sample abstract for research paper pdf

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An abstract is a short summary of your (published or unpublished) research paper, usually about a paragraph (c. 6-7 sentences, 150-250 words) long.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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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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How to Write an Abstract APA Format

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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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Example of Abstract for Your Research Paper: Tips, Dos, and Don’ts

Research papers serve as vital tools for disseminating knowledge and expanding the boundaries of human understanding. Yet, prior to delving into the complexities of your research, readers typically encounter the abstract—an abbreviated summary that contains the core of the paper.

In this article, we will explore key factors that are considered while writing an abstract and give an illustrative example to help you in formulating your own.

Table of Contents

A research paper abstract is a concise summary of your study, designed to quickly inform journal editors and researchers about your work and encourage them to read further. In today’s digital age, where online publication databases are prevalent, writing a compelling abstract is more critical than ever.

Think of the abstract as the “executive summary” or “gist” of your research. It serves to “sell” your work and provide a brief overview of its most important aspects. Given the online nature of academic transactions, you have a limited time to impress readers amid increased competition from other abstracts.

The Academic Publishing and Conferences International (APCI) emphasizes 12 questions or “points” considered during the selection process for journals and conferences. Crafting an abstract that addresses these points is crucial, as it may be your only opportunity to persuade readers to delve deeper into your study.

To create an effective abstract, consider the following suggestions:

• Clearly state the purpose and key aspects of your study.
• Summarize your methodology and key findings concisely.
• Emphasize the significance and contribution of your research.
• Use clear and straightforward language, avoiding jargon.
• Follow the structure and guidelines recommended for abstracts in your field.
• Spend time refining and editing your abstract to ensure it accurately represents your study and engages your target audience.

Imagine browsing a bookstore shelf, scanning titles and summaries to find a book that captures your interest. The abstract of a research paper serves a similar function—it’s the window through which readers glimpse the significance and scope of your work.

An abstract distills the essence of your research, enabling readers to quickly determine if your paper aligns with their interests or research needs.

What is the ideal length for an abstract?

When preparing your abstract, it’s important to consider its length and style. Abstracts serve the purpose of summarizing your study, with two main styles to choose from: descriptive and informative.

A descriptive abstract is typically shorter, around 100-200 words, focusing on introducing the paper’s background, purpose, and objectives while omitting detailed results and methods.

On the other hand, informative abstracts are more comprehensive, ranging from a paragraph to a full page. They encapsulate every aspect of your study, including results, acting as a condensed version of your paper.

Informative abstracts are more common, especially in scientific and technical fields, while descriptive abstracts are often seen in humanities and social sciences.

To determine the right type for your abstract, refer to journal submission guidelines and read examples in your field.

Elements of an Abstract

A well-crafted abstract should contain the following elements:

Context and Importance: Start by clearly stating the research problem or question and explaining why it matters. What gap in knowledge does your research aim to address?

Research Methodology: Briefly describe the approach you used for your research, whether it was a literature review, an experiment, a survey, or another method. This helps readers understand how you conducted your study.

Key Findings: Highlight the most significant results or conclusions from your research. What new insights did you discover? What implications do these findings have for the broader field?

Implications and Applications: Discuss the implications of your findings. How do they contribute to existing knowledge? What real-world applications or recommendations can be drawn from your research?

Keywords: Include relevant keywords that will help other researchers find your paper in databases and search engines.

An Example of a Research Paper Abstract

Title: Social Media’s Effect on Mental Health

This research paper explores the relationship between social media use and its effects on mental health. Through a thorough review of existing literature and quantitative analysis of survey data from a diverse group of participants, this study aims to provide a detailed understanding of how social media influences psychological well-being.

The literature review synthesizes various theoretical frameworks that explain how social media can affect mental health, including social comparison, fear of missing out (FOMO), cyberbullying, and the development of unrealistic self-perceptions. Additionally, the review examines protective factors such as social support and positive online experiences that may mitigate the negative impacts of social media.

To empirically investigate this relationship, a structured survey was conducted among participants from different age groups and social media platforms, ensuring a representative sample.

Writing an Abstract

Writing a concise yet comprehensive abstract is crucial for effectively communicating the key aspects of your research. It is recommended to draft the abstract after completing your paper, as this allows for a more accurate distillation of the most important points and findings. Aim for clarity, coherence, and an engaging narrative that captures the interest of readers and encourages them to explore your work further.

The abstract serves as the first impression of your paper, offering a glimpse into the intellectual journey you have undertaken. Mastering the art of abstract writing enables you to effectively convey the significance and impact of your research to the broader academic community.

Guidelines and Requirements for Research Abstract

When crafting a research abstract, it’s crucial to adhere closely to the guidelines outlined in your target journal’s Guide for Authors. This level of attention to detail extends to submissions for conferences and academic assignments.

Publishers often have specific formatting and structural requirements. Here are key questions typically addressed in journal guidelines:

• What are the word/character length limits?
• What style and formatting guidelines should be followed?
• Which type of abstract is appropriate?
• Are there specific rules for content and organization?

Following these guidelines ensures your abstract meets the criteria for submission, preventing it from being disregarded upon initial review.

