G., Amaya, S., Andresen, P., Anjum, G., Ansari, D., Arriaga, P., . . . Aczel, B. (2022). Situational factors shape moral judgements in the trolley dilemma in Eastern, Southern and Western countries in a culturally diverse sample. Nature Human Behaviour , 6 (6), 880 - 895. https://doi.org/10.1038/s41562-022-01319-5

Sample Abstract 2

Social sciences Abstract 

Reference : 

Hanlon, M., Yeung, K., & Zuo, L. (2021). Behavioral Economics of Accounting: A review of archival research on individual decision makers*. Contemporary Accounting Research , 39 (2), 1150 - 1214. https://doi.org/10.1111/1911-3846.12739

Sample Abstract 3

Abstract for the Sciences

Reference: 

Widen, E., Junna, N., Ruotsalainen, S., Surakka, I., Mars, N., Ripatti, P., Partanen, J., Aro, J., Mustonen, P., Tuomi, T., Palotie, A., Salomaa, V., Kaprio, J., Partanen, J., Hotakainen, K., Pollanen, P., & Ripatti, S. (2022). How Communicating Polygenic and Clinical Risk for Atherosclerotic Cardiovascular Disease Impacts Health Behavior: an Observational Follow-up Study. Circulation , 15 (2). https://doi.org/10.1161/circgen.121.003459

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Sample IMRaD Abstract

Here are some PDF samples of the abstract; check them out for a more detailed understanding: 

Abstract For a Research Paper Example

Abstract For a Research Paper Sample

Abstract For a Research Paper APA 7

Abstract For a Research Paper Proposal

Tips For Writing an Abstract

Here are some essential tips for writing an effective abstract:

• Understand the Types : Familiarize yourself with different types of abstracts - such as descriptive abstracts and informative abstracts.
• Clarity is Key: A good abstract is clear, concise, and easily understandable. Avoid unnecessary jargon or complex language.
• Follow a Structure : Organize your abstract with a structured format, including the research problem, methodology, key findings, and conclusions.
• Stay Within Word Limits : Adhere to specified word limits. Balancing brevity while conveying essential information is crucial.
• Define the Research Problem : Clearly state the research problem or objective to provide context for your study.
• Highlight Methodology : Briefly describe the methods used in your research, giving readers insight into your approach.
• Include Vital Information: Specify the type of information covered in your research abstract.
• Active Voice and Strong Verbs : Use active voice and strong verbs to convey a sense of authority and engagement.
• Follow Guidelines : Adhere to formatting requirements stated in the title page or table of contents.
• Choose Impactful Keywords: Incorporate relevant keywords that potential readers might use when searching for similar studies.
• Revise and Edit : Prioritize the clarity and coherence of your abstract, ensuring it aligns with guidelines and objectives.

 Abstract Checklist

Here's a checklist for writing an abstract for a research paper:

In summary, writing a compelling abstract is essential for conveying your research paper's core elements concisely. Remember, clarity and brevity are key. Feel free to revisit the examples provided for inspiration. 

If you face challenges in any section, including the abstract, reach out to CollegeEssay.org for professional assistance. Our expert writing service is here to guide you through academic intricacies. 

Get research paper writing help today for tailored support in achieving your scholarly goals.

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• How to Write An Abstract For Research Papers: Tips & Examples

In many ways, an abstract is like a trailer of a movie or the synopsis of your favorite book. Its job is to whet the reader’s appetite by sharing important information about your work. After reading a well-written abstract, one should have enough interest to explore the full research thesis. 

So how do you write an interesting abstract that captures the core of your study? First, you need to understand your research objectives and match them with the key results of your study. In this article, we will share some tips for writing an effective abstract, plus samples you can learn from. 

What is an Abstract in Research Writing?

In simple terms, an abstract is a concise write-up that gives an overview of your systematic investigation. According to Grammarly, it is a self-contained summary of a larger work, and it serves as a preview of the bigger document. 

It usually appears at the beginning of your thesis or research paper and helps the reader to have an overview of your work without going into great detail. This means that when someone reads your abstract, it should give them a clear idea of the purpose of your systematic investigation, your problem statement, key results, and any gaps requiring further investigation. 

So how long should your abstract be to capture all of these details? The reality is you don’t need a lot of words to capture key pieces of information in your abstract. Typically, 6–7 sentences made up of 150–250 words should be just right. 

Read: Writing Research Proposals: Tips, Examples & Mistakes

What are the Characteristics of a Good Abstract? 

• A good abstract clearly states the aims and objectives of the research.
• It outlines the research methodology for data gathering , processing and analysis. 
• A good abstract summarizes specific research results.
• It states the key conclusions of the systematic investigation.
• It is brief yet straight to the point. 
• A good abstract is unified and coherent. 
• It is easy to understand and devoid of technical jargon. 
• It is written in an unbiased and objective manner. 

What is the Purpose of an Abstract? 

Every abstract has two major purposes. First, it communicates the relevance of your systematic investigation to readers. After reading your abstract, people can determine how relevant your study is to their primary or secondary research purpose. 

The second purpose of an abstract is to communicate your key findings to those who don’t have time to read the whole paper. Research papers typically run into tens of pages so it takes time to read and digest them. To help readers grasp the core ideas in a systematic investigation, it pays to have a well-written abstract that outlines important information concerning your study. 

In all, your abstract should accurately outline the most important information in your research. Many times, it determines whether people would go ahead to read your dissertation. Abstracts are often indexed along with keywords on academic databases, so they make your thesis easily findable.

Learn About: How to Write a Problem Statement for your Research

What are the Sections of an Abstract?

You already know the key pieces of information that your abstract should communicate. These details are broken into six important sections of the abstract which are: 

• The Introduction or Background
• Research Methodology
• Aims and Objectives 
• Limitations

Let’s discuss them in detail. 

• The Introduction or Background 

The introduction or background is the shortest part of your abstract and usually consists of 2–3 sentences. In fact, some researchers write a single sentence as the introduction of their abstract. The whole idea here is to take the reader through the important events leading to your research. 

Understandably, this information may appear difficult to convey in a few sentences. To help out, consider answering these two questions in the background to your study : 

• What is already known about the subject, related to the paper in question? 
• What is not known about the subject (this is the focus of your study)? 

As much as possible, ensure that your abstract’s introduction doesn’t eat into the word count for the other key information. 

• Research Methodology 

This is the section where you spell out any theories and methods adopted for your study. Ideally, you should cover what has been done and how you went about it to achieve the results of your systematic investigation. It is usually the second-longest section in the abstract. 

In the research methodology section, you should also state the type of research you embarked on; that is, qualitative research or quantitative research —this will inform your research methods too. If you’ve conducted quantitative research, your abstract should contain information like the sample size, data collection methods , sampling technique, and duration of your experiment. 

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In the end, readers are most interested in the results you’ve achieved with your study. This means you should take time to outline every relevant outcome and show how they affect your research population . Typically, the results section should be the longest one in your abstract and nothing should compromise its range and quality. 

An important thing you should do here is spelled out facts and figures about research outcomes. Instead of a vague statement like, “we noticed that response rates differed greatly between high-income and low-income respondents”, try this: “The response rate was higher in high-income respondents than in their low-income counterparts (59% vs 30%, respectively; P

• Conclusion 

Like the introduction, your conclusion should contain a few sentences that wrap up your abstract. Most researchers express a theoretical opinion about the implications of their study, here. 

Your conclusion should contain three important elements: 

• The primary take-home message
• The additional findings of importance
• The perspective 

Although the conclusion of your abstract should be short, it has a great impact on how readers perceive your study. So, take advantage of this section to reiterate the core message in your systematic investigation. Also, make sure any statements here reflect the true outcomes and methods of your research. 

• Limitations 

Chances are you must have faced certain challenges in the course of your research—it could be at the data collection phase or during sampling . Whatever these challenges are, it pays to let your readers know about them, and the impact they had on your study. 

For example, if you had to switch to convenience sampling or snowball sampling due to difficulties in contacting well-suited research participants, you should include this in your abstract. Also, a lack of previous studies in the research area could pose a limitation on your study. Research limitations provide an opportunity to make suggestions for further research. 

Research aims and objectives speak to what you want to achieve with your study. Typically, research aims focus on a project’s long-term outcomes while the objectives focus on the immediate, short-term outcome of the investigation. You may summarize both using a single paragraph comprising a few sentences.

Stating your aims and objectives will give readers a clear idea of the scope, depth, and direction that your research will ultimately take. Readers would measure your research outcomes against stated aims and objectives to know if you achieved the purpose of your study. 

Use For Free: Research Form Templates

Abstract Writing Styles and General Guidelines 

Now that you know the different sections plus information that your abstract should contain, let’s look at how to write an abstract for your research paper.

A common question that comes up is, should I write my abstract first or last? It’s best to write your abstract after you’ve finished working on the research because you have full information to present to your readers. However, you can always create a draft at the beginning of your systematic investigation and fill in the gaps later.  

Does writing an abstract seem like a herculean task? Here are a few tips to help out. 

1. Always create a framework for your abstract 

Before you start writing, take time to develop a detailed outline for your abstract. Break it into sections and sketch the main and supporting points for each section. You can list keywords plus 1–2 sentences that capture your core messaging. 

2. Read Other Abstracts 

Abstracts are one of the most common research documents, and thousands of them have been written in time past. So, before writing yours, try to study a couple of samples from others. You can find lots of dissertation abstract examples in thesis and dissertation databases.

3. Steer Clear of Jargon As Much As Possible 

While writing your abstract, emphasize clarity over style. This means you should communicate in simple terms and avoid unnecessary filler words and ambiguous sentences. Remember, your abstract should be understandable to readers who are not familiar with your topic. 

4. Focus on Your Research

It goes without saying that your abstract should be solely focused on your research and what you’ve discovered. It’s not the time to cite primary and secondary data sources unless this is absolutely necessary. 

This doesn’t mean you should ignore the scholarly background of your work. You might include a sentence or two summarizing the scholarly background to show the relevance of your work to a broader debate, but there’s no need to mention specific publications. 

Going further, here are some abstract writing guidelines from the University of Bergen: 

• An abstract briefly explains the salient aspects of the content. 
• Abstracts should be accurate and succinct, self-contained, and readable.  
• The abstract should paraphrase and summarise rather than quote from the paper.
• Abstracts should relate only to the paper to be presented/assessed.

Types of Abstracts with Examples 

According to the University of Adelaide, there are two major types of abstracts written for research purposes. First, we have informative abstracts and descriptive abstracts. 

