research paper summary table

Drafting a summary table

Contributor: Logan Miller

A summary table allows you to compare common research methods, findings, limitations, etc. You can order the entries in any way that you find useful; consider ordering your research alphabetically, by timeliness, or even by grouping similar study aims, models, or results.

Once compiled, you can use this table to compare studies side by side. Such comparison can help you see trends in findings, identify gaps in the research, and rank each study by relative strength. In short, it helps you organize information on a broad topic, which is a crucial first step in synthesizing that information within a research paper.

Summary areas might include

Authors / date : If a paper has numerous authors, consider the level of detail you require to identify a given study.

Aim of study / paper : What were the researchers hoping to learn? This section may include research questions or hypotheses.

Type of study / information : These might be systematic reviews, randomized controlled trials, etc. If you’re less familiar with what these designs entail, writing a short description can be useful.

Main findings / conclusions : The level of detail you employ will come down to necessity and experience, but in listing specific findings, you may see trends or discrepancies across studies.

Strengths / limitations : Strengths may include good research design or data-based conclusions. Remember, a study may mention its limitations explicitly, but many limitations require careful inquiry to uncover.

*Azzopardi, D., Patel, K., Jaunky, T., Santopietro, S., Camacho, O. M., McAughey, J., Gaça, M. (2016). Electronic cigarette aerosol induces significantly less cytotoxicity than tobacco smoke. Toxicology Mechanisms and Methods 26(6), 477-497, doi: 10.1080/15376516.2016.1217112

• Linguistics
• Composition Studies

Five tips for developing useful literature summary tables for writing review articles

• Evidence-Based Nursing 24(2)

• Memorial University of Newfoundland

• The University of Sheffield

Discover the world's research

• 25+ million members
• 160+ million publication pages
• 2.3+ billion citations
• Heart Lung Circ

• Alyne Santos Borges
• Paola Pugian Jardim

• Pearse McCusker

• Hamzah Shahid Rafiq

• Creativ Nurs

• Richard Booth

• Bethany Jackson
• Esther Weir
• Jonathan Mead

• Maryanna Cruz da Costa e Silva Andrade
• Juliana de Melo Vellozo Pereira Tinoco
• Isabelle Andrade Silveira

• Recruit researchers
• Join for free
• Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

Nursing and Allied Health: Building a Summary Table or Synthesis Matrix

• Nursing Library Services
• Library Support for Nursing Accreditation
• Academic Research Libraries (ACRL) Information Literacy Standards for Science
• ACRL Guidelines for Distance Learning
• AACN Resources: Information Literacy
• The Essentials: Core Competencies for Professional Nursing Education
• Accreditation Commision for Education
• ACEN Learning Resources | Definitions & Standards
• Tutoring & Paper Review: College of Nursing & Allied Health Students
• Technology and Collaboration
• Affordable Learning Louisiana
• NIH Virtual Reality Funding
• Assistive Technology Resources
• Web Accessibility Initiative WC3
• Healthcare Links for Persons With Disabilities
• Accessibility
• Accessibility Tools: Videos
• Braile Institute: Blind and Low Vision Web Accessibility
• Braile Institute: Assistive Technology for the Visually Impaired This link opens in a new window
• Mental Health Resources for Students & Faculty
• Student Activities & Organizations
• Anatomage FAQ's
• APA Reference Worksheet With Examples This link opens in a new window
• APA Style and Grammar Guidelines, 7.0
• What's New in APA Guide, 7.0 This link opens in a new window
• APA Instructional Aids for Professors/Instructors
• APA Handouts & Guides This link opens in a new window
• Sample Papers for Students and Instructors
• Academic Writer Tutorial: Basics This link opens in a new window
• APA Styling Your Paper
• When to cite or not cite a database
• Video: A Step-By-Step Guide for APA Style Student Papers
• Video: Citing Works in Text Using APA 7.0 This link opens in a new window
• Video: Creating References Using APA Guide, 7.0 This link opens in a new window
• Journal Article Reporting Standards
• Digital Information Literacy
• Tips Sheet: Copyright Essentials for Higher Education This link opens in a new window
• Citing National Patient Safety Goals (Joint Commission)
• Citing Agency for Healthcare Research and Quality (AHRQ) in APA format
• Best Nursing Apps
• Writing an Abstract for Your PILT or Special Project
• PILT Poster Presentation Archive
• Academic Success
• Healthcare Career Salaries
• Industry Statistics: Healthcare
• Nursing Organizations
• Radiology Organizations
• Controlled Medical Vocabularies
• COVID-19 Current Vaccines (Medscape)
• COVID-19 Current and Candidate Vaccine Landscape and Tracker (WHO)
• COVID-19: Clinician Care Guidance (CDC.gov) This link opens in a new window
• COVID -19 Contract Tracing & Patient Privacy (Cornell) This link opens in a new window
• COVID-19: Coronavirus Dashboard (Johns Hopkins Epidemiology)
• COVID-19: Coronavirus Guidelines (Up-To-Date) This link opens in a new window
• COVID-19: Critical Care Evidence (Cochrane) This link opens in a new window
• COVID-19: Diagnosis & Treatment (JAMA) This link opens in a new window
• COVID-19: Free Video Access (Jove) This link opens in a new window
• COVID-19: Healthcare Hub (Elsevier) This link opens in a new window
• COVID-19: Keeping Up With A Moving Target (Johns Hopkins Nursing Videos)
• COVID-19: LitCovid Daily Update (NLM)
• COVID 19 - Long Term Health Effects Stemming From COVID-19
• COVID-19: Louisiana Department of Health
• COVID-19: Novel Coronavirus Information Center (Elsevier) This link opens in a new window
• COVID-19 Nursing Resources (Medscape)
• COVID-19: Red Book - Recent Pediatric Updates (AAP)
• COVID-19: Washing Your Hands Thoroughly (NHS)
• COVID-19: Well-Being Initiative (ANF)
• Properly Putting On Your Facemask & Getting a Good Seal (Dr. Scheiner) This link opens in a new window
• Creating Personal Accounts
• Creating a CINAHL MyFolder Account
• Creating a PubMed | MyNCBI Personal Account
• Creating a ProQuest Nursing & Allied Health Premium | MyResearch Folder
• Creating an OVID MyWorkspace Personal Account
• Mobile APPS | CINAHL for Apple and Android Mobile Devices
• My Circulation Login
• Interlibrary Loan Personal Account
• Data Visualization Products
• International Classification of Diseases (ICD)
• Diagnostic and Statistical Manual of Mental Disorders | DSM-5-TR
• [C1] Infections | Infectious Diseases
• [C04] Neoplasms
• [C05] Musculoskeletal Diseases
• [C06] Digestive System Diseases
• [C07] Stomatognathic Diseases
• [C08] Respiratory Tract Diseases
• [C09] Otorhinolaryngologic Diseases
• [C10] Nervous System Diseases
• [C11] Eye Diseases
• [C12] Urogenital Diseases
• [C14] Cardiovascular Diseases
• [C15] Hemic and Lymphatic Diseases
• [C16] Congenital, Hereditary, and Neonatal Diseases and Abnormalities
• [C17] Skin and Connective Tissue Diseases
• [C18] Nutritional and Metabolic Diseases
• [C19] Endocrine System Diseases
• [C20] Immune System Diseases
• [C21] Disorders of Environmental Origin
• [C22] Animal Diseases [Zoonotic diseases]
• [C23] Pathological Conditions, Signs and Symptoms
• [C24] Occupational Diseases
• [C25] Chemically-Induced Disorders
• [C26] Wounds and Injuries
• WHO Drug Information [Relative to Diseases]
• NDDK Patient Education Tool Kit
• Clinical Tools & Patient Education
• NDDK Resources on Medline Plus
• NDDK Open Research
• Dietary Guidelines for Americans
• Physical Activity Guidelines for Americans
• Move Your Way Community Resources
• National Youth Sports Strategy
• President’s Council on Sports, Fitness & Nutrition
• White House Conference on Hunger, Nutrition, and Health
• Equitable Long-Term Recovery and Resilience
• National Health Observances
• Finding Clinical Trials
• NIH News in Health
• Dosage Calculations & Pharmacology
• PICO - EBM Video This link opens in a new window
• PICO Slides
• Fillable CONSAH Pico Form
• Evidence Based Practice for Nursing
• Evidence-Based Nursing: -Step 2
• Evidence Appraisal - Step 3
• Evidence Application - Step 4
• Outcome Evaluation - Step 5
• Evidence Translation - Step 6
• Google Advanced Search for EBM
• Nursing Research Methods
• Faculty Book Request
• Proctor Request Form
• Peer Reviewed Literature: Assessment Goals
• Full Text Finder
• EBSCO e-Books Nursing 2021
• EBSCO eBooks Anesthesia
• EBSCO eBooks Radiology Science & Allied Health
• EBSCO eBooks: Writing About Nursing and Allied Health
• Alzheimers and Dementia
• Statistics on Aging
• CDC Bibliography: Alzheimers & Aging This link opens in a new window
• Health Conditions
• Health Behaviors
• Populations
• Settings and Systems
• Social Determinants of Health
• ILL Interlibrary Loan
• Gestational Diabetes and Fast Foods (MeSH)
• Mobile Resources
• Nursing Theory
• Psychiatric Nursing Journals
• Display, sort and; navigate
• Similar articles
• Cite, save and share
• Citations in PubMed
• All About PubMed Filters
• PubMed Quick Tours and Tutorials
• Evidence Based Practice Tutorial (PubMed) This link opens in a new window
• Developing a Clinical Question This link opens in a new window
• Using PubMed to Find Relevant Articles This link opens in a new window
• Next Steps This link opens in a new window
• Scenario (practice) This link opens in a new window
• Radiology Books and e-Books
• History of Radiology & Radiography
• Radiology: Anatomage This link opens in a new window
• Radiology Anatomy Atlas Viewer
• Advanced Radiographic Research
• Diagnostic Imaging Selected Articles
• Faculty and Administrative Resources
• Radiology Tech and MRI Salaries (Bureau of Labor Statistics)
• Radiology Technician Demand by State
• Review Tools for Graduate Students
• Training & Videos
• Register for an Online Meeting
• Joining an Online Meeting
• Training Videos & Search Examples
• Training Survey
• Sources for Health Statistics
• Ebola and Infectious Diseases
• Nursing Sites
• Writing Research Papers

Building a Summary Table or Synthesis Matrix

Quick Links | Nursing & Allied Health

• Library Home
• Campus Computer Labs
• Circulation Policies
• Catalog Search (books/ebooks)
• Contact Your Librarian For Research Assistance             (link sends email)
• Database Directory >> Nursing & Allied Health
• Faculty Materials Request Form
• Holidays & University Closures
• Interlibrary Loan Request Form
• Journals Full Text Finder
• LibGuides (Online Help)
• Review My Paper**
• Shreveport Proctor Request Form
• Shreveport Main Phone:  (318) 677-3007
• Shreveport Librarian Phone:  (318) 677-3013
• Student Help Desk :  Phone: (318) 357-6696  [email protected]
• The 20-20-20 Rule
• Training Videos

** Submit your research paper for grammar review

   GOOGLE MAP  |  LINKED

• Simplifying Synthesis | Download the Article PDF Copy
• Writing a Literature Review and Using a Synthesis Matrix

What a Summary Table or Synthesis Matrix looks like

Use the "Literature Review Matrix Template" as a guideline to help you sort through your thoughts, note important points and think through the similarities and differences: 

You are organizing the review by ideas and not by sources .  The literature review is not just a summary of the already published works.  Your synthesis should show how various articles are linked. 

A summary table is also called a synthesis matrix.  The table helps you organize and compare information for your systematic review, scholarly report, dissertation or thesis

Synthesis Matrix.

A summary table is also called a synthesis matrix . A summary table helps you record the main points of each source and document how sources relate to each other. After summarizing and evaluating your sources, arrange them in a matrix to help you see how they relate to each other, and apply to each of your themes or variables.

Faculty who typically guide students find it challenging to help students learn how to synthesize material (Blondy, Blakesless, Scheffer, Rubenfeld, Cronin, & Luster-Turner, 2016; Kearney, 2015) .  Writers  can easily summarize material but seem to struggle to adequately synthesize knowledge about their topic and express that in their writing. So, whether you are writing a student papers, dissertations, or scholarly report it is necessary to learn a few tips and tricks to organize your ideas.

Building a summary table and developing solid synthesis skills is important for nurses, nurse practitioners, and allied health researchers.  Quality evidence-based practice initiatives and nursing care and medicine are based on understanding and evaluating the resources and research available, identifying gaps, and building a strong foundation for future work.

Good synthesis is about putting the data gathered, references read, and literature analyzed together in a new way that shows connections and relationships. ( Shellenbarger, 2016 ). The Merriam-Webster dictionary defines synthesis as something that is made by combining different things or the composition or combination of parts or elements so as to form a whole (Synthesis, n.d.).  

In other words, building a summary table or synthesis matrix  involves taking information from a variety of sources, evaluating that information and forming new ideas or insights in an original way.  This can be a new and potentially challenging experience for students and researchers who are used to just repeating what is already in the literature.

Visit Our Libraries

   Interlibrary Loan    |    Shreveport Education Center Library   |    Eugene P. Watson Memorial Library    |     NSU Leesville Library 

Cammie G. Henry Research Center    |   Prince Music Media Library

• << Previous: Best Nursing Apps
• Next: Writing an Abstract for Your PILT or Special Project >>
• Last Updated: Jul 29, 2024 2:38 PM
• URL: https://libguides.nsula.edu/NursingandAlliedHealth

How to Write a Research Paper Summary

One of the most important skills you can imbibe as an academician is to know how to summarize a research paper. During your academic journey, you may need to write a summary of findings in research quite often and for varied reasons – be it to write an introduction for a peer-reviewed publication , to submit a critical review, or to simply create a useful database for future referencing.

It can be quite challenging to effectively write a research paper summary for often complex work, which is where a pre-determined workflow can help you optimize the process. Investing time in developing this skill can also help you improve your scientific acumen, increasing your efficiency and productivity at work. This article illustrates some useful advice on how to write a research summary effectively. But, what is research summary in the first place?  

A research paper summary is a crisp, comprehensive overview of a research paper, which encapsulates the purpose, findings, methods, conclusions, and relevance of a study. A well-written research paper summary is an indicator of how well you have understood the author’s work. 

Table of Contents

Draft a research paper summary in minutes with paperpal. click here to start writing.

• 2. Invest enough time to understand the topic deeply 

Use Paperpal to summarize your research paper. Click here to get started!

• Mistakes to avoid while writing your research paper summary 

Let Paperpal do the heavy lifting. Click here to start writing your summary now!

Frequently asked questions (faq), how to write a research paper summary.

Writing a good research paper summary comes with practice and skill. Here is some useful advice on how to write a research paper summary effectively.  

1. Determine the focus of your summary

Before you begin to write a summary of research papers, determine the aim of your research paper summary. This will give you more clarity on how to summarize a research paper, including what to highlight and where to find the information you need, which accelerates the entire process. If you are aiming for the summary to be a supporting document or a proof of principle for your current research findings, then you can look for elements that are relevant to your work.

On the other hand, if your research summary is intended to be a critical review of the research article, you may need to use a completely different lens while reading the paper and conduct your own research regarding the accuracy of the data presented. Then again, if the research summary is intended to be a source of information for future referencing, you will likely have a different approach. This makes determining the focus of your summary a key step in the process of writing an effective research paper summary. 

2. Invest enough time to understand the topic deeply

In order to author an effective research paper summary, you need to dive into the topic of the research article. Begin by doing a quick scan for relevant information under each section of the paper. The abstract is a great starting point as it helps you to quickly identify the top highlights of the research article, speeding up the process of understanding the key findings in the paper. Be sure to do a careful read of the research paper, preparing notes that describe each section in your own words to put together a summary of research example or a first draft. This will save your time and energy in revisiting the paper to confirm relevant details and ease the entire process of writing a research paper summary.

When reading papers, be sure to acknowledge and ignore any pre-conceived notions that you might have regarding the research topic. This will not only help you understand the topic better but will also help you develop a more balanced perspective, ensuring that your research paper summary is devoid of any personal opinions or biases. 

3. Keep the summary crisp, brief and engaging

A research paper summary is usually intended to highlight and explain the key points of any study, saving the time required to read through the entire article. Thus, your primary goal while compiling the summary should be to keep it as brief, crisp and readable as possible. Usually, a short introduction followed by 1-2 paragraphs is adequate for an effective research article summary. Avoid going into too much technical detail while describing the main results and conclusions of the study. Rather focus on connecting the main findings of the study to the hypothesis , which can make the summary more engaging. For example, instead of simply reporting an original finding – “the graph showed a decrease in the mortality rates…”, you can say, “there was a decline in the number of deaths, as predicted by the authors while beginning the study…” or “there was a decline in the number of deaths, which came as a surprise to the authors as this was completely unexpected…”.

Unless you are writing a critical review of the research article, the language used in your research paper summaries should revolve around reporting the findings, not assessing them. On the other hand, if you intend to submit your summary as a critical review, make sure to provide sufficient external evidence to support your final analysis. Invest sufficient time in editing and proofreading your research paper summary thoroughly to ensure you’ve captured the findings accurately. You can also get an external opinion on the preliminary draft of the research paper summary from colleagues or peers who have not worked on the research topic. 

Mistakes to avoid while writing your research paper summary

Now that you’ve understood how to summarize a research paper, watch out for these red flags while writing your summary. 

• Not paying attention to the word limit and recommended format, especially while submitting a critical review 
• Evaluating the findings instead of maintaining an objective , unbiased view while reading the research paper 
• Skipping the essential editing step , which can help eliminate avoidable errors and ensure that the language does not misrepresent the findings 
• Plagiarism, it is critical to write in your own words or paraphrase appropriately when reporting the findings in your scientific article summary 

We hope the recommendations listed above will help answer the question of how to summarize a research paper and enable you to tackle the process effectively. 

Summarize your research paper with Paperpal

Paperpal, an AI academic writing assistant, is designed to support academics at every step of the academic writing process. Built on over two decades of experience helping researchers get published and trained on millions of published research articles, Paperpal offers human precision at machine speed. Paperpal Copilot, with advanced generative AI features, can help academics achieve 2x the writing in half the time, while transforming how they research and write.

How to summarize a research paper with Paperpal?

To generate your research paper summary, simply login to the platform and use the Paperpal Copilot Summary feature to create a flawless summary of your work. Here’s a step-by-step process to help you craft a summary in minutes:

• Paste relevant research articles to be summarized into Paperpal; the AI will scan each section and extract key information.
• In minutes, Paperpal will generate a comprehensive summary that showcases the main paper highlights while adhering to academic writing conventions.
• Check the content to polish and refine the language, ensure your own voice, and add citations or references as needed.

The abstract and research paper summary serve similar purposes but differ in scope, length, and placement. The abstract is a concise yet detailed overview of the research, placed at the beginning of a paper, with the aim of providing readers with a quick understanding of the paper’s content and to help them decide whether to read the full article. Usually limited to a few hundred words, it highlights the main objectives, methods, results, and conclusions of the study. On the other hand, a research paper summary provides a crisp account of the entire research paper. Its purpose is to provide a brief recap for readers who may want to quickly grasp the main points of the research without reading the entire paper in detail.

The structure of a research summary can vary depending on the specific requirements or guidelines provided by the target publication or institution. A typical research summary includes the following key sections: introduction (including the research question or objective), methodology (briefly describing the research design and methods), results (summarizing the key findings), discussion (highlighting the implications and significance of the findings), and conclusion (providing a summary of the main points and potential future directions).

The summary of a research paper is important because it provides a condensed overview of the study’s purpose, methods, results, and conclusions. It allows you to quickly grasp the main points and relevance of the research without having to read the entire paper. Research summaries can also be an invaluable way to communicate research findings to a broader audience, such as policymakers or the general public.

  When writing a research paper summary, it is crucial to avoid plagiarism by properly attributing the original authors’ work. To learn how to summarize a research paper while avoiding plagiarism, follow these critical guidelines: (1) Read the paper thoroughly to understand the main points and key findings. (2) Use your own words and sentence structures to restate the information, ensuring that the research paper summary reflects your understanding of the paper. (3) Clearly indicate when you are paraphrasing or quoting directly from the original paper by using appropriate citation styles. (4) Cite the original source for any specific ideas, concepts, or data that you include in your summary. (5) Review your summary to ensure it accurately represents the research paper while giving credit to the original authors.

Paperpal is a comprehensive AI writing toolkit that helps students and researchers achieve 2x the writing in half the time. It leverages 21+ years of STM experience and insights from millions of research articles to provide in-depth academic writing, language editing, and submission readiness support to help you write better, faster.  

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

Experience the future of academic writing – Sign up to Paperpal and start writing for free!  

Related Reads:

• 5 Reasons for Rejection After Peer Review
• Ethical Research Practices For Research with Human Subjects
• How to Write a Conclusion for Research Papers (with Examples)
• Publish or Perish – Understanding the Importance of Scholarly Publications in Academia

PhD Dissertation Outline: Creating a Roadmap to Success

How ai can improve the academic writing experience, you may also like, how to choose a dissertation topic, how to write an abstract in research papers..., how to write dissertation acknowledgements, how to write a high-quality conference paper, measuring academic success: definition & strategies for excellence, is it ethical to use ai-generated abstracts without..., what are journal guidelines on using generative ai..., should you use ai tools like chatgpt for..., 9 steps to publish a research paper, how to make translating academic papers less challenging.

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

Methodology

• How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

• Search for relevant literature
• Evaluate sources
• Identify themes, debates, and gaps
• Outline the structure
• Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

Instantly correct all language mistakes in your text

Upload your document to correct all your mistakes in minutes

Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

• Quick Run-through
• Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

• Demonstrate your familiarity with the topic and its scholarly context
• Develop a theoretical framework and methodology for your research
• Position your work in relation to other researchers and theorists
• Show how your research addresses a gap or contributes to a debate
• Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

• Academic style
• Vague sentences
• Style consistency

See an example

Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

• Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
• Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
• Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
• Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

• Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
• Body image, self-perception, self-esteem, mental health
• Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

• Your university’s library catalogue
• Google Scholar
• Project Muse (humanities and social sciences)
• Medline (life sciences and biomedicine)
• EconLit (economics)
• Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

• What question or problem is the author addressing?
• What are the key concepts and how are they defined?
• What are the key theories, models, and methods?
• Does the research use established frameworks or take an innovative approach?
• What are the results and conclusions of the study?
• How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
• What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

Prevent plagiarism. Run a free check.

To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

• Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
• Themes: what questions or concepts recur across the literature?
• Debates, conflicts and contradictions: where do sources disagree?
• Pivotal publications: are there any influential theories or studies that changed the direction of the field?
• Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

• Most research has focused on young women.
• There is an increasing interest in the visual aspects of social media.
• But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

• Look at what results have emerged in qualitative versus quantitative research
• Discuss how the topic has been approached by empirical versus theoretical scholarship
• Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

• Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically evaluate: mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

Scribbr slides are free to use, customize, and distribute for educational purposes.