10 Essential Tips for Writing an Effective Research Paper Abstract

Your research paper’s abstract is similar to an elevator pitch—it must be concise, informative, and captivating. Here are ten strategies to help you create an abstract that stands out:

• Understand its Purpose: Acknowledge that an abstract provides a condensed overview of your entire paper, introducing the research question, methodology, key findings, and significance.
• Begin Strong: Engage your reader immediately with a clear and succinct statement about the research problem you’re addressing.
• Methodology Matters: Briefly outline the research methods used to investigate the problem.
• Highlight Key Findings: Summarize your most significant results without delving into excessive detail.
• Emphasize Significance: Clearly articulate the contribution your research makes to existing knowledge in your field.
• Prioritize Clarity: Use straightforward language, avoiding jargon or overly technical terms that may be unfamiliar to a general scientific audience.
• Follow Structure Guidelines: Adhere to the recommended abstract structure in your field, typically involving background, research question, methodology, findings, and significance.
• Word Limits: Stay within the word count specified by the journal or conference, ensuring every word contributes meaningfully.
• Proofread and Edit: Present a polished abstract by thoroughly proofreading for typos and grammatical errors.
• Revise Thoroughly: Refine your abstract through multiple revisions until it effectively encapsulates the essence of your research.

Dos and Don’ts of Writing an Abstract for a Research Paper

Writing an abstract is crucial for clearly presenting your research. Following these guidelines, including an example abstract, understanding abstract components, and using tips for effective writing, can help you craft an informative and engaging abstract. A strong abstract acts as a gateway to your research, encouraging readers to explore your paper further.

After the Completion of Your First Draft Abstract

After drafting your abstract, it’s crucial to revise it thoroughly. Here are steps to enhance its quality:

• Revise for Errors: Check for grammatical and spelling mistakes and ensure proper formatting.
• Seek Feedback: Have a peer review your abstract to gauge its clarity and effectiveness in summarizing your research. Ask them to summarize your study independently to check if key points are communicated clearly.
• Consult Experts: Consider consulting with professors, writing center consultants, or specialists to gain different perspectives on your abstract.
• Professional Editing: For a polished final version, consider hiring an academic editor to fix grammatical, stylistic, and formatting errors. This step can significantly improve the readability and impact of your abstract.

Including headings can also enhance the organization and readability of your abstract.

Mastering the art of writing an abstract is essential for effectively communicating your research. By understanding the components of a strong abstract and following practical tips, you can create a concise and compelling summary of your work.

Remember to highlight the significance of your research, present your findings clearly, and adhere to the recommended structure. Avoid common pitfalls such as including excessive background information, citing references, or using unexplained abbreviations.

By following these guidelines and carefully proofreading your abstract, you can ensure that it serves as an inviting window into your research, encouraging readers to delve deeper into your paper.

Misbah Rashid, an expert in Technology Management, holds an MBA and an MS in Information Systems and Technology Management. She has experience teaching marketing and technology in business at the university level.

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How to write an abstract for a paper

I’ve been teaching small workshops for my lab on how to do scientific writing. Doing these short, quick courses helps me provide them with insights on how I write my own papers, and how they can write their own papers (plus dissertations and theses). With these classes, I also create a shared knowledge base and approach to investigating a topic and presenting research. Yesterday, I realized that while I have written a ton of blog posts on research, I had not published any blog posts on abstracts nor conclusions. This and my next blog post try to make amends for these omissions.

I really, really love Dr. Jessica Calarco’s 5 sentences model.

With abstracts, I typically aim for a 5-sentence model that mirrors the structure of the rest of the paper: S1: what we know S2: what we don't S3: how you answer that question S4: what you find S5: why it's important — Jess Calarco (@JessicaCalarco) April 14, 2019

Several suggestions I got off my Twitter request:

• The Kent Bent’s 4 sentence structure ( check insights shared by Bent et al in this panel )
• A handout I found from the University of Melbourne.
• Andrade’s paper offering guidance on how to write abstracts on the Indian Journal of Psychiatry
• Dr. Leah Carroll’s handout. Dr. Carroll works for The Office of Undergraduate Research at University of Berkeley
• The incomparable Dr. Inger Mewburn (Thesis Whisperer) on 7 strategies to write a journal article (on PhD2Published) – note this is part 2, the abstract.
• A great series of templates by Daniel (the creator of Organizing Creativity) on how to write abstracts , also based on Kamler and Thomson.
• The Kamler and Thomson version of how to use Tiny Texts to help create an abstract on WikiHow, with additions from Mewburn.

Here you’ll find all the links to our @JClinEpi papers: https://t.co/FpwlvPTBBL pic.twitter.com/BdlAE5L9ve — Jochen Cals (@JochenCals) July 12, 2018

My initial draft of an abstract is just the first sentence of every paragraph in the intro. — Austin Henley (@AustinZHenley) July 12, 2018

Two sentences for intro. One for research question. 1 for methodology. 1 for main results. 1-2 for discussion/conclusions. This results about 200 words. — Alex Arreola (@astrobiologiste) July 13, 2018

In CS, many of us apply Kent Bent's four-sentence structure ( https://t.co/eqikhkNHha ): The first states the problem. The second states why the problem is a problem. The third is my startling sentence. The fourth states the implication of my startling sentence. For non-CS, YMMV. — Titus Barik (@barik) July 12, 2018

For a concise review of Discussion & Conclusions I always refer to Gustavi (2003) How to write and illustrate a scientific paper. Chap 15. Helps you focus and not digress. I have a copy to share! — Mary Jo Figuerero (@mjofiguerero) July 13, 2018

Here's a quick overview of tiny texts: https://t.co/Pns3RZ18Fr — Michael Healy (@mojohealy) July 12, 2018

I've got a worksheet for writing abstracts and a little write-up of how to use it – target audience was undergrads preparing conference proposals but it works well just the same. Email [email protected] to get a copy (open to all). — Dr. Leanne C. Powner (@LeanneCPowner) July 12, 2018

Must note, thanks to Frank Cichocki et al. (2017) for the example abstract! https://t.co/bhtvzdm8PC — Tessa Campbell (@ScientistTess) July 13, 2018