1. Informative Abstract  

An informative abstract is the more common type of abstract written for academic research. It highlights the most important aspects of your systematic investigation without going into unnecessary or irrelevant details that the reader might not find useful. 

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 longer work, it may be much less.

In any informative abstract, you’d touch on information like the purpose, method, scope, results, and conclusion of your study. By now, you’re thinking, “this is the type of abstract we’ve been discussing all along”, and you wouldn’t be far from the truth. 

Advantages of Informative Abstracts

• These abstracts save time for both the researcher and the readers. 
• It’s easy to refer to these abstracts as secondary research sources. 

Disadvantages of Informative Abstracts

• These types of abstracts lack personality.

Example of an Informative Abstract

• Sample Informative Abstract Based on Experimental Work From Colorado State University
• Sample Informative Abstract Based on Non-experimental Work From Colorado State University

2. Descriptive Abstract 

A descriptive abstract reads like a synopsis and focuses on enticing the reader with interesting information. They don’t care as much for data and details, and instead read more like overviews that don’t give too much away. 

You’d find descriptive abstracts in artistic criticism pieces and entertainment research as opposed to scientific investigations. This type of abstract makes no judgments about the work, nor does it provide results or conclusions of the research. They are usually written in 100 words or less. 

Advantages of Descriptive Abstracts

• It gives a very brief overview of the research paper. 
• It is easier to write descriptive abstracts compared to informational abstracts. 

Disadvantages of Descriptive Abstracts

• They are suitable for scientific research. 
• Descriptive abstracts might omit relevant information that deepens your knowledge of the systematic investigation.

Example of Descriptive Abstracts 

• Sample Descriptive Abstract From Colorado State University

FAQs About Writing Abstracts in Research Papers

1. How Long Should an Abstract Be?

A typical abstract should be about six sentences long or less than 150 words. Most universities have specific word count requirements that fall within 150–300 words. 

2. How Do You Start an Abstract Sentence?

There are several ways to start your abstract. Consider the following methods: 

• State a problem or uncertainty
• Make a general statement with the present research action.
• State the purpose or objective of your research
• State a real-world phenomena or a standard practice.

3. Should you cite in an abstract?

While you can refer to information from specific research papers, there’s no need to cite sources in your abstract. Your abstract should focus on your original research, not on the work of others. 

4. What should not be included in an abstract?

An abstract shouldn’t have numeric references, bibliographies, sections, or even footnotes. 

5. Which tense is used in writing an abstract?

An abstract should be written in the third-person present tense. Use the simple past tense when describing your methodology and specific findings from your study. 

Writing an abstract might appear challenging but with these steps, you should get it right. The easiest approach to writing a good abstract is centering it on key information including your research problem and objectives, methodology, and key results.

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Writing an Abstract

What is an abstract.

An abstract is a summary of your paper and/or research project. It is NOT an introduction to your paper; rather, it should highlight your major points, explain why your work is important, describe how you researched your problem, and offer your conclusions. Typically, an abstract should be approximately 250-300 words. 

How do I prepare an abstract?

Review the components of an abstract.

The exact content of your abstract will depend on the status of your project, disciplinary norms, and feedback from your mentor; however, it should include several of the components listed below: 

• Problem:  What is the central problem or question you investigated? 
• Context: Provide brief background to place your project into context. Explain previous studies, concepts, or theoretical or critical frameworks relevant to your research (i.e., what’s already known or has been done on this topic). 
• Purpose: Outline how your work is contributing to the existing knowledge or is addressing gaps within your field (i.e., why this area of research is important and what’s the rationale for your work). 
• Hypothesis: What prediction(s) did you make based on your research question? 
• Methods: Describe the important methods you used to perform your research or evidence you examined. 
• Results: What are the major results, findings or arguments of the research project?  
• Interpretation: How do your results relate back to your central problem? 
• Implications: Why are your results important? What can we learn from them? 

Understand the structure of an abstract

Once you are familiar with the key components of an abstract, the next step is to understand how to organize these elements effectively. The composition of your abstract can also take different forms depending on the type of research and the conventions of your specific discipline. Below are common structures for projects in STEM fields and in the humanities suggested by The Writing Center . 

For STEM and experimental projects

• Objective/Goal/Significance (Why did you do it or why did it need to be done? Why is this question important/worth asking?) 
• Methods/Approach (What did you do? How did you attempt to answer this question?) 
• Results (What did you find/expect to find? What did the research reveal?) 
• Conclusions (What did you learn?) 

For humanities projects

(Version 1)

• Background (What’s the importance of your topic?) 
• Thesis (What argument or claim are you making?) 
• Theoretical Approach (if applicable) 
• Conclusion 

(Version 2)

• Background (Existing conversation, contribution of research) 

Consider your audience

For the purposes of the symposium, the wording of an abstract should be understandable to a well-read, interdisciplinary audience. Specialized terms should be either defined or avoided. 

Consult additional resources

• Creating an Abstract resource from  WUSTL University Libraries  
• How to construct a  Nature summary paragraph  (biological and biomedical sciences) 
• Abstract Guide  from the American Psychological Association 
• Writing an Abstract for Your Research Paper  from the University of Wisconsin Writing Center 
• View students’ abstracts from last year’s Fall and Spring Undergraduate Research Symposia 

Get help and feedback

Share your abstract with your mentor well in advance of the deadline to receive their input. Your abstract must have the approval of your research mentor or advisor. 

In addition you may wish to make an appointment  with The Writing Center at any stage of the abstract writing process.  

Journal Article References

This page contains reference examples for journal articles, including the following:

• Journal article
• Journal article with an article number
• Journal article with missing information
• Retracted journal article
• Retraction notice for a journal article
• Abstract of a journal article from an abstract indexing database
• Monograph as part of a journal issue
• Online-only supplemental material to a journal article

1. Journal article

Grady, J. S., Her, M., Moreno, G., Perez, C., & Yelinek, J. (2019). Emotions in storybooks: A comparison of storybooks that represent ethnic and racial groups in the United States. Psychology of Popular Media Culture , 8 (3), 207–217. https://doi.org/10.1037/ppm0000185

• Parenthetical citation : (Grady et al., 2019)
• Narrative citation : Grady et al. (2019)
• If a journal article has a DOI, include the DOI in the reference.
• Always include the issue number for a journal article.
• If the journal article does not have a DOI and is from an academic research database, end the reference after the page range (for an explanation of why, see the database information page ). The reference in this case is the same as for a print journal article.
• Do not include database information in the reference unless the journal article comes from a database that publishes works of limited circulation or original, proprietary content, such as UpToDate .
• If the journal article does not have a DOI but does have a URL that will resolve for readers (e.g., it is from an online journal that is not part of a database), include the URL of the article at the end of the reference.

2. Journal article with an article number

Jerrentrup, A., Mueller, T., Glowalla, U., Herder, M., Henrichs, N., Neubauer, A., & Schaefer, J. R. (2018). Teaching medicine with the help of “Dr. House.” PLoS ONE , 13 (3), Article e0193972. https://doi.org/10.1371/journal.pone.0193972

• Parenthetical citation : (Jerrentrup et al., 2018)
• Narrative citation : Jerrentrup et al. (2018)
• If the journal article has an article number instead of a page range, include the word “Article” and then the article number instead of the page range.

3. Journal article with missing information

Missing volume number.

Lipscomb, A. Y. (2021, Winter). Addressing trauma in the college essay writing process. The Journal of College Admission , (249), 30–33. https://www.catholiccollegesonline.org/pdf/national_ccaa_in_the_news_-_nacac_journal_of_college_admission_winter_2021.pdf

Missing issue number

Sanchiz, M., Chevalier, A., & Amadieu, F. (2017). How do older and young adults start searching for information? Impact of age, domain knowledge and problem complexity on the different steps of information searching. Computers in Human Behavior , 72 , 67–78. https://doi.org/10.1016/j.chb.2017.02.038

Missing page or article number

Butler, J. (2017). Where access meets multimodality: The case of ASL music videos. Kairos: A Journal of Rhetoric, Technology, and Pedagogy , 21 (1). http://technorhetoric.net/21.1/topoi/butler/index.html

• Parenthetical citations : (Butler, 2017; Lipscomb, 2021; Sanchiz et al., 2017)
• Narrative citations : Butler (2017), Lipscomb (2021), and Sanchiz et al. (2017)
• If the journal does not use volume, issue, and/or article or page numbers, omit the missing element(s) from the reference.
• If the journal is published quarterly and the month or season (Fall, Winter, Spring, Summer) is noted, include that with the date element; see the Lipscomb example.
• If the volume, issue, and/or article or page numbers have simply not yet been assigned, use the format for an advance online publication (see Example 7 in the Publication Manual ) or an in-press article (see Example 8 in the Publication Manual ).

4. Retracted journal article

Joly, J. F., Stapel, D. A., & Lindenberg, S. M. (2008). Silence and table manners: When environments activate norms. Personality and Social Psychology Bulletin , 34 (8), 1047–1056. https://doi.org/10.1177/0146167208318401 (Retraction published 2012, Personality and Social Psychology Bulletin, 38 [10], 1378)

• Parenthetical citation : (Joly et al., 2008)
• Narrative citation : Joly et al. (2008)
• Use this format to cite the retracted article itself, for example, to discuss the contents of the retracted article.
• First provide publication details of the original article. Then provide information about the retraction in parentheses, including its year, journal, volume, issue, and page number(s).

5. Retraction notice for a journal article

de la Fuente, R., Bernad, A., Garcia-Castro, J., Martin, M. C., & Cigudosa, J. C. (2010). Retraction: Spontaneous human adult stem cell transformation. Cancer Research , 70 (16), 6682. https://doi.org/10.1158/0008-5472.CAN-10-2451

The Editors of the Lancet. (2010). Retraction—Ileal-lymphoid-nodular hyperplasia, non-specific colitis, and pervasive developmental disorder in children. The Lancet , 375 (9713), 445. https://doi.org/10.1016/S0140-6736(10)60175-4

• Parenthetical citations : (de la Fuente et al., 2010; The Editors of the Lancet, 2010)
• Narrative citations : de la Fuente et al. (2010) and The Editors of the Lancet (2010)
• Use this format to cite a retraction notice rather than a retracted article, for example, to provide information on why an article was retracted.
• The author of the retraction notice may be an editor, editorial board, or some or all authors of the article. Examine the retraction notice to determine who to credit as the author.
• Reproduce the title of the retraction notice as shown on the work. Note that the title may include the words “retraction,” “retraction notice,” or “retraction note” as well as the title of the original article.