Open Google Slides Download PowerPoint

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

There are several reasons to conduct a literature review at the beginning of a research project:

• To familiarize yourself with the current state of knowledge on your topic
• To ensure that you’re not just repeating what others have already done
• To identify gaps in knowledge and unresolved problems that your research can address
• To develop your theoretical framework and methodology
• To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your thesis or dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

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.

McCombes, S. (2023, September 11). How to Write a Literature Review | Guide, Examples, & Templates. Scribbr. Retrieved August 26, 2024, from https://www.scribbr.com/dissertation/literature-review/

Is this article helpful?

Shona McCombes

Other students also liked, what is a theoretical framework | guide to organizing, what is a research methodology | steps & tips, how to write a research proposal | examples & templates, "i thought ai proofreading was useless but..".

I've been using Scribbr for years now and I know it's a service that won't disappoint. It does a good job spotting mistakes”

Literature Review Basics

• What is a Literature Review?
• Synthesizing Research
• Using Research & Synthesis Tables
• Additional Resources

About the Research and Synthesis Tables

Research Tables and Synthesis Tables are useful tools for organizing and analyzing your research as you assemble your literature review. They represent two different parts of the review process: assembling relevant information and synthesizing it. Use a Research table to compile the main info you need about the items you find in your research -- it's a great thing to have on hand as you take notes on what you read! Then, once you've assembled your research, use the Synthesis table to start charting the similarities/differences and major themes among your collected items.

We've included an Excel file with templates for you to use below; the examples pictured on this page are snapshots from that file.

• Research and Synthesis Table Templates This Excel workbook includes simple templates for creating research tables and synthesis tables. Feel free to download and use!

Using the Research Table

This is an example of a  research table,  in which you provide a basic description of the most important features of the studies, articles, and other items you discover in your research. The table identifies each item according to its author/date of publication, its purpose or thesis, what type of work it is (systematic review, clinical trial, etc.), the level of evidence it represents (which tells you a lot about its impact on the field of study), and its major findings. Your job, when you assemble this information, is to develop a snapshot of what the research shows about the topic of your research question and assess its value (both for the purpose of your work and for general knowledge in the field).

Think of your work on the research table as the foundational step for your analysis of the literature, in which you assemble the information you'll be analyzing and lay the groundwork for thinking about what it means and how it can be used.

Using the Synthesis Table

This is an example of a  synthesis table  or  synthesis matrix , in which you organize and analyze your research by listing each source and indicating whether a given finding or result occurred in a particular study or article ( each row lists an individual source, and each finding has its own column, in which X = yes, blank = no). You can also add or alter the columns to look for shared study populations, sort by level of evidence or source type, etc. The key here is to use the table to provide a simple representation of what the research has found (or not found, as the case may be). Think of a synthesis table as a tool for making comparisons, identifying trends, and locating gaps in the literature.

How do I know which findings to use, or how many to include?  Your research question tells you which findings are of interest in your research, so work from your research question to decide what needs to go in each Finding header, and how many findings are necessary. The number is up to you; again, you can alter this table by adding or deleting columns to match what you're actually looking for in your analysis. You should also, of course, be guided by what's actually present in the material your research turns up!

• << Previous: Synthesizing Research
• Next: Additional Resources >>
• Last Updated: Sep 26, 2023 12:06 PM
• URL: https://usi.libguides.com/literature-review-basics

• All eBooks & Audiobooks
• Academic eBook Collection
• Home Grown eBook Collection
• Off-Campus Access
• Literature Resource Center
• Opposing Viewpoints
• ProQuest Central
• Course Guides
• Citing Sources
• Library Research
• Websites by Topic
• Book-a-Librarian
• Research Tutorials
• Use the Catalog
• Use Databases
• Use Films on Demand
• Use Home Grown eBooks
• Use NC LIVE
• Evaluating Sources
• Primary vs. Secondary
• Scholarly vs. Popular
• Make an Appointment
• Writing Tools
• Annotated Bibliographies
• Summaries, Reviews & Critiques
• Writing Center

Service Alert

Article Summaries, Reviews & Critiques

Writing an article summary.

• Writing an article REVIEW
• Writing an article CRITIQUE
• Citing Sources This link opens in a new window
• About RCC Library

Text: 336-308-8801

Email: [email protected]

Call: 336-633-0204

Schedule: Book-a-Librarian

Like us on Facebook

Links on this guide may go to external web sites not connected with Randolph Community College. Their inclusion is not an endorsement by Randolph Community College and the College is not responsible for the accuracy of their content or the security of their site.

When writing a summary, the goal is to compose a concise and objective overview of the original article. The summary should focus only on the article's main ideas and important details that support those ideas.

Guidelines for summarizing an article:

• State the main ideas.
• Identify the most important details that support the main ideas.
• Summarize in your own words.
• Do not copy phrases or sentences unless they are being used as direct quotations.
• Express the underlying meaning of the article, but do not critique or analyze.
• The summary should be about one third the length of the original article. 

Your summary should include:

• Give an overview of the article, including the title and the name of the author.
• Provide a thesis statement that states the main idea of the article.
• Use the body paragraphs to explain the supporting ideas of your thesis statement.
• One-paragraph summary - one sentence per supporting detail, providing 1-2 examples for each.
• Multi-paragraph summary - one paragraph per supporting detail, providing 2-3 examples for each.
• Start each paragraph with a topic sentence.
• Use transitional words and phrases to connect ideas.
• Summarize your thesis statement and the underlying meaning of the article.

 Adapted from "Guidelines for Using In-Text Citations in a Summary (or Research Paper)" by Christine Bauer-Ramazani, 2020

Additional Resources

All links open in a new window.

How to Write a Summary - Guide & Examples  (from Scribbr.com)

Writing a Summary  (from The University of Arizona Global Campus Writing Center)

• Next: Writing an article REVIEW >>
• Last Updated: Mar 15, 2024 9:32 AM
• URL: https://libguides.randolph.edu/summaries

Effective Use of Tables and Figures in Research Papers

Research papers are often based on copious amounts of data that can be summarized and easily read through tables and graphs. When writing a research paper , it is important for data to be presented to the reader in a visually appealing way. The data in figures and tables, however, should not be a repetition of the data found in the text. There are many ways of presenting data in tables and figures, governed by a few simple rules. An APA research paper and MLA research paper both require tables and figures, but the rules around them are different. When writing a research paper, the importance of tables and figures cannot be underestimated. How do you know if you need a table or figure? The rule of thumb is that if you cannot present your data in one or two sentences, then you need a table .

Using Tables

Tables are easily created using programs such as Excel. Tables and figures in scientific papers are wonderful ways of presenting data. Effective data presentation in research papers requires understanding your reader and the elements that comprise a table. Tables have several elements, including the legend, column titles, and body. As with academic writing, it is also just as important to structure tables so that readers can easily understand them. Tables that are disorganized or otherwise confusing will make the reader lose interest in your work.

• Title: Tables should have a clear, descriptive title, which functions as the “topic sentence” of the table. The titles can be lengthy or short, depending on the discipline.
• Column Titles: The goal of these title headings is to simplify the table. The reader’s attention moves from the title to the column title sequentially. A good set of column titles will allow the reader to quickly grasp what the table is about.
• Table Body: This is the main area of the table where numerical or textual data is located. Construct your table so that elements read from up to down, and not across.

Related: Done organizing your research data effectively in tables? Check out this post on tips for citing tables in your manuscript now!

The placement of figures and tables should be at the center of the page. It should be properly referenced and ordered in the number that it appears in the text. In addition, tables should be set apart from the text. Text wrapping should not be used. Sometimes, tables and figures are presented after the references in selected journals.

Using Figures

Figures can take many forms, such as bar graphs, frequency histograms, scatterplots, drawings, maps, etc. When using figures in a research paper, always think of your reader. What is the easiest figure for your reader to understand? How can you present the data in the simplest and most effective way? For instance, a photograph may be the best choice if you want your reader to understand spatial relationships.

• Figure Captions: Figures should be numbered and have descriptive titles or captions. The captions should be succinct enough to understand at the first glance. Captions are placed under the figure and are left justified.
• Image: Choose an image that is simple and easily understandable. Consider the size, resolution, and the image’s overall visual attractiveness.
• Additional Information: Illustrations in manuscripts are numbered separately from tables. Include any information that the reader needs to understand your figure, such as legends.

Common Errors in Research Papers

Effective data presentation in research papers requires understanding the common errors that make data presentation ineffective. These common mistakes include using the wrong type of figure for the data. For instance, using a scatterplot instead of a bar graph for showing levels of hydration is a mistake. Another common mistake is that some authors tend to italicize the table number. Remember, only the table title should be italicized .  Another common mistake is failing to attribute the table. If the table/figure is from another source, simply put “ Note. Adapted from…” underneath the table. This should help avoid any issues with plagiarism.

Using tables and figures in research papers is essential for the paper’s readability. The reader is given a chance to understand data through visual content. When writing a research paper, these elements should be considered as part of good research writing. APA research papers, MLA research papers, and other manuscripts require visual content if the data is too complex or voluminous. The importance of tables and graphs is underscored by the main purpose of writing, and that is to be understood.

Frequently Asked Questions

"Consider the following points when creating figures for research papers: Determine purpose: Clarify the message or information to be conveyed. Choose figure type: Select the appropriate type for data representation. Prepare and organize data: Collect and arrange accurate and relevant data. Select software: Use suitable software for figure creation and editing. Design figure: Focus on clarity, labeling, and visual elements. Create the figure: Plot data or generate the figure using the chosen software. Label and annotate: Clearly identify and explain all elements in the figure. Review and revise: Verify accuracy, coherence, and alignment with the paper. Format and export: Adjust format to meet publication guidelines and export as suitable file."

"To create tables for a research paper, follow these steps: 1) Determine the purpose and information to be conveyed. 2) Plan the layout, including rows, columns, and headings. 3) Use spreadsheet software like Excel to design and format the table. 4) Input accurate data into cells, aligning it logically. 5) Include column and row headers for context. 6) Format the table for readability using consistent styles. 7) Add a descriptive title and caption to summarize and provide context. 8) Number and reference the table in the paper. 9) Review and revise for accuracy and clarity before finalizing."

"Including figures in a research paper enhances clarity and visual appeal. Follow these steps: Determine the need for figures based on data trends or to explain complex processes. Choose the right type of figure, such as graphs, charts, or images, to convey your message effectively. Create or obtain the figure, properly citing the source if needed. Number and caption each figure, providing concise and informative descriptions. Place figures logically in the paper and reference them in the text. Format and label figures clearly for better understanding. Provide detailed figure captions to aid comprehension. Cite the source for non-original figures or images. Review and revise figures for accuracy and consistency."

"Research papers use various types of tables to present data: Descriptive tables: Summarize main data characteristics, often presenting demographic information. Frequency tables: Display distribution of categorical variables, showing counts or percentages in different categories. Cross-tabulation tables: Explore relationships between categorical variables by presenting joint frequencies or percentages. Summary statistics tables: Present key statistics (mean, standard deviation, etc.) for numerical variables. Comparative tables: Compare different groups or conditions, displaying key statistics side by side. Correlation or regression tables: Display results of statistical analyses, such as coefficients and p-values. Longitudinal or time-series tables: Show data collected over multiple time points with columns for periods and rows for variables/subjects. Data matrix tables: Present raw data or matrices, common in experimental psychology or biology. Label tables clearly, include titles, and use footnotes or captions for explanations."

Enago is a very useful site. It covers nearly all topics of research writing and publishing in a simple, clear, attractive way. Though I’m a journal editor having much knowledge and training in these issues, I always find something new in this site. Thank you

“Thank You, your contents really help me :)”

Rate this article Cancel Reply

Your email address will not be published.

Enago Academy's Most Popular Articles

• Reporting Research

Explanatory & Response Variable in Statistics — A quick guide for early career researchers!

Often researchers have a difficult time choosing the parameters and variables (like explanatory and response…

• Manuscript Preparation
• Publishing Research

How to Use Creative Data Visualization Techniques for Easy Comprehension of Qualitative Research

“A picture is worth a thousand words!”—an adage used so often stands true even whilst…

• Figures & Tables

Effective Use of Statistics in Research – Methods and Tools for Data Analysis

Remember that impending feeling you get when you are asked to analyze your data! Now…

• Old Webinars
• Webinar Mobile App

SCI中稿技巧: 提升研究数据的说服力

如何寻找原创研究课题 快速定位目标文献的有效搜索策略 如何根据期刊指南准备手稿的对应部分 论文手稿语言润色实用技巧分享，快速提高论文质量

Distill: A Journal With Interactive Images for Machine Learning Research

Research is a wide and extensive field of study. This field has welcomed a plethora…

Explanatory & Response Variable in Statistics — A quick guide for early career…

How to Create and Use Gantt Charts

Sign-up to read more

Subscribe for free to get unrestricted access to all our resources on research writing and academic publishing including:

• 2000+ blog articles
• 50+ Webinars
• 10+ Expert podcasts
• 50+ Infographics
• 10+ Checklists
• Research Guides

We hate spam too. We promise to protect your privacy and never spam you.

• Industry News
• AI in Academia
• Promoting Research
• Career Corner
• Diversity and Inclusion
• Infographics
• Expert Video Library
• Other Resources
• Enago Learn
• Upcoming & On-Demand Webinars
• Peer Review Week 2024
• Open Access Week 2023
• Conference Videos
• Enago Report
• Journal Finder
• Enago Plagiarism & AI Grammar Check
• Editing Services
• Publication Support Services
• Research Impact
• Translation Services
• Publication solutions
• AI-Based Solutions
• Thought Leadership
• Call for Articles
• Call for Speakers
• Author Training
• Edit Profile

I am looking for Editing/ Proofreading services for my manuscript Tentative date of next journal submission:

In your opinion, what is the most effective way to improve integrity in the peer review process?

• Privacy Policy

Home » Tables in Research Paper – Types, Creating Guide and Examples

Tables in Research Paper – Types, Creating Guide and Examples

Table of Contents

Tables in Research Paper

Definition:

In Research Papers , Tables are a way of presenting data and information in a structured format. Tables can be used to summarize large amounts of data or to highlight important findings. They are often used in scientific or technical papers to display experimental results, statistical analyses, or other quantitative information.

Importance of Tables in Research Paper

Tables are an important component of a research paper as they provide a clear and concise presentation of data, statistics, and other information that support the research findings . Here are some reasons why tables are important in a research paper:

• Visual Representation : Tables provide a visual representation of data that is easy to understand and interpret. They help readers to quickly grasp the main points of the research findings and draw their own conclusions.
• Organize Data : Tables help to organize large amounts of data in a systematic and structured manner. This makes it easier for readers to identify patterns and trends in the data.
• Clarity and Accuracy : Tables allow researchers to present data in a clear and accurate manner. They can include precise numbers, percentages, and other information that may be difficult to convey in written form.
• Comparison: Tables allow for easy comparison between different data sets or groups. This makes it easier to identify similarities and differences, and to draw meaningful conclusions from the data.
• Efficiency: Tables allow for a more efficient use of space in the research paper. They can convey a large amount of information in a compact and concise format, which saves space and makes the research paper more readable.

Types of Tables in Research Paper

Most common Types of Tables in Research Paper are as follows:

• Descriptive tables : These tables provide a summary of the data collected in the study. They are usually used to present basic descriptive statistics such as means, medians, standard deviations, and frequencies.
• Comparative tables : These tables are used to compare the results of different groups or variables. They may be used to show the differences between two or more groups or to compare the results of different variables.
• Correlation tables: These tables are used to show the relationships between variables. They may show the correlation coefficients between variables, or they may show the results of regression analyses.
• Longitudinal tables : These tables are used to show changes in variables over time. They may show the results of repeated measures analyses or longitudinal regression analyses.
• Qualitative tables: These tables are used to summarize qualitative data such as interview transcripts or open-ended survey responses. They may present themes or categories that emerged from the data.

How to Create Tables in Research Paper

Here are the steps to create tables in a research paper:

• Plan your table: Determine the purpose of the table and the type of information you want to include. Consider the layout and format that will best convey your information.
• Choose a table format : Decide on the type of table you want to create. Common table formats include basic tables, summary tables, comparison tables, and correlation tables.
• Choose a software program : Use a spreadsheet program like Microsoft Excel or Google Sheets to create your table. These programs allow you to easily enter and manipulate data, format the table, and export it for use in your research paper.
• Input data: Enter your data into the spreadsheet program. Make sure to label each row and column clearly.
• Format the table : Apply formatting options such as font, font size, font color, cell borders, and shading to make your table more visually appealing and easier to read.
• Insert the table into your paper: Copy and paste the table into your research paper. Make sure to place the table in the appropriate location and refer to it in the text of your paper.
• Label the table: Give the table a descriptive title that clearly and accurately summarizes the contents of the table. Also, include a number and a caption that explains the table in more detail.
• Check for accuracy: Review the table for accuracy and make any necessary changes before submitting your research paper.

Examples of Tables in Research Paper

Examples of Tables in the Research Paper are as follows:

Table 1: Demographic Characteristics of Study Participants

This table shows the demographic characteristics of 200 participants in a research study. The table includes information about age, gender, and education level. The mean age of the participants was 35.2 years with a standard deviation of 8.6 years, and the age range was between 21 and 57 years. The table also shows that 46% of the participants were male and 54% were female. In terms of education, 10% of the participants had less than a high school education, 30% were high school graduates, 35% had some college education, and 25% had a bachelor’s degree or higher.

Table 2: Summary of Key Findings

This table summarizes the key findings of a study comparing three different groups on a particular variable. The table shows the mean score, standard deviation, t-value, and p-value for each group. The asterisk next to the t-value for Group 1 indicates that the difference between Group 1 and the other groups was statistically significant at p < 0.01, while the differences between Group 2 and Group 3 were not statistically significant.

Purpose of Tables in Research Paper

The primary purposes of including tables in a research paper are:

• To present data: Tables are an effective way to present large amounts of data in a clear and organized manner. Researchers can use tables to present numerical data, survey results, or other types of data that are difficult to represent in text.
• To summarize data: Tables can be used to summarize large amounts of data into a concise and easy-to-read format. Researchers can use tables to summarize the key findings of their research, such as descriptive statistics or the results of regression analyses.
• To compare data : Tables can be used to compare data across different variables or groups. Researchers can use tables to compare the characteristics of different study populations or to compare the results of different studies on the same topic.
• To enhance the readability of the paper: Tables can help to break up long sections of text and make the paper more visually appealing. By presenting data in a table, researchers can help readers to quickly identify the most important information and understand the key findings of the study.

Advantages of Tables in Research Paper

Some of the advantages of using tables in research papers include:

• Clarity : Tables can present data in a way that is easy to read and understand. They can help readers to quickly and easily identify patterns, trends, and relationships in the data.
• Efficiency: Tables can save space and reduce the need for lengthy explanations or descriptions of the data in the main body of the paper. This can make the paper more concise and easier to read.
• Organization: Tables can help to organize large amounts of data in a logical and meaningful way. This can help to reduce confusion and make it easier for readers to navigate the data.
• Comparison : Tables can be useful for comparing data across different groups, variables, or time periods. This can help to highlight similarities, differences, and changes over time.
• Visualization : Tables can also be used to visually represent data, making it easier for readers to see patterns and trends. This can be particularly useful when the data is complex or difficult to understand.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

APA Research Paper Format – Example, Sample and...

Data Collection – Methods Types and Examples

Research Gap – Types, Examples and How to...

Data Verification – Process, Types and Examples

Data Interpretation – Process, Methods and...

Delimitations in Research – Types, Examples and...

Extract key information from research papers with our AI summarizer.

Get a snapshot of what matters – fast . Break down complex concepts into easy-to-read sections. Skim or dive deep with a clean reading experience.

Summarize, analyze, and organize your research in one place.

Features built for scholars like you, trusted by researchers and students around the world.

Summarize papers, PDFs, book chapters, online articles and more.

Easy import

Drag and drop files, enter the url of a page, paste a block of text, or use our browser extension.

Enhanced summary

Change the summary to suit your reading style. Choose from a bulleted list, one-liner and more.

Read the key points of a paper in seconds with confidence that everything you read comes from the original text.

Clean reading

Clutter free flashcards help you skim or diver deeper into the details and quickly jump between sections.

Highlighted key terms and findings. Let evidence-based statements guide you through the full text with confidence.

Summarize texts in any format

Scholarcy’s ai summarization tool is designed to generate accurate, reliable article summaries..

Our summarizer tool is trained to identify key terms, claims, and findings in academic papers. These insights are turned into digestible Summary Flashcards.

Scroll in the box below to see the magic ⤸

The knowledge extraction and summarization methods we use focus on accuracy. This ensures what you read is factually correct, and can always be traced back to the original source .

What students say

It would normally take me 15mins – 1 hour to skim read the article but with Scholarcy I can do that in 5 minutes.

Scholarcy makes my life easier because it pulls out important information in the summary flashcard.

Scholarcy is clear and easy to navigate. It helps speed up the process of reading and understating papers.

Join over 400,000 people already saving time.

From a to z with scholarcy, generate flashcard summaries. discover more aha moments. get to point quicker..

Understand complex research. Jump between key concepts and sections.   Highlight text. Take notes.

Build a library of knowledge. Recall important info with ease. Organize, search, sort, edit.

Bring it all together. Export Flashcards in a range of formats. Transfer Flashcards into other apps.

Apply what you’ve learned. Compile your highlights, notes, references. Write that magnum opus 🤌

Go beyond summaries

Get unlimited summaries, advanced research and analysis features, and your own personalised collection with Scholarcy Library!

With Scholarcy Library you can import unlimited documents and generate summaries for all your course materials or collection of research papers.

Scholarcy Library offers additional features including access to millions of academic research papers, customizable summaries, direct import from Zotero and more.

Scholarcy lets you build and organise your summaries into a handy library that you can access from anywhere. Export from a range of options, including one-click bibliographies and even a literature matrix.

Compare plans

Summarize 3 articles a day with our free summarizer tool, or upgrade to
Scholarcy Library to generate and save unlimited article summaries.

Import a range of file formats

Export flashcards (one at a time)

Everything in Free

Unlimited summarization

Generate enhanced summaries

Save your flashcards

Take notes, highlight and edit text

Organize flashcards into collections

Frequently Asked Questions

How do i use scholarcy, what if i’m having issues importing files, can scholarcy generate a plain language summary of the article, can scholarcy process any size document, how do i change the summary to get better results, what if i upload a paywalled article to scholarcy, is it violating copyright laws.

Jump to navigation

Cochrane Training

Chapter 14: completing ‘summary of findings’ tables and grading the certainty of the evidence.