This is the technique I was taught. It is amazing how many abstracts fit this pattern! Not sure if it applies to your type of science but the concept/pattern (once cracked!) is very useful in deconstructing other's writing and doing your own. pic.twitter.com/8v7NkmMtzt — Tessa Campbell (@ScientistTess) July 13, 2018

FWIW, this is how I write my abstacts: https://t.co/jAv9YohOMq and how I write conclusions (which I always name "Summary and Conclusions"): https://t.co/voNNrUETJ2 — Dr Eva Lantsoght (@evalantsoght) July 13, 2018

Screenshot of a handout I got in grad school for writing concise abstracts. Bullet point info to guide each sentence, and then scale up to 1-3+ sentences depending on the abstract word limit. #AcWri pic.twitter.com/SAXGgjfmKj — Peggy Shannon-Baker (@PShannonBaker) July 13, 2018

1. What did we do 2. Why did we do it 3. How did we do it 4. What were the results 5. What do we think it means — Suzan Verberne (@suzan) July 13, 2018

I hope these resources are helpful!

EDIT – a few additional resources after Dr. Compton requested more…

I developed this abstract questionnaire for a grad publishing class I taught a while back. The first part are questions that a reader should be able to answer after reading it, the second is a mag style quiz https://t.co/fz915UM7Pc — Omar Lizardo (@omar_lizardo) April 14, 2019

Seconded. See also the NIH Specific Aims model https://t.co/88KcluXvTy — Bradley Dilger (@cbdilger) April 14, 2019

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By Raul Pacheco-Vega – July 18, 2018

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This is very helpful for me to get a better understanding of the structure of an abstract. If you get around to it, it would be especially helpful to see some examples of good abstracts. I’m working on a lit review, and I have seen any examples of that specific type of article. When you come across some, would you post them here for us? That would be much appreciated. Regards!

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Writing an abstract

You may be asked to write an abstract for a piece of work that you do. Although it is usually brief (typically 150-300 words), an abstract provides an important overview which helps your reader to understand your work. 

Whereas the purpose of an introduction is to broadly introduce your topic and your key message, the purpose of an abstract is to give an overview of your entire project, in particular its findings and contribution to the field. An abstract should be a standalone summary of your paper.

Typically, an abstract includes the following.

• A brief introduction to the topic that you're investigating.
• Explanation of why the topic is important in your field/s.
• Statement about the problem or research gap that you are addressing.
• Your research question/s or aim/s.
• An indication of your research methods and approach.
• Your key message.
• A summary of your key findings.
• An explanation of why your findings and key message contribute to the field/s.

In other words, an abstract includes points covering these questions.

• What is your paper about?
• Why is it important?
• How did you do it?
• What did you find?
• Why are your findings important?

To see the specific conventions in your field/s, have a look at the structure of a variety of abstracts from relevant journal articles. Do they include the same kinds of information as listed above? What structure do they follow? You can model your own abstract on these conventions.

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Enterprise’s Strategic Agility and Resource Allocation Choice: A Case of SMEs in China

• Published: 22 May 2024

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• Xiangsheng Dou   ORCID: orcid.org/0000-0001-7795-9111 1 &
• Fizza Ishaq 1  

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Enterprises must optimize resource allocation to achieve their strategic objectives in the context of international competition. This paper proposes a comprehensive index to measure the strategic agility of small and medium-sized enterprises (SMEs) using the basic data of online surveys based on multiple indicators and Likert scale. Then, the paper constructs an econometric model to conduct empirical analysis with representative sample data from the SEMs in the computer, communication, and other manufacturing industries in China. The paper demonstrates the nature and measurement of strategic agility and the matching of resources with strategic agility and advances a theoretical framework that enterprises’ strategic agility determines the joint allocation of non-financial resources to support strategies. The results indicate that enterprises must jointly allocate their resources according to their strategic agility, only in this way can they achieve their strategic goals and outperform their competitors. The paper further develops the concept and idea of strategic agility level zone of effective zone, inert zone, and hyper-power zone, so that enterprises may adopt different strategic decision-making based on different zones. The paper contribute to the literature on interdependencies between strategic agility and resource allocation.

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Dou, X., Ishaq, F. Enterprise’s Strategic Agility and Resource Allocation Choice: A Case of SMEs in China. J Knowl Econ (2024). https://doi.org/10.1007/s13132-024-02046-0

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A pilot study on preferences from surgeons to deal with an innovative customized and connected knee prosthesis – A discret choice experiment

Mathieu le stum.

a Université de Brest, UBO, LATIM, UMR 1101, 22 rue Camille Desmoulins, 29200, Brest, France

b Institut National de la Santé et de la Recherche Médicale, Inserm, LaTIM, UMR 1101, 22 rue Camille Desmoulins, 29200, Brest, France

Arnaud Clave

c Service d'orthopédie, Clinique Saint George, 2 Avenue de Rimiez, 06100, Nice, France

Koffi Adzinyo Agbemanyole

d Institut Mines-Telecom, IMT Atlantique, LATIM, UMR 1101, M@rsouin, 655 Av. du Technopôle, 29280, Plouzané, France

Eric Stindel

e Centre Hospitalo-Universitaire de Brest, CHU Brest, LATIM, UMR 1101, 2 Avenue Foch, 29200, Brest, France

Myriam Le Goff-Pronost

Associated data.

The data have not been deposited into a publicly available repository. The data that has been used is confidential.

To address the increasing global demand for Total Knee Arthroplasty and reduce the need for revisions, several technologies combining 3D planning and artificial intelligence have emerged. These innovations aim to enhance customization, improve component positioning accuracy and precision. The integration of these advancements paves the way for the development of personalized and connected knee implant.