6. Abstract of a journal article from an abstract indexing database

Hare, L. R., & O'Neill, K. (2000). Effectiveness and efficiency in small academic peer groups: A case study (Accession No. 200010185) [Abstract from Sociological Abstracts]. Small Group Research , 31 (1), 24–53. https://doi.org/10.1177/104649640003100102

• Parenthetical citation : (Hare & O’Neill, 2000)
• Narrative citation : Hare and O’Neill (2000)
• Although it is preferable to cite the whole article, the abstract can be cited if that is your only available source.
• The foundation of the reference is the same as for a journal article.
• If the abstract has a database accession number, place it in parentheses after the title.
• Note that you retrieved only the abstract by putting the words “Abstract from” and then the name of the abstract indexing database in square brackets. Place this bracketed description after the title and any accession number.
• Accession numbers are sometimes referred to as unique identifiers or as publication numbers (e.g., as PubMed IDs); use the term provided by the database in your reference.

7. Monograph as part of a journal issue

Ganster, D. C., Schaubroeck, J., Sime, W. E., & Mayes, B. T. (1991). The nomological validity of the Type A personality among employed adults [Monograph]. Journal of Applied Psychology , 76 (1), 143–168. http://doi.org/10.1037/0021-9010.76.1.143

• Parenthetical citation : (Ganster et al., 1991)
• Narrative citation : Ganster et al. (1991)
• For a monograph with an issue (or whole) number, include the issue number in parentheses followed by the serial number, for example, 58 (1, Serial No. 231).
• For a monograph bound separately as a supplement to a journal, give the issue number and supplement or part number in parentheses after the volume number, for example, 80 (3, Pt. 2).

8. Online-only supplemental material to a journal article

Freeberg, T. M. (2019). From simple rules of individual proximity, complex and coordinated collective movement [Supplemental material]. Journal of Comparative Psychology , 133 (2), 141–142. https://doi.org/10.1037/com0000181

• Parenthetical citation : (Freeberg, 2019)
• Narrative citation : Freeberg (2019)
• Include the description “[Supplemental material]” in square brackets after the article title.
• If you cite both the main article and the supplemental material, provide only a reference for the article.

Journal article references are covered in the seventh edition APA Style manuals in the Publication Manual Section 10.1 and the Concise Guide Section 10.1

Interactions between latent variables in count regression models

• Special Issue/Methodological Challenges of Complex Latent Mediator and Moderator Models
• Open access
• Published: 26 August 2024

Cite this article

You have full access to this open access article

• Christoph Kiefer   ORCID: orcid.org/0000-0002-9166-400X 1 ,
• Sarah Wilker   ORCID: orcid.org/0000-0002-0887-4672 2 &
• Axel Mayer   ORCID: orcid.org/0000-0001-9716-878X 1  

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In psychology and the social sciences, researchers often model count outcome variables accounting for latent predictors and their interactions. Even though neglecting measurement error in such count regression models (e.g., Poisson or negative binomial regression) can have unfavorable consequences like attenuation bias, such analyses are often carried out in the generalized linear model (GLM) framework using fallible covariates such as sum scores. An alternative is count regression models based on structural equation modeling, which allow to specify latent covariates and thereby account for measurement error. However, the issue of how and when to include interactions between latent covariates or between latent and manifest covariates is rarely discussed for count regression models. In this paper, we present a latent variable count regression model (LV-CRM) allowing for latent covariates as well as interactions among both latent and manifest covariates. We conducted three simulation studies, investigating the estimation accuracy of the LV-CRM and comparing it to GLM-based count regression models. Interestingly, we found that even in scenarios with high reliabilities, the regression coefficients from a GLM-based model can be severely biased. In contrast, even for moderate sample sizes, the LV-CRM provided virtually unbiased regression coefficients. Additionally, statistical inferences yielded mixed results for the GLM-based models (i.e., low coverage rates, but acceptable empirical detection rates), but were generally acceptable using the LV-CRM. We provide an applied example from clinical psychology illustrating how the LV-CRM framework can be used to model count regressions with latent interactions.

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Introduction

In psychology and the social sciences, researchers often model count outcomes accounting for latent predictors and their possible interactions. For example, Wilker et al. ( 2017 ) regressed symptom severity (i.e., how often did symptoms occur) of posttraumatic stress disorder on traumatic load, mental defeat, and their interaction. Both predictors were assessed using multiple items from psychometric questionnaires. Others studied the interactive effect of psychological distress and gender on problematic drinking behavior (i.e., number of alcoholic drinks; Rodriguez, Litt, & Stewart, 2020 ) or of callous traits and gender on antisocial outcomes (e.g., number of arrests; McMahon, Witkiewitz, Kotler, & The Conduct Problems Prevention Research Group, 2010 .

Such analyses often apply a generalized linear model (GLM; McCullagh & Nelder, 1998 ) using fallible predictors such as a sum score. Prominent options for count outcomes are Poisson or negative binomial regression (Hilbe, 2011 ). These are GLMs with a logarithmic link function and a Poisson or negative binomial distributed random component, which take the discrete and non-negative nature of count outcomes into account. The predictors are assumed to be observed without error and fixed by design, which is often not plausible for psychological measurements such as test scores.

While it seems to be a wide-spread approach to neglect measurement error in such analyses (Cheung, Cooper-Thomas, Lau, & Wang, 2021 ; Cortina, Markell-Goldstein, Green, & Chang, 2021 ), it is well known to have unfavorable consequences in GLMs: First, measurement error typically attenuates the regression coefficients towards zero, but in settings with multiple error-prone predictors both over- and underestimation can occur (Carroll, Ruppert, Stefanski, & Crainiceanu, 2006 ; Kiefer, & Mayer, 2021a ). Thus, attenuation bias complicates the identification of relevant product terms. Second, the reliability of the product term of two variables depends on their respective reliabilities and is typically lower than either of these (Bohrnstedt & Marwell, 1978 ; Busemeyer & Jones, 1983 ). Thus, products of fallible predictors strongly contribute to attenuation bias in parameter estimation. Consequently, there is a need for count regression models accounting for latent predictors and their (latent) interactions.

While latent interaction models with continuous outcomes (e.g., Kelava et al., 2011 ; Klein & Moosbrugger, 2000 ) with possible extensions for non-normally distributed latent variable indicators (e.g., Jin, Vegelius, & Yang-Wallentin, 2020 ) are well understood, latent interactions in count regression models are rarely discussed. A notable exception is the negative binomial multigroup structural equation model (NB-MG-SEM) by Kiefer and Mayer ( 2021a , 2021b ). The NB-MG-SEM allows interactions between latent continuous predictors and manifest categorical predictors by using a multigroup SEM approach. Recently, Rockwood ( 2021 ) proposed a generalized structural equation model (G-SEM) which can be used for the estimation of count regression models with latent predictors. While the G-SEM framework is very versatile, the formulation and implementation of Rockwood ( 2021 ) does not include product terms of the latent predictors.

In this paper, we contribute to the literature on latent interaction models for count outcomes in three ways: First, we present a general framework for a latent variable count regression model (LV-CRM) allowing for latent interactions. This framework is derived as extension of a GLM and also builds on the G-SEM framework by Rockwood ( 2021 ). Second, in three Monte Carlo simulation studies we compare the estimation accuracy of the proposed approach to GLM-based count regression models. Third, we provide an empirical example from clinical psychology to illustrate how the LV-CRM can be used to model count regressions with latent interactions in applied research.

Generalized linear models for count outcomes

In the following, we derive the LV-CRM as an extension of the GLM because many applied researchers are familiar with the GLM notation as well as GLM-based count regression models like Poisson or negative binomial regression. We start with describing the core elements of a GLM-based Poisson regression model, explain how interactions can be included within a GLM, and discuss the impact of measurement error in the predictors on the parameter estimation. In the next section, we introduce the LV-CRM as extension of the GLM allowing for latent covariates and latent interactions.

GLMs have been proposed by Nelder and Wedderburn ( 1972 ) and it can be shown that several well-known regression models, as for instance, the logistic regression model or the general linear model, are special cases of the GLM (McCullagh & Nelder, 1998 ). The key idea is that all these regression models can be decomposed into three main components: (a) a random component describing the conditional distribution of the outcome variable; (b) a weighted linear combination of the predictor variables (i.e., the linear predictor ), and; (c) a functional connection between the two, called the link function .

In principle, each component can be modified independently from the other two, which results in a very flexible way to model regressive dependencies among manifest variables.

Illustration of the interaction effects in linear and Poisson regression models without and with a dedicated interaction term. Red lines reflect linear approximations of the regression lines at \(\eta =1\) and \(\Delta \) indicates the slope of these approximations

Poisson regression model

GLMs for count outcomes are referred to as the family of Poisson regression models (e.g., Coxe, West, & Aiken, 2009 ). The standard Poisson regression model, while being parsimonious and comprehensible, is usually not suitable in applied scenarios. Thus, alternatives as the negative binomial regression are also part of the family of Poisson regressions. For a gentle introduction to Poisson regression models, see Coxe et al. ( 2009 ).

Consider a vector of N i.i.d. sampled outcome variables \(\varvec{y}= (Y_1,\dots ,Y_N)'\) , where the index \(i=1,\dots ,N\) indicates the individual observations, and for each individual the observation of m fixed predictor values \(\varvec{z}_i = (1, z_{1i}, \dots , z_{mi})\) with index \(j=1,\dots ,m\) . Then, according to McCullagh and Nelder ( 1998 ), the GLM-formulation of a standard Poisson reg-ression model involves the following three main components:

(a) the random component is Poisson distributed, \(Y_i \sim \mathcal {P}(\mu _{Y_i})\) , that is, we consider each observation \(Y_i\) of our count outcome to follow a Poisson distribution with expectation \(\text {E}(Y_i) = \mu _{Y_i}\) . The Poisson distribution comes with the property of equidispersion, meaning that the variance and the expectation of \(Y_i\) are identical. However, researchers often encounter overdispersed count outcomes, that is, the variance of \(Y_i\) exceeds its mean. In this case, an additional variance component can be introduced to the model, leading to Poisson-mixture distributions such as the negative binomial distribution (i.e., a Poisson-gamma mixture; Hilbe, 2011 ) or the Poisson-lognormal (PLN) distribution (Bulmer, 1974 ).