Holger J Schünemann, Julian PT Higgins, Gunn E Vist, Paul Glasziou, Elie A Akl, Nicole Skoetz, Gordon H Guyatt; on behalf of the Cochrane GRADEing Methods Group (formerly Applicability and Recommendations Methods Group) and the Cochrane Statistical Methods Group

Key Points:

• A ‘Summary of findings’ table for a given comparison of interventions provides key information concerning the magnitudes of relative and absolute effects of the interventions examined, the amount of available evidence and the certainty (or quality) of available evidence.
• ‘Summary of findings’ tables include a row for each important outcome (up to a maximum of seven). Accepted formats of ‘Summary of findings’ tables and interactive ‘Summary of findings’ tables can be produced using GRADE’s software GRADEpro GDT.
• Cochrane has adopted the GRADE approach (Grading of Recommendations Assessment, Development and Evaluation) for assessing certainty (or quality) of a body of evidence.
• The GRADE approach specifies four levels of the certainty for a body of evidence for a given outcome: high, moderate, low and very low.
• GRADE assessments of certainty are determined through consideration of five domains: risk of bias, inconsistency, indirectness, imprecision and publication bias. For evidence from non-randomized studies and rarely randomized studies, assessments can then be upgraded through consideration of three further domains.

Cite this chapter as: Schünemann HJ, Higgins JPT, Vist GE, Glasziou P, Akl EA, Skoetz N, Guyatt GH. Chapter 14: Completing ‘Summary of findings’ tables and grading the certainty of the evidence. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.4 (updated August 2023). Cochrane, 2023. Available from www.training.cochrane.org/handbook .

14.1 ‘Summary of findings’ tables

14.1.1 introduction to ‘summary of findings’ tables.

‘Summary of findings’ tables present the main findings of a review in a transparent, structured and simple tabular format. In particular, they provide key information concerning the certainty or quality of evidence (i.e. the confidence or certainty in the range of an effect estimate or an association), the magnitude of effect of the interventions examined, and the sum of available data on the main outcomes. Cochrane Reviews should incorporate ‘Summary of findings’ tables during planning and publication, and should have at least one key ‘Summary of findings’ table representing the most important comparisons. Some reviews may include more than one ‘Summary of findings’ table, for example if the review addresses more than one major comparison, or includes substantially different populations that require separate tables (e.g. because the effects differ or it is important to show results separately). In the Cochrane Database of Systematic Reviews (CDSR),  all ‘Summary of findings’ tables for a review appear at the beginning, before the Background section.

14.1.2 Selecting outcomes for ‘Summary of findings’ tables

Planning for the ‘Summary of findings’ table starts early in the systematic review, with the selection of the outcomes to be included in: (i) the review; and (ii) the ‘Summary of findings’ table. This is a crucial step, and one that review authors need to address carefully.

To ensure production of optimally useful information, Cochrane Reviews begin by developing a review question and by listing all main outcomes that are important to patients and other decision makers (see Chapter 2 and Chapter 3 ). The GRADE approach to assessing the certainty of the evidence (see Section 14.2 ) defines and operationalizes a rating process that helps separate outcomes into those that are critical, important or not important for decision making. Consultation and feedback on the review protocol, including from consumers and other decision makers, can enhance this process.

Critical outcomes are likely to include clearly important endpoints; typical examples include mortality and major morbidity (such as strokes and myocardial infarction). However, they may also represent frequent minor and rare major side effects, symptoms, quality of life, burdens associated with treatment, and resource issues (costs). Burdens represent the impact of healthcare workload on patient function and well-being, and include the demands of adhering to an intervention that patients or caregivers (e.g. family) may dislike, such as having to undergo more frequent tests, or the restrictions on lifestyle that certain interventions require (Spencer-Bonilla et al 2017).

Frequently, when formulating questions that include all patient-important outcomes for decision making, review authors will confront reports of studies that have not included all these outcomes. This is particularly true for adverse outcomes. For instance, randomized trials might contribute evidence on intended effects, and on frequent, relatively minor side effects, but not report on rare adverse outcomes such as suicide attempts. Chapter 19 discusses strategies for addressing adverse effects. To obtain data for all important outcomes it may be necessary to examine the results of non-randomized studies (see Chapter 24 ). Cochrane, in collaboration with others, has developed guidance for review authors to support their decision about when to look for and include non-randomized studies (Schünemann et al 2013).

If a review includes only randomized trials, these trials may not address all important outcomes and it may therefore not be possible to address these outcomes within the constraints of the review. Review authors should acknowledge these limitations and make them transparent to readers. Review authors are encouraged to include non-randomized studies to examine rare or long-term adverse effects that may not adequately be studied in randomized trials. This raises the possibility that harm outcomes may come from studies in which participants differ from those in studies used in the analysis of benefit. Review authors will then need to consider how much such differences are likely to impact on the findings, and this will influence the certainty of evidence because of concerns about indirectness related to the population (see Section 14.2.2 ).

Non-randomized studies can provide important information not only when randomized trials do not report on an outcome or randomized trials suffer from indirectness, but also when the evidence from randomized trials is rated as very low and non-randomized studies provide evidence of higher certainty. Further discussion of these issues appears also in Chapter 24 .

14.1.3 General template for ‘Summary of findings’ tables

Several alternative standard versions of ‘Summary of findings’ tables have been developed to ensure consistency and ease of use across reviews, inclusion of the most important information needed by decision makers, and optimal presentation (see examples at Figures 14.1.a and 14.1.b ). These formats are supported by research that focused on improved understanding of the information they intend to convey (Carrasco-Labra et al 2016, Langendam et al 2016, Santesso et al 2016). They are available through GRADE’s official software package developed to support the GRADE approach: GRADEpro GDT (www.gradepro.org).

Standard Cochrane ‘Summary of findings’ tables include the following elements using one of the accepted formats. Further guidance on each of these is provided in Section 14.1.6 .

• A brief description of the population and setting addressed by the available evidence (which may be slightly different to or narrower than those defined by the review question).
• A brief description of the comparison addressed in the ‘Summary of findings’ table, including both the experimental and comparison interventions.
• A list of the most critical and/or important health outcomes, both desirable and undesirable, limited to seven or fewer outcomes.
• A measure of the typical burden of each outcomes (e.g. illustrative risk, or illustrative mean, on comparator intervention).
• The absolute and relative magnitude of effect measured for each (if both are appropriate).
• The numbers of participants and studies contributing to the analysis of each outcomes.
• A GRADE assessment of the overall certainty of the body of evidence for each outcome (which may vary by outcome).
• Space for comments.
• Explanations (formerly known as footnotes).

Ideally, ‘Summary of findings’ tables are supported by more detailed tables (known as ‘evidence profiles’) to which the review may be linked, which provide more detailed explanations. Evidence profiles include the same important health outcomes, and provide greater detail than ‘Summary of findings’ tables of both of the individual considerations feeding into the grading of certainty and of the results of the studies (Guyatt et al 2011a). They ensure that a structured approach is used to rating the certainty of evidence. Although they are rarely published in Cochrane Reviews, evidence profiles are often used, for example, by guideline developers in considering the certainty of the evidence to support guideline recommendations. Review authors will find it easier to develop the ‘Summary of findings’ table by completing the rating of the certainty of evidence in the evidence profile first in GRADEpro GDT. They can then automatically convert this to one of the ‘Summary of findings’ formats in GRADEpro GDT, including an interactive ‘Summary of findings’ for publication.

As a measure of the magnitude of effect for dichotomous outcomes, the ‘Summary of findings’ table should provide a relative measure of effect (e.g. risk ratio, odds ratio, hazard) and measures of absolute risk. For other types of data, an absolute measure alone (such as a difference in means for continuous data) might be sufficient. It is important that the magnitude of effect is presented in a meaningful way, which may require some transformation of the result of a meta-analysis (see also Chapter 15, Section 15.4 and Section 15.5 ). Reviews with more than one main comparison should include a separate ‘Summary of findings’ table for each comparison.

Figure 14.1.a provides an example of a ‘Summary of findings’ table. Figure 15.1.b  provides an alternative format that may further facilitate users’ understanding and interpretation of the review’s findings. Evidence evaluating different formats suggests that the ‘Summary of findings’ table should include a risk difference as a measure of the absolute effect and authors should preferably use a format that includes a risk difference .

A detailed description of the contents of a ‘Summary of findings’ table appears in Section 14.1.6 .

Figure 14.1.a Example of a ‘Summary of findings’ table

Summary of findings (for interactive version click here )

a All the stockings in the nine studies included in this review were below-knee compression stockings. In four studies the compression strength was 20 mmHg to 30 mmHg at the ankle. It was 10 mmHg to 20 mmHg in the other four studies. Stockings come in different sizes. If a stocking is too tight around the knee it can prevent essential venous return causing the blood to pool around the knee. Compression stockings should be fitted properly. A stocking that is too tight could cut into the skin on a long flight and potentially cause ulceration and increased risk of DVT. Some stockings can be slightly thicker than normal leg covering and can be potentially restrictive with tight foot wear. It is a good idea to wear stockings around the house prior to travel to ensure a good, comfortable fit. Participants put their stockings on two to three hours before the flight in most of the studies. The availability and cost of stockings can vary.

b Two studies recruited high risk participants defined as those with previous episodes of DVT, coagulation disorders, severe obesity, limited mobility due to bone or joint problems, neoplastic disease within the previous two years, large varicose veins or, in one of the studies, participants taller than 190 cm and heavier than 90 kg. The incidence for the seven studies that excluded high risk participants was 1.45% and the incidence for the two studies that recruited high-risk participants (with at least one risk factor) was 2.43%. We have used 10 and 30 per 1000 to express different risk strata, respectively.

c The confidence interval crosses no difference and does not rule out a small increase.

d The measurement of oedema was not validated (indirectness of the outcome) or blinded to the intervention (risk of bias).

e If there are very few or no events and the number of participants is large, judgement about the certainty of evidence (particularly judgements about imprecision) may be based on the absolute effect. Here the certainty rating may be considered ‘high’ if the outcome was appropriately assessed and the event, in fact, did not occur in 2821 studied participants.

f None of the other studies reported adverse effects, apart from four cases of superficial vein thrombosis in varicose veins in the knee region that were compressed by the upper edge of the stocking in one study.

Figure 14.1.b Example of alternative ‘Summary of findings’ table

14.1.4 Producing ‘Summary of findings’ tables

The GRADE Working Group’s software, GRADEpro GDT ( www.gradepro.org ), including GRADE’s interactive handbook, is available to assist review authors in the preparation of ‘Summary of findings’ tables. GRADEpro can use data on the comparator group risk and the effect estimate (entered by the review authors or imported from files generated in RevMan) to produce the relative effects and absolute risks associated with experimental interventions. In addition, it leads the user through the process of a GRADE assessment, and produces a table that can be used as a standalone table in a review (including by direct import into software such as RevMan or integration with RevMan Web), or an interactive ‘Summary of findings’ table (see help resources in GRADEpro).

14.1.5 Statistical considerations in ‘Summary of findings’ tables

14.1.5.1 dichotomous outcomes.

‘Summary of findings’ tables should include both absolute and relative measures of effect for dichotomous outcomes. Risk ratios, odds ratios and risk differences are different ways of comparing two groups with dichotomous outcome data (see Chapter 6, Section 6.4.1 ). Furthermore, there are two distinct risk ratios, depending on which event (e.g. ‘yes’ or ‘no’) is the focus of the analysis (see Chapter 6, Section 6.4.1.5 ). In the presence of a non-zero intervention effect, any variation across studies in the comparator group risks (i.e. variation in the risk of the event occurring without the intervention of interest, for example in different populations) makes it impossible for more than one of these measures to be truly the same in every study.

It has long been assumed in epidemiology that relative measures of effect are more consistent than absolute measures of effect from one scenario to another. There is empirical evidence to support this assumption (Engels et al 2000, Deeks and Altman 2001, Furukawa et al 2002). For this reason, meta-analyses should generally use either a risk ratio or an odds ratio as a measure of effect (see Chapter 10, Section 10.4.3 ). Correspondingly, a single estimate of relative effect is likely to be a more appropriate summary than a single estimate of absolute effect. If a relative effect is indeed consistent across studies, then different comparator group risks will have different implications for absolute benefit. For instance, if the risk ratio is consistently 0.75, then the experimental intervention would reduce a comparator group risk of 80% to 60% in the intervention group (an absolute risk reduction of 20 percentage points), but would also reduce a comparator group risk of 20% to 15% in the intervention group (an absolute risk reduction of 5 percentage points).

‘Summary of findings’ tables are built around the assumption of a consistent relative effect. It is therefore important to consider the implications of this effect for different comparator group risks (these can be derived or estimated from a number of sources, see Section 14.1.6.3 ), which may require an assessment of the certainty of evidence for prognostic evidence (Spencer et al 2012, Iorio et al 2015). For any comparator group risk, it is possible to estimate a corresponding intervention group risk (i.e. the absolute risk with the intervention) from the meta-analytic risk ratio or odds ratio. Note that the numbers provided in the ‘Corresponding risk’ column are specific to the ‘risks’ in the adjacent column.

For the meta-analytic risk ratio (RR) and assumed comparator risk (ACR) the corresponding intervention risk is obtained as:

As an example, in Figure 14.1.a , the meta-analytic risk ratio for symptomless deep vein thrombosis (DVT) is RR = 0.10 (95% CI 0.04 to 0.26). Assuming a comparator risk of ACR = 10 per 1000 = 0.01, we obtain:

For the meta-analytic odds ratio (OR) and assumed comparator risk, ACR, the corresponding intervention risk is obtained as:

Upper and lower confidence limits for the corresponding intervention risk are obtained by replacing RR or OR by their upper and lower confidence limits, respectively (e.g. replacing 0.10 with 0.04, then with 0.26, in the example). Such confidence intervals do not incorporate uncertainty in the assumed comparator risks.

When dealing with risk ratios, it is critical that the same definition of ‘event’ is used as was used for the meta-analysis. For example, if the meta-analysis focused on ‘death’ (as opposed to survival) as the event, then corresponding risks in the ‘Summary of findings’ table must also refer to ‘death’.

In (rare) circumstances in which there is clear rationale to assume a consistent risk difference in the meta-analysis, in principle it is possible to present this for relevant ‘assumed risks’ and their corresponding risks, and to present the corresponding (different) relative effects for each assumed risk.

The risk difference expresses the difference between the ACR and the corresponding intervention risk (or the difference between the experimental and the comparator intervention).

For the meta-analytic risk ratio (RR) and assumed comparator risk (ACR) the corresponding risk difference is obtained as (note that risks can also be expressed using percentage or percentage points):

As an example, in Figure 14.1.b the meta-analytic risk ratio is 0.41 (95% CI 0.29 to 0.55) for diarrhoea in children less than 5 years of age. Assuming a comparator group risk of 22.3% we obtain:

For the meta-analytic odds ratio (OR) and assumed comparator risk (ACR) the absolute risk difference is obtained as (percentage points):

Upper and lower confidence limits for the absolute risk difference are obtained by re-running the calculation above while replacing RR or OR by their upper and lower confidence limits, respectively (e.g. replacing 0.41 with 0.28, then with 0.55, in the example). Such confidence intervals do not incorporate uncertainty in the assumed comparator risks.

14.1.5.2 Time-to-event outcomes

Time-to-event outcomes measure whether and when a particular event (e.g. death) occurs (van Dalen et al 2007). The impact of the experimental intervention relative to the comparison group on time-to-event outcomes is usually measured using a hazard ratio (HR) (see Chapter 6, Section 6.8.1 ).

A hazard ratio expresses a relative effect estimate. It may be used in various ways to obtain absolute risks and other interpretable quantities for a specific population. Here we describe how to re-express hazard ratios in terms of: (i) absolute risk of event-free survival within a particular period of time; (ii) absolute risk of an event within a particular period of time; and (iii) median time to the event. All methods are built on an assumption of consistent relative effects (i.e. that the hazard ratio does not vary over time).

(i) Absolute risk of event-free survival within a particular period of time Event-free survival (e.g. overall survival) is commonly reported by individual studies. To obtain absolute effects for time-to-event outcomes measured as event-free survival, the summary HR can be used in conjunction with an assumed proportion of patients who are event-free in the comparator group (Tierney et al 2007). This proportion of patients will be specific to a period of time of observation. However, it is not strictly necessary to specify this period of time. For instance, a proportion of 50% of event-free patients might apply to patients with a high event rate observed over 1 year, or to patients with a low event rate observed over 2 years.

As an example, suppose the meta-analytic hazard ratio is 0.42 (95% CI 0.25 to 0.72). Assuming a comparator group risk of event-free survival (e.g. for overall survival people being alive) at 2 years of ACR = 900 per 1000 = 0.9 we obtain:

so that that 956 per 1000 people will be alive with the experimental intervention at 2 years. The derivation of the risk should be explained in a comment or footnote.

(ii) Absolute risk of an event within a particular period of time To obtain this absolute effect, again the summary HR can be used (Tierney et al 2007):

In the example, suppose we assume a comparator group risk of events (e.g. for mortality, people being dead) at 2 years of ACR = 100 per 1000 = 0.1. We obtain:

so that that 44 per 1000 people will be dead with the experimental intervention at 2 years.

(iii) Median time to the event Instead of absolute numbers, the time to the event in the intervention and comparison groups can be expressed as median survival time in months or years. To obtain median survival time the pooled HR can be applied to an assumed median survival time in the comparator group (Tierney et al 2007):

In the example, assuming a comparator group median survival time of 80 months, we obtain:

For all three of these options for re-expressing results of time-to-event analyses, upper and lower confidence limits for the corresponding intervention risk are obtained by replacing HR by its upper and lower confidence limits, respectively (e.g. replacing 0.42 with 0.25, then with 0.72, in the example). Again, as for dichotomous outcomes, such confidence intervals do not incorporate uncertainty in the assumed comparator group risks. This is of special concern for long-term survival with a low or moderate mortality rate and a corresponding high number of censored patients (i.e. a low number of patients under risk and a high censoring rate).

14.1.6 Detailed contents of a ‘Summary of findings’ table

14.1.6.1 table title and header.

The title of each ‘Summary of findings’ table should specify the healthcare question, framed in terms of the population and making it clear exactly what comparison of interventions are made. In Figure 14.1.a , the population is people taking long aeroplane flights, the intervention is compression stockings, and the control is no compression stockings.

The first rows of each ‘Summary of findings’ table should provide the following ‘header’ information:

Patients or population This further clarifies the population (and possibly the subpopulations) of interest and ideally the magnitude of risk of the most crucial adverse outcome at which an intervention is directed. For instance, people on a long-haul flight may be at different risks for DVT; those using selective serotonin reuptake inhibitors (SSRIs) might be at different risk for side effects; while those with atrial fibrillation may be at low (< 1%), moderate (1% to 4%) or high (> 4%) yearly risk of stroke.

Setting This should state any specific characteristics of the settings of the healthcare question that might limit the applicability of the summary of findings to other settings (e.g. primary care in Europe and North America).

Intervention The experimental intervention.

Comparison The comparator intervention (including no specific intervention).

14.1.6.2 Outcomes

The rows of a ‘Summary of findings’ table should include all desirable and undesirable health outcomes (listed in order of importance) that are essential for decision making, up to a maximum of seven outcomes. If there are more outcomes in the review, review authors will need to omit the less important outcomes from the table, and the decision selecting which outcomes are critical or important to the review should be made during protocol development (see Chapter 3 ). Review authors should provide time frames for the measurement of the outcomes (e.g. 90 days or 12 months) and the type of instrument scores (e.g. ranging from 0 to 100).

Note that review authors should include the pre-specified critical and important outcomes in the table whether data are available or not. However, they should be alert to the possibility that the importance of an outcome (e.g. a serious adverse effect) may only become known after the protocol was written or the analysis was carried out, and should take appropriate actions to include these in the ‘Summary of findings’ table.

The ‘Summary of findings’ table can include effects in subgroups of the population for different comparator risks and effect sizes separately. For instance, in Figure 14.1.b effects are presented for children younger and older than 5 years separately. Review authors may also opt to produce separate ‘Summary of findings’ tables for different populations.

Review authors should include serious adverse events, but it might be possible to combine minor adverse events as a single outcome, and describe this in an explanatory footnote (note that it is not appropriate to add events together unless they are independent, that is, a participant who has experienced one adverse event has an unaffected chance of experiencing the other adverse event).

Outcomes measured at multiple time points represent a particular problem. In general, to keep the table simple, review authors should present multiple time points only for outcomes critical to decision making, where either the result or the decision made are likely to vary over time. The remainder should be presented at a common time point where possible.

Review authors can present continuous outcome measures in the ‘Summary of findings’ table and should endeavour to make these interpretable to the target audience. This requires that the units are clear and readily interpretable, for example, days of pain, or frequency of headache, and the name and scale of any measurement tools used should be stated (e.g. a Visual Analogue Scale, ranging from 0 to 100). However, many measurement instruments are not readily interpretable by non-specialist clinicians or patients, for example, points on a Beck Depression Inventory or quality of life score. For these, a more interpretable presentation might involve converting a continuous to a dichotomous outcome, such as >50% improvement (see Chapter 15, Section 15.5 ).

14.1.6.3 Best estimate of risk with comparator intervention

Review authors should provide up to three typical risks for participants receiving the comparator intervention. For dichotomous outcomes, we recommend that these be presented in the form of the number of people experiencing the event per 100 or 1000 people (natural frequency) depending on the frequency of the outcome. For continuous outcomes, this would be stated as a mean or median value of the outcome measured.

Estimated or assumed comparator intervention risks could be based on assessments of typical risks in different patient groups derived from the review itself, individual representative studies in the review, or risks derived from a systematic review of prognosis studies or other sources of evidence which may in turn require an assessment of the certainty for the prognostic evidence (Spencer et al 2012, Iorio et al 2015). Ideally, risks would reflect groups that clinicians can easily identify on the basis of their presenting features.

An explanatory footnote should specify the source or rationale for each comparator group risk, including the time period to which it corresponds where appropriate. In Figure 14.1.a , clinicians can easily differentiate individuals with risk factors for deep venous thrombosis from those without. If there is known to be little variation in baseline risk then review authors may use the median comparator group risk across studies. If typical risks are not known, an option is to choose the risk from the included studies, providing the second highest for a high and the second lowest for a low risk population.

14.1.6.4 Risk with intervention

For dichotomous outcomes, review authors should provide a corresponding absolute risk for each comparator group risk, along with a confidence interval. This absolute risk with the (experimental) intervention will usually be derived from the meta-analysis result presented in the relative effect column (see Section 14.1.6.6 ). Formulae are provided in Section 14.1.5 . Review authors should present the absolute effect in the same format as the risks with comparator intervention (see Section 14.1.6.3 ), for example as the number of people experiencing the event per 1000 people.

For continuous outcomes, a difference in means or standardized difference in means should be presented with its confidence interval. These will typically be obtained directly from a meta-analysis. Explanatory text should be used to clarify the meaning, as in Figures 14.1.a and 14.1.b .

