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Research Summary – Structure, Examples and Writing Guide

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Research Summary

Definition:

A research summary is a brief and concise overview of a research project or study that highlights its key findings, main points, and conclusions. It typically includes a description of the research problem, the research methods used, the results obtained, and the implications or significance of the findings. It is often used as a tool to quickly communicate the main findings of a study to other researchers, stakeholders, or decision-makers.

Structure of Research Summary

The Structure of a Research Summary typically include:

• Introduction : This section provides a brief background of the research problem or question, explains the purpose of the study, and outlines the research objectives.
• Methodology : This section explains the research design, methods, and procedures used to conduct the study. It describes the sample size, data collection methods, and data analysis techniques.
• Results : This section presents the main findings of the study, including statistical analysis if applicable. It may include tables, charts, or graphs to visually represent the data.
• Discussion : This section interprets the results and explains their implications. It discusses the significance of the findings, compares them to previous research, and identifies any limitations or future directions for research.
• Conclusion : This section summarizes the main points of the research and provides a conclusion based on the findings. It may also suggest implications for future research or practical applications of the results.
• References : This section lists the sources cited in the research summary, following the appropriate citation style.

How to Write Research Summary

Here are the steps you can follow to write a research summary:

• Read the research article or study thoroughly: To write a summary, you must understand the research article or study you are summarizing. Therefore, read the article or study carefully to understand its purpose, research design, methodology, results, and conclusions.
• Identify the main points : Once you have read the research article or study, identify the main points, key findings, and research question. You can highlight or take notes of the essential points and findings to use as a reference when writing your summary.
• Write the introduction: Start your summary by introducing the research problem, research question, and purpose of the study. Briefly explain why the research is important and its significance.
• Summarize the methodology : In this section, summarize the research design, methods, and procedures used to conduct the study. Explain the sample size, data collection methods, and data analysis techniques.
• Present the results: Summarize the main findings of the study. Use tables, charts, or graphs to visually represent the data if necessary.
• Interpret the results: In this section, interpret the results and explain their implications. Discuss the significance of the findings, compare them to previous research, and identify any limitations or future directions for research.
• Conclude the summary : Summarize the main points of the research and provide a conclusion based on the findings. Suggest implications for future research or practical applications of the results.
• Revise and edit : Once you have written the summary, revise and edit it to ensure that it is clear, concise, and free of errors. Make sure that your summary accurately represents the research article or study.
• Add references: Include a list of references cited in the research summary, following the appropriate citation style.

Example of Research Summary

Here is an example of a research summary:

Title: The Effects of Yoga on Mental Health: A Meta-Analysis

Introduction: This meta-analysis examines the effects of yoga on mental health. The study aimed to investigate whether yoga practice can improve mental health outcomes such as anxiety, depression, stress, and quality of life.

Methodology : The study analyzed data from 14 randomized controlled trials that investigated the effects of yoga on mental health outcomes. The sample included a total of 862 participants. The yoga interventions varied in length and frequency, ranging from four to twelve weeks, with sessions lasting from 45 to 90 minutes.

Results : The meta-analysis found that yoga practice significantly improved mental health outcomes. Participants who practiced yoga showed a significant reduction in anxiety and depression symptoms, as well as stress levels. Quality of life also improved in those who practiced yoga.

Discussion : The findings of this study suggest that yoga can be an effective intervention for improving mental health outcomes. The study supports the growing body of evidence that suggests that yoga can have a positive impact on mental health. Limitations of the study include the variability of the yoga interventions, which may affect the generalizability of the findings.

Conclusion : Overall, the findings of this meta-analysis support the use of yoga as an effective intervention for improving mental health outcomes. Further research is needed to determine the optimal length and frequency of yoga interventions for different populations.

References :

• Cramer, H., Lauche, R., Langhorst, J., Dobos, G., & Berger, B. (2013). Yoga for depression: a systematic review and meta-analysis. Depression and anxiety, 30(11), 1068-1083.
• Khalsa, S. B. (2004). Yoga as a therapeutic intervention: a bibliometric analysis of published research studies. Indian journal of physiology and pharmacology, 48(3), 269-285.
• Ross, A., & Thomas, S. (2010). The health benefits of yoga and exercise: a review of comparison studies. The Journal of Alternative and Complementary Medicine, 16(1), 3-12.

Purpose of Research Summary

The purpose of a research summary is to provide a brief overview of a research project or study, including its main points, findings, and conclusions. The summary allows readers to quickly understand the essential aspects of the research without having to read the entire article or study.

Research summaries serve several purposes, including:

• Facilitating comprehension: A research summary allows readers to quickly understand the main points and findings of a research project or study without having to read the entire article or study. This makes it easier for readers to comprehend the research and its significance.
• Communicating research findings: Research summaries are often used to communicate research findings to a wider audience, such as policymakers, practitioners, or the general public. The summary presents the essential aspects of the research in a clear and concise manner, making it easier for non-experts to understand.
• Supporting decision-making: Research summaries can be used to support decision-making processes by providing a summary of the research evidence on a particular topic. This information can be used by policymakers or practitioners to make informed decisions about interventions, programs, or policies.
• Saving time: Research summaries save time for researchers, practitioners, policymakers, and other stakeholders who need to review multiple research studies. Rather than having to read the entire article or study, they can quickly review the summary to determine whether the research is relevant to their needs.