(b) The linear predictor \(\pi _i\) is defined as a weighted linear combination of the predictors \(\varvec{z}_i\) , where the weights \(\varvec{\beta } = (\beta _0,\beta _1,\dots ,\beta _m)'\) are called regression coefficients:

Below, we show how interactions between two or more predictors can be included in a GLM. It is important to note that the \(z_{ji}\) are treated as fixed constants. As a consequence, they are treated as perfectly reliable measures. However, this is not plausible if fallible scores of latent constructs (e.g., test scores from an intelligence test) are used as predictors, which can lead to attenuation bias in the estimated regression coefficients.

(c) For count outcomes, the expectation of the outcome variable \(\mu _{Y_i}\) and the linear predictor \(\pi _i\) are commonly connected via a logarithmic link function (short: log link), that is,

which naturally accounts for the lower bound of count outcomes at zero.

Left panel: Poisson regression ( black line ) of Y on the true scores of a predictor variable \(\eta \) ( black dots ). Right panel: Poisson regression ( black line ) of Y on fallible scores of the predictor variable (i.e., \(\eta \) plus a measurement error \(\epsilon \) ; black dots ). Dashed regression lines reflect deviations from the Poisson regression with true scores

Estimation of a Poisson regression model can be done via iteratively weighted least squares to find the maximum likelihood estimates and the corresponding standard errors. For more details, see Hilbe ( 2011 , Ch. 4)

Interactions in Poisson regression models

Whenever the effect of one predictor depends on the values of another, we can model this using product terms. In the GLM framework, product terms of the observed variables can be added as a new variable to the linear predictor, e.g., \(z_{3i} := z_{1i} \cdot z_{2i}\) . In a simple example with only two covariates and their interaction, the equation for the linear predictor is:

If, for instance, \(z_2\) is a binary trauma variable (e.g., \(z_2=1\) : trauma experienced vs. \(z_2=0\) not experienced) and \(z_1\) is age, we can compute the conditional regression of the count outcome on age given values of the trauma variable:

The first equation represents the relationship between the outcome Y and the predictor \(z_1\) (i.e., age) if a trauma was not experienced ( \(z_2=0\) ), and the second equation if a trauma was experienced, respectively.

It is important to note that Poisson regression models – just like other non-linear models – can contain interaction effects even if the coefficient of the product term is zero, that is, \(\beta _3=0\) . This phenomenon is called natural (or sometimes: model-inherent) interaction (Karaca-Mandic, Norton, & Dowd, 2012 ; McCabe, Halvorson, King, Cao, & Kim, 2022 ) and it is illustrated in Fig.  1 . In the upper right panel, the coefficient of \(z_1\) is identical for both \(z_2=0\) and \(z_2=1\) . However, for someone with a value of \(z_1=1\) the slope (as indicated by the red lines) varies considerably depending on the moderator. This is in contrast to the linear model (upper left panel) where the absence of a product term implies parallel lines. Thus, a product term can add to the complexity of the interaction pattern in a Poisson regression (lower right panel), but its absence is not equivalent to the absence of interaction.

The (linear) slopes of \(z_1\) , which are illustrated with the red lines in Fig.  1 , are called marginal effects and they are defined as the first derivative of the regression function. The effect of a third variable (i.e., \(z_2\) ) on the marginal effects of \(z_1\) , can then be defined as second-order mixed partial derivative (Kim & McCabe, 2022 ):

This definition of an interactive effect has two important properties: First, \(\zeta _{ijk}\) can be non-zero even if product terms are excluded (or \(\beta _3=0\) ). Second, \(\zeta _{jk}\) varies among individuals and is not a constant. That is, interaction effects vary as function of the predictors both involved and not involved in a product term.

Kim and McCabe ( 2022 ) propose three approaches to summarize and report the interaction effects \(\zeta _{jk}\) : First, it is possible to plug-in the observed predictor values and then compute summary statistics of the individual interaction effects, for example, an average interaction effect. Second, \(\zeta _{jk}\) is computed for representative points in the sample, for example, an “average” person (i.e., at the means of all covariates) and one standard deviation above and below this average. We will illustrate this approach in our empirical example below. Third, \(\zeta _{jk}\) is computed at substantively relevant points, for example, at a specific cutoff. It is possible to obtain standard errors for the interaction effects \(\zeta _{jk}\) by using the Delta method (Raykov & Marcoulides, 2004 ). Note, however, that if the interaction effects are computed at values estimated from the sample (e.g., sample mean), their sampling variance also has to be taken into account for reliable inferences (Liu, West, Levy, & Aiken, 2017 ).

Measurement error in the covariates

As stated before, a GLM assumes fixed predictors, which (a) are perfectly reliable and (b) do not vary from one sample to another. In psychological research, this is often not a realistic assumption, especially if predictors are randomly sampled, fallible measures of unobservable constructs (e.g., motivation, intelligence). If random measurement error in predictors is ignored, the regression coefficients get attenuated towards zero. This phenomenon known as attenuation bias (Carroll et al., 2006 ) is illustrated in Fig.  2 . While the left panel shows a Poisson regression based on the true values of a covariate \(\eta \) , the right panel shows the attenuation of the regression line as an effect of measurement error \(\epsilon \) added to the covariate. While attenuation bias is usually associated with attenuation towards zero, biases in all directions can be observed with multiple fallible covariates (Kiefer & Mayer, 2021a ; Carroll et al., 2006 ).

In the literature, several approaches have been proposed dealing with measurement error in covariates. Some approaches assume that the distribution of the latent variables is known (e.g., normally distributed with known mean and variance) and use this information to adjust the estimates of the regression coefficient (Guo & Li, 2002 ; Kukush, Schneeweis, & Wolf, 2004 ). Other approaches include a measurement model to estimate the distribution of the latent variables (Carroll et al., 2006 ; Skrondal & Kuha, 2012 ). These later approaches are called regression calibration . The measurement model is either included directly into a joint estimation with the regression coefficients or estimated first in a two-step procedure, where then distributional parameters or factor scores are used in the regression estimation (for more information on the two-step procedure, see Rosseel & Loh, 2022 ). However, these approaches are rarely extended to scenarios with product terms in non-linear models, with some exceptions treating this issue for logistic regression models (e.g., Carroll et al., 2006 , p.165). We are not aware of any contribution specifically addressing such adjustments focusing on both Poisson regressions and product terms.

Attenuation bias affects fallible predictors in general, but is likely to be exacerbated when product terms from fallible predictors are involved. This is because the reliability of the product term is usually lower than that of either of the interacting variables (Busemeyer & Jones, 1983 ). Bohrnstedt and Marwell ( 1978 ) show that for two predictors with reliability of .8, the reliability of the product term can drop below .6 (depending on their scaling and correlation). Nevertheless, it still seems to be a widespread approach to neglect measurement error in regression analyses containing interactions (Cheung et al., 2021 ; Cortina et al., 2021 ).

Latent variable count regression model

In this section, we introduce a latent variable count regression model (LV-CRM) framework for count regression models involving latent predictors, their interactions, manifest predictors, and possible latent-manifest interactions. For didactic reasons, we show how the LV-CRM can be derived as an extension of the GLM and therefore also stick to the common notation of the three main parts of the GLM.

We consider two steps to extend a GLM to a LV-CRM: (a) adding a measurement model as fourth model component and second, allowing latent variables, their interactions, and interactions between latent and manifest predictors as part of the linear predictor. Table 1 provides an overview and comparison of the GLM and the LV-CRM.

Note that the LV-CRM overlaps with the G-SEM framework (Rockwood, 2021 ), which, however, does not allow for interaction terms involving latent variables. The LV-CRM can be estimated with general purpose statistical software, for example, Mplus (Muthén & Muthén, 1998-2017 ), the GLLAMM approach in Stata (Skrondal & Rabe-Hesketh, 2004 ), or Stan (Stan Development Team, 2024 ). However, to our knowledge, the LV-CRM has not been previously described in the literature nor is there a technical documentation of how the LV-CRM is implemented, for example, in Mplus. Below, we will provide Mplus syntax for the empirical example as well as an open-source implementation in R.

Measurement model

In psychology and the social sciences, explicitly modeling measurement error and latent variables using a common factor technique (Bollen, 1989 ) is a popular approach. The key idea is that we have q measurements \(\varvec{w}_i=(W_{1i},\dots ,W_{q})'\) (e.g., items) intended to measure (multiple) latent variables (e.g., intelligence) and common factors \(\varvec{\eta }_i=(\eta _{1i},\ldots ,\eta _{pi})'\) with \(p \le q\) are introduced to model the correlations among the measurements:

where \(\varvec{\nu }\) is a \(q \times 1\) vector of intercepts; \(\varvec{\Lambda }\) is a \(q \times p\) matrix of factor loadings; and \(\varvec{\epsilon }_i\) is a \(q \times 1\) vector of measurement error variables. The observed indicators \(\varvec{w}_i\) are represented by a linear function of the latent variable plus measurement error. We assume that the measurement error variables \(\varvec{\epsilon }_i=(\epsilon _{1i},\ldots ,\epsilon _{qi})\) as well as the latent variables \(\varvec{\eta }_i\) are multivariate normally distributed with \(\varvec{\epsilon }_i \sim \mathcal {N}(\textbf{0}, \varvec{\Theta })\) and \(\varvec{\eta }_i \sim \mathcal {N}(\varvec{\mu }_{\eta }, \varvec{\Sigma }_{\eta })\) . Latent variables and measurement errors are independent from each other.

Identification of the model can be achieved through standard identification rules for structural equation models. That is, the scale of the latent variables has to be specified. Two popular methods for scaling the latent variables are (a) fixing one loading to one and one intercept to zero (typically for the first indicator) or (b) fixing the mean and variance of the latent variable to 0 and 1, respectively (cf. Kline & Little, 2023 ). Different scaling methods lead to equivalent models (i.e., point estimates are algebraic transformations of each other), but statistical inferences based on the Wald test can vary among scaling methods (Klopp, & Klößner, 2021 ).