Questions/purposes

These groundbreaking advancements may necessitate changes in surgical practices. Hence, it is important to comprehend surgeons' intentions in integrating these technologies into their routine procedures. Our study aims to assess how surgeons' preferences will affect the acceptability of using this new implant and associated technologies within the entire care chain.

We employed a Discrete Choice Experiment, a predictive technique mirroring real-world healthcare decisions, to assess surgeons' trade-off evaluations and preferences.

A total of 90 experienced surgeons, performing a significant number of procedures annually (mostly over 51) answered. Analysis indicates an affinity for technology but limited interest in integrating digital advancements like preoperative software and robotics. However, they are receptive to practice improvements and considering the adoption of future sensors.

Conclusions

In conclusion, surgeons prefer customized prostheses via augmented reality, accepting extra cost. Embedded sensor technology is deemed premature by them.

1. Introduction

Total Knee arthroplasty (TKA) is one of the most predominant orthopedic procedures worldwide with respectively 720,000 in 2019 and more than 700,000 surgeries in Europe [ 1 ] and the USA [ 2 ]. This number is continuously increasing for several decades and is expected to explode in the next years (+147 % by 2030 in the USA [ 2 ]).

This overall increase in TKA is chiefly driven by the natural rise in the incidence of osteoarthritis, related in particular to the combined effects of population aging and obesity [ 3 ]. Nonetheless, another factor is the broadening of TKA indications towards younger patients (<65 years) allowed by improvements in both surgical techniques and knee implants [ 4 , 5 ]. As a result, implanted for more than 20 years in active subjects, these prostheses are more frequently revised, leading to expensive and less effective procedures. A +182 % growth in revision Knee Arthroplasty is, for example, expected in the USA by 2030 [ 6 ].

To address this major public health problem and improve primary TKA surgery, thereby preventing revisions caused by premature wear, loosening, and infection, several factors must be considered: implant design, surgical technique, and patient follow-up [ [7] , [8] , [9] ] [ [7] , [8] , [9] ] [ [7] , [8] , [9] ].

Since the last decades, implant design has been improved by the use of advanced technologies mixing 3D planning and artificial intelligence. This led to the development of customized implants, suitable to patient morphology thanks to dedicated CT images [ 10 , 11 ]. To improve accuracy and precision in components positioning, several assisted surgical technologies have been developed, such as navigation, robot, or Personalized Surgery Instrument (PSI) [ 10 , [12] , [13] , [14] , [15] ]. Among these new technologies, Augmented Reality (AR) is expanding and appeared to be a promising technology [ 16 , 17 ]. At the same time, to provide not only therapeutic benefits but also follow-up capabilities, different sensors types have been developed [ 18 ]. These are smart electronic devices that measure physical properties such as pressure, cinematic, or temperature, and send information to an electronic processor [ 8 ]. The ability of sensors to measure several types of data allows them to be used in the surgery itself or during the postoperative patient follow-up. At present most stay in a research state but some technologies start to be implanted [ 19 ].

The integration of these improvements will enable the development of personalized and connected implants, as proposed in FollowKnee project [ 20 ]. However, these advancements also represent a breakthrough, and the implementation of this new care chain may necessitate adaptations and changes in surgical practices. Therefore, it is crucial to understand surgeons' intentions regarding the adoption of these technologies as part of their routine practice. By considering their preferences, we can better assess the impact of these technologies on patient care.

Thus to evaluate the trade-off made by surgeons, we conducted a Discrete Choice Experiment, which is a technique that is predictive of choices, and mimicked real-world decisions in healthcare decision-making, to elicit preference [ 21 ].

Our study aims to assess how surgeons' preferences will affect the acceptability of using this new implant and associated technologies within the entire care chain. To the best of our knowledge, no study on surgeons' choices has been reported thus far.

2. Materials and METHODS

2.1. study design.

Discrete Choice Experiment (DCE) represents a quantitative stated preference technique for eliciting individual preferences [ 22 ]. This method relies on the execution of a survey employing a structured questionnaire tailored to ascertain the relative significance of attributes within the domain of services and healthcare programs. Its principal objective is to elucidate the trade-offs individuals are prepared to undertake between attribute levels to optimize their utility within the spectrum of available alternatives. Since utility is not directly observable by the analyst, it is inferred from the choices made by respondents among the various alternatives presented to them [ 23 ].

This method explores, for a specific good or service, the importance of trade-offs that individuals make among attributes and their alternatives using a sequence of choice sets depicting hypothetical scenarios. In practice, respondents are presented with various options or scenarios representing different levels for the same good, aiming to collect their preferences. It is well known that individuals tend to choose options that maximize their utility. Therefore, knowing the utility derived from the consumption of a good or service helps increase individuals' adherence to them [ 23 ]. The DCE method has the advantage of being able to simulate existing goods or services as well as eliciting preferences and values for goods or services that do not yet exist and are therefore hypothetical. DCE is thus one of the most widely employed methods for understanding the factors that influence choice. The DCE is suitable for examining our research question. While other preference elicitation methods offer similar potential, they come with drawbacks, such as increased complexity for both analysts and participants, and a higher susceptibility to biases (e.g., Time Trade-off and Standard Gamble), or a reduced fidelity to real-world scenarios (such as ranking and evaluation methods) [ 24 ]. Consequently, we have opted for the DCE in this study. This approach is regarded as the most fitting one meeting the requirements of welfare theory [ 25 ], as it involves individuals in decision-making processes akin to those encountered in their daily lives.