14.1.6.5 Risk difference

For dichotomous outcomes, the risk difference can be provided using one of the ‘Summary of findings’ table formats as an additional option (see Figure 14.1.b ). This risk difference expresses the difference between the experimental and comparator intervention and will usually be derived from the meta-analysis result presented in the relative effect column (see Section 14.1.6.6 ). Formulae are provided in Section 14.1.5 . Review authors should present the risk difference in the same format as assumed and corresponding risks with comparator intervention (see Section 14.1.6.3 ); for example, as the number of people experiencing the event per 1000 people or as percentage points if the assumed and corresponding risks are expressed in percentage.

For continuous outcomes, if the ‘Summary of findings’ table includes this option, the mean difference can be presented here and the ‘corresponding risk’ column left blank (see Figure 14.1.b ).

14.1.6.6 Relative effect (95% CI)

The relative effect will typically be a risk ratio or odds ratio (or occasionally a hazard ratio) with its accompanying 95% confidence interval, obtained from a meta-analysis performed on the basis of the same effect measure. Risk ratios and odds ratios are similar when the comparator intervention risks are low and effects are small, but may differ considerably when comparator group risks increase. The meta-analysis may involve an assumption of either fixed or random effects, depending on what the review authors consider appropriate, and implying that the relative effect is either an estimate of the effect of the intervention, or an estimate of the average effect of the intervention across studies, respectively.

14.1.6.7 Number of participants (studies)

This column should include the number of participants assessed in the included studies for each outcome and the corresponding number of studies that contributed these participants.

14.1.6.8 Certainty of the evidence (GRADE)

Review authors should comment on the certainty of the evidence (also known as quality of the body of evidence or confidence in the effect estimates). Review authors should use the specific evidence grading system developed by the GRADE Working Group (Atkins et al 2004, Guyatt et al 2008, Guyatt et al 2011a), which is described in detail in Section 14.2 . The GRADE approach categorizes the certainty in a body of evidence as ‘high’, ‘moderate’, ‘low’ or ‘very low’ by outcome. This is a result of judgement, but the judgement process operates within a transparent structure. As an example, the certainty would be ‘high’ if the summary were of several randomized trials with low risk of bias, but the rating of certainty becomes lower if there are concerns about risk of bias, inconsistency, indirectness, imprecision or publication bias. Judgements other than of ‘high’ certainty should be made transparent using explanatory footnotes or the ‘Comments’ column in the ‘Summary of findings’ table (see Section 14.1.6.10 ).

14.1.6.9 Comments

The aim of the ‘Comments’ field is to help interpret the information or data identified in the row. For example, this may be on the validity of the outcome measure or the presence of variables that are associated with the magnitude of effect. Important caveats about the results should be flagged here. Not all rows will need comments, and it is best to leave a blank if there is nothing warranting a comment.

14.1.6.10 Explanations

Detailed explanations should be included as footnotes to support the judgements in the ‘Summary of findings’ table, such as the overall GRADE assessment. The explanations should describe the rationale for important aspects of the content. Table 14.1.a lists guidance for useful explanations. Explanations should be concise, informative, relevant, easy to understand and accurate. If explanations cannot be sufficiently described in footnotes, review authors should provide further details of the issues in the Results and Discussion sections of the review.

Table 14.1.a Guidance for providing useful explanations in ‘Summary of findings’ (SoF) tables. Adapted from Santesso et al (2016)

14.2 Assessing the certainty or quality of a body of evidence

14.2.1 the grade approach.

The Grades of Recommendation, Assessment, Development and Evaluation Working Group (GRADE Working Group) has developed a system for grading the certainty of evidence (Schünemann et al 2003, Atkins et al 2004, Schünemann et al 2006, Guyatt et al 2008, Guyatt et al 2011a). Over 100 organizations including the World Health Organization (WHO), the American College of Physicians, the American Society of Hematology (ASH), the Canadian Agency for Drugs and Technology in Health (CADTH) and the National Institutes of Health and Clinical Excellence (NICE) in the UK have adopted the GRADE system ( www.gradeworkinggroup.org ).

Cochrane has also formally adopted this approach, and all Cochrane Reviews should use GRADE to evaluate the certainty of evidence for important outcomes (see MECIR Box 14.2.a ).

MECIR Box 14.2.a Relevant expectations for conduct of intervention reviews

For systematic reviews, the GRADE approach defines the certainty of a body of evidence as the extent to which one can be confident that an estimate of effect or association is close to the quantity of specific interest. Assessing the certainty of a body of evidence involves consideration of within- and across-study risk of bias (limitations in study design and execution or methodological quality), inconsistency (or heterogeneity), indirectness of evidence, imprecision of the effect estimates and risk of publication bias (see Section 14.2.2 ), as well as domains that may increase our confidence in the effect estimate (as described in Section 14.2.3 ). The GRADE system entails an assessment of the certainty of a body of evidence for each individual outcome. Judgements about the domains that determine the certainty of evidence should be described in the results or discussion section and as part of the ‘Summary of findings’ table.

The GRADE approach specifies four levels of certainty ( Figure 14.2.a ). For interventions, including diagnostic and other tests that are evaluated as interventions (Schünemann et al 2008b, Schünemann et al 2008a, Balshem et al 2011, Schünemann et al 2012), the starting point for rating the certainty of evidence is categorized into two types:

• randomized trials; and
• non-randomized studies of interventions (NRSI), including observational studies (including but not limited to cohort studies, and case-control studies, cross-sectional studies, case series and case reports, although not all of these designs are usually included in Cochrane Reviews).

There are many instances in which review authors rely on information from NRSI, in particular to evaluate potential harms (see Chapter 24 ). In addition, review authors can obtain relevant data from both randomized trials and NRSI, with each type of evidence complementing the other (Schünemann et al 2013).

In GRADE, a body of evidence from randomized trials begins with a high-certainty rating while a body of evidence from NRSI begins with a low-certainty rating. The lower rating with NRSI is the result of the potential bias induced by the lack of randomization (i.e. confounding and selection bias).

However, when using the new Risk Of Bias In Non-randomized Studies of Interventions (ROBINS-I) tool (Sterne et al 2016), an assessment tool that covers the risk of bias due to lack of randomization, all studies may start as high certainty of the evidence (Schünemann et al 2018). The approach of starting all study designs (including NRSI) as high certainty does not conflict with the initial GRADE approach of starting the rating of NRSI as low certainty evidence. This is because a body of evidence from NRSI should generally be downgraded by two levels due to the inherent risk of bias associated with the lack of randomization, namely confounding and selection bias. Not downgrading NRSI from high to low certainty needs transparent and detailed justification for what mitigates concerns about confounding and selection bias (Schünemann et al 2018). Very few examples of where not rating down by two levels is appropriate currently exist.

The highest certainty rating is a body of evidence when there are no concerns in any of the GRADE factors listed in Figure 14.2.a . Review authors often downgrade evidence to moderate, low or even very low certainty evidence, depending on the presence of the five factors in Figure 14.2.a . Usually, certainty rating will fall by one level for each factor, up to a maximum of three levels for all factors. If there are very severe problems for any one domain (e.g. when assessing risk of bias, all studies were unconcealed, unblinded and lost over 50% of their patients to follow-up), evidence may fall by two levels due to that factor alone. It is not possible to rate lower than ‘very low certainty’ evidence.

Review authors will generally grade evidence from sound non-randomized studies as low certainty, even if ROBINS-I is used. If, however, such studies yield large effects and there is no obvious bias explaining those effects, review authors may rate the evidence as moderate or – if the effect is large enough – even as high certainty ( Figure 14.2.a ). The very low certainty level is appropriate for, but is not limited to, studies with critical problems and unsystematic clinical observations (e.g. case series or case reports).

Figure 14.2.a Levels of the certainty of a body of evidence in the GRADE approach. *Upgrading criteria are usually applicable to non-randomized studies only (but exceptions exist).

14.2.2 Domains that can lead to decreasing the certainty level of a body of evidence   

We now describe in more detail the five reasons (or domains) for downgrading the certainty of a body of evidence for a specific outcome. In each case, if no reason is found for downgrading the evidence, it should be classified as 'no limitation or not serious' (not important enough to warrant downgrading). If a reason is found for downgrading the evidence, it should be classified as 'serious' (downgrading the certainty rating by one level) or 'very serious' (downgrading the certainty grade by two levels). For non-randomized studies assessed with ROBINS-I, rating down by three levels should be classified as 'extremely' serious.

(1) Risk of bias or limitations in the detailed design and implementation

Our confidence in an estimate of effect decreases if studies suffer from major limitations that are likely to result in a biased assessment of the intervention effect. For randomized trials, these methodological limitations include failure to generate a random sequence, lack of allocation sequence concealment, lack of blinding (particularly with subjective outcomes that are highly susceptible to biased assessment), a large loss to follow-up or selective reporting of outcomes. Chapter 8 provides a discussion of study-level assessments of risk of bias in the context of a Cochrane Review, and proposes an approach to assessing the risk of bias for an outcome across studies as ‘Low’ risk of bias, ‘Some concerns’ and ‘High’ risk of bias for randomized trials. Levels of ‘Low’. ‘Moderate’, ‘Serious’ and ‘Critical’ risk of bias arise for non-randomized studies assessed with ROBINS-I ( Chapter 25 ). These assessments should feed directly into this GRADE domain. In particular, ‘Low’ risk of bias would indicate ‘no limitation’; ‘Some concerns’ would indicate either ‘no limitation’ or ‘serious limitation’; and ‘High’ risk of bias would indicate either ‘serious limitation’ or ‘very serious limitation’. ‘Critical’ risk of bias on ROBINS-I would indicate extremely serious limitations in GRADE. Review authors should use their judgement to decide between alternative categories, depending on the likely magnitude of the potential biases.

Every study addressing a particular outcome will differ, to some degree, in the risk of bias. Review authors should make an overall judgement on whether the certainty of evidence for an outcome warrants downgrading on the basis of study limitations. The assessment of study limitations should apply to the studies contributing to the results in the ‘Summary of findings’ table, rather than to all studies that could potentially be included in the analysis. We have argued in Chapter 7, Section 7.6.2 , that the primary analysis should be restricted to studies at low (or low and unclear) risk of bias where possible.

Table 14.2.a presents the judgements that must be made in going from assessments of the risk of bias to judgements about study limitations for each outcome included in a ‘Summary of findings’ table. A rating of high certainty evidence can be achieved only when most evidence comes from studies that met the criteria for low risk of bias. For example, of the 22 studies addressing the impact of beta-blockers on mortality in patients with heart failure, most probably or certainly used concealed allocation of the sequence, all blinded at least some key groups and follow-up of randomized patients was almost complete (Brophy et al 2001). The certainty of evidence might be downgraded by one level when most of the evidence comes from individual studies either with a crucial limitation for one item, or with some limitations for multiple items. An example of very serious limitations, warranting downgrading by two levels, is provided by evidence on surgery versus conservative treatment in the management of patients with lumbar disc prolapse (Gibson and Waddell 2007). We are uncertain of the benefit of surgery in reducing symptoms after one year or longer, because the one study included in the analysis had inadequate concealment of the allocation sequence and the outcome was assessed using a crude rating by the surgeon without blinding.

(2) Unexplained heterogeneity or inconsistency of results

When studies yield widely differing estimates of effect (heterogeneity or variability in results), investigators should look for robust explanations for that heterogeneity. For instance, drugs may have larger relative effects in sicker populations or when given in larger doses. A detailed discussion of heterogeneity and its investigation is provided in Chapter 10, Section 10.10 and Section 10.11 . If an important modifier exists, with good evidence that important outcomes are different in different subgroups (which would ideally be pre-specified), then a separate ‘Summary of findings’ table may be considered for a separate population. For instance, a separate ‘Summary of findings’ table would be used for carotid endarterectomy in symptomatic patients with high grade stenosis (70% to 99%) in which the intervention is, in the hands of the right surgeons, beneficial, and another (if review authors considered it relevant) for asymptomatic patients with low grade stenosis (less than 30%) in which surgery appears harmful (Orrapin and Rerkasem 2017). When heterogeneity exists and affects the interpretation of results, but review authors are unable to identify a plausible explanation with the data available, the certainty of the evidence decreases.

(3) Indirectness of evidence

Two types of indirectness are relevant. First, a review comparing the effectiveness of alternative interventions (say A and B) may find that randomized trials are available, but they have compared A with placebo and B with placebo. Thus, the evidence is restricted to indirect comparisons between A and B. Where indirect comparisons are undertaken within a network meta-analysis context, GRADE for network meta-analysis should be used (see Chapter 11, Section 11.5 ).

Second, a review may find randomized trials that meet eligibility criteria but address a restricted version of the main review question in terms of population, intervention, comparator or outcomes. For example, suppose that in a review addressing an intervention for secondary prevention of coronary heart disease, most identified studies happened to be in people who also had diabetes. Then the evidence may be regarded as indirect in relation to the broader question of interest because the population is primarily related to people with diabetes. The opposite scenario can equally apply: a review addressing the effect of a preventive strategy for coronary heart disease in people with diabetes may consider studies in people without diabetes to provide relevant, albeit indirect, evidence. This would be particularly likely if investigators had conducted few if any randomized trials in the target population (e.g. people with diabetes). Other sources of indirectness may arise from interventions studied (e.g. if in all included studies a technical intervention was implemented by expert, highly trained specialists in specialist centres, then evidence on the effects of the intervention outside these centres may be indirect), comparators used (e.g. if the comparator groups received an intervention that is less effective than standard treatment in most settings) and outcomes assessed (e.g. indirectness due to surrogate outcomes when data on patient-important outcomes are not available, or when investigators seek data on quality of life but only symptoms are reported). Review authors should make judgements transparent when they believe downgrading is justified, based on differences in anticipated effects in the group of primary interest. Review authors may be aided and increase transparency of their judgements about indirectness if they use Table 14.2.b available in the GRADEpro GDT software (Schünemann et al 2013).

(4) Imprecision of results

When studies include few participants or few events, and thus have wide confidence intervals, review authors can lower their rating of the certainty of the evidence. The confidence intervals included in the ‘Summary of findings’ table will provide readers with information that allows them to make, to some extent, their own rating of precision. Review authors can use a calculation of the optimal information size (OIS) or review information size (RIS), similar to sample size calculations, to make judgements about imprecision (Guyatt et al 2011b, Schünemann 2016). The OIS or RIS is calculated on the basis of the number of participants required for an adequately powered individual study. If the 95% confidence interval excludes a risk ratio (RR) of 1.0, and the total number of events or patients exceeds the OIS criterion, precision is adequate. If the 95% CI includes appreciable benefit or harm (an RR of under 0.75 or over 1.25 is often suggested as a very rough guide) downgrading for imprecision may be appropriate even if OIS criteria are met (Guyatt et al 2011b, Schünemann 2016).

(5) High probability of publication bias

The certainty of evidence level may be downgraded if investigators fail to report studies on the basis of results (typically those that show no effect: publication bias) or outcomes (typically those that may be harmful or for which no effect was observed: selective outcome non-reporting bias). Selective reporting of outcomes from among multiple outcomes measured is assessed at the study level as part of the assessment of risk of bias (see Chapter 8, Section 8.7 ), so for the studies contributing to the outcome in the ‘Summary of findings’ table this is addressed by domain 1 above (limitations in the design and implementation). If a large number of studies included in the review do not contribute to an outcome, or if there is evidence of publication bias, the certainty of the evidence may be downgraded. Chapter 13 provides a detailed discussion of reporting biases, including publication bias, and how it may be tackled in a Cochrane Review. A prototypical situation that may elicit suspicion of publication bias is when published evidence includes a number of small studies, all of which are industry-funded (Bhandari et al 2004). For example, 14 studies of flavanoids in patients with haemorrhoids have shown apparent large benefits, but enrolled a total of only 1432 patients (i.e. each study enrolled relatively few patients) (Alonso-Coello et al 2006). The heavy involvement of sponsors in most of these studies raises questions of whether unpublished studies that suggest no benefit exist (publication bias).

A particular body of evidence can suffer from problems associated with more than one of the five factors listed here, and the greater the problems, the lower the certainty of evidence rating that should result. One could imagine a situation in which randomized trials were available, but all or virtually all of these limitations would be present, and in serious form. A very low certainty of evidence rating would result.

Table 14.2.a Further guidelines for domain 1 (of 5) in a GRADE assessment: going from assessments of risk of bias in studies to judgements about study limitations for main outcomes across studies

Table 14.2.b Judgements about indirectness by outcome (available in GRADEpro GDT)

Intervention:

Comparator:

Direct comparison:

Final judgement about indirectness across domains:

14.2.3 Domains that may lead to increasing the certainty level of a body of evidence

Although NRSI and downgraded randomized trials will generally yield a low rating for certainty of evidence, there will be unusual circumstances in which review authors could ‘upgrade’ such evidence to moderate or even high certainty ( Table 14.3.a ).

• Large effects On rare occasions when methodologically well-done observational studies yield large, consistent and precise estimates of the magnitude of an intervention effect, one may be particularly confident in the results. A large estimated effect (e.g. RR >2 or RR <0.5) in the absence of plausible confounders, or a very large effect (e.g. RR >5 or RR <0.2) in studies with no major threats to validity, might qualify for this. In these situations, while the NRSI may possibly have provided an over-estimate of the true effect, the weak study design may not explain all of the apparent observed benefit. Thus, despite reservations based on the observational study design, review authors are confident that the effect exists. The magnitude of the effect in these studies may move the assigned certainty of evidence from low to moderate (if the effect is large in the absence of other methodological limitations). For example, a meta-analysis of observational studies showed that bicycle helmets reduce the risk of head injuries in cyclists by a large margin (odds ratio (OR) 0.31, 95% CI 0.26 to 0.37) (Thompson et al 2000). This large effect, in the absence of obvious bias that could create the association, suggests a rating of moderate-certainty evidence.  Note : GRADE guidance suggests the possibility of rating up one level for a large effect if the relative effect is greater than 2.0. However, if the point estimate of the relative effect is greater than 2.0, but the confidence interval is appreciably below 2.0, then some hesitation would be appropriate in the decision to rate up for a large effect. Another situation allows inference of a strong association without a formal comparative study. Consider the question of the impact of routine colonoscopy versus no screening for colon cancer on the rate of perforation associated with colonoscopy. Here, a large series of representative patients undergoing colonoscopy may provide high certainty evidence about the risk of perforation associated with colonoscopy. When the risk of the event among patients receiving the relevant comparator is known to be near 0 (i.e. we are certain that the incidence of spontaneous colon perforation in patients not undergoing colonoscopy is extremely low), case series or cohort studies of representative patients can provide high certainty evidence of adverse effects associated with an intervention, thereby allowing us to infer a strong association from even a limited number of events.
• Dose-response The presence of a dose-response gradient may increase our confidence in the findings of observational studies and thereby enhance the assigned certainty of evidence. For example, our confidence in the result of observational studies that show an increased risk of bleeding in patients who have supratherapeutic anticoagulation levels is increased by the observation that there is a dose-response gradient between the length of time needed for blood to clot (as measured by the international normalized ratio (INR)) and an increased risk of bleeding (Levine et al 2004). A systematic review of NRSI investigating the effect of cyclooxygenase-2 inhibitors on cardiovascular events found that the summary estimate (RR) with rofecoxib was 1.33 (95% CI 1.00 to 1.79) with doses less than 25mg/d, and 2.19 (95% CI 1.64 to 2.91) with doses more than 25mg/d. Although residual confounding is likely to exist in the NRSI that address this issue, the existence of a dose-response gradient and the large apparent effect of higher doses of rofecoxib markedly increase our strength of inference that the association cannot be explained by residual confounding, and is therefore likely to be both causal and, at high levels of exposure, substantial.  Note : GRADE guidance suggests the possibility of rating up one level for a large effect if the relative effect is greater than 2.0. Here, the fact that the point estimate of the relative effect is greater than 2.0, but the confidence interval is appreciably below 2.0 might make some hesitate in the decision to rate up for a large effect
• Plausible confounding On occasion, all plausible biases from randomized or non-randomized studies may be working to under-estimate an apparent intervention effect. For example, if only sicker patients receive an experimental intervention or exposure, yet they still fare better, it is likely that the actual intervention or exposure effect is larger than the data suggest. For instance, a rigorous systematic review of observational studies including a total of 38 million patients demonstrated higher death rates in private for-profit versus private not-for-profit hospitals (Devereaux et al 2002). One possible bias relates to different disease severity in patients in the two hospital types. It is likely, however, that patients in the not-for-profit hospitals were sicker than those in the for-profit hospitals. Thus, to the extent that residual confounding existed, it would bias results against the not-for-profit hospitals. The second likely bias was the possibility that higher numbers of patients with excellent private insurance coverage could lead to a hospital having more resources and a spill-over effect that would benefit those without such coverage. Since for-profit hospitals are likely to admit a larger proportion of such well-insured patients than not-for-profit hospitals, the bias is once again against the not-for-profit hospitals. Since the plausible biases would all diminish the demonstrated intervention effect, one might consider the evidence from these observational studies as moderate rather than low certainty. A parallel situation exists when observational studies have failed to demonstrate an association, but all plausible biases would have increased an intervention effect. This situation will usually arise in the exploration of apparent harmful effects. For example, because the hypoglycaemic drug phenformin causes lactic acidosis, the related agent metformin was under suspicion for the same toxicity. Nevertheless, very large observational studies have failed to demonstrate an association (Salpeter et al 2007). Given the likelihood that clinicians would be more alert to lactic acidosis in the presence of the agent and over-report its occurrence, one might consider this moderate, or even high certainty, evidence refuting a causal relationship between typical therapeutic doses of metformin and lactic acidosis.

14.3 Describing the assessment of the certainty of a body of evidence using the GRADE framework

Review authors should report the grading of the certainty of evidence in the Results section for each outcome for which this has been performed, providing the rationale for downgrading or upgrading the evidence, and referring to the ‘Summary of findings’ table where applicable.

Table 14.3.a provides a framework and examples for how review authors can justify their judgements about the certainty of evidence in each domain. These justifications should also be included in explanatory notes to the ‘Summary of Findings’ table (see Section 14.1.6.10 ).

Chapter 15, Section 15.6 , describes in more detail how the overall GRADE assessment across all domains can be used to draw conclusions about the effects of the intervention, as well as providing implications for future research.

Table 14.3.a Framework for describing the certainty of evidence and justifying downgrading or upgrading

14.4 Chapter information

Authors: Holger J Schünemann, Julian PT Higgins, Gunn E Vist, Paul Glasziou, Elie A Akl, Nicole Skoetz, Gordon H Guyatt; on behalf of the Cochrane GRADEing Methods Group (formerly Applicability and Recommendations Methods Group) and the Cochrane Statistical Methods Group

Acknowledgements: Andrew D Oxman contributed to earlier versions. Professor Penny Hawe contributed to the text on adverse effects in earlier versions. Jon Deeks provided helpful contributions on an earlier version of this chapter. For details of previous authors and editors of the Handbook , please refer to the Preface.