Latent predictors and interactions

Now, we add the latent variables defined in the measurement model, and their possible interactions to the linear predictor component of the LV-CRM:

As denoted in the braces, the first part is equivalent to the linear predictor of the GLM. By adding the latent variables with regression coefficients \(\gamma _k\) to the predictor (i.e., the second part), we obtain a special case of the G-SEM (Rockwood, 2021 ). The third part adds latent interactions with regression coefficients \(\gamma _{kl}\) to the linear predictor Footnote 1 . The fourth part allows for interactions between latent and observed predictors with regression coefficients \(\omega _{jk}\) . Of course, some of the regression coefficients can be zero leading to more parsimonious models. The linear predictor in matrix notation is:

where \(\varvec{\gamma }\) is a \(p \times 1\) vector of regression coefficients; \(\varvec{\Gamma }\) is a \(p \times p\) upper triagonal matrix of regression coefficients; \(\varvec{\Omega }\) is a \(p \times m\) matrix of regression coefficients. Conceptually, the LV-CRM belongs to the regression calibration approaches mentioned earlier (Carroll et al., 2006 ; Skrondal & Kuha, 2012 ).

In the LV-CRM, the product terms are identified if the latent variables are identified. There are no additional assumptions or specifications necessary. This is achieved through the specification on an individual level: If the individual values of the latent variables are identified, then the individual product terms are also identified. Note that different estimation methods will approach this specification differently. For example, in a Bayesian framework, individual values of the latent variables will be sampled and directly plugged in the formulas. In contrast, the marginal maximum likelihood approach will integrate the latent variables out of the individual likelihood function. The next section provides an overview of the marginal maximum likelihood estimation.

Parameter estimation and standard errors

In this section, we provide a brief overview of maximum likelihood estimation of the proposed model. The overview is meant to give some intuition on the estimation technique and why no additional measurement models (e.g., as in a product-indicator approach; Kenny & Judd, 1984 ) or distributional assumptions (e.g., as in the LMS approach; Klein & Moosbrugger, 2000 ) are required for identification of the product terms. For a comprehensive illustration of the marginal likelihood technique and possible implementations, see Rockwood ( 2021 ) or Skrondal and Rabe-Hesketh ( 2004 , Ch. 6). Alternative estimation methods for the LV-CRM exist, for instance, using an EM algorithm as in Mplus (Muthén & Muthén, 1998-2017 ) or Bayesian methods (Asparouhov & Muthén, 2021 ; Stan Development Team, 2024 ).

Path model depicting the four components of a LV-CRM. Example shows the Poisson regression of outcome variable Y on the manifest predictors \(z_1\) to \(z_3\) , the latent predictors \(\eta _1\) and \(\eta _2\) , and their interaction term \(\eta _1 \cdot \eta _2\)

For didactic reasons, we will restrict ourselves to describing the maximum likelihood estimation for the model depicted in Fig.  3 . This is actually the model used for simulation study 2 and very similar to the empirical example. The case-wise log-likelihood function for this model can be written as:

where \(y_i\) , \(\varvec{z}_i = (z_{1i}, z_{2i}, z_{3i})\) , and \(\varvec{w}_i = (W_{1i}, W_{2i}, W_{3i},\) \( W_{4i}, W_{5i}, W_{6i},)\) are the individual values of the observed variables. Since the values of the latent variables \(\eta _1\) and \(\eta _2\) are not observed, they are integrated out.

There is no closed-form solution for the log-likelihood function and hence it has to be approximated through numerical techniques:

where M is the number of integration points, \(\omega _j\) is an integ-ration weight, and \(\eta _{1j}^*\) and \(\eta _{2j}^*\) are the integration points, respectively. An advantage of this procedure is that it provides a fixed set of values for the latent variables for each person in each iteration. Similar to the procedure in a GLM, we can use these latent variable values to compute product terms within the linear predictor. This is why the latent interaction term is presented as part of the linear predictor in Fig.  3 , but not as part of the measurement model. The product term is only part of the linear predictor and the linear predictor is only part of the density function of the outcome variable \(f(y_i|\varvec{z}_i, \eta _{1j}, \eta _{2j})\) . Now, for each part sum of the approximated case-wise likelihood, we can simply compute the linear predictor \(\pi _i(j)\) as a function of the integration points:

These models can become computationally demanding if the number of latent variables and thus the integration points rises, and we will discuss some approaches to reduce the computational burden. Standard errors can be derived using standard maximum likelihood theory, but this step is also computationally demanding as the second order derivatives of the log-likelihood have to be numerically approximated, too.

Simulation studies

We conducted three Monte Carlo simulation studies to examine the performance of the LV-CRM framework under various empirical conditions and compared it to GLM-based Poisson or negative binomial regressions. From a substantive point of view, it is most interesting under which conditions the potential gains from the LV-CRM (e.g., reducing attenuation bias, increasing power) outweigh the costs (e.g., additional distributional assumptions, potential bias and numerical instability for insufficient sample sizes). Thus, we aligned our simulation studies with the aim to provide guidelines for substantive researchers which model to prefer under which conditions. The first simulation study focused on the extent of attenuation bias in a Poisson regression model with two latent variables and their interaction. It examines the question of how much bias one can expect given certain reliabilities of the sum scores, while still being computationally feasible to replicate by the interested reader. The second simulation study focused on two questions, namely, (a) if and how much attenuation bias can spill over to regression coefficients of perfectly reliable measures, and (b) how the statistical inferences from the LV-CRM perform and how they compare to GLM-based inferences. As this simulation study includes standard error estimation for the LV-CRM, it is computationally more burdensome. The third simulation study focused on attenuation bias in more complex scenarios, where we considered three latent variables and their two-fold interactions. We examined attenuation bias for different combinations of product term coefficients as well as correlational patterns among the latent variables. Due to the required three-dimensional numerical integration, this simulation was computationally demanding, too. The corresponding R code as well as the final results for all three simulation studies are available from OSF via https://osf.io/q7knc .

Simulation study 1

The main focus of our first simulation study is to investigate the effect of different magnitudes of reliability of the fallible predictors on attenuation bias and how well the LV-CRM can de-attenuate the estimated regression coefficients. We pursue this focus with a small-scale simulation that can be reproduced by the interested reader within reasonable time. In the simulation studies 2 and 3, we will investigate additional aspects of statistical inferences and higher-dimensional numerical integration which are computationally more demanding. Final results for all three simulation studies are included in the OSF repository.

In this simulation study, we used a model with two latent variables, \(\eta _1\) and \(\eta _2\) , and their interaction as predictors of the outcome variable Y in a Poisson regression model. The linear predictor was:

where we are particularly interested in the estimation of the product term coefficient \(\gamma _{12}\) .

The latent variables were simulated as standard bivariate normally distributed with a correlation of \(r=.3\) and measured with three indicators each. We also computed sum scores as fallible substitutes of the latent variables over the three indicators, respectively. The sum scores were z -standardized for comparability with the latent variables. The reliabilities of the sum scores were manipulated independently by altering the measurement error variances of the indicators. We investigated the six reliability combinations for the sum scores of both latent variables, considering the reliabilities of 0.7, 0.8, and 0.9 respectively. Additional design factors where the sample size ( \(N=100,~200,~500,~1000\) ) and the size and direction of the interaction parameter ( \(\gamma _{12}=-0.3,~0,~0.3\) )

We estimated the model with both a LV-CRM (where the means of the latent variables were fixed to 0 and the variances to 1) and a GLM (with z -standardized sum scores) and investigated and compared the bias and efficiency of the estimated product term parameter \(\hat{\gamma }_{12}\) (or \(\hat{\beta }_4\) in the GLM, respectively).

Simulation study 1: (Relative) bias of estimated product term coefficients in the LV-CRM ( purple ) and the GLM ( green ). The upper panel shows bias for conditions with \(\gamma _{12}=0\) , the lower panel shows relative bias for conditions with \(\gamma _{12}\ne 0\) . Columns reflect the six combinations of reliabilities of the sum scores, rows reflect the size and direction of the product term coefficient, x -axis reflect sample size N

Convergence

We ran the simulation with \(R=1000\) replications including non-converged solutions first in order to examine the convergence behavior of both approaches. Both approaches yielded convergence rates of virtually 100% in this simulation. Only in six out of 72 conditions was there one out of 1000 replications where the LV-CRM did not converge. These six conditions had a positive product term coefficient in common, but were unsystematic regarding the other design conditions (i.e., large and small sample sizes, high and low reliabilities). Thus, convergence seemed to be no issue for the specified model in sample sizes from \(N=100\) upwards.

The following analyses are based on a second run of the simulation with \(R=1000\) replications excluding non-converged solutions, that is, if one of both models did not converge the replication was repeated until both models converged.

We investigated the bias of the estimated product term coefficient \(\hat{\gamma }_{12}\) in the LV-CRM and \(\hat{\beta }_4\) the GLM, respectively. The results are presented (a) as bias for cases where the true parameter \(\gamma _{12}=0\) and (b) as relative bias for cases where the true parameter was non-zero, i.e., \(\gamma _{12}\ne 0\) . The results are illustrated in Fig.  4 Both models yielded very small biases in conditions where the true parameter \(\gamma _{12}\) was zero. For the GLM, the bias ranged between \(-0.006\) and 0.002. The largest negative bias of about \(-0.015\) was found for the LV-CRM in a condition with low reliabilities (both 0.7) and a small sample size of \(N=100\) . The upper bound of the bias for the LV-CRM was 0.000. Overall, the LV-CRM tended to underestimate the true parameter more than the GLM approach. This is not surprising, as measurement error is expected to attenuate the estimated regression coefficients of a GLM towards zero and in conditions with a true coefficient of zero, the attenuation is ’favorable’ for the estimation of this zero.

The unfavorable effects of attenuation become clear, when looking at the relative bias of the estimated product term coefficient in scenarios where the true parameter is not zero. The relative bias of the estimated product term parameter in the GLM approach ranged between \(-5.6 \%\) and \(-33.2 \%\) . That is, even in scenarios with highly reliable score variables (both .9), we found at least 5% underestimation. If at least one predictor had a reliability of .8 or lower, the underestimation was about 10% or more. On the other hand, the LV-CRM performed better and relative bias ranged between \(-4.9\%\) and \(8.2\%\) . Interestingly, overestimation of the product term coefficient occurred in scenarios with positive product term coefficient, highly reliable score variables, and small sample sizes. Overall, the LV-CRM provided more accurate estimates (i.e., less bias) for the product term coefficient than the GLM. For sample sizes of \(N=200\) or larger, the LV-CRM yielded relative bias below \(\pm 5 \%\) under all conditions.

Relative efficiency

The results for the relative efficiency of the LV-CRM compared to the GLM (i.e., ratio of the respective RMSE) are presented in Fig.  5 . In conditions with a true product term coefficient of \(\gamma _{12} = 0\) , the relative efficiency of the LV-CRM approach compared to the GLM approach ranged between 1.048 and 1.270. That is, the RMSE of the LV-CRM approach is about 4.8–27% higher than that of the GLM. Again, that is not surprising given the ’favorable’ effect of the attenuation bias in these conditions.