In our experiment, a DCE was administrated to French surgeons (1) via an online survey, distributed through the French Orthopaedic National Society (Sofcot) and (2) through a regional congress (SOO- Western Orthopaedic Society), from January to June 2022.

The survey takes 10 min to complete and was divided into five sections: (i) sociodemographic (ii) information on current surgical practice, (iii) preference, on the use of an innovative prosthesis, (iv) potential development of practice (i.e. What conditions would you require for the use of a personalized and connected prosthesis?), and (v) affinity for technology interaction (ATI). The survey was designed collaboratively with specialists in both the humanities and social sciences, as well as surgeons. The latter group aided in identifying any inconsistencies in the wording of the questions pertinent to the surgical field.

In the Preferences section, surgeons select their favorite scenario from a series of two hypothetical but realistic scenarios for a customized, connected prosthesis. They were asked in each to select the one they would prefer. The scenarios were described by a set of attributes which were further specified by levels.

To define attributes, good research practices for stated-preference studies [ 26 ] were followed. Attributes ( Table 1 ) were identified by a literature review and findings from interviews with representative experts (four orthopedic surgeons, a cognitive scientist specializing in technology adoption, and a rehabilitation physician). It was pointed out the importance of (1) the care pathway before and after the surgery, (2) anatomical planning, (3) precision of the prosthesis placement during the surgery, (4) post-surgery data and their usability, and (5) cost. The full questionnaire was pretested on eight representative orthopedic surgeons to assess their understanding of its content and gather feedback on the questions. The results led us to consider three technical attributes and one related to cost. The technical attributes are “Customized implant” (link to previous point 2), “integrated sensors” (points 1 and 5), and usage of “Augmented reality” (point 3). All the potential use of an innovative customized and connected prosthesis is thus covered. The next step consisted of assigning levels to each attribute. The literature recommends that these should be realistic, well-defined, plausible, and should potentially involve trade-offs. All technical attributes were dichotomous to make able the expression of use, or not, in the current practice. As new technologies often led to an increase in cost, a relating attribute was defined by a low (“+10 %”) or moderate (“+25 %”) rise.

Attributes and level included in the Discrete Choice Experiment.

Data were gathered anonymously. Because our study did not involve the collection of health or personal information, ethics committee approval was not required.

2.2. Experimental design

The four attributes with two levels have a possible 2 4  = 16 scenarios (four attributes with two levels) and (16*15)/2 = 240 possible pairwise choices. Since there are too many possible scenarios, it is impossible to present this full factorial design to the surgeons. Therefore, to simplify the scenario settings, a fractional plan (i.e. selection of the best interaction combinations) was developed that maximizes D-efficiency. D-efficiency is a standard measure of goodness of fit. It indicates how well the main effects can be estimated and retained. A D-efficient design (minimizing D(B) error) was generated by using the R package Idefix to reduce the number of choice scenarios into a manageable number of 16 choice sets for presentation [ 27 , 28 ].

For most realistic results, it is recommended to stay as close to the real world as possible. When modeling the potential adoption of a new intervention or service, which is a key objective of this paper, there is much consensus that a DCE should include an opt-out option, that figures out a reference point, or their current situation [ [29] , [30] , [31] , [32] ]. In this study, surgeons are presented with two generic alternatives and an opt-out option ( Fig. 1 ). Opt-out was included to not force the surgeons to choose between the proposed alternatives when those were not considered suitable compared to their current practice. The opt-out option did not describe an alternative model of practice but encompassed all other actual well-proven technologies.

Example of a DCE choice set. DCE, discrete choice experiment.

2.3. Study size

As there is no consensus to calculate the minimum require sample size in DCE, we used a common rule of thumb [ 33 ]. The minimum sample size (N) required for the experiment is thus obtained by formula (1) :

In which c = equal to the largest number of levels for any of the attributes, t = number of choice set and a = number of alternatives). This results to a minimum sample size of 31 respondents.

2.4. Statistical model and data analysis

The answers were analyzed in accordance with McFadden's Random Utility Theory (RUT) (1974), which incorporates economic rationality and utility maximization. Utility is thus not directly derived from the good taken as a whole, but rather derived from each attribute of the good [ 34 ]. Accordingly, the RUT posits that the utility gained from selecting a good exhibits a probabilistic nature (McFadden, 1974), with only the deterministic component of this utility being observable to researchers [ 35 ]. In other words, individual preferences are influenced by a set of characteristics, among which some are indirectly observable and specific to individuals, while others are random and therefore unobservable. So, according to RUT, each respondent (n) choses their preferred (utility-maximizing) scenario across the three alternatives in each of the 16 choice sets. The utility function (2) as described in Refs. [ 36 , 37 ], can be specified as:

where Vnj is the observable component and εnj is a non-explicable error term (independent and identically distribute). With k attributes, we have the following functional form (3):

And so (2) can be rewritten as:

where Unj is the utility that respondent n assigns to alternative j; Xnj, a vector of the observed characteristics of the alternatives (levels); and βn, the vector of coefficients assigned to each level (reflecting the desirability of the attributes) (4).

It is assumed that the form of the function is common across individuals within the sample, but that parameters vary across individuals. To account for heterogeneity in preferences and responses within the surgeons, a mixed logit model (MXL) was used. The MXL identifies attributes for which there is significant preference variation without explaining this variation in depth.

In consequence, the β n 's random coefficients can be decomposed into two part, as follows (5):

Where β ‾ is the population mean, and η n is a stochastic deviation representing preference heterogeneity. Thus, equation (4) can be rewriten as (6):

The stochastic portion of utility (i.e., X' nj η n  + ε nj ) is correlated across choice situations due to the common influence of η n .