Funding: This work was in part supported by funding from the Michael G DeGroote Cochrane Canada Centre and the Ontario Ministry of Health.

14.5 References

Alonso-Coello P, Zhou Q, Martinez-Zapata MJ, Mills E, Heels-Ansdell D, Johanson JF, Guyatt G. Meta-analysis of flavonoids for the treatment of haemorrhoids. British Journal of Surgery 2006; 93 : 909-920.

Atkins D, Best D, Briss PA, Eccles M, Falck-Ytter Y, Flottorp S, Guyatt GH, Harbour RT, Haugh MC, Henry D, Hill S, Jaeschke R, Leng G, Liberati A, Magrini N, Mason J, Middleton P, Mrukowicz J, O'Connell D, Oxman AD, Phillips B, Schünemann HJ, Edejer TT, Varonen H, Vist GE, Williams JW, Jr., Zaza S. Grading quality of evidence and strength of recommendations. BMJ 2004; 328 : 1490.

Balshem H, Helfand M, Schünemann HJ, Oxman AD, Kunz R, Brozek J, Vist GE, Falck-Ytter Y, Meerpohl J, Norris S, Guyatt GH. GRADE guidelines: 3. Rating the quality of evidence. Journal of Clinical Epidemiology 2011; 64 : 401-406.

Bhandari M, Busse JW, Jackowski D, Montori VM, Schünemann H, Sprague S, Mears D, Schemitsch EH, Heels-Ansdell D, Devereaux PJ. Association between industry funding and statistically significant pro-industry findings in medical and surgical randomized trials. Canadian Medical Association Journal 2004; 170 : 477-480.

Brophy JM, Joseph L, Rouleau JL. Beta-blockers in congestive heart failure. A Bayesian meta-analysis. Annals of Internal Medicine 2001; 134 : 550-560.

Carrasco-Labra A, Brignardello-Petersen R, Santesso N, Neumann I, Mustafa RA, Mbuagbaw L, Etxeandia Ikobaltzeta I, De Stio C, McCullagh LJ, Alonso-Coello P, Meerpohl JJ, Vandvik PO, Brozek JL, Akl EA, Bossuyt P, Churchill R, Glenton C, Rosenbaum S, Tugwell P, Welch V, Garner P, Guyatt G, Schünemann HJ. Improving GRADE evidence tables part 1: a randomized trial shows improved understanding of content in summary of findings tables with a new format. Journal of Clinical Epidemiology 2016; 74 : 7-18.

Deeks JJ, Altman DG. Effect measures for meta-analysis of trials with binary outcomes. In: Egger M, Davey Smith G, Altman DG, editors. Systematic Reviews in Health Care: Meta-analysis in Context . 2nd ed. London (UK): BMJ Publication Group; 2001. p. 313-335.

Devereaux PJ, Choi PT, Lacchetti C, Weaver B, Schünemann HJ, Haines T, Lavis JN, Grant BJ, Haslam DR, Bhandari M, Sullivan T, Cook DJ, Walter SD, Meade M, Khan H, Bhatnagar N, Guyatt GH. A systematic review and meta-analysis of studies comparing mortality rates of private for-profit and private not-for-profit hospitals. Canadian Medical Association Journal 2002; 166 : 1399-1406.

Engels EA, Schmid CH, Terrin N, Olkin I, Lau J. Heterogeneity and statistical significance in meta-analysis: an empirical study of 125 meta-analyses. Statistics in Medicine 2000; 19 : 1707-1728.

Furukawa TA, Guyatt GH, Griffith LE. Can we individualize the 'number needed to treat'? An empirical study of summary effect measures in meta-analyses. International Journal of Epidemiology 2002; 31 : 72-76.

Gibson JN, Waddell G. Surgical interventions for lumbar disc prolapse: updated Cochrane Review. Spine 2007; 32 : 1735-1747.

Guyatt G, Oxman A, Vist G, Kunz R, Falck-Ytter Y, Alonso-Coello P, Schünemann H. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ 2008; 336 : 3.

Guyatt G, Oxman AD, Akl EA, Kunz R, Vist G, Brozek J, Norris S, Falck-Ytter Y, Glasziou P, DeBeer H, Jaeschke R, Rind D, Meerpohl J, Dahm P, Schünemann HJ. GRADE guidelines: 1. Introduction-GRADE evidence profiles and summary of findings tables. Journal of Clinical Epidemiology 2011a; 64 : 383-394.

Guyatt GH, Oxman AD, Kunz R, Brozek J, Alonso-Coello P, Rind D, Devereaux PJ, Montori VM, Freyschuss B, Vist G, Jaeschke R, Williams JW, Jr., Murad MH, Sinclair D, Falck-Ytter Y, Meerpohl J, Whittington C, Thorlund K, Andrews J, Schünemann HJ. GRADE guidelines 6. Rating the quality of evidence--imprecision. Journal of Clinical Epidemiology 2011b; 64 : 1283-1293.

Iorio A, Spencer FA, Falavigna M, Alba C, Lang E, Burnand B, McGinn T, Hayden J, Williams K, Shea B, Wolff R, Kujpers T, Perel P, Vandvik PO, Glasziou P, Schünemann H, Guyatt G. Use of GRADE for assessment of evidence about prognosis: rating confidence in estimates of event rates in broad categories of patients. BMJ 2015; 350 : h870.

Langendam M, Carrasco-Labra A, Santesso N, Mustafa RA, Brignardello-Petersen R, Ventresca M, Heus P, Lasserson T, Moustgaard R, Brozek J, Schünemann HJ. Improving GRADE evidence tables part 2: a systematic survey of explanatory notes shows more guidance is needed. Journal of Clinical Epidemiology 2016; 74 : 19-27.

Levine MN, Raskob G, Landefeld S, Kearon C, Schulman S. Hemorrhagic complications of anticoagulant treatment: the Seventh ACCP Conference on Antithrombotic and Thrombolytic Therapy. Chest 2004; 126 : 287S-310S.

Orrapin S, Rerkasem K. Carotid endarterectomy for symptomatic carotid stenosis. Cochrane Database of Systematic Reviews 2017; 6 : CD001081.

Salpeter S, Greyber E, Pasternak G, Salpeter E. Risk of fatal and nonfatal lactic acidosis with metformin use in type 2 diabetes mellitus. Cochrane Database of Systematic Reviews 2007; 4 : CD002967.

Santesso N, Carrasco-Labra A, Langendam M, Brignardello-Petersen R, Mustafa RA, Heus P, Lasserson T, Opiyo N, Kunnamo I, Sinclair D, Garner P, Treweek S, Tovey D, Akl EA, Tugwell P, Brozek JL, Guyatt G, Schünemann HJ. Improving GRADE evidence tables part 3: detailed guidance for explanatory footnotes supports creating and understanding GRADE certainty in the evidence judgments. Journal of Clinical Epidemiology 2016; 74 : 28-39.

Schünemann HJ, Best D, Vist G, Oxman AD, Group GW. Letters, numbers, symbols and words: how to communicate grades of evidence and recommendations. Canadian Medical Association Journal 2003; 169 : 677-680.

Schünemann HJ, Jaeschke R, Cook DJ, Bria WF, El-Solh AA, Ernst A, Fahy BF, Gould MK, Horan KL, Krishnan JA, Manthous CA, Maurer JR, McNicholas WT, Oxman AD, Rubenfeld G, Turino GM, Guyatt G. An official ATS statement: grading the quality of evidence and strength of recommendations in ATS guidelines and recommendations. American Journal of Respiratory and Critical Care Medicine 2006; 174 : 605-614.

Schünemann HJ, Oxman AD, Brozek J, Glasziou P, Jaeschke R, Vist GE, Williams JW, Jr., Kunz R, Craig J, Montori VM, Bossuyt P, Guyatt GH. Grading quality of evidence and strength of recommendations for diagnostic tests and strategies. BMJ 2008a; 336 : 1106-1110.

Schünemann HJ, Oxman AD, Brozek J, Glasziou P, Bossuyt P, Chang S, Muti P, Jaeschke R, Guyatt GH. GRADE: assessing the quality of evidence for diagnostic recommendations. ACP Journal Club 2008b; 149 : 2.

Schünemann HJ, Mustafa R, Brozek J. [Diagnostic accuracy and linked evidence--testing the chain]. Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen 2012; 106 : 153-160.

Schünemann HJ, Tugwell P, Reeves BC, Akl EA, Santesso N, Spencer FA, Shea B, Wells G, Helfand M. Non-randomized studies as a source of complementary, sequential or replacement evidence for randomized controlled trials in systematic reviews on the effects of interventions. Research Synthesis Methods 2013; 4 : 49-62.

Schünemann HJ. Interpreting GRADE's levels of certainty or quality of the evidence: GRADE for statisticians, considering review information size or less emphasis on imprecision? Journal of Clinical Epidemiology 2016; 75 : 6-15.

Schünemann HJ, Cuello C, Akl EA, Mustafa RA, Meerpohl JJ, Thayer K, Morgan RL, Gartlehner G, Kunz R, Katikireddi SV, Sterne J, Higgins JPT, Guyatt G, Group GW. GRADE guidelines: 18. How ROBINS-I and other tools to assess risk of bias in nonrandomized studies should be used to rate the certainty of a body of evidence. Journal of Clinical Epidemiology 2018.

Spencer-Bonilla G, Quinones AR, Montori VM, International Minimally Disruptive Medicine W. Assessing the Burden of Treatment. Journal of General Internal Medicine 2017; 32 : 1141-1145.

Spencer FA, Iorio A, You J, Murad MH, Schünemann HJ, Vandvik PO, Crowther MA, Pottie K, Lang ES, Meerpohl JJ, Falck-Ytter Y, Alonso-Coello P, Guyatt GH. Uncertainties in baseline risk estimates and confidence in treatment effects. BMJ 2012; 345 : e7401.

Sterne JAC, Hernán MA, Reeves BC, Savović J, Berkman ND, Viswanathan M, Henry D, Altman DG, Ansari MT, Boutron I, Carpenter JR, Chan AW, Churchill R, Deeks JJ, Hróbjartsson A, Kirkham J, Jüni P, Loke YK, Pigott TD, Ramsay CR, Regidor D, Rothstein HR, Sandhu L, Santaguida PL, Schünemann HJ, Shea B, Shrier I, Tugwell P, Turner L, Valentine JC, Waddington H, Waters E, Wells GA, Whiting PF, Higgins JPT. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ 2016; 355 : i4919.

Thompson DC, Rivara FP, Thompson R. Helmets for preventing head and facial injuries in bicyclists. Cochrane Database of Systematic Reviews 2000; 2 : CD001855.

Tierney JF, Stewart LA, Ghersi D, Burdett S, Sydes MR. Practical methods for incorporating summary time-to-event data into meta-analysis. Trials 2007; 8 .

van Dalen EC, Tierney JF, Kremer LCM. Tips and tricks for understanding and using SR results. No. 7: time‐to‐event data. Evidence-Based Child Health 2007; 2 : 1089-1090.

For permission to re-use material from the Handbook (either academic or commercial), please see here for full details.

• Resources Home 🏠
• Try SciSpace Copilot
• Search research papers
• Add Copilot Extension
• Try AI Detector
• Try Paraphraser
• Try Citation Generator
• April Papers
• June Papers
• July Papers

Research paper summarizer | An overview of the best AI summarizers

Table of Contents

In scholarly publishing, keeping abreast of the latest research findings and breakthroughs is vital. However, with the ever-expanding scope of scientific knowledge, reading and understanding research article is becoming a hard and time-consuming task.

Plus, the prevalent use of acronyms, jargon, and complex terminologies in research papers is impeding scientific engagement. Therefore, affecting the researcher’s reading interest and perceived understanding of research articles.

In light of this, a recent study from Science Direct enunciated that “automatic summarization of scientific articles helps students speed up their investigation process”. And this underscores the importance of AI tools like research paper summarizers.

This article enunciates the role and advantages of AI summarizers aka ChatPDF tools in enhancing reading comprehension.

What is a Research Paper Summarizer?

Research paper summarizer is an AI-powered article summarizer tool designed to condense extensive academic papers into concise summaries.

These summaries capture the critical points, key findings, and main arguments of a research article and represent them in the most succinct way possible. As a result, researchers quickly grasp the scope of the research paper without spending much time.

What are the benefits of research paper summarizers?

AI summarizers or research paper summarizers are a revolutionary tool that is changing the conventional reading method of scholarly publishing. While the inception of research paper summarizers may seem like a radical shift. By embracing this technology aid, the academic community can manage the challenge of reading comprehension.

Here's where AI summarizers steps in:

Saves you plenty of time

Research paper summarizers offer a streamlined path to the key points, insights, and findings of a paper, saving researchers hours of reading and sifting through vast information.

Imagine the productivity boost when you can certainly review ten papers in the time it used to take to read just one.

Managing information overload

Research paper summarizers combat information overload by presenting the most critical information from a paper instantly. This enables researchers to quickly identify whether key information in a paper is relevant to their work, while saving time from diving into lengthy papers that may not be directly related to their domain or research area of interest.

Improved accessibility for both academicians and non-academicians

Technical research papers are difficult to understand by non-academicians due to scientific jargon and complexity. However, these AI summarization tools make research more inclusive and understandable to non-scientific users, facilitating enhanced knowledge dissemination to users.

Extracts key findings in seconds

With PDF summarizers or AI summarizers, researchers can get critical findings of the research articles with a single click. These AI summarizers pull out the main key points of a long article efficiently, ensuring readers quickly grasp the essence of the study.

For example, Scholarcy, an AI-based tool, creates a summary-length flashcard of research papers enlisting the key insights, references, and figures. This way, it helps you speed-read the article consuming less time.

Cross-disciplinary insights

Traditional research papers are often confined within disciplinary boundaries, making it challenging for researchers to explore ideas beyond their domain or area of interest. Research paper summarizers, however, assist them in comprehending interdisciplinary insights by summarizing the paper in the simplest way possible.

That way, researchers can easily understand and summarize studies from diverse fields, fostering scientific innovation and novel perspectives.

Also read: Top online tools to boost your academic performance

Top 5 AI summarizers — For summarizing research papers

Scispace copilot.

SciSpace Copilot, an AI tool helps researchers understand research papers by summarizing every bit of the highlighted information. You just have to select the text portion and click on summarize, it generates a summary of the text in seconds. Once you have the summaries, it also allows you to ask follow-up questions if you have. Unlike other tools, it is not only limited to generating summaries, it also assists you with explaining math, tables, figures, and equations.

• Summarizes and explains text, math, tables, and equations.
• Get summaries in multiple languages. You can interact with the paper in 70+ languages
• It acts as a Chatbot for your paper. You can ask any questions relevant to your paper and it explains it to you
• The answers are reliable as they’re backed by citations.
• Sometimes, it shows repetitive responses

Scholarly is an online article summarizer tool that assists students and researchers in quickly summarizing and comprehending research articles, book chapters, reports, and other documents. The tool simplifies difficult information into digestible chunks, gives context to important sentences, highlights important passages, and enables users to quickly save or export summaries as word documents for later use.

For students and researchers who need to keep up with their academic reading and writing, Scholarcy is a great resource. This AI summarizing tool highlights important facts and results while breaking down intricate information into interactive flashcards. It highlights key points and generate links to open-access versions of cited sources. Any device can read, share, and annotate these flashcards, making it simple to understand the research papers.

• Provides key insights of a lengthy research paper in multiple summary flashcards
• Save your flashcards in a dedicated Scholarcy library
• Free Edge and Chrome extension
• Only 3 free summary flashcards per day
• Glitchy interface
• Need a subscription to access advanced features

TLDR this is an AI-powered tool quickly summarizes any research paper, essay , document, report, and others in just a click. You can get the article summary in two different types — short and brief summary (actual TLDR) or long and detailed summary based on your requirements. All you have to do is, enter the website URL or paste the link to the content and generate a summary

• Generate 10 free summaries at no cost
• The interface is pretty straightforward
• It also tells you if the summary sounds AI-generated or human-like
• The quality of the summary has to be improved as there is essentially no difference between short and long summaries
• Output throws a few sentences from the original text and doesn’t produce an authentic summary

Quillbot Summarizer

Quillbot is another AI summarizing tool designed to break down lengthy articles, papers, or documents into their essential points in an instant and easy way. It works similarly to its paraphrasing tool. By leveraging the power of AI and NLP models, Quillbot online summarizer ensures that the core information is summarized without losing the original context.

Users can benefit from two different AI modes, choosing between "Key Sentences" or "Paragraph Mode" summaries. This summarization tool offers unlimited usage and is 100% free, making it an invaluable asset for researchers and writers alike.

• Availability of different modes of summarization based on the type and length of the content
• You can also paraphrase the obtained summary for a better understanding
• The free version comes with a word limit of 1200 words
• It's observed that the accuracy goes off the line sometimes

Amidst these dedicated AI summarizers, let's not forget ChatGPT. While not exclusively a research paper summarizer, ChatGPT can be an effective tool for summarizing long articles , books, news articles, research articles, reports, and more. By feeding it with the text you wish to summarize, you can get a tailored summary in real time.

• Completely free to use
• Users can clarify, refine, or request more detailed summaries interactively.
• Can produce summaries of varying lengths based on user requirements.
• Might occasionally provide less accurate summaries for very niche topics
• The summaries can sometimes be more verbose

Wrapping up!

While the journey of research paper summarizers has seen massive amounts of growth and adaptation, it's also evident that challenges still exist in terms of accuracy. However, with the rapid pace of technological advancements and the solutions emerging in response to these changes, the future looks promising. These tools will become even more intuitive, accurate, and user-centric, further bridging the gap between new scientific discoveries and their easy comprehension.

Although AI summarizers are valuable tools for quickly extracting essential information from lengthy research papers they should be only used as aids for initial comprehension rather than as substitutes for in-depth reading and analysis. The quality of the summary may vary, so it's essential to evaluate their accuracy for your specific needs.

You can explore all the above-listed tools and let us know which one helped you the most!

Good reads, curated just for you!

Best AI Tools for Research Paper Writing

How To Write A Research Summary

AI tools for research: Revolutionize your work with top research assistants

5 literature review tools to ace your reseach (+2 bonus tools)

ChatPDF vs. SciSpace Copilot: AI tools to chat with your PDF

Citation Machine Alternatives — A comparison of top citation generator tools 2023

You might also like

ChatPDF Showdown: SciSpace Chat PDF vs. Adobe PDF Reader

Boosting Citations: A Comparative Analysis of Graphical Abstract vs. Video Abstract

The Impact of Visual Abstracts on Boosting Citations

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Turk J Urol
• v.39(Suppl 1); 2013 Sep

How to clearly articulate results and construct tables and figures in a scientific paper?

The writing of the results section of a scientific paper is very important for the readers for clearly understanding of the study. This review summarizes the rules for writing the results section of a scientific paper and describes the use of tables and figures.

Introduction

Medical articles consist of review articles, case reports, and letters to the editor which are prepared with the intention of publishing in journals related to the medical discipline of the author. For an academician to be able to progress in carreer, and make his/her activities known in the academic environment, require preparation of the protocol of his/her academic research article, and acquiring sufficient information, and experience related to the composition of this article. In this review article, the information related to the writing of the ‘Results’ section, and use of tables, and figures will be presented to the attention of the readers.

Writing the ‘Results’ section

The ‘Results’ section is perhaps the most important part of a research article. In fact the authors will share the results of their research/study with their readers. Renown British biologist Thomas Henry Huxley (1825–1895) indicated his feelings as “The great tragedy of science: the slaying of a beautiful hypothesis by an ugly fact.” which emphasizes the importance of accurately, and impressively written results.

In essence results provide a response for the question” What is found in the research performed?”. Therefore, it is the most vital part of the article. As a priority, while drafting the ‘Results’ section of a manuscript one should not firstly write down methods in the ‘Material and Method’ section. The first sentence should give information about the number of patients who met the inclusion criteria, and thus enrolled in the study. [ 1 ] Besides information about the number of patients excluded from the study, and the reasons for exclusion is very important in that they will enlighten the readers, and reviewers who critically evaluate the manuscript, and also reflect the seriousness of the study. On the other hand, the results obtained should be recorded in chronological order, and without any comments. [ 2 ] In this section use of simple present tense is more appropriate. The findings should be expressed in brief, lucid, and explicable words. The writing style should not be boring for the reader. During writing process of a research article, a generally ill-conceived point is that positive, and significant findings are more important, attractive, and valuable, while negative, and insignificant findings are worthless, and less attractive. A scientific research is not performed to confirm a hypothesis, rather to test it. Not only positive, and significant results are worth writing, on the other hand negative or statistically insignificant result which support fallacy of a widely accepted opinion might be valuable. Therefore, all findings obtained during research should be inclıuded in the ‘Results’ section. [ 1 ]

While writing the ‘Results’ section, the sequence of results, tabulated data, and information which will be illustrated as figures should be definitively indicated. In indicating insignificant changes, do not use expressions as “decreased” or “increased”, these words should be reserved for significant changes. If results related to more than one parameter would be reported, it is appropriate to write the results under the subheading of its related parameter so as to facilitate reading, and comprehension of information. [ 2 ] Only data, and information concerning the study in question should be included in the ‘Results’ section. Results not mentioned in this section should not be included in the ‘Discussion’ and ‘Summary’ sections. Since the results obtained by the authors are cited in the ‘Results’ section, any reference should not be indicated in this section. [ 3 ]

In the ‘Results’ section, numerical expressions should be written in technically appropriate terms. The number of digits (1, 2 or 3 digits) to be written after a comma (in Turkish) or a point (in especially American English) should be determined The number of digits written after the punctuation marks should not be changed all throughout the text. Data should be expressed as mean/median ± standard deviation. Data as age, and scale scores should be indicated together with ranges of values. Absolute numerical value corresponding to a percentage must be also indicated. P values calculated in statistical analysis should be expressed in their absolute values. While writing p values of statistically significant data, instead of p<0.05 the actual level of significance should be recorded. If p value is smaller than 0.001, then it can be written as p <0.01. [ 2 ] While writing the ‘Results’ section, significant data which should be recalled by the readers must be indicated in the main text. It will be appropriate to indicate other demographic numerical details in tables or figures.