Simulation study 1: Relative efficiency of estimated product term coefficient in the LV-CRM compared to GLM (i.e., RMSE of LV-CRM divided by the RMSE of the GLM). Columns reflect the six combinations of reliabilities of the sum scores, rows reflect the size and direction of the product term coefficient, x -axis reflect sample size N

Simulation study 2: Spill-over effect \(S(\hat{\beta }_1, \hat{\beta }_2, \hat{\beta }_3)\) of estimated regression coefficients in the LV-CRM and in the GLM. Columns reflect the six combinations of reliabilities of the sum scores, rows reflect the size and direction of the product term coefficient, x -axis reflect sample size N

In conditions with a true interaction parameter of \(\gamma _{12} \ne 0\) , the relative efficiency ranges from 0.304 to 1.622. As can be seen in Fig.  5 , the LV-CRM is typically more efficient in scenarios with a negative interaction parameter, especially with larger sample sizes. With a positive product term coefficient, the LV-CRM is typically more efficient if at least one predictor has a reliability of 0.7 or both reliabilities were .8 (with few exceptions in sample sizes of \(N=100\) ). However, with increasing reliability of the fallible score variable the LV-CRM was less efficient than the GLM.

Simulation study 2

In the second simulation study, we extended the design of our first study in two regards: First, we investigated whether attenuation bias can have a spill-over effect on other regression coefficients, for instance, those of perfectly reliable predictors. Second, we examined whether the bias reduction in the LV-CRM approach also comes with improved statistical inferences, for example, an increase of power to detect non-zero product term coefficients. Thus, we computed 95% confidence intervals (CIs) and the empirical detection rate for each condition.

The simulation design followed our first simulation study with a few additions: First, three additional manifest and perfectly reliable predictors were added to the regression model. These predictors were generated as independent from each other and from the latent variables. This was done to investigate potential spill-over effects of the fallible score variables.

The linear predictor was

Second, standard errors, confidence intervals, and the empirical detection rate for the interaction parameter \(\gamma _{12}\) were computed. Third, the random component was chosen as negative binomial instead of a Poisson distribution. This is a more realistic scenario, as it incorporates additional variance in the outcome not explained for by the predictors (which is usually the case in applied settings), but the estimation is slightly more demanding. It is also closely related to our empirical example below, where we use a negative binomial regression model.

Spill-over effect

We used the Euclidean norm of the biases of the three regression coefficients of the observed covariates (i.e., \(B(\hat{\beta }_1)\) , \(B(\hat{\beta }_2)\) , \(B(\hat{\beta }_3)\) ) to get an overall evaluation of possible spill-over effects, that is,

The results are summarized in Fig.  6 . We also computed bias and relative efficiency of the remaining coefficients (i.e., of the latent variables and the interaction term), but do not illustrate the results here as they closely resemble our findings from the first simulation study. The complete results can be found in the OSF repository.

Overall, the results indicate no spill-over effect of the fallible score variables on the estimated regression coefficients of the perfectly reliable covariates. The spill-over effect \(S(\hat{\beta }_1, \hat{\beta }_2, \hat{\beta }_3)\) ranged from 0.0004 to 0.0149 for the GLM and from 0.0007 to 0.0149 for the LV-CRM. The highest values were obtained in scenarios with mixed reliabilities (i.e., one high, one low) on both fallible scores and rather low sample sizes. However, the corresponding regression coefficients appeared virtually unbiased under all conditions.

Coverage and empirical detection rate

We examined the coverage rate (i.e., the proportion of CIs including the true parameter value), and the empirical detection rate (i.e., the proportion of CIs not including zero) for the 95 % confidence intervals (CI) of the interaction parameter \(\gamma _{12}\) estimated with both approaches (i.e., \(\hat{\gamma }_{12}\) in the LV-CRM and \(\hat{\beta }_6\) in the GLM). The results are summarized in Fig.  7 .

In scenarios where the true interaction parameter was \(\gamma _{12}=0\) , both the coverage rate and the empirical detection rate (i.e., the type I error rate in these scenarios) were acceptable for both approaches. For the GLM, the actual coverage rate of the CIs ranged between 0.918 and 0.948 and the empirical detection rate between 0.052 and 0.085, respectively. For the LV-CRM, the actual coverage rate of the CIs ranged between 0.923 and 0.957 and the empirical detection rate between 0.043 and 0.077, respectively.

Simulation study 2: Coverage rates ( upper panel ) and empirical detection rates ( lower panel ) of estimated interaction coefficient \(\hat{\gamma }_{12}\) in the LV-CRM and in the GLM. Columns reflect the six combinations of reliabilities of the sum scores, rows reflect the size and direction of the product term coefficient, x -axis reflect sample size N

In contrast, in scenarios where the true product term coefficient was not zero (i.e., \(\gamma _{12}\ne 0\) ), coverage and empirical detection rate yielded diverging results. For the GLM, the actual coverage rate of the CIs ranged between 0.199 and 0.951 and the empirical detection rate (i.e., the power in these scenarios) between 0.127 and 1.000, respectively. Notably, the coverage rate was more accurate for small interaction sizes (i.e., \(\gamma _{12} = |0.1|\) ), but barely acceptable for larger interaction sizes (i.e., \(\gamma _{12} = |0.3|\) ). For the LV-CRM, the actual coverage rate of the CIs ranged between 0.904 and 0.966 and the empirical detection rate between 0.121 and 1.000, respectively. Overall, the power was similar for both approaches. On average, the power was 0.7% higher for the LV-CRM, where the differences in power between the two approaches ranged from -3.9% (i.e., higher power in the GLM) to 8.2% (i.e., higher power in the LV-CRM).

Simulation study 3: (Relative) bias of estimated interaction coefficients in the LV-CRM ( yellow , blue , magenta ) and the GLM ( green , purple , orange ). Numbers in the legend refer to the index of the estimated regression coefficient, for example, GLM_12 reflects the estimate of \(\gamma _{12}\) in a GLM. The upper panel shows bias for conditions where all interaction coefficients were zero, the lower panel shows relative bias for the remaining conditions. In conditions with mixed coefficients, (relative) bias for \(\gamma _{12}=0\) is not shown. Columns reflect the correlational patterns among the LVs, rows reflect the size and direction of the product term coefficients, x -axis reflects different combinations of reliabilities of the sum scores

When it comes to statistical inferences, these findings indicate that attenuation bias in the GLM is somewhat compensated for by an overconfident (i.e., too small) standard error. As a result, hypothesis testing seemed to work reasonably well, but the confidence intervals were too narrow and did often (i.e., up to 80.1%) not include the true parameter value. In contrast, the LV-CRM yielded unbiased point estimates and accurately accounted for multiple sources of uncertainty (e.g., measurement error, regression residual) resulting in wider CIs (compared to the GLM). Thus, null hypothesis testing would be expected to work with both approaches, but substantive interpretation of the CI is more reliable with the LV-CRM.

Simulation study 3

In the third simulation study, we focused on scenarios with three latent variables and their two-fold interactions. Our goal was to investigate the extent of attenuation bias in this complex settings given different combinations of reliability, correlations, and interactional patterns among the latent variables. Similar to the first simulation study, we restricted ourselves to consider bias and relative efficiency of the estimated interaction parameters alone and did not investigate statistical inferences in order to keep the simulation computationally feasible.

The design of the simulation study is similar to the first simulation study, but with three latent variables and their three two-fold interactions. The linear predictor was:

We manipulated the following three factors: First, reliability of the sum scores of each latent variable could take the values 0.7 or 0.9, resulting in eight reliability combinations. Second, we investigated four different correlational patterns among the latent variables. These four patterns where (a) small negative correlations ( \(r=-.3\) ) among all LVs, (b) small positive correlations ( \(r=.3\) ) among all LVs, (c) no correlations ( \(r=0\) ) among all LVs, and (d) mixed correlations (negative, positive, null) among the LVs. Third, we investigated four different interactional patterns. These were (similar to the correlations) (a) small negative interaction coefficients ( \(\gamma =-.3\) ) for all LVs, (b) small positive interaction coefficients ( \(\gamma =.3\) ) for all LVs, (c) no product-term induced interaction ( \(\gamma =0\) ) for all LVs, and (d) mixed interaction coefficients (negative, positive, null) for the LVs. We did not investigate different sample sizes in this simulation, but choose a single sample size of \(N=500\) throughout all conditions.

Simulation study 3: Relative efficiency of estimated interaction coefficients in the LV-CRM compared to GLM (i.e., RMSE of LV-CRM divided by the RMSE of the GLM). Numbers in the legend refer to the index of the estimated regression coefficient, for example, GLM_12 reflects the estimate of \(\gamma _{12}\) in a GLM. Columns reflect the correlational patterns among the LVs, rows reflect the size and direction of the product term coefficients, x -axis reflects different combinations of reliabilities of the sum scores

The results on attenuation bias are presented (a) as bias for scenarios where all interaction coefficients were zero and (b) as relative bias for non-zero interaction coefficients. An overview of the results is given in Fig.  8 .

In conditions where all three interaction coefficients were zero, the bias ranged between -0.002 and 0.002 for the GLM and between -0.004 and 0.003 for the LV-CRM. As in the first simulation study, this result is not surprising given the ’favorable’ effect of attenuation bias in these conditions.

In conditions where interaction coefficients could differ from zero, we found a common pattern of relative bias in most conditions, but with a notable exception (i.e., all correlations and interactions positive), which we will discuss separately. The common pattern shows a substantial relative bias for all three estimated interaction coefficients in the GLM (between -0.451 and 0.016), but comparably low relative bias for the estimated interaction coefficients for the LV-CRM (between -0.112 and 0.020).

However, in conditions with positive correlations among the LVs and three positive product term coefficients, a rather unsystematic pattern of relative bias occurred – as displayed in Fig.  8 . Here, relative biases in both directions were observed, that is, between -0.225 and 0.261 for the GLM and between -0.169 and 0.190 for the LV-CRM. In order to examine if this pattern was caused by the medium sample size and possible estimation issues, we re-run these conditions with a larger sample size of \(N=2000\) . However, we found the same pattern again. We are not sure why the relative bias behaves so differently under these conditions, but suspect an unfavorable combination of multicollinearity of the latent variables and their interaction terms, measurement error, and rather steep conditional effects (i.e., simple slopes) leading to highly dispersed outcome values. However, it shows that attenuation bias can have rather unexpected effects in complex scenarios involving multiple latent variables.