In our model, the choice among alternatives depends on four attributes. The utility function to be specified is thus (7):

with β kn  ∼ N (β k , σ k ), MXL yields both a mean effect and a standard deviation of effects across the sample. Thus, MXL explicitly assumes a distribution of preference weights (coefficient β) across the sample, reflecting differences in preferences among respondents for the utility derived from the use of a personalized and connected prosthesis. β0 represents the Alternative Specific Constant (ASC), measuring the effect of the opt-out option.

Analyses were performed on all surgeons who answered to the survey, resulting in four sub-groups. These sub-groups were determined based on the main factors that influence surgical outcomes, namely age and experience [ 38 ]. In the case of France, where the average age of orthopedic surgeons is 50 and the median age is 51, surgeons under 50 were compared to those over 50 [ 39 ]. It is also recognized that a surgeon's experience is related to the volume of procedures performed per year. Therefore, we assumed that experienced surgeons perform over 51 procedures annually, based on the available data. These experienced surgeons are compared to those who perform fewer procedures [ [40] , [41] , [42] , [43] ]. The p-value significance of the attributes and levels presented in choice experiments, are the main evaluation criteria used in this study.

This analysis is feasible as long as the minimum population size required is applied to each subgroup [ 44 ]. The sub-groups comparison was performed by using Pearson's Khi 2 test on main variables. A p-value <0.05 was considered to be statistically significant. Multivariate logistic regression was used to identify relationships between variables.

ATI scale, which is graduated on six levels, was studied through mean, standard error, and Cronbach alpha coefficient. Sub-groups were compared by using the Wilcoxon test. A mean above four indicates a high or very high (over five) ATI and, in contrast, below, a low (three) or very low (two) ATI [ 45 , 46 ]. A Cronbach's alpha above 0.6 is considered satisfactory [ 47 ].

Data were analyzed by using R version 4.0.2.

3.1. Respondents’ characteristics

A total of 90 male surgeons completed the questionnaire, providing their characteristics ( Table 2 ). Most surgeons are over 50 years old, worked in public hospitals, and performed over 51 implants annually. They also mostly not used planning software, navigation systems, or robots in their surgeries. However, they expressed interest in adopting technological innovations, willing to extend surgical time by 10–20 min. Specifically, they were interested in using sensors to monitor patients, alongside standard consultations.

Respondents’ characteristics. It is important to emphase that individuals under the age of 50 are distinct from those who performed fewer than 51 implants annually.

No significant relationships were found between categorical variables and age in terms of working structure, planning software use, navigation systems or robots use, extra surgical time, and sensor use. However, significance was found for the number of prostheses per year ( Appendix A-1 ).

No significant relationships were found between categorical variables and the number of procedures performed per year with planning software, extra surgical time, and sensors. However, significance was observed for working structure, age, and use of navigation systems or robots ( Appendix A-2 ).

Logistic regression analysis revealed that being over 50 years old was associated with a higher probability of performing more than 51 procedures per year and not utilizing data from sensors. No significant impact of the other variables was observed ( Appendix B-1 ). Logistic regression analysis showed that performing over 51 procedures per year was associated with a higher likelihood of working in a public structure, being over 50 years old, and using navigation or robots. No significant impact of other variables was observed ( Appendix B-2 ).

Surgeons showed a high affinity for technology interaction with no significant differences between subgroups ( Appendix C ).

3.2. Discrete choice experiment

Table 3 displays the estimated parameters of the MXL model analysis. Positive and significant coefficients are observed for use of technology-related attributes such as customized and connected implant, and AR. This suggests that surgeons find utility in using these attributes in their current practice. In terms of financial considerations, surgeons prefer a "+10 %" additional cost rather than "+25 %", indicating a willingness to incur limited expenses for implementing these technology-related attributes. Furthermore, the significant ASC indicates that surgeons prefer maintaining current practice despite desiring certain benefits from proposed technologies.

Results from the random parameters mixed logit model. “ASC” stand for Alternative Specific Constant and “sd” for the standard deviation.

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1.

Higher coefficients for attributes indicate greater utility derived from them. Among the attributes considered, AR and personalization show similar levels of utility, making them the most significant factors. On the other hand, the use of sensors has the lowest coefficient, indicating relatively lower importance compared to other attributes ( Table 3 ).

All sub-groups preferred the current practice over the proposed technologies (positive and significant ASC).

Age-based subgroup analysis reveals that individuals over 50 do not significantly prefer sensors. Among those under 50, sensors are their least preferred option. AR is most preferred by those over 50 and ranks second for those under 50. Personalized prostheses are strongly preferred by those under 50, whereas personalized implants are the least preferred option for the other group. Annual procedure numbers-based subgroup demonstrates a distinct contrast between the two groups. Personalized prostheses provide the highest utility in both groups. Among surgeons performing fewer than 51 procedures annually, AR ranks equally with it, with sensor usage and a slight financial surcharge ranking second. In contrast, among surgeons performing over 51 procedures per year, AR is the second-highest preference, while sensors rank last. Finally, significant standard deviations in all groups indicate statistically significant heterogeneity in surgeons' preferences for all attributes.

4. Discussion

The analysis of our surgeon sample shows an experienced population, performing a significant number of procedures per year (mostly over 51) and spanning a wide age range. While they have a strong affinity for technology, they show limited inclination to integrate digital technology (e.g., preoperative software, navigation, robotics) into their surgeries. However, they are receptive to practice advancements and show willingness to allocate additional time and potentially adopt future sensors.

A detailed subcategory analysis reveals patterns beyond the correlation of annual procedures and age. Being over 50 years old negatively affects the utilization of sensor data, while performing over 51 procedures per year positively correlates with adopting navigation technology in a "public" work environment.