As an example elucidating the abovementioned topics a research paper written by the authors of this review article, and published in the Turkish Journal of Urology in the year 2007 (Türk Üroloji Dergisi 2007;33:18–23) is presented below:

“A total of 9 (56.2%) female, and 7 (43.8%) male patients with were included in this study. Mean age of all the patients was 44.3±13.8 (17–65) years, and mean dimensions of the adrenal mass was 4.5±3.4 (1–14) cm. Mean ages of the male, and female patients were 44.1 (30–65), and 42.4 (17–64) years, while mean diameters of adrenal masses were 3.2 (1–5), and 4.5 (1–14) cm (p age =0.963, p mass size =0.206). Surgical procedures were realized using transperitoneal approach through Chevron incision in 1 (6.2%), and retroperitoneal approach using flank incision with removal of the 11. rib in 15 (93.7%) patients. Right (n=6; 37.5%), and left (n=2; 12.5%) adrenalectomies were performed. Two (12.5%) patients underwent bilateral adrenalectomy in the same session because of clinical Cushing’s syndrome persisted despite transsphenoidal hipophysectomy. Mean operative time, and length of the hospital stay were 135 (65–190) min, and 3 (2–6) days, respectively. While resecting 11. rib during retroperitoneal adrenalectomy performed in 1 patient, pleura was perforated for nearly 1.5 cm. The perforated region was drained, and closed intraoperatively with 4/0 polyglyctan sutures. The patient did not develop postoperative pneumothorax. In none of the patients postoperative complications as pneumothorax, bleeding, prolonged drainage were seen. Results of histopathological analysis of the specimens retrieved at the end of the operation were summarized in Table 1 .” Table 1. Histopathological examination results of the patients Histopathological diagnosis Men n (%) Women n (%) Total n (%) Adrenal cortical adenoma 5 (31.3) 6 (37.6) 11 (68.8) Pheochromocytoma 1 (6.2) 1 (6.2) 2 (12.6) Ganglioneuroma 1 (6.2) - 1 (6.2) Myelolipoma - 1 (6.2) 1 (6.2) Adrenal carcinoma - 1 (6.2) 1 (6.2) Total 7 (43.7) 9 (56.2) 16 (100) Open in a separate window

Use of tables, and figures

To prevent the audience from getting bored while reading a scientific article, some of the data should be expressed in a visual format in graphics, and figures rather than crowded numerical values in the text. Peer-reviewers frequently look at tables, and figures. High quality tables, and figures increase the chance of acceptance of the manuscript for publication.

Number of tables in the manuscript should not exceed the number recommended by the editorial board of the journal. Data in the main text, and tables should not be repeated many times. Tables should be comprehensible, and a reader should be able to express an opinion about the results just at looking at the tables without reading the main text. Data included in tables should comply with those mentioned in the main text, and percentages in rows, and columns should be summed up accurately. Unit of each variable should be absolutely defined. Sampling size of each group should be absolutely indicated. Values should be expressed as values±standard error, range or 95% confidence interval. Tables should include precise p values, and level of significance as assessed with statistical analysis should be indicated in footnotes. [ 2 ] Use of abbreviations in tables should be avoided, if abbreviations are required they should be defined explicitly in the footnotes or legends of the tables. As a general rule, rows should be arranged as double-spaced Besides do not use pattern coloring for cells of rows, and columns. Values included in tables should be correctly approximated. [ 1 , 2 ]

As an example elucidating the abovementioned topics a research paper written by the authors of this review article, and published in the Turkish Journal of Urology in the year 2007 (Türk Üroloji Dergisi 2007;33:18–23).is shown in Table 1 .

Most of the readers priorly prefer to look at figures, and graphs rather than reading lots of pages. Selection of appropriate types of graphs for demonstration of data is a critical decision which requires artist’s meticulousness. As is the case with tables, graphs, and figures should also disploay information not provided in the text. Bar, line, and pie graphs, scatter plots, and histograms are some examples of graphs. In graphs, independent variables should be represented on the horizontal, and dependent variables on the vertical axis. Number of subjects in every subgroup should be indicated The labels on each axis should be easily understandable. [ 2 ] The label of the Y axis should be written vertically from bottom to top. The fundamental point in writing explanatory notes for graphs, and figures is to help the readers understand the contents of them without referring to the main text. Meanings of abbreviations, and acronyms used in the graphs, and figures should be provided in explanatory notes. In the explanatory notes striking data should be emphasized. Statistical tests used, levels of significance, sampling size, stains used for analyses, and magnification rate should be written in order to facilitate comprehension of the study procedures. [ 1 , 2 ]

Flow diagram can be utilized in the ‘Results’ section. This diagram facilitates comprehension of the results obtained at certain steps of monitorization during the research process. Flow diagram can be used either in the ‘Results’ or ‘Material and Method’ section. [ 2 , 3 ]

Histopathological analyses, surgical technique or radiological images which are considered to be more useful for the comprehension of the text by the readers can be visually displayed. Important findings should be marked on photos, and their definitions should be provided clearly in the explanatory legends. [ 1 ]

As an example elucidating the abovementioned issues, graphics, and flow diagram in the ‘Results’ section of a research paper written by the authors of this review article, and published in the World Journal of Urology in the year 2010 (World J Urol 2010;28:17–22.) are shown in Figures 1 , and ​ and2 2 .

a The mean SHIM scores of the groups before and after treatment. SHIM sexual health inventory for male. b The mean IPSS scores of the groups before and after treatment. IPSS international prostate symptom score

Flowchart showing patients’ progress during the study. SHIM sexual health inventory for male, IIEF international index of erectile function, IPSS international prostate symptom score, QoL quality of life, Q max maximum urinary flow rate. PRV post voiding residual urine volume

In conclusion, in line with the motto of the famous German physicist Albert Einstein (1879–1955). ‘If you are out to describe the truth, leave elegance to the tailor .’ results obtained in a scientific research article should be expressed accurately, and with a masterstroke of a tailor in compliance with certain rules which will ensure acceptability of the scientific manuscript by the editorial board of the journal, and also facilitate its intelligibility by the readers.

Use AI to summarize scientific articles and research papers in seconds

Send a document, get a summary. It's that easy.

If GPT had a PhD

• Unlimited Summaries
• Summarize articles up to 200,000 words.
• 5 Figure and table analysis with AI
• Unlimited Chat Messages
• Unlimited article searches
• Import and summarize references with the click of a button
• 30,000 words summarized
• 5 Figures or Tables analyzed with AI
• 100 Chat Messages
• Maximum document length of 200,000 words
• Unlimited bulk summaries
• Unlimited chat messages per month
• Unlimited figure and table analysis with AI
• 1,000 documents indexed for semantic search

Be the boss of your literature review

Download this free article summary table template.

When dealing with the literature, summarise the articles you read as you go along. This will ensure that you don't read and forget. Using the Article Summary Table template, you can neatly add a summary of each study to a table. This table is handy because you can easily refer to a specific article without searching through piles of pdfs.

Get the Article Summary Table template in Microsoft Word AND Microsoft Excel - for FREE

• Research Guides
• Vanderbilt University Libraries

Artificial Intelligence for Peabody College

Ai research tools.

• AI @ Vanderbilt
• AI & Academic Integrity
• AI & Ethics

About This Table

The resources described in the table represent an incomplete list of tools specifically geared toward exploring and synthesizing research. As generative AI becomes more integrated into  online   search tools , even the early research and topic development stages could incorporate AI. If you have any questions about using these tools for your research, please email us at [email protected]

• << Previous: AI & Academic Integrity
• Next: AI & Ethics >>
• Last Updated: Aug 27, 2024 10:37 AM
• URL: https://researchguides.library.vanderbilt.edu/aiforpeabody

• Kreyòl Ayisyen

Cash-back Fees

Executive summary, cash-back transactions, benefits and costs to merchants.

Access to cash is a necessary component of a resilient financial system and dynamic economy. Many people rely on cash for day-to-day transactions due its privacy and reliability, and cash accessibility is particularly critical in the case of a disruption or outage of digital payment systems. While people use various means of getting cash, one common method is to get “cash back” at a store when making a purchase with a debit or prepaid card. This option may be particularly important in banking deserts and in areas where banks and ATM operators charge significant fees. Retailers are essentially filling a void in access to cash, which has historically been supplied by banks and credit unions in an affordable way.

Providing cash back is valuable to consumers and merchants. Survey data show that it is a popular method to get money via consumers’ bank debit or prepaid cards. Merchants offer cash back to attract customers and reduce their cash handling costs. In its recent engagement and market monitoring, the CFPB observed that some retailers charge a fee for this transaction.

This spotlight provides an overview of consumers’ use of cash back, the benefits and costs of such transactions to merchants, and the practices of other market actors which do not charge fees for this service. The CFPB also analyzed the cash-back fees of a sample of national retailers.

Fees for cash back may serve as a barrier and reduce people’s access to cash when they need it. The CFPB will continue to monitor developments related to the fees consumers pay for accessing cash, and the underlying failure of banks and credit unions to adequately supply cash throughout the country in an affordable manner.

Key Findings

• Cash-back fees are costing consumers millions of dollars . The CFPB found that three companies in the sample charge cash-back fees and estimates that they collect over $90 million in fees annually for people to access their cash. The CFPB also estimates that the marginal cost to merchants for processing each transaction may be a few pennies, compared to the much higher fees charged by these retailers to consumers. While there may be other costs related to cash handling, these are generally reduced by the provision of cash back, as it reduces merchants’ cash on hand.
• Three major firms charge cash-back fees even though other competitors offer it for free. Three retail companies Dollar General, Dollar Tree, and Kroger, which also operate brands such as Family Dollar, Harris Teeter, Ralph’s, and others, charge fees for this service while other national retail companies sampled by the CFPB do not charge a fee. At the two largest dollar store corporations, cash-back fees for small withdrawal amounts are the highest in the sample ($1 or more for amounts under $50). Kroger, the country’s largest grocery chain, recently expanded cash-back fees to its Harris Teeter brand (75 cents for $100 or less), higher than those in place among its other brands (50 cents for $100 or less), in addition to higher fees for larger amounts.
• Cash-back fees are levied on low pre-set cash withdrawal amounts . Many merchants pre-determine the withdrawal amount options in a single transaction, commonly between $5 and $50. The fees charged on small, constrained amounts often constitute a high percentage of the cash withdrawal and limit consumers’ ability to spread the cost of that fee over larger amounts. It may also induce repeat withdrawals, with consumers incurring a new fee each time.
• Consumers with lower incomes or fewer banking choices may be more likely to encounter cash-back fees . Dollar stores are frequently located in small rural towns, communities of color, and low-income communities. These areas are also more likely to be places where there are fewer branch locations, and communities where people are more reliant on cash for daily transactions than others.

This section summarizes the importance of cash availability and the use of cash-back as an access point for consumers.

Cash is a critical part of a resilient payment ecosystem. Surveys show people still try to have cash on hand 1 and nearly 90 percent of people used cash in the last 30 days. 2 Cash accessibility is necessary should other types of digital payment systems experience failures, 3 such as in the event of a natural disaster or some other catastrophe, 4 or a technological malfunction at a single company. 5 Additionally, some populations are more reliant on cash than others for day-to-day transactions. For example, cash is more frequently used by people with lower incomes, racial minorities, and older Americans than other populations. 6 As discussed below, cash back is a common method for obtaining cash for many consumers.

How cash back works

Consumers may obtain cash during the completion of a purchase transaction at certain stores when using a PIN-authenticated debit card or prepaid card at the register. Some merchants also provide cash back at self-service registers. Consumers typically must choose from pre-set withdrawal amount options presented at the payment terminal at the time of the transaction. In a cash-back transaction, consumers are usually limited to a maximum withdrawal amount ranging from $5 to $50, though some merchants may allow higher amounts.

Scope of usage

CFPB analysis of data from the Diary and Survey of Consumer Payment Choice (Survey) found that from 2017 to 2022, cash withdrawals at retail locations made up 17 percent of all transactions by which people got cash from their checking account, savings account, or prepaid card. As shown in Figure 1, cash withdrawals at retail are second only to ATMs (61%) and more frequently used than bank tellers (14%). The Survey and methodology are discussed in the Tables and Notes section .

Figure 1: Instances of getting cash from bank account or prepaid card, by location, 2017 to 2022, combined

Source : CFPB tabulations of the Diary and Survey of Consumer Payment Choice.

The Survey data also show that from 2017 to 2022, cash withdrawals at a retail location (restricted to those where the source of funds was the consumer’s checking, savings, or a prepaid card) had a mean withdrawal amount of $34 (median: $20). 7 By contrast, during this same timeframe, the mean ATM withdrawal among survey participants was $126 (median: $100). 8 A study by researchers at the Federal Reserve Bank of Atlanta utilizing Survey data found that cash withdrawals at a retail store had the lowest average amount of cash withdrawal, and noted that “[t]he amount of cash received at a retail store is constrained by the store’s limits, so the amount of cash received in this way is not necessarily at the discretion of the consumer.” 9

Cash back may serve as a particularly important point of access in the absence of other banking services. A 2014 study by the Federal Reserve Bank of Richmond analyzed cash-back transactions from a national discount retail chain from 2010 to 2012. 10 Looking specifically at the Richmond bank’s district, the area with the highest frequency of cash-back transactions was in the southeastern region of South Carolina, an area “that has been subject to ‘persistent poverty’” and “has some of the sparsest dispersion of bank branches.” 11 The study also illustrated the lucrative nature of cash-back fees: During the course of this study period, the merchant introduced a fee for cash back. Data from this report indicates that the retailer collected approximately $21 million in cash-back fees in a year. 12

Merchants benefit from offering cash back at point-of-sale. First, the service may attract potential shoppers, either people making a purchase in order to get cash back or people who prefer one retail location over another in order to conveniently combine tasks. Second, it reduces merchants’ cash handling costs. 13 Dispensing cash to consumers, such as through cash-back transactions, reduces merchants’ supply of cash and therefore also reduces their cost of handling, transporting, and depositing excess cash.

Merchants incur costs for processing any type of payment transaction, including cash-back transactions. On any purchase using an electronic payment method, including a PIN-authorized debit-card or prepaid card, a merchant will incur a range of fees for processing that payment, such as interchange, network, and processing fees. While the merchant incurs these fees for a consumer’s purchase, there is an additional cost for providing cash back to the consumer.

To assess this additional transaction cost to the merchant for providing cash back, the CFPB modeled potential scenarios based on publicly available data and our market monitoring activities. The model incorporates estimates of merchant-incurred fees, such as interchange, network, processing, and fraud control fees. Methodology is discussed in detail in the Table and Figure Notes. The CFPB estimates that the additional marginal transactional cost to a merchant for processing a typical cash-back debit card transaction may range from a penny to about 20 cents (Table 1).

Table 1: Estimated additional merchant cost of a debit card cash-back transaction

Source : CFPB calculations based on public data about industry practices and averages. See Table and Figure Notes below for methodology .

This section provides an analysis of cash-back fee practices of eight national retail chains. It includes a discussion of the variation of these practices among these national chains and other actors, such as local independent grocers. The analysis is supplemented by market monitoring discussions with merchants about fees, costs, and consumer trends, both among merchants who charge cash back fees and those who do not. The CFPB also conducted consumer experience interviews and reviewed consumer complaints submitted to the CFPB. It concludes with a discussion of how these fees appear to function differently than fees for cash withdrawals at ATMs.

Current market practices

As of August 2024, there is no publicly available survey data regarding merchants’ cash-back practices or fees. To establish a baseline, the CFPB documented the fee practices of eight large retail companies. The sample consists of the two largest retail actors, measured by number of locations, across four different sectors: Dollar Stores, Grocery Stores, Drugstores, and Discount Retailers. 14 Using this approach, the eight retailers sampled are: Dollar General and Dollar Tree Inc. (Dollar Stores), Kroger Co. and Albertsons Companies (Grocery Stores), Walgreens and CVS (Drugstores), and Walmart and Target (Discount Retailers).

All retailers in our sample offer cash-back services, but only Dollar General, Dollar Tree Inc., and Kroger Co. brands charge a fee. Other retailers offer cash-back for free, even for withdrawal amounts similar to or larger than those provided by the three retailers who charge. (Table 2). Among the national chains that charge these cash-back fees, the CFPB estimates that they collect over $90 million in fees annually for people to access their cash. 15

Table 2: Cash-back fee practices, major retail companies

Source : CFPB analysis of the retail cash-back market. See Table and Figure Notes for methodology .

Beyond these national chains, there are other providers offering cash back as a free service to their customers. Through its market monitoring activities, the CFPB observed that many local independent grocers offer the service, but do not charge a fee. They do not charge a fee even though they are likely to have thinner profit margins and less bargaining power than national chains to negotiate on pricing on costs they incur from wholesalers or fees for payment processors. The U.S. Postal Service also offers cash back on debit transactions, in increments of $10 up to a $50 maximum, free of charge. 16

Cash-back fees at dollar stores

Among the merchants sampled, Dollar General and Dollar Tree Inc. charge the highest fees for withdrawal amounts under $50. These fees combined with the constrained withdrawal amount may mean that the fee takes up a hefty percentage relative to the amount of cash withdrawn, and people may be less able to limit the impact of the fee by taking out more cash.

Additionally, the geographic distribution of dollar store chains and their primary consumer base raises concerns that these fees may be borne by economically vulnerable populations and those with limited banking access. Dollar stores are prevalent in rural communities, low-income communities, and communities of color – the same communities who may also face challenges in accessing banking services. 17 For example, Dollar General noted that in 2023 “approximately 80% of [its] stores are located in towns of 20,000 or fewer people,” 18 while Dollar Tree Inc. operated at least 810 dual-brand combination stores (Family Dollar and Dollar Tree in a single building) designed specifically “for small towns and rural communities…with populations of 3,000 to 4,000 residents.” 19

Though they are open to and serve consumers of all income levels, dollar stores report that they locate stores specifically to serve their core customers: lower-income consumers. 20 In urban communities, one study shows, “proximity to dollar stores is highly associated with neighborhoods of color even when controlling for other factors.” 21 These same communities may also face challenges in accessing banking services. Low-income communities and communities of color often face barriers to access to banking services, and rural communities are 10 times more likely to meet the definition of a banking desert than urban areas. 22

Though the dollar store concept existed as far back as the 1950s, it has experienced significant expansion and consolidation since the 2000s. 23 Dollar Tree Inc. acquired Family Dollar in 2015. 24 From 2018 to 2021, nearly half of all retail locations opened in the U.S. were dollar stores. 25 In research examining the impact of dollar store expansion, studies indicate that the opening of a dollar store is associated with the closure of nearby local grocery retailers. 26

Variation of fees charged

In its scan of current market practices, the CFPB found variations in fee charges among store locations and brands owned by the same company. For example, as reflected in Table 2, Dollar Tree charges consumers $1 for cash back at Dollar Tree branded stores, but $1.50 in its Family Dollar stores. Similarly, Kroger Co. has two different fee tiers for its brands. In 2019, Kroger Co. rolled out a $0.50 cash-back fee for amounts of $100 or less, and $3.50 for amounts between $100 and $300. This took effect at brands such as Kroger, Fred Meyers, Ralph’s, QFC, Pick ‘N Save, and others. At the time of the rollout, the company noted two exceptions: Electronic benefits transfer (EBT) card users would not be charged a fee, and customers using their Kroger Plus card would not be charged for amounts under $100 but would be charged $0.50 for larger amounts. Kroger Co. acquired the southern grocery chain Harris Teeter in 2014, but it did not begin charging a cash-back fee at those stores until January 2024, at $0.75 for amounts of $100 or less, and $3 for larger amounts. 27

In its engagement with stakeholders, the CFPB learned that Dollar General’s fees appeared to vary in different locations. To better understand this potential variation, in December 2022, the CFPB mystery shopped at nine locations in one state, across a mix of rural, suburban, and urban communities. The CFPB acknowledges this is a small sample and is not intended to be representative. The data collected is based on the knowledge of the store associates at the time of each interaction.

In these findings, the CFPB learned of a range of fee variations across store locations: five of the nine respondents noted that the fee varies depending on the type of card used for the transaction. When probed for the meaning of “type of card,” most noted that it is dependent on the customer’s bank, though it is not exactly clear what fees will be triggered by what card type prior to initiating the transaction. Additionally, reported fees range from $1 to $2.50, with some stores reporting a flat fee structure of $1.50 and others reporting a range that tiered up with larger withdrawal amounts (with a cap of withdrawal amounts at $40). Most stores in this sample had a range of fees between $1.00 and $1.50, although two stores located in small, completely rural counties had a higher range of fees. The store located in the smallest and most isolated county within the sample, with only about 3,600 people, had the highest reported fee amount of $2.50.

Distinction from ATM fees

One of the market dynamics likely contributing to retailers’ ability to charge these fees is the high fees also charged to consumers for using out-of-network automated teller machines (ATMs). One source estimates that the average out-of-network ATM fee is $4.77, accounting for both the surcharge fee charged by the ATM owner and the foreign fee charged by the consumer’s financial institution. 28 By comparison, a $2 fee for cash back at a retailer may appear cheaper, and usually does not trigger an additional fee by the consumers’ financial institution or prepaid card issuer. Notwithstanding the high ATM fees, there are reasons for focused attention on the consumer risk of cash-back fees charged by retailers, primarily the amount of the fee relative to the value of the cash withdrawal and the distribution of the fee burden across income groups.

In a typical ATM transaction, a consumer has a greater ability to distribute the cost of the fee across a larger amount of cash than with cash back. There may be some exceptions to this for consumers who have only $10 or $20 in their bank account, but as shown in Table 3, low-income consumers and others withdraw greater amounts at ATMs than via cash-back, on average. In cash-back transactions, lower withdrawal limits are in place, and consumers do not have that option to withdraw larger amounts. CFPB analysis of the Diary and Survey of Consumer Payment Choice from 2017 to 2022 show that even among consumers with incomes below $50,000, the amount withdrawn at an ATM is more than double the typical cash-back withdrawal amount. Additionally, for the average and median amounts, across all incomes the ATM withdrawal amounts are larger than cash-back withdrawal amounts. (Table 3).

Table 3: Average ATM and cash-back withdrawal amounts, by income, 2017 to 2022 combined

Source: CFPB tabulations of the Diary and Survey of Consumer Payment Choice. See Table and Figure Notes for methodology .

Further, while merchants limit the amount of a single withdrawal, there is no limit on the number of withdrawals. So, if a consumer needs $100 cash at a store which limits a single withdrawal to a maximum amount of $50 with a $2 fee, the consumer would have to make two $50 withdrawals for a $4 fee plus the cost of any otherwise unwanted purchase required to access the cash-back service.

Finally, the burden of cash-back fees may be distributed differently than ATM fee burdens. The share of borrowers who pay ATM fees for cash withdrawals is relatively evenly distributed across income levels, according to a study based on the Diary and Survey of Consumer Payment Choice. 29 The study found little variation in the percentage of consumers who encountered a fee for an ATM cash withdrawal by income quintile, though the study did not look at the amount of the ATM fees paid. Analogous data are not available for cash-back fees, but a similarly even distribution across incomes is unlikely given the demographics of the consumer base served by the largest retailers which charge fees (dollar stores).

While the use of digital payment methods is on the rise, cash accessibility remains a critical component of a resilient financial infrastructure and dynamic economy. Bank mergers, branch closures, and bank fee creep have reduced the supply of free cash access points for consumers. In this void, people may be more reliant on retailers for certain financial services historically provided by banks and credit unions, such as cash access. In this context, we observe that some retailers provide cash back as a helpful service to their customers, while other retailers may be exploiting these conditions by charging fees to their consumers for accessing their cash.