The results for the relative efficiency of the estimated interaction coefficients in the LV-CRM compared to the GLM were similar to our findings from simulation studies 1 and 2 and are therefore not discussed in detail again. An overview is given in Fig.  9 and the complete results are available from the OSF repository.

Empirical example

We provide an empirical example from clinical psychology to illustrate how the LV-CRM framework can be applied to model count regressions with latent interactions in applied settings. Wilker et al. ( 2017 ) examined the effects of trauma load, mental defeat, and their interaction on symptom severity (i.e., incidence of symptoms) of posttraumatic stress disorder (PTSD) and dissociation in Ugandan war survivors.

Theoretical background

The experience of traumatic events such as war, torture, sexual violence, accidents, or natural disasters can lead to the development of PTSD. The disorder is characterized by intrusive re-experiencing of the traumatic events, avoidance of trauma reminders, persistent alterations of mood and cognition, and a state of elevated arousal (American Psychiatric Association, 2022 ). In addition to these symptoms, survivors of multiple and interpersonal trauma are at elevated risk to show dissociative symptoms, which include feelings of derealization (e.g., feeling as if the own experience is not real), depersonalization (e.g., feeling as if being outside the own body), dizziness, and an incapability to move (Schauer & Elbert, 2010 ; Vermetten & Spiegel, 2014 ).

Importantly, after a single or few traumatic events, the majority of individuals do not develop trauma-associated psychopathology (Kessler et al., 2005 ). Whether an individual will develop mental health symptoms after a traumatic event largely depends on individual risk and resilience factors as well as on trauma-related predictors (Kessler et al., 2021 ). However, research from post-conflict settings indicates that with an increasing number of different types of traumatic events (termed traumatic load) almost every individual will develop mental health symptoms, and individual risk and resilience factors only play a subordinate role (Neuner et al., 2004 ; Wilker et al., 2015 ).

Peritraumatic cognitive processes, referring to thoughts which occur at the time of the trauma, have been identified to influence both the memory and the appraisal of the traumatic event. Therefore, they represent risk factors for trauma-associated psychopathology and important targets for trauma-focused interventions which aim at the modification of trauma memories and associated negative cognitions. One important peritraumatic cognitive process is termed mental defeat (Kleim, Ehlers, & Glucksman, 2012 ) and refers to a loss of mental resistance and human dignity during the trauma (Dunmore, Clark, & Ehlers, 1999 , 2001 ). The experience of mental defeat during a trauma is associated with the development of permanent negative cognitions about the self (e.g. “I am weak” or “I am destroyed”) and the world (e.g., “I can trust nobody”), which are known to be important symptoms of PTSD. At the same time, they lead to increased avoidance of trauma-associated memories and thereby lead to the maintenance and chronification of psychopathology (Dunmore et al., 2001 ; Ehlers et al., 1998 ).

While there is a lot of evidence indicating that the peritraumatic cognitive process of mental defeat is a central risk factor for PTSD in individuals from relatively peaceful, industrialized countries, research from post-conflict settings on mental defeat was completely lacking. Since the burden of PTSD is much higher in post-conflict settings compared to industrialized countries (Charlson et al., 2019 ), research from this context is urgently needed to better understand factors central to trauma-associated psychopathology and its treatment in this context. Therefore, Wilker et al. ( 2017 ) conducted a study to investigate whether mental defeat would be an important predictor of PTSD and dissociative symptoms in a post-conflict population from northern Uganda. In more detail, they investigated the interplay of trauma load and mental defeat on PTSD risk, PTSD symptoms, and dissociative symptoms. Because previous research showed that individual predictors become less important at higher levels of trauma load, potential trauma load \(\times \) mental defeat interaction effects were of particular interest to the study.

The description of the methods is taken from Wilker et al. ( 2017 , pp. 3–5). For the complete methods, the reader is referred to the original article.

Data collection took place in villages of Nwoya district in northern Uganda. This area was severely affected by the war between the Lord’s Resistance Army (LRA) rebel group and the Ugandan governmental forces, which lasted almost two decades. The atrocities committed during this war included forced recruitment and abductions of children and young adults, killings, mutilations, and sexual offenses. Data collection took place in 2013, 8 years after the cease-fire agreement between the LRA and the governmental troops in 2005. The final sample of \(N=227\) was 54% female, with a mean age of 33.29 (SD = 10.56, range = 18–62).

Trauma exposure was assessed by means of a 62-item event list. This event list comprised general traumatic experiences (e.g., natural disasters, accidents), war-related traumatic events (e.g., being close to combat), as well as events specific for the LRA conflict (e.g., being forced to kill somebody by the LRA). We calculated the number of different traumatic event types experienced to assess the amount of trauma exposure (traumatic load). As previously shown in the same sample, the retest reliability of this variable was \(r = .82\) (Wilker et al., 2015 ) and, thus, was treated as a latent predictor using a single indicator approach in our analysis.

The extent of mental defeat was assessed for the worst traumatic event using the Mental Defeat Questionnaire (MDQ) in the form of an interview (Dunmore et al., 1999 , 2001 ). The MDQ comprises 11 unipolar items (e.g., “I lost any will-power”, “I felt destroyed as a person”) and requires responses on a five-point Likert-type scale ranging from not at all to very strong. The MDQ showed a good internal consistency in the present sample (Cronbach’s \(\alpha = .89\) ) and was modeled as a latent predictor using a multiple indicator approach in our analysis.

The main outcome of our analysis were dissociative symptoms assessed by means of the Shutdown Dissociation Scale (Shut-D; Schalinski, Schauer, & Elbert, 2015 ). The Shut-D includes 13 unipolar items (e.g., “Have you fainted?” “Have you felt like you were outside of your body?” “Have you felt suddenly weak and warm?” “Have you felt nauseous? Have you felt as though you were about to throw up? Have you felt yourself break out in a cold sweat?”) investigating current bodily dissociative symptoms for the past 6 months. Participants were requested to answer on a four-point scale ranging from 0 ( never ) to 3 ( several times a week ). Thus, the scale score acts as a proxy of the incidence of dissociative symptoms and behaves similarly as a count variable, that is, the lower bound represents zero symptom occurrences, the variable only takes non-negative integer values, and a certain amount of heteroscedasticity is present. Thus, Wilker et al. ( 2017 ) handled the outcome as a count variable. The Shut-D showed a high internal reliability in the present study (Cronbach’s \(\alpha = .91\) ).

Statistical analysis

Wilker et al. ( 2017 ) compared models of varying complexity (i.e., with and without including the covariates age, sex, and age at worst event and with and without considering potential trauma load - mental defeat product terms). In this study, in order to investigate the differences between the GLM and the LV-CRM, we calculated the full model. Accordingly, our model included the main effects of sex, age, and age at worst event. Further, trauma load, mental defeat as well their interaction were included as predictors in the regression models.

Negative binomial regression

As in the original study by Wilker et al. ( 2017 ), we estimated a negative binomial regression. That is, the outcome variable \(Y_i\) (i.e., the Shut-D score) is linked to the linear predictor with a log link and is assumed to follow a negative binomial distribution.

The linear predictor in this model was

In addition, we used the LV-CRM framework to carry out the same analysis, but including a measurement model for the latent trauma load ( \(\eta _{\text {TL};i}\) ) and mental defeat ( \(\eta _{\text {MD};i}\) ) variables in order to account for measurement error:

Both scales were fixed to a mean of zero and a variance of one and, consequently, all intercepts and loadings as well as the latent covariance were estimated freely.

Note that we modeled trauma load \(\eta _{\text {TL};i}\) using a fixed-reliability single indicator approach as proposed by Savalei ( 2019 ) for two reasons: First, trauma load is not a traditional psychometric variable, but the items reflect different traumatic event types. The items are not meant to measure a common factor and are likely to be uncorrelated to some extent (i.e., experiencing a natural disaster is not necessarily correlated to having an accident). Thus, a multiple indicator approach would not have been appropriate. Second, the retest reliability of 0.82 (Wilker et al., 2015 ) indicates that trauma load cannot be assessed exactly, meaning there is some kind of measurement error involved. According to our simulation studies, we would expect a substantial attenuation bias on the product term coefficient given this level of reliability and, thus, explicitly controlling for this measurement error seems warranted. In order to fix the reliability of trauma load to 0.82, we constrained its measurement error variance to:

where \(\text {Rel}_{\text {TLS}} = 0.82\) . Then, the linear predictor for the LV-CRM was

where the standardized test scores for mental defeat and trauma load are replaced with the corresponding latent variables.

Conditional regressions for the relation between latent mental defeat (MDQ) and dissociative symptoms (SDQ) given several values of trauma load (at 2 SD below mean in dark green ; at 1 SD below mean in light green ; at mean in yellow ; at 1 SD above mean in orange ; at 2 SD above mean in red ). Black dots indicate value combinations where the interaction effect \(\zeta \) is significant

In a first step, we inspected and compared the estimated regression coefficients from both models. Table 2 shows the regression coefficients, their standard errors, and p  values of the estimated GLM and the LV-CRM, respectively. As can be seen, the estimated coefficients for trauma load, mental defeat, and their interaction are larger if measurement errors are considered, as in the LV-CRM. These results are in line with our simulation results on attenuation bias and illustrate that the GLM is likely to underestimate the true parameter effects even if the reliability of the latent variables is relatively high.

Notably, the coefficient of the product term of trauma load and mental defeat was not significant in the GLM. Therefore, Wilker et al. ( 2017 ) identified a main effect model as the most parsimonious model with the best data fit and reported their results from this model. By contrast, the LV-CRM was able to identify a significant coefficient for the product of trauma load \(\times \) mental defeat. Note that interaction effects are likely to be present in both models because of the phenomenon of natural interaction, that we discussed above. However, the significance of \(\hat{\gamma }_{12}\) in the LV-CRM indicates that the product term of the latent variables can help explain additional complexity of the interaction pattern.