To assess surgeons' responses to implementing a new technological care chain, such as personalized and connected prostheses, we used the DCE method. Despite heterogeneity, all selected technological attributes positively influenced surgeons' preferences, with a willingness to adopt if costs were minimized. Surgeons over 50 were reluctant about sensor data, and overall, surgeons preferred their current practices. AR was favored, followed by personalization, while sensor utilization ranked lowest. Preferences varied by age and experience, with older surgeons preferring AR and more experienced surgeons favoring personalization.

The technologies in this new care chain are at different stages of maturity and usage, reflecting the preferences expressed. Personalization and assistive technologies are more advanced, while sensing is in its early stages.

The utilization of 3D planning software and 3D printing enables customized implants (CI) to reduce revision problems through individualized approaches. Accurate positioning and fit of knee prostheses are crucial for patient outcomes. Although currently used selectively, recent developments aim to promote wider adoption. Customized implants preserve the patient's unique geometry compared to off-the-shelf implants, but further improvements in mechanical properties are needed [ [48] , [49] , [50] ]. Surgeons in our study maintain high expectations for this technology [ 51 ]. Preference variation between young and experienced surgeons may be influenced by practical experience and the development stage of CI [ 9 ].

Proper positioning of CI is crucial due to individual patient morphology. Challenges in accurate positioning to ensure good functional outcomes that align with the anatomical needs have been reported. Nowadays, surgeons utilize navigation systems or robotics to replicate the resection plane from design software, aiding in achieving correct fit. Over the past two decades, the utilization of assisted technologies (Computer-Assisted Orthopedic Surgery [CAOS], robots, or PSI in Knee Arthroplasty has increased by 154 % from 2008 to 2015. For instance, robot utilization in hospitals increased by over 500 % from 2009 to 2013 [ 15 ]. Knee arthroplasty has the highest usage rate among other joints, with 18 % of knee surgeons reporting assisted technologies use in 2015 [ 12 , 52 ]. These proportion is expected to reach 32 % by 2032 [ 14 ]. CAOS and robots have demonstrated improved accuracy and precision in component positioning compared to PSI and conventional methods. However, no significant difference has been found in functional outcomes between them and conventional methods [ 52 ]. While current assisted technologies improve efficiency compared to conventional methods [ 52 ], they can be complex and bulky in the operating room, resulting in additional surgical time. On average, TKA takes an additional 15–25 min due to their use [ 15 ]. As part of the continuous effort to improve patient outcomes, AR has emerged as a promising innovation, streamlining workflow procedures, although limited studies with clinical results exist [ 17 ]. Indeed, existing systems often require surgeons to divert attention to a monitor, whereas AR partially addresses these limitations [ 53 ].

In our study, 31.1 % of surgeons utilized navigation systems or robots, with approximately 75 % requiring additional surgical time under 20 min. These findings align with Boylan's study [ 12 ], reporting a 29.2 % utilization rate of robotic assistance in New York hospitals in 2018. Surgeons' high preference for AR indirectly indicates their openness to user-friendly technologies.

Smart sensors, incorporated into implants to provide personalized data, show promise in monitoring post-operative and intraoperative parameters, assisting surgeons in problem detection and personalized rehabilitation [ 8 ]. However, challenges remain in areas like design, robustness, wireless communication, power, and biocompatibility. The use of connected implants in orthopedic surgeries (such as knee, hip, spine, and fractures) has been limited, with only around 100 patients involved, over the past few decades [ 18 ]. While some recent technologies have been adopted in routine practice, most evidence comes from clinical case studies [ 19 ]. Further advancements are needed to improve diagnostic capabilities, explore self-treatment options, ensure safety, data security, and reduce costs. Additionally, beyond technological aspects, it is crucial to enhance the safety of implants (including regulatory authorizations), ensure data security, and reduce costs. High costs may impede adoption in publicly funded healthcare systems [ 8 ]. Despite their potential, these technologies still have limitations and insufficient evidence. Surgeons' preferences reflect this.

Economic considerations affect indirectly choices and global adoption of technologies, depending on affordability and healthcare models [ 54 ]. For instance, in the United States, patients with private insurance and high-volume hospitals are more likely to undergo technology-assisted surgery, compared respectively to Medicare and Medicaid patients and lower-volume hospitals [ 12 ]. Larger hospitals can distribute technology costs and develop cost-effective care pathways [ 12 , 54 ]. In France, where the healthcare system determines costs, surgeons have limited control and moderate expense increases are expected to adopt these new technologies. However, a significant increase (+25 %) would negatively impact technology utilization.

This study has limitations. Firstly, surgeons were asked about technologies still under development, preventing pre-testing prior to answering the scenarios. Envisioning potential usage may have caused cognitive fatigue, possibly influencing choices towards the end of the 16 choice sets. The methodology was adapted to mitigate this effect. Secondly, survey respondents showed a tech-oriented population based on the ATI score. This introduces a potential selection bias, especially considering the small sample size, even if it meets the DCE criteria, in comparison to the practitioner population as a whole. However, this aligns with the "diffusion of innovation" theory, proposed by E. Rogers, new technologies and practices typically require endorsement from "early adopters" among surgeons [ 54 ].

Technology spread and adoption vary across countries due to different influencing factors [ 54 ]. Comparing relative preferences between French surgeons and those from other countries can provide insights into convergences and divergences in perceptions of new technologies.

In conclusion, our study reveals that, despite heterogeneity in responses, surgeons express a preference for utilizing a customized prosthesis through augmented reality, even at an additional measured cost. However, it appears that embedded sensor technology is currently less appealing to them, possibly due to its early-stage development.