This spotlight examines the presence of retailer cash-back fees and impact to consumers. Cash-back fees are being levied by just a small handful of large retail conglomerates (Dollar General, Dollar Tree Inc., and Kroger Co.) amidst a backdrop of consolidation in these segments. Meanwhile, other larger retailers continue to offer cash-back services free. The CFPB estimates cash-back fees cost consumers about $90 million a year.

The CFPB is concerned that reduced access to cash undermines the resilience of the financial system and deprives consumers of a free, reliable, and private means of engaging in day-to-day transactions. The CFPB will continue to monitor developments related to the fees consumers pay for accessing cash, and work with agencies across the federal government to ensure people have fair and meaningful access to the money that underpins our economy.

Table and Figure Notes

Notes for figure 1.

The Federal Reserve Bank of Atlanta’s annual Diary and Survey of Consumer Payment Choice (Survey) tracks consumers’ self-reported payment habits over a three-day period in October using a nationally representative sample. The survey includes a question about whether and how consumers access cash, such as where they made the withdrawal, the source of the cash, and the amount of the withdrawal. Figure 1 provides a percentage of all cash-back withdrawal transactions from a bank account, checking account, or prepaid card reported between 2017 and 2022, by location (ATM, Retail point-of-sale, Bank teller, and Other). The number of observations during this time is 192 transactions. It does not include cash-back transactions made using a credit card cash advance feature or other form of credit.

Notes for Table 1

This model assumes that 80 percent of the merchant transaction cost is due to interchange fees, 15 percent due to network fees, and 5 percent due to payment acquirer fees. It also includes a $0.01 fee for fraud protection. For regulated transactions, the interchange fees are $0.22 + 0.05% of the transaction amount. Regulated transactions are those where the debit card used is issued by a bank with more than $10 billion in assets, and subject to 15 U.S.C. § 1693o-2. Exempt transactions are those not subject to this statutory cap on interchange fees. While Mastercard does not publish its fees for exempt transactions, Visa does. This model uses Visa’s published fees as of October 2023 for card-present transactions: for the National Discount Chain, the fees for Exempt Retail Debit ($0.15 + 0.80%), and for the National Grocery Chain, Exempt Supermarket Debit ($0.30 flat fee). An October 2023 Federal Reserve report on interchange fee revenue found that in 2021, the most recent data available, 56.21 percent of debit transactions were regulated and 43.79 percent were exempt. This composition is reflected in the table.

Notes for Table 2

The storefront counts for each of the retailers come from their websites, last visited on March 28, 2024, or their most recent reports to investors. Fee information was gathered either through publicly available information such as the merchant’s website, and/or verified through the CFPB’s market monitoring activities.

Dollar Tree Inc. announced on March 13, 2024 that it will close 1,000 of its Family Dollar and Dollar Tree brands stores over the course of the year. If those closures occur, Dollar Tree, Inc. will still have over 15,000 storefronts across the country.

In October 2022, Kroger Co. and Albertsons Companies announced their proposal to merge, though on February 26, 2024, the Federal Trade Commission and nine state attorneys general sued to block this proposal, alleging that the deal is anti-competitive. On April 22, 2024, Kroger Co. and Albertsons Companies announced a revised plan in which, if the merger is approved, the combined entity would divest 579 stores to C&S Wholesalers. If the divestiture occurs, the combined entity will still have over 4,400 stores across the country.

Notes for Table 3

See above notes for Figure 1 about the Diary and Survey of Consumer Payment Choice (Survey). Table 3 provides mean and median amounts of ATM and Retail point-of-sale cash withdrawal transactions by income. In the Survey, participants were asked to report the total combined income of all family members over age 15 living in the household during the past 12 months. From these responses, we constructed five income brackets – four of $25,000 each plus a fifth bin for any respondents reporting more than $100,000 in annual household income for each respondent in each year.

See e.g., Jay Lindsay, A Fatal Cash Crash? Conditions Were Ripe for It After the Pandemic Hit, but It Didn’t Happen , Fed. Rsrv. Bank of Boston (Nov. 2, 2023), https://www.bostonfed.org/news-and-events/news/2023/11/cash-crash-pandemic-increasing-credit-card-use-diary-of-consumer-payment-choice.aspx

Kevin Foster, Claire Greene, & Joanna Stavins, The 2023 Survey and Diary of Consumer Payment Choice , Fed. Rsrv Bank of Atlanta (June 2024), https://doi.org/10.29338/rdr2024-01

See e.g., Hilary Allen, Payments Failure, Boston College Law Review, Forthcoming, American University, WCL Research Paper No. 2021- 11, (Feb. 21, 2020) available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3539797

See e.g., Scarlett Heinbuch, Cash Is Critical in Times of Crisis , Fed. Rsrv. Bank of Atlanta (Mar. 7, 2022), https://www.atlantafed.org/blogs/take-on-payments/2022/03/07/cash-in-crisis

See e.g., Carly Page, Square Says It Has Resolved Daylong Outage , TechCrunch, (Sept. 8, 2023), https://techcrunch.com/2023/09/08/square-day-long-outage-resolved/ . See also Caroline Haskins, The Global CrowdStrike Outage Triggered a Surprise Return to Cash , Wired, (July 19, 2024), https://www.wired.com/story/microsoft-crowdstrike-outage-cash/ .

See Berhan Bayeh, Emily Cubides and Shaun O’Brien, 2024 Findings from the Diary of Consumer Payment Choice , Fed. Rsrv. (May 13, 2024), https://www.frbservices.org/binaries/content/assets/crsocms/news/research/2024-diary-of-consumer-payment-choice.pdf (findings related to low-income consumers and older Americans use of cash); Emily Cubides and Shaun O’Brian, 2023 Findings from the Diary of Consumer Payment Choice , Fed. Rsrv., (May 19, 2024), https://www.frbsf.org/cash/wp-content/uploads/sites/7/2023-Findings-from-the-Diary-of-Consumer-Payment-Choice.pdf (findings related to unbanked households use of cash), and Michelle Faviero, , More Americans are Joining the ‘Cashless’ Economy ,” Pew Rsch. Ctr, (Oct. 5, 2022), https://www.pewresearch.org/short-reads/2022/10/05/more-americans-are-joining-the-cashless-economy/ (findings related to use of cash by race and other demographics).

Similarly, the average cash-back withdrawal amount was $33 in 2012, the most recent data available from the Federal Reserve Payments Study. The study was based on self-reported information from financial institutions surveyed by the Federal Reserve. Of the reported transactions, 73 percent were debit cards with an average amount of $33 and 27 percent on general purpose prepaid cards with an average withdrawal amount of $19. 2013 Federal Reserve Payments Study: Recent and Long-Term Payment Trends in the United States: 2003 – 2012 , Fed. Rsrv. Bd. (July 2014), https://www.frbservices.org/binaries/content/assets/crsocms/news/research/2013-fed-res-paymt-study-summary-rpt.pdf

The amounts in the Survey are lower than the average ATM withdrawal amounts reported in 2022 Federal Reserve Payments study, which utilizes data from surveying financial institutions. Per this study, in 2021, the average ATM withdrawal was $198. The Federal Reserve Payments Study: 2022 Triennial Initial Data Release , Fed. Rsrv. Bd. (Apr. 21, 2023), https://www.federalreserve.gov/paymentsystems/fr-payments-study.htm

Claire Green and Oz Shy, How Consumers Get Cash: Evidence from a Diary Survey , Fed. Rsrv. Bank of Atlanta, (Apr. 2019), at 5, https://www.atlantafed.org/-/media/documents/banking/consumer-payments/research-data-reports/2019/05/08/how-consumers-get-cash-evidence-from-a-diary-survey/rdr1901.pdf (finding, “For the largest amounts of cash, respondents mostly turned to employers, with an average dollar value of cash received of $227. At bank tellers and ATMs, consumers also received average dollar values greater than the overall average: $159 and $137, respectively. Consumers received smaller amounts from family or friends ($93) and, notably, cash back at a retail store ($34). All these dollar amounts are weighted. The amount of cash received at a retail store is constrained by the store’s limits, so the amount of cash received in this way is not necessarily at the discretion of the consumer.”)

Neil Mitchell and Ann Ramage, The Second Participant in the Consumer to Business Payments Study , Fed. Rsrv. Bank of Richmond (Sept. 15, 2014), https://www.richmondfed.org/~/media/richmondfedorg/banking/payments_services/understanding_payments/pdf/psg_ck_20141118.pdf

Id. at 8, Figures 7 and 8.

See e.g., Stan Sienkiewicz, The Evolution of EFT Networks from ATMs to New On-Line Debit Payment Products , Discussion Paper, Payment Cards Ctr. of the Fed. Rsrv. Bank of Philadelphia (Apr. 2002), https://www.philadelphiafed.org/-/media/frbp/assets/consumer-finance/discussion-papers/eftnetworks_042002.pdf?la=en&hash=88302801FC98A898AB167AC2F9131CE1 (“The cash back option became popular with supermarket retailers, since store owners recognized savings as a result of less cash to count at the end of the day, a chore that represented a carrying cost to the establishment.”).

These market segments and retailers for purposes of markets analysis are similar to those used in other academic literature related to dollar store locations in the context of food access or impact on other market dynamics, such as on local grocers. See e.g., El Hadi Caoui, Brett Hollenbeck, and Matthew Osbourne, The Impact of Dollar Store Expansion on Local Market Structure and Food Access ,” (June 22, 2022), available at https://ssrn.com/abstract=4163102 (finding "In 2021, there were more of these stores operating than all the Walmarts, CVS, Walgreens, and Targets combined by a large margin.”) and Yue Cao, The Welfare Impact of Dollar Stores ,” available at https://yuecao.dev/assets/pdf/YueCaoDollarStore.pdf (last visited Aug. 23, 2024) (using the categories of dollar stores, groceries, and mass merchandise (such as Walmart) for comparisons across retail segments and noting that dollar stores regard these other segments as competitors).

Estimate based on information voluntarily provided in the CFPB's market monitoring activities.

What Forms of Payment are Accepted? U.S. Postal Serv., https://faq.usps.com/s/article/What-Forms-of-Payment-are-Accepted (last visited Aug. 23, 2024).

See generally, Stacy Mitchell, Kennedy Smith, and Susan Holmberg , The Dollar Store Invasion , Inst. for Local Self Reliance (Mar. 2023), https://cdn.ilsr.org/wp-content/uploads/2023/01/ILSR-Report-The-Dollar-Store-Invasion-2023.pdf . There is also extensive research on dollar store locations in other contexts such as food access and impact on consumer spending habits. El Hadi Caoui, Brett Hollenbeck, and Matthew Osbourne, The Impact of Dollar Store Expansion on Local Market Structure and Food Access ,” at 5, (June 22, 2022), available at https://ssrn.com/abstract=4163102

Dollar General Annual Report (Form10-K) at 7 (Mar. 25. 2024), https://investor.dollargeneral.com/websites/dollargeneral/English/310010/us-sec-filing.html?format=convpdf&secFilingId=003b8c70-dfa4-4f21-bfe7-40e6d8b26f63&shortDesc=Annual%20Report .

Dollar Tree, Inc. Annual Report (Form 10-K) at 7 (Mar. 20. 2024), https://corporate.dollartree.com/investors/sec-filings/content/0000935703-23-000016/0000935703-23-000016.pdf

See e.g., Dollar General Annual Report (Form10-K) at 7 (Mar. 25. 2024) (“We generally locate our stores and plan our merchandise selections to best serve the needs of our core customers, the low and fixed income households often underserved by other retailers, and we are focused on helping them make the most of their spending dollar.” And, Dollar Tree, Inc. Annual Report (Form 10-K) at 6 (Mar. 20. 2024), (“Family Dollar primarily serves a lower than average income customer in urban and rural locations, offering great values on everyday items.”)

Dr. Jerry Shannon, Dollar Stores, Retailer Redlining, and the Metropolitan Geographies of Precarious Consumption , Ann. of the Am. Assoc. of Geographers, Vol. 111, No. 4, 1200-1218 (2021), (analyzing over 29,000 storefront locations of Dollar General, Dollar Tree, and Family Dollar locations across the three largest MSA in each of the nine U.S. Census Bureau-defined divisions.)

Kristen Broady, Mac McComas, and Amine Ouazad, An Analysis of Financial Institutions in Black-Majority Communities: Black Borrowers and Depositors Face Considerable Challenges in Accessing Banking Services ,” Brookings Inst., (Nov. 2, 2021), https://www.brookings.edu/articles/an-analysis-of-financial-institutions-in-black-majority-communities-black-borrowers-and-depositors-face-considerable-challenges-in-accessing-banking-services/ and Drew Dahl and Michelle Franke, Banking Deserts Become a Concern as Branches Dry Up , Fed. Rsrv. Bank of St. Louis, https://www.stlouisfed.org/publications/regional-economist/second-quarter-2017/banking-deserts-become-a-concern-as-branches-dry-up (July 25, 2017).

El Hadi Caoui, Brett Hollenbeck, and Matthew Osbourne, The Impact of Dollar Store Expansion on Local Market Structure and Food Access ,” (June 22, 2022), available at https://ssrn.com/abstract=4163102 .

Dollar Tree Completes Acquisition of Family Dollar , Dollar Tree Inc., (July 6, 2015), available at https://corporate.dollartree.com/news-media/press-releases/detail/120/dollar-tree-completes-acquisition-of-family-dollar

El Hadi Caoui, Brett Hollenbeck, and Matthew Osbourne, The Impact of Dollar Store Expansion on Local Market Structure and Food Access ,” (June 22, 2022), available at https://ssrn.com/abstract=4163102 and Yue Cao, The Welfare Impact of Dollar Stores, https://yuecao.dev/assets/pdf/YueCaoDollarStore.pdf (last visited Aug. 23. 2024).

Evan Moore, Harris Teeter Introduces New Fees that Have Customers Upset. What To Know Before You’re Charged , Charlotte Observer, (Mar. 14, 2024), https://amp.charlotteobserver.com/news/business/article286627340.html

Karen Bennett and Matthew Goldberg, Survey: ATM fees Reach 26-year High While Overdraft Fees Inch Back Up , Bankrate.com (Aug. 21, 2024), https://www.bankrate.com/banking/checking/checking-account-survey/

Oz Shy and Joanna Stavins, Who Is Paying All These Fees? An Empirical Analysis of Bank Account and Credit Card Fees , Fed. Rsrv. Bank of Boston, Working Paper No. 22-18, at Table 2, (Aug. 2022), https://www.bostonfed.org/publications/research-department-working-paper/2022/who-is-paying-all-these-fees-an-empirical-analysis-of-bank-account-and-credit-card-fees .

A systematic review of micro-texture formation based on milling: from mechanism, existing techniques, characterization to typical applications

• Critical Review
• Published: 27 August 2024

Cite this article

• Zhiwen Jiang 1 , 2 ,
• Dongju Chen 1 , 2 ,
• Kun Sun 1 , 2 ,
• Ri Pan 1 , 2 ,
• Jinwei Fan 1 , 2 &
• Yuhang Tang 3  

Milling-based micro-texturing is an emerging technique that employs mechanical milling to create precise and flexible surface patterns, enabling controlled surface property modulation. With high precision, controllability, repeatability, and mass production, it finds extensive applications in optics, biomedical engineering, mechanical engineering, and among others. Herein, this paper systematically summarizes the key contents of micro-texturing technology from the perspective of mechanical milling for the first time. Firstly, the surface texture generation mechanisms are systematically described, encompassing milling forces modeling, texture formation process, and size effect. Secondly, the importance of tool selection and manufacturing in micro-milling is briefly addressed, followed by a detailed classification and comparison of existing milling-based micro-texturing techniques for metallic and non-metallic materials. Subsequently, the design criteria of surface micro-texturing, methods for characterizing its performance, and typical applications of this technology are summarized in detail. Finally, a brief summary and outlook for future work are delineated. This research is expected to facilitate the enhancement of surface performance, the development of functional materials, and the exploration of novel applications in response to ultra-precision manufacturing demands.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Explore related subjects

Zhang Q, Wang Q, Zhang Z, Fu Y, Xu J (2022) Surface micro-texture on sapphire fabricated by laser ablation trajectory regulation. Chin J Aeronaut 35(3):525–536

Article   Google Scholar  

Zhang J, Zhang S, Chen G, Jia Z, Qu Y, Guo Z (2022) Laser micro-texture formation mechanism based on modified heat-mass transfers and hydrodynamic models. Int J Mech Sci 230:107528

Cunha W, Carvalho O, Henriques B, Silva FS, Ozcan M, Souza JCM (2022) Surface modification of zirconia dental implants by laser texturing. Lasers Med Sci 37(1):77–93

Li JZ, Shen FH, Yu ZY, Natsu W (2013) Influence of microstructure of alloy on the machining performance of micro EDM. Surf Coat Technol 228:S460–S465

Zheng Z-P, Cheng W-H, Huang F-Y, Yan B-H (2007) 3D microstructuring of Pyrex glass using the electrochemical discharge machining process. J Micromech Microeng 17(5):960–966

Xu S, Shimada K, Mizutani M, Kuriyagawa T (2014) Fabrication of hybrid micro/nano-textured surfaces using rotary ultrasonic machining with one-point diamond tool. Int J Mach Tools Manuf 86:12–17

Zhang S, Zhou Y, Zhang H, Xiong Z, To S (2019) Advances in ultra-precision machining of micro-structured functional surfaces and their typical applications. Int J Mach Tools Manuf 142:16–41

Kim J, Lee S-K (2016) Micro-patterning technique using a rotating cutting tool controlled by an electromagnetic actuator. Int J Mach Tools Manuf 101:52–64

Kim GD, Loh BG (2013) Cutting force variation with respect to tilt angle of trajectory in elliptical vibration V-grooving. Int J Precis Eng Manuf 14(10):1861–1864

Kim GD, Loh BG (2011) Direct machining of micro patterns on nickel alloy and mold steel by vibration assisted cutting. Int J Precis Eng Manuf 12(4):583–588

Grazia Guerra M, Lavecchia F (2023) Measurement of additively manufactured freeform artefacts: the influence of surface texture on measurements carried out with optical techniques. Measurement 209:112540

Zheng Y, Zhao H, Cai Y, Jurado-Sanchez B, Dong R (2022) Recent advances in one-dimensional micro/nanomotors: fabrication, propulsion and application. Nano Lett 15(1):20

Lipovsek B, Krc J, Topic M (2018) Microtextured light-management foils and their optimization for planar organic and perovskite solar cells. IEEE J Photovolt 8(3):783–792

Aurich JC, Reichenbach IG, Schüler GM (2012) Manufacture and application of ultra-small micro end mills. CIRP Ann 61(1):83–86

Chen W, Zheng L, Xie W, Yang K, Huo D (2019) Modelling and experimental investigation on textured surface generation in vibration-assisted micro-milling. J Mater Process Technol 266:339–350

Pratap T, Patra K (2020) Tribological performances of symmetrically micro-textured Ti-6Al-4V alloy for hip joint. Int J Mech Sci 182:105736

Han J, Hao X, Li L, Liu L, Chen N, Zhao G, He N (2020) Investigation on surface quality and burr generation of high aspect ratio (HAR) micro-milled grooves. J Manuf Process 52:35–43

Greco S, Kieren-Ehses S, Kirsch B, Aurich JC (2020) Micro milling of additively manufactured AISI 316L: impact of the layerwise microstructure on the process results. Int J Adv Manuf Technol 112(1-2):361–373

Tillmann W, Hagen L, Stangier D, Paulus M, Tolan M, Sakrowski R, Biermann D, Freiburg D (2019) Microstructural characteristics of high-feed milled HVOF sprayed WC-Co coatings. Surf Coat Technol 374:448–459

Zhang X, Ehmann KF, Yu T, Wang W (2016) Cutting forces in micro-end-milling processes. Int J Mach Tools Manuf 107:21–40

Sun Q, Zhou J, Li P (2022) Simulations and experiments on the micro-milling process of a thin-walled structure of Al6061-T6. Materials 15(10):3568

Fu MW, Wang JL (2021) Size effects in multi-scale materials processing and manufacturing. Int J Mach Tools Manuf 167:103755

de Oliveira FB, Rodrigues AR, Coelho RT, de Souza AF (2015) Size effect and minimum chip thickness in micromilling. Int J Mach Tools Manuf 89:39–54

Attanasio A, Gelfi M, Pola A, Ceretti E, Giardini C (2013) Influence of material microstructures in micromilling of Ti6Al4V alloy. Materials 6(9):4268–4283

Chen MJ, Ni HB, Wang ZJ, Jiang Y (2012) Research on the modeling of burr formation process in micro-ball end milling operation on Ti–6Al–4V. Int J Adv Manuf Technol 62(9-12):901–912

Baumann J, Krebs E, Biermann D (2019) Chatter avoidance in milling by using advanced cutting tools with structured functional surfaces. MM Sci J 2019(04):3019–3026

Gao Q, Li W, Chen X (2019) Surface quality and tool wear in micro-milling of single-crystal aluminum. Proc Inst Mech Eng C J Mech Eng Sci 233(16):5597–5609

Yuan Y, Jing X, Ehmann KF, Cao J, Li H, Zhang D (2018) Modeling of cutting forces in micro end-milling. J Manuf Process 31:844–858

Yuan Y, Zhang D, Jing X, Cao J, Ehmann KF (2019) Micro texture fabrication by a non-resonant vibration generator. J Manuf Process 45:732–745

He J, Guo Z, Lian H, Wang J, Chen X, Liu J (2019) Improving the machining quality of micro structures by using electrophoresis-assisted ultrasonic micromilling machining. Int J Precis Eng Manuf-Green Technol 7(1):151–161

Wang M, Zhang R, Shang Y, Zheng J, Wang X, Xu X (2023) Micro-milling microstructures in air-shielding ultrasonic assisted electrochemical machining. J Manuf Process 97:171–184

Vishnoi M, Kumar P, Murtaza Q (2021) Surface texturing techniques to enhance tribological performance: a review. Surf Interfaces 27:101463

Ronen A, Etsion I, Kligerman Y (2001) Friction-reducing surface-texturing in reciprocating automotive components. Tribol Trans 44(3):359–366

Hsu SM, Jing Y, Zhao F (2015) Self-adaptive surface texture design for friction reduction across the lubrication regimes. Surf Topogr Metrol Properties 4(1):014004

Bhaumik S, Chowdhury D, Batham A, Sehgal U, Ghosh C, Bhattacharya B, Datta S (2020) Analysing the frictional properties of micro dimpled surface created by milling machine under lubricated condition. Tribol Int 146:106260

Vogler MP, DeVor RE, Kapoor SG (2003) Microstructure-level force prediction model for micro-milling of multi-phase materials. ASME Int Mech Eng Congress Expos 125(2):202–209

Google Scholar  

Vogler MP, Kapoor SG, DeVor RE (2004) On the modeling and analysis of machining performance in micro-endmilling, part ii: cutting force prediction. J Manuf Sci Eng 126(4):695–705