In a second step, we looked at the specific interaction effects, that is, we computed \(\zeta \) from Eq.  1 with respect to \(\eta _{\text {MD}}\) and \(\eta _{\text {TL}}\) . Figure 10 shows conditional regression plots, that is, the regression of the dissociative symptoms Y on mental defeat \(\eta _{\text {MD}}\) conditional on values of trauma load \(\eta _{\text {TL}}\) . The illustration is similar to simple slopes in OLS regression, but shows non-linear relationships. The color indicates the extend of trauma load (green to red); the latent variable \(\eta \) (MDQ) has a standardized scale, that is, mean of 0 and standard deviation of 1. The covariates age, sex, and age at worst event were fixed to their means. If trauma load was below the average or at the average (green and yellow lines; 1 and 2 SD below average and average, respectively), there was a (strong) positive association between mental defeat and dissociative symptoms. However, the association declines at an average trauma load and above average (yellow and orange line), and changes sign at 2 SD above average.

Slope of \(\eta _{\text {MD}}\) for the relation between latent mental defeat (MDQ) and dissociative symptoms (SDQ) depending on \(\eta _{\text {TL}}\) at \(\eta _{\text {MD}}=0\) and remaining covariates at their means. Vertical lines indicate where the interaction effects (i.e., slopes of the slopes curve) were computed

We computed the interaction effect \(\zeta \) , to gain more information if and how much the slopes of the regression of dissociative symptoms on mental defeat change due to the trauma load. The results are presented in Table 3 . Again, we fixed the covariates age, sex, and age at worst event to their means. We can see, that the (instantaneous) positive change in slopes due to trauma load is especially significant for values below and at average on both latent variables. This means that for persons with below or at average values of mental defeat the relationship to dissociative symptoms depends on the amount of trauma load, at least if trauma load is also below or at average. Vice versa, the relationship between mental defeat and dissociative symptoms does not (significantly) depend on trauma load, if trauma load is above average.

These results provide a first glimpse into the highly complex interactional patterns. For example, the slope of mental defeat depending on trauma load for a person with an average value of mental defeat (i.e., \(\eta _{\text {MD}}=0\) ) is illustrated in Fig.  11 . We reported the interaction effect (i.e., slope of the slope curve) from representative values of the trauma load variables (i.e., slopes where vertical lines intersect with the slope curve), but there are alternative techniques to summarize the interactional pattern. However, such techniques (e.g., average marginal/interaction effect) have to be adapted for models with latent variables.

Discussion of empirical example

Previous research showed that at higher levels of trauma load, the interindividual variability in trauma-associated symptoms decreases and individual risk factors may only play a subordinate role (Kolassa et al., 2010 ; Mollica, McInnes, Pool, & Tor, 1998 ; Neuner et al., 2004 ; Wilker et al., 2015 ). This should be reflected by significant interactions between risk factors, such as peritraumatic mental defeat, and trauma load on the outcome variable. While this effect was only present at a trend level when employing classical negative binomial regression models, the novel method introduced in this paper allowed us to discover such interaction effects.

At the same time, the strong importance of both trauma load and mental defeat as predictors of Shutdown dissociation were replicated by the novel analyses. Due to the de-attenuation, the effects were even stronger than reported in the original analyses.

In psychology and the social sciences, interactions between latent predictors in count regressions are often of interest. While it is well known that using fallible scores and not accounting for measurement error generally leads to attenuation bias in the estimated regression coefficients (Carroll et al., 2006 ), the extent of these effects has not been previously studied for count regression models. In this paper, we introduced the latent variable count regression model (LV-CRM) framework. We examined its performance regarding point estimation as well as statistical inferences using simulation studies and illustrated its use in an empirical example from clinical psychology.

In our simulation studies, we found that severe attenuation bias (i.e., relative bias below \(-10 \%\) ) can occur for the product terms even if the fallible scores had considerably high reliabilities (i.e., both 0.9). For non-zero product term coefficients, the estimated parameters from the GLM were attenuated up to \(-33 \%\) . Attenuation bias this high was observed both in scenarios with two and three latent variables and their respective interactions. In contrast, the LV-CRM yielded virtually unbiased estimates under most conditions and provided de-attenuated point estimates. In our third simulation study, we found a notable exception to this rule: In scenarios with three positively correlated latent variables and three positive product term coefficients, the relative bias fluctuated rather unsystematically for both the GLM and the LV-CRM with larger biases for the newly proposed approach. For product term coefficients of zero, however, both approaches worked equally well, with a slight advantage for the GLM due to the attenuation bias.

With regard to the relative efficiency of the point estimates, we found similar results. That is, for scenarios with a product term coefficient of zero the GLM was slightly more efficient, as the attenuation bias has a ’favorable’ effect in this case. In scenarios with non-zero product term coefficients, however, the LV-CRM was often considerably more efficient than the GLM, especially if reliabilities of 0.8 or below were involved.

Our second simulation study also investigated statistical inferences for the GLM and the LV-CRM. Interestingly, we found that the empirical detection rates (i.e., type I error rates and power) were acceptable and on the same level for both approaches. In the GLM, the biased point estimates are compensated by overconfident standard error estimates, that is, even though the point estimates are systematically closer to zero, the confidence intervals are too narrow and therefore do not necessarily include the zero too often. In contrast, the coverage rates were often poor for the GLM, especially in scenarios with larger product term coefficients. That is, the confidence intervals were often too narrow to include the true product term parameter, leading to coverage rates down to 19.9%. The LV-CRM, however, yielded accurate coverage rates under all conditions.

Limitations and extensions

The partial derivative framework by Kim and McCabe ( 2022 ) offers a modern technique to quantify interaction effects in non-linear models, but the adaption of this framework to latent variable models can be challenging. In the empirical example, we used this framework to report interaction effects at the means of the covariates and at selected points of the latent variables. However, estimating individual interaction effects and then computing aggregates of them (e.g., average interaction effect) is not straightforward for latent variable models because the individual values of the latent variables are unobserved. Computing an average interaction effect would in this case require a mixed averaging procedure (i.e., sample average for observed predictors and integration techniques for latent predictors) or additional distributional assumptions for the observed predictors. Thus, extending the partial derivative framework for latent variable models is an important task for future research.

Wald test-based statistical inferences for estimated parameters in a SEM (e.g., for a product term coefficient) are not invariant against different methods of scaling the latent variables (Gonzalez & Griffin, 20001 ). In both the simulations studies and the empirical example, we identified the latent variables as standard normal scales, which performed well in terms of power and efficiency in previous studies (Klopp, & Klößner, 2021 ). Additionally, in the simulation studies, the data-generating model exactly matched our identification method. In the empirical example, however, a different scaling method would affect the standard errors of the estimated parameters and, thus, also the interaction effects, which are functions of these. While single parameters can alternatively be tested with a likelihood-ratio test (Gonzalez & Griffin, 20001 ), we are not aware of an alternative for the interaction effects. Thus, critically reflecting the choice of scale and comparing results between scaling methods seems warranted.

A well-known limitation of the marginal maximum likelihood approach is the computational burden, which becomes unfeasible if multiple latent variables ( \(\ge 3\) ) are involved. However, there exist different techniques to alleviate the computational burden (see Skrondal & Rabe-Hesketh, 2004 , Ch. 6, for an accessible overview): First, numerically efficient techniques from the family of Gauss–Hermite quadratures can be used for normally distributed latent variables. Here, the integration points and weights are derived through rule-based computations. Exponential growth of the number of integration points can be drastically reduced with techniques like adaptive Gauss–Hermite quadrature or Laplace approximation. An alternative can be the use of sparse grids (Heiss & Winschel, 2008 ), where integration points are removed if their weight falls below a certain cutoff point, resulting in a considerably smaller grid. Second, Monte Carlo integration offers an alternative for high-dimensional integration problems as well as in situations with non-normal latent variables. Here, the integration points and weights are randomly drawn from the target distribution. In contrast to Gauss–Hermite techniques, the number of integration points does not necessarily grow exponentially and the weights are always equal to 1. Especially for non-normally distributed latent variables, this technique can be facilitated with a Gauss–Hermite rule-based importance sampling approach (Elvira et al., 2021 ). Third, in some cases, it is possible to reduce the dimension of numerical integration below the number of latent variables. Rockwood ( 2021 ) illustrates this in an example with five latent dimensions, where one dimension of integration suffices after a re-parameterization of the model. While this reduction technique does not generalize directly to a model with interaction terms, it can be useful in situations where only few of the latent variables are actually involved in interactions.

While the LV-CRM is an extension of both the G-SEM framework (Rockwood, 2021 ) and the NB-MG-SEM framework (Kiefer & Mayer, 2021a , b ), it is more restrictive as these frameworks in some regards. The LV-CRM can in principle be extended to be a full generalization of the G-SEM framework. Such a generalization would include multiple outcome variables, a structural model among the latent variables, and allow for manifest covariates in the measurement model. Especially the possibility for multiple outcomes would allow for more complex regression models, for example, zero-inflated count regression models. In addition, a G-SEM model also allows for non-linear measurement models, that is, item response theory (IRT) models for categorical and count outcomes can be adapted for the measurement model (Rasch, 1960 ). Vice versa, modern IRT models for count models could be adapted to provide more versatile count regression models (Beisemann, 2022 ; Forthmann et al., 2020 ).

The two main differences (besides the latent interactions) between the LV-CRM and the NB-MG-SEM are: First, the NB-MG-SEM is based on a multigroup framework which allows for more modeling flexibility when it comes to group-specific effects. For example, it is possible to estimate group-specific overdispersion parameters or measurement error variances. Thus, it offers an alternative to model heterogeneity in parameters. Second, in the LV-CRM, we distinguished between stochastic and fixed observed variables. That is, manifest predictors in the LV-CRM are considered as fixed by design. The NB-MG-SEM models all observed variables as being stochastic (i.e., randomly sampled). While this distinction should have no effect on the estimation of the regression coefficients (Kiefer & Mayer, 2019 ), the stochastic approach additionally estimates various moments (i.e., expectation, variance, covariance) of the manifest predictors, which can be used for further analyses.

Availability of data and materials

The datasets generated during and/or analyzed during the simulation studies of the current study are available in the OSF repository, https://osf.io/q7knc The dataset analyzed for the empirical example of the current study are not publicly available due to data privacy laws. Because of this limitation, analysis code is illustrated with a synthetic dataset, which is also available from the OSF repository.

Code availability

Materials and analysis code are available at https://osf.io/q7knc .

It is possible to allow for quadratic terms of the latent variables (e.g., \(\eta _k^2\) ) by changing the starting index of the second sum from \(k+1\) to k .

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Kiefer, C., Wilker, S. & Mayer, A. Interactions between latent variables in count regression models. Behav Res (2024). https://doi.org/10.3758/s13428-024-02483-4

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