Data availability statement

This work benefited from state aid managed by the French National Research Agency under the France 2030 Program with reference N°. ANR-17-RHUS-0005 (Project Follow-Knee). No commercial funding was received for this study.

CRediT authorship contribution statement

Mathieu Le Stum: Writing – review & editing, Writing – original draft, Software, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Arnaud Clave: Writing – review & editing, Writing – original draft, Methodology, Investigation, Conceptualization. Koffi Adzinyo Agbemanyole: Writing – review & editing, Software, Formal analysis. Eric Stindel: Writing – review & editing, Validation, Supervision, Methodology, Investigation, Funding acquisition, Conceptualization. Myriam Le Goff-Pronost: Writing – review & editing, Writing – original draft, Validation, Supervision, Project administration, Methodology, Investigation, Conceptualization.

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interestsStindel Eric reports financial support was provided by French National Research Agency. Stindel Eric reports a relationship with Ostesys SAS that includes: consulting or advisory. Clave Arnaud reports a relationship with ATF Lapée Médical that includes: consulting or advisory, speaking and lecture fees, and travel reimbursement. Clave Arnaud reports a relationship with Zimmer Biomet that includes: speaking and lecture fees. Clave Arnaud reports a relationship with CAOS France that includes: board membership. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The authors would like to thank Sofcot (Société Française de Chirurgie Orthopédique et Traumatologique) and SOO (Société Orthopédique de l'Ouest) for their assistance in disseminating the questionnaire.

Appendix A. 

Comparison of sub-group. 1. Age. 2. Number of procedures performed per year

Appendix B. 

Logistic multivariate results (p = p-value). 1. Age (as main variable). 2. Number of procedures performed per year (as main variable).

Appendix C. 

Affinity for Technology Interaction (ATI) score. No significant differences were observed between subgroups (p > 0.05). Affinity for technology interaction are as follow: between 1 and 2, very low; between 2 and 3 low; between 3 and 4 medium; between 4 and 5 high; and between 5 and 6 very high.

Millimeter-sized battery-free epidural cortical stimulators

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Refractory neurological and psychiatric disorders are increasingly treated with brain stimulation therapies using implanted neuromodulation devices. Current commercially available stimulation systems, however, are limited by the need for implantable pulse generators and wired power; the complexity of this architecture creates multiple failure points including lead fractures, migration, and infection. Enabling less invasive approaches could increase access to these therapies. Here we demonstrate the first millimeter-sized leadless brain stimulator in large animal and human subjects. This Digitally programmable Over-brain Therapeutic (or DOT) is approximately 1 cm in width yet can produce sufficient energy to stimulate cortical activity on-demand through the dura. This extreme miniaturization is possible using recently developed magnetoelectric wireless power transfer that allows us to reach power levels required to stimulate the surface of the brain without direct contact to the cortical surface. This externally powered cortical stimulation (XCS) opens the possibility of simple minimally invasive surgical procedures to enable precise, long-lasting, and at-home neuromodulation with tiny implants that never contact the surface of the brain.

Competing Interest Statement

JTR, AS, SuAS, SaAS, and JW receive monetary and/or equity compensation from Motif Neurotech. SaAS has consulting agreements with Zimmer Biomet, Boston Scientific, Koh Young, Neuropace, Varian, Sensoria Therapeutics. SuAS has consulting agreements with Viz.AI, Penumbra, and Imperative Care as well as grant funding from Viz.AI and NIH. The terms of these arrangements have been reviewed and approved by Rice University, UTHealth, and Baylor college of Medicine in accordance with their policies on conflict of interest in research. The other authors declare no competing interests.

Funding Statement

Funding for this work was provided by the McNair Foundation.

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I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

IRB of Baylor College of Medicine and affiliated hospitals gave ethical approval for this work. This is not a health-related intervention and there were no health-related outcomes from this study. As a result, this study was not registered with a regulatory agency.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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Subject Area

• Addiction Medicine (324)
• Allergy and Immunology (633)
• Anesthesia (168)
• Cardiovascular Medicine (2402)
• Dentistry and Oral Medicine (289)
• Dermatology (207)
• Emergency Medicine (381)
• Endocrinology (including Diabetes Mellitus and Metabolic Disease) (852)
• Epidemiology (11799)
• Forensic Medicine (10)
• Gastroenterology (705)
• Genetic and Genomic Medicine (3770)
• Geriatric Medicine (350)
• Health Economics (637)
• Health Informatics (2409)
• Health Policy (940)
• Health Systems and Quality Improvement (905)
• Hematology (342)
• HIV/AIDS (787)
• Infectious Diseases (except HIV/AIDS) (13348)
• Intensive Care and Critical Care Medicine (769)
• Medical Education (369)
• Medical Ethics (105)
• Nephrology (401)
• Neurology (3524)
• Nursing (199)
• Nutrition (529)
• Obstetrics and Gynecology (681)
• Occupational and Environmental Health (669)
• Oncology (1835)
• Ophthalmology (539)
• Orthopedics (221)
• Otolaryngology (287)
• Pain Medicine (234)
• Palliative Medicine (66)
• Pathology (447)
• Pediatrics (1038)
• Pharmacology and Therapeutics (426)
• Primary Care Research (424)
• Psychiatry and Clinical Psychology (3192)
• Public and Global Health (6185)
• Radiology and Imaging (1293)
• Rehabilitation Medicine and Physical Therapy (751)
• Respiratory Medicine (832)
• Rheumatology (380)
• Sexual and Reproductive Health (374)
• Sports Medicine (324)
• Surgery (406)
• Toxicology (50)
• Transplantation (172)
• Urology (147)