Lai X, Li H, Li C, Lin Z, Ni J (2008) Modelling and analysis of micro scale milling considering size effect, micro cutter edge radius and minimum chip thickness. Int J Mach Tool Manu 48(1):1–14

Wan M, Wen D-Y, Zhang W-H, Yang Y (2023) Prediction of cutting forces in flexible micro milling processes by considering the change of instantaneous cutting direction. J Manuf Process 90:180–195

Zhou Y, Tian Y, Jing X, Ehmann KF (2017) A novel instantaneous uncut chip thickness model for mechanistic cutting force model in micro-end-milling. Int J Adv Manuf Technol 93(5-8):2305–2319

Zhang X, Yu T, Wang W (2018) Prediction of cutting forces and instantaneous tool deflection in micro end milling by considering tool run-out. Int J Mech Sci 136:124–133

Zhang X, Yu T, Xu P, Zhao J (2022) In-process stochastic tool wear identification and its application to the improved cutting force modeling of micro milling. Mech Syst Signal Process 164:108233

Zhang Y, Bai Q, Zhang F, Wang P (2022) Calculation and analysis of quasi-dynamic cutting force and specific cutting energy in micro-milling Ti6Al4V. Int J Adv Manuf Technol 120(9-10):6067–6078

Jing X, Lv R, Song B, Xu J, Jaffery SHI, Li H (2021) A novel run-out model based on spatial tool position for micro-milling force prediction. J Manuf Process 68:739–749

Zhou L, Deng B, Peng F, Yang M, Yan R (2020) Semi-analytic modelling of cutting forces in micro ball-end milling of NAK80 steel with wear-varying cutting edge and associated nonlinear process characteristics. Int J Mech Sci 169:105343

Chen N, Li L, Wu J, Qian J, He N, Reynaerts D (2019) Research on the ploughing force in micro milling of soft-brittle crystals. Int J Mech Sci 155:315–322

Zhou L, Peng FY, Yan R, Yao PF, Yang CC, Li B (2015) Analytical modeling and experimental validation of micro end-milling cutting forces considering edge radius and material strengthening effects. Int J Mach Tools Manuf 97:29–41

Xiao X, Zheng K, Liao W (2014) Theoretical model for cutting force in rotary ultrasonic milling of dental zirconia ceramics. Int J Adv Manuf Technol 75(9-12):1263–1277

Jin X, Altintas Y (2012) Prediction of micro-milling forces with finite element method. J Mater Process Technol 212(3):542–552

Thepsonthi T, Özel T (2013) Experimental and finite element simulation based investigations on micro-milling Ti-6Al-4V titanium alloy: effects of cBN coating on tool wear. J Mater Process Technol 213(4):532–542

Thepsonthi T, Özel T (2015) 3-D finite element process simulation of micro-end milling Ti-6Al-4V titanium alloy: experimental validations on chip flow and tool wear. J Mater Process Technol 221:128–145

Bai QS, Yang K, Liang YC, Yang CL, Wang B (2009) Tool runout effects on wear and mechanics behavior in microend milling. J Vac Sci Technol B Microelectron Nanometer Struct 27(3):1566

Pratap T, Patra K, Dyakonov AA (2015) Modeling cutting force in micro-milling of Ti-6Al-4V titanium alloy. Procedia Eng 129:134–139

Attanasio A, Abeni A, Özel T, Ceretti E (2018) Finite element simulation of high speed micro milling in the presence of tool run-out with experimental validations. Int J Adv Manuf Technol 100(1-4):25–35

Li H, Wu B (2016) Development of a hybrid cutting force model for micromilling of brass. Int J Mech Sci 115-116:586–595

Sahoo P, Pratap T, Patra K (2019) A hybrid modelling approach towards prediction of cutting forces in micro end milling of Ti-6Al-4V titanium alloy. Int J Mech Sci 150:495–509

Sahoo P, Patra K, Singh VK, Gupta MK, Song Q, Mia M, Pimenov DY (2020) Influences of TiAlN coating and limiting angles of flutes on prediction of cutting forces and dynamic stability in micro milling of die steel (P-20). J Mater Process Technol 278:116500

Liu H, Xu X, Zhang J, Liu Z, He Y, Zhao W, Liu Z (2022) The state of the art for numerical simulations of the effect of the microstructure and its evolution in the metal-cutting processes. Int J Mach Tools Manuf 177:103890

Wu Y, Chen N, Bian R, He N, Li Z, Li L (2020) Investigations on burr formation mechanisms in micro milling of high-aspect-ratio titanium alloy ti-6al-4 v structures. Int J Mech Sci 185:105884

Rahman MA, Amrun MR, Rahman M, Kumar AS (2017) Variation of surface generation mechanisms in ultra-precision machining due to relative tool sharpness (RTS) and material properties. Int J Mach Tools Manuf 115:15–28

Ji H, Song Q, Du Y, Zhao Y, Liu Z (2022) Grain-scale material removal mechanisms of crystalline material micro-cutting. Int J Mech Sci 233:107671

Popov KB, Dimov SS, Pham DT, Minev RM, Rosochowski A, Olejnik L (2006) Micromilling: material microstructure effects. Proc Inst Mech Eng B J Eng Manuf 220(11):1807–1813

Han J, Ma R, Kong L, Hao X, Chen N, Li L, He N (2022) Investigation on chip formation mechanism of high-aspect-ratio micro-milled structures. J Manuf Process 80:743–753

Zhang C, Feng P, Zhang J, Wu Z, Yu D (2012) Investigation into the rotary ultrasonic face milling of K9 glass with mechanism study of material removal. Int J Manuf Technol Manag 25(4):248–266

Wang J, Yan Y, Li C, Geng Y (2023) Material removal mechanism and subsurface characteristics of silicon 3D nanomilling. Int J Mech Sci 242:108020

Wang J, Yan Y, Li Z, Geng Y, Luo X, Fan P (2021) Processing outcomes of atomic force microscope tip-based nanomilling with different trajectories on single-crystal silicon. Precis Eng 72:480–490

Aramcharoen A, Mativenga PT (2009) Size effect and tool geometry in micromilling of tool steel. Precis Eng 33(4):402–407

Sahoo P, Patra K, Szalay T, Dyakonov AA (2020) Determination of minimum uncut chip thickness and size effects in micro-milling of P-20 die steel using surface quality and process signal parameters. Int J Adv Manuf Technol 106(11-12):4675–4691

Filiz S, Xie L, Weiss LE, Ozdoganlar OB (2008) Micromilling of microbarbs for medical implants. Int J Mach Tools Manuf 48(3-4):459–472

Arslan A, Masjuki HH, Kalam MA, Varman M, Mufti RA, Mosarof MH, Khuong LS, Quazi MM (2016) Surface texture manufacturing techniques and tribological effect of surface texturing on cutting tool performance: a review. Crit Rev Solid State Mater Sci 41(6):447–481

Boswell B, Islam MN, Davies IJ (2017) A review of micro-mechanical cutting. Int J Adv Manuf Technol 94(1-4):789–806

Sun Y, Gong YD, Wen XL, Yin GQ, Meng FT (2020) Micro milling characteristics of LS-WEDM fabricated helical and corrugated micro end mill. Int J Mech Sci 167:105277

Suzuki H, Okada M, Fujii K, Matsui S, Yamagata Y (2013) Development of micro milling tool made of single crystalline diamond for ceramic cutting. CIRP Ann 62(1):59–62

Chen N, Li HN, Wu J, Li Z, Li L, Liu G, He N (2021) Advances in micro milling: from tool fabrication to process outcomes. Int J Mach Tools Manuf 160:103670

Han J, Hao X, Li L, He N, Zhao G, Chen N (2019) Fabrication of large aspect ratio (LAR) PCD micro-end mill with a hybrid method and performance verification. Int J Adv Manuf Technol 104(1-4):1473–1483

Han J, Ma R, Kong L, He B, Hao X, He Q, Li L, He N (2022) Investigation on self-fabricated PCD cutter and its application in deep-and-narrow micro-grooves. Int J Adv Manuf Technol 119(9-10):6743–6760

Elias JV, Venkatesh NP, Lawrence KD, Mathew J (2020) Tool texturing for micro-turning applications – an approach using mechanical micro indentation. Mater Manuf Process 36(1):84–93

Guo X, Huang Q, Wang C, Liu T, Zhang Y, He H, Zhang K (2022) Effect of magnetic field on cutting performance of micro-textured tools under Fe3O4 nanofluid lubrication condition. J Mater Process Technol 299:117382

Wood RW, Loomis AL (2009) The physical and biological effects of high-frequency sound-waves of great intensity. London Edinburgh Dublin Philos Mag J Sci 4(22):417–436

Mokhtari A, Jalili MM, Mazidi A, Abootorabi MM (2019) Size dependent vibration analysis of micro-milling operations with process damping and structural nonlinearities. Eur J Mech A/Solids 76:57–69

Article   MathSciNet   Google Scholar  

Liu X, Wu D, Zhang J, Hu X, Cui P (2019) Analysis of surface texturing in radial ultrasonic vibration-assisted turning. J Mater Process Technol 267:186–195

Kuo K, Tsao C (2012) Rotary ultrasonic-assisted milling of brittle materials. Trans Nonferrous Metals Soc China 22:s793–s800

Sun L, Zheng K, Liao W, Liu J, Feng J, Dong S (2020) Investigation on chatter stability of robotic rotary ultrasonic milling. Robot Comput Integr Manuf 63:101911

Qin S, Zhu L, Wiercigroch M, Ren T, Hao Y, Ning J, Zhao J (2022) Material removal and surface generation in longitudinal-torsional ultrasonic assisted milling. Int J Mech Sci 227:107375

Shen X-H, Xu G-F (2017) Study of milling force variation in ultrasonic vibration-assisted end milling. Mater Manuf Process 33(6):644–650

Chen W, Zheng L, Huo D, Chen Y (2018) Surface texture formation by non-resonant vibration assisted micro milling. J Micromech Microeng 28(2):025006

Maroju NK, Jin X (2018) Vibration-assisted dimple generation on bulk metallic glass. Procedia Manuf 26:317–328

Li K-M, Wang S-L (2013) Effect of tool wear in ultrasonic vibration-assisted micro-milling. Proc Inst Mech Eng B J Eng Manuf 228(6):847–855

Liu Q, Xu J, Yu H (2020) Experimental study of tool wear and its effects on cutting process of ultrasonic-assisted milling of Ti6Al4V. Int J Adv Manuf Technol 108(9-10):2917–2928

Shen XH, Shi YL, Zhang JH, Zhang QJ, Tao GC, Bai LJ (2020) Effect of process parameters on micro-textured surface generation in feed direction vibration assisted milling. Int J Mech Sci 167:105267

Zheng Z, Zhang J, Feng P, Wang J (2023) Controllable fabrication of microstructures on the metallic surface using oblique rotary ultrasonic milling. Int J Mech Sci 237:107805

Zhang Z, Liu W, Chen X, Zhang Y, Xu C, Wang K, Wang W, Jiang X (2022) Generation mechanism of surface micro-texture in axial ultrasonic vibration-assisted milling (AUVAM). Int J Adv Manuf Technol 122(3-4):1651–1667

Lu H, Zhu L, Yang Z, Lu H, Yan B, Hao Y, Qin S (2021) Research on the generation mechanism and interference of surface texture in ultrasonic vibration assisted milling. Int J Mech Sci 208:106681

Huang F, Jin X (2021) Surface texture generation using high-feed milling with spindle speed modulation. Precis Eng 72:13–24

Amini S, Baraheni M, Khaki M (2021) Empirical study on ultrasonic assisted turn-milling. Proc Inst Mech Eng Part E J Process Mech Eng 235(5):1469–1478

Hao X, Xu W, Chen M, Wang C, Han J, Li L, He N (2021) Laser hybridizing with micro-milling for fabrication of high aspect ratio micro-groove on oxygen-free copper. Precis Eng 70:15–25

Zou X, Jiang B, Wang Z (2023) Laser surface texturing-based hybrid micro-milling of Ti6Al4V alloy. Int J Adv Manuf Technol 125(9-10):4341–4352

Xia H, Zhao G, Zhang Y, Li L, He N, Hansen HN (2022) Nanosecond laser-induced controllable oxidation of TiB2–TiC ceramic composites for subsequent micro milling. Ceram Int 48(2):2470–2481

Nakamoto K, Katahira K, Ohmori H, Yamazaki K, Aoyama T (2012) A study on the quality of micro-machined surfaces on tungsten carbide generated by PCD micro end-milling. CIRP Ann 61(1):567–570

Gao X, Cheng X, Ling S, Zheng G, Li Y, Liu H (2022) Research on optimization of micro-milling process for curved thin wall structure. Precis Eng 73:296–312

Kakinuma Y, Kidani S, Aoyama T (2012) Ultra-precision cryogenic machining of viscoelastic polymers. CIRP Ann 61(1):79–82

Liu Q, Cheng J, Liao Z, Luo X, Yang Y, Li M, Yang H, Tan C, Wang G, Ding W, Yin Z, Zhao L, Chen M (2023) Research on the light intensity modulation and characterizing methods of surface texture on KDP optics generated in fly-cutting and micro ball-end milling processes. CIRP J Manuf Sci Technol 41:30–43

Wang J, Yan Y, Li Z, Geng Y (2021) Towards understanding the machining mechanism of the atomic force microscopy tip-based nanomilling process. Int J Mach Tools Manuf 162:103701

Reichenbach IG, Aurich JC (2014) Application of CAD/CAM and micro end mills with 20 to 120 μm diameter for the direct machining of microstructures in PMMA. Adv Mater Res 907:299–306

Cheng CT, Zhang G, To S (2016) Wetting characteristics of bare micro-patterned cyclic olefin copolymer surfaces fabricated by ultra-precision raster milling. RSC Adv 6(2):1562–1570

Wang G, Yu T, Zhou X, Guo R, Chen M, Sun Y (2023) Material removal mechanism and microstructure fabrication of GDP during micro-milling. Int J Mech Sci 240:107946

Weinert K, Petzoldt V (2008) Machining NiTi micro-parts by micro-milling. Mater Sci Eng A 481-482:672–675

Du H, Wu C, Li D, Yip WS, Wang Z, Ta S (2023) Feasibility study on ultraprecision micro-milling of the additively manufactured NiTi alloy for generating microstructure arrays. J Mater Res Technol 25:55–67

Wan, Y.; Zhang, X.; Yu, Z.; Xu, J.; Yu, H., High speed micro-milling experiment of hydrophobic microstructure 2013 IEEE International Conference on Mechatronics and Automation, Takamatsu, Japan 2013, 174-178.

Shi Z, Liu Z, Song H, Zhang X (2016) Prediction of contact angle for hydrophobic surface fabricated with micro-machining based on minimum Gibbs free energy. Appl Surf Sci 364:597–603

Pratap T, Patra K (2018) Mechanical micro-texturing of Ti-6Al-4V surfaces for improved wettability and bio-tribological performances. Surf Coat Technol 349:71–81

Jain A, Bajpai V (2019) Mechanical micro-texturing and characterization on Ti6Al4V for the improvement of surface properties. Surf Coat Technol 380:125087

Jain A, Kumari N, Jagadevan S, Bajpaia V (2020) Surface properties and bacterial behavior of micro conical dimple textured Ti6Al4V surface through micro-milling. Surf Interfaces 21:100714

Hosseinabadi HN, Sajjady SA, Amini S (2018) Creating micro textured surfaces for the improvement of surface wettability through ultrasonic vibration assisted turning. Int J Adv Manuf Technol 96(5-8):2825–2839

Shen X, Tao G (2015) Tribological behaviors of two micro textured surfaces generated by vibrating milling under boundary lubricated sliding. Int J Adv Manuf Technol 79(9-12):1995–2002

Konneh, M.; Bagum, M. N.; Ali, M. Y.; Amin, A. K. M. N., Surface morphology study in high speed milling of soda lime glass. In 8th International Conference on Nanoscience and Nanotechnology 2017 (Nano-SciTech 2017), 2018; Vol. 1958, p 020005.

Wang J, Wang Y, Yang Y, Yang R, Liao W-H, Guo P (2020) Fabrication of structurally colored basso-relievo with modulated elliptical vibration texturing. Precis Eng 64:113–121

Torta M, Albertelli P, Monno M (2020) Surface morphology prediction model for milling operations. Int J Adv Manuf Technol 106(7-8):3189–3201

Chen P-C, Pan C-W, Lee W-C, Li K-M (2014) Optimization of micromilling microchannels on a polycarbonate substrate. Int J Precis Eng Manuf 15(1):149–154

Yuan W, Li L, Lee W, Chan C (2018) Fabrication of microlens array and its application: a review. Chin J Mech Eng 31(1)

Sun Z, To S, Yu KM (2018) One-step generation of hybrid micro-optics with high-frequency diffractive structures on infrared materials by ultra-precision side milling. Opt Express 26(21):28161–28177

Wang P, Bai Q, Cheng K, Zhao L, Zhang Y (2023) Multi-objective optimization of micro-milling parameters—the trade-offs between machining quality, efficiency, and sustainability in the fabrication of thin-walled microstructures. Appl Sci 13(16)

Zhang Y, Bai Q, Wang P (2023) 3D surface topography analysis and functionality-related performance of the machined surface in slot micro-milling titanium alloy Ti6Al4V. Int J Adv Manuf Technol 127(3-4):1609–1629

Yang Y, Han J, Hao X, Li L, He N (2019) Investigation on micro-milling of micro-grooves with high aspect ratio and laser deburring. Proc Inst Mech Eng B J Eng Manuf 234(5):871–880

Dutterer BS, Lineberger JL, Smilie PJ, Hildebrand DS, Harriman TA, Davies MA, Suleski TJ, Lucca DA (2014) Diamond milling of an Alvarez lens in germanium. Precis Eng 38(2):398–408

Li L, Yi AY (2010) Development of a 3D artificial compound eye. Opt Express 18(17):18125–18137

Ding W, Cao Z, Wang B, Xu S, Wang Z (2019) Construction of grating structure model based on Gibbs free energy and experimental verification by micro-milling. Appl Phys A 125(6):380

Hu P, Lei W, Jiang Y, Huang Y, Song R, Chen H, Dong Y (2018) Development of a 0.32-THz folded waveguide traveling wave tube. IEEE Trans Electron Devices 65(6):2164–2169

Bhardwaj RK, Sudhamani HS, Dutta VP, Bhatnagar N (2021) Micromachining and characterisation of folded waveguide structure at 0.22THz. J Infrared Millim Terahertz Waves 42(3):229–238

Özel T, Biermann D, Enomoto T, Mativenga P (2021) Structured and textured cutting tool surfaces for machining applications. CIRP Ann 70(2):495–518

Wang G, Wan Y, Ren B, Liu Z (2019) Bioactivity of micropatterned TiO(2) nanotubes fabricated by micro-milling and anodic oxidation. Mater Sci Eng C Mater Biol Appl 95:114–121

Lin YS, Yang CH, Wang CY, Chang FR, Huang KS, Hsieh WC (2012) An aluminum microfluidic chip fabrication using a convenient micromilling process for fluorescent poly(DL-lactide-co-glycolide) microparticle generation. Sensors 12(2):1455–1467

Jung YC, Bhushan B (2010) Biomimetic structures for fluid drag reduction in laminar and turbulent flows. J Phys Condens Matter 22(3):035104

Yao C-W, Lai C-L, Alvarado JL, Zhou J, Aung KT, Mejia JE (2017) Experimental study on effect of surface vibration on micro textured surfaces with hydrophobic and hydrophilic materials. Appl Surf Sci 412:45–51

Chakraborty A, Mulroney AT, Gupta MC (2021) Superhydrophobic surfaces by microtexturing: a critical review. Prog Adhes Adhes 6:621–649

Wan Y, Yang J, Yu H (2018) Superhydrophobic surface prepared by micro-milling and WEDM on aluminum alloy. Mater Res Express 5(6):066504

Zhang X, Wan Y, Ren B, Wang H, Yu M, Liu A, Liu Z (2020) Preparation of superhydrophobic surface on titanium alloy via micro-milling, anodic oxidation and fluorination. Micromachines 11(3):316

Pei S, Xu H, Yun M, Shi F, Hong J (2016) Effects of surface texture on the lubrication performance of the floating ring bearing. Tribol Int 102:143–153

Henry Y, Bouyer J, Fillon M (2014) An experimental analysis of the hydrodynamic contribution of textured thrust bearings during steady-state operation: a comparison with the untextured parallel surface configuration. Proc Inst Mech Eng Part J J Eng Tribol 229(4):362–375

Yue H, Deng J, Ge D, Li X, Zhang Y (2019) Effect of surface texturing on tribological performance of sliding guideway under boundary lubrication. J Manuf Process 47:172–182

Grabon W, Koszela W, Pawlus P, Ochwat S (2013) Improving tribological behaviour of piston ring–cylinder liner frictional pair by liner surface texturing. Tribol Int 61:102–108

Hamilton DB, Walowit JA, Allen CM (1966) A theory of lubrication by microirregularities. J Basic Eng 88(1):177–185

Tillmann W, Stangier D, Lopes-Dias N-F, Biermann D, Krebs E (2017) Adjustment of friction by duplex-treated, bionic structures for Sheet-Bulk Metal Forming. Tribol Int 111:9–17

Xu J, Feng P, Feng F, Zha H, Liang G (2021) Subsurface damage and burr improvements of aramid fiber reinforced plastics by using longitudinal–torsional ultrasonic vibration milling. J Mater Process Technol 297

Download references

This work is supported by grant 51875005 from the National Natural Science Foundation of China.

Author information

Authors and affiliations.

Mechanical Industry Key Laboratory of Heavy Machine Tool Digital Design and Testing, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, 100124, China

Zhiwen Jiang, Dongju Chen, Kun Sun, Ri Pan & Jinwei Fan

Beijing Key Laboratory of Advanced Manufacturing Technology, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, 100124, China

Beijing Institute of Control Engineering, Beijing, 100190, China

Yuhang Tang

You can also search for this author in PubMed   Google Scholar

Contributions

Zhiwen Jiang involved in conceptualization, methodology, and writing original draft. Dongju Chen supervised and provided fund support. Kun Sun, Ri Pan, Jinwei Fan, and Yuhang Tang conducted review, editing, and supervision.

Corresponding author

Correspondence to Dongju Chen .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Jiang, Z., Chen, D., Sun, K. et al. A systematic review of micro-texture formation based on milling: from mechanism, existing techniques, characterization to typical applications. Int J Adv Manuf Technol (2024). https://doi.org/10.1007/s00170-024-14177-4

Download citation

Received : 13 December 2023

Accepted : 21 July 2024

Published : 27 August 2024

DOI : https://doi.org/10.1007/s00170-024-14177-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Milling-based micro-texturing
• Surface texture generation mechanism
• Performance characterization
• Typical applications
• Find a journal
• Publish with us
• Track your research