Characteristics of Research Summary

The following are some of the key characteristics of a research summary:

• Concise : A research summary should be brief and to the point, providing a clear and concise overview of the main points of the research.
• Objective : A research summary should be written in an objective tone, presenting the research findings without bias or personal opinion.
• Comprehensive : A research summary should cover all the essential aspects of the research, including the research question, methodology, results, and conclusions.
• Accurate : A research summary should accurately reflect the key findings and conclusions of the research.
• Clear and well-organized: A research summary should be easy to read and understand, with a clear structure and logical flow.
• Relevant : A research summary should focus on the most important and relevant aspects of the research, highlighting the key findings and their implications.
• Audience-specific: A research summary should be tailored to the intended audience, using language and terminology that is appropriate and accessible to the reader.
• Citations : A research summary should include citations to the original research articles or studies, allowing readers to access the full text of the research if desired.

When to write Research Summary

Here are some situations when it may be appropriate to write a research summary:

• Proposal stage: A research summary can be included in a research proposal to provide a brief overview of the research aims, objectives, methodology, and expected outcomes.
• Conference presentation: A research summary can be prepared for a conference presentation to summarize the main findings of a study or research project.
• Journal submission: Many academic journals require authors to submit a research summary along with their research article or study. The summary provides a brief overview of the study’s main points, findings, and conclusions and helps readers quickly understand the research.
• Funding application: A research summary can be included in a funding application to provide a brief summary of the research aims, objectives, and expected outcomes.
• Policy brief: A research summary can be prepared as a policy brief to communicate research findings to policymakers or stakeholders in a concise and accessible manner.

Advantages of Research Summary

Research summaries offer several advantages, including:

• Time-saving: A research summary saves time for readers who need to understand the key findings and conclusions of a research project quickly. Rather than reading the entire research article or study, readers can quickly review the summary to determine whether the research is relevant to their needs.
• Clarity and accessibility: A research summary provides a clear and accessible overview of the research project’s main points, making it easier for readers to understand the research without having to be experts in the field.
• Improved comprehension: A research summary helps readers comprehend the research by providing a brief and focused overview of the key findings and conclusions, making it easier to understand the research and its significance.
• Enhanced communication: Research summaries can be used to communicate research findings to a wider audience, such as policymakers, practitioners, or the general public, in a concise and accessible manner.
• Facilitated decision-making: Research summaries can support decision-making processes by providing a summary of the research evidence on a particular topic. Policymakers or practitioners can use this information to make informed decisions about interventions, programs, or policies.
• Increased dissemination: Research summaries can be easily shared and disseminated, allowing research findings to reach a wider audience.

Limitations of Research Summary

Limitations of the Research Summary are as follows:

• Limited scope: Research summaries provide a brief overview of the research project’s main points, findings, and conclusions, which can be limiting. They may not include all the details, nuances, and complexities of the research that readers may need to fully understand the study’s implications.
• Risk of oversimplification: Research summaries can be oversimplified, reducing the complexity of the research and potentially distorting the findings or conclusions.
• Lack of context: Research summaries may not provide sufficient context to fully understand the research findings, such as the research background, methodology, or limitations. This may lead to misunderstandings or misinterpretations of the research.
• Possible bias: Research summaries may be biased if they selectively emphasize certain findings or conclusions over others, potentially distorting the overall picture of the research.
• Format limitations: Research summaries may be constrained by the format or length requirements, making it challenging to fully convey the research’s main points, findings, and conclusions.
• Accessibility: Research summaries may not be accessible to all readers, particularly those with limited literacy skills, visual impairments, or language barriers.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Writing a Summary – Explanation & Examples

Published by Alvin Nicolas at October 17th, 2023 , Revised On October 17, 2023

In a world bombarded with vast amounts of information, condensing and presenting data in a digestible format becomes invaluable. Enter summaries. 

A summary is a brief and concise account of the main points of a larger body of work. It distils complex ideas, narratives, or data into a version that is quicker to read and easier to understand yet still retains the essence of the original content.

Importance of Summaries

The importance of summarising extends far beyond just making reading more manageable. In academic settings, summaries aid students in understanding and retaining complex materials, from textbook chapters to research articles. They also serve as tools to showcase one’s grasp of the subject in essays and reports. 

In professional arenas, summaries are pivotal in business reports, executive briefings, and even emails where key points need to be conveyed quickly to decision-makers. Meanwhile, summarising skills come into play in our personal lives when we relay news stories to friends, recap a movie plot, or even scroll through condensed news or app notifications on our smartphones.

Why Do We Write Summaries?

In our modern information age, the sheer volume of content available can be overwhelming. From detailed research papers to comprehensive news articles, the quest for knowledge is often met with lengthy and complex resources. This is where the power of a well-crafted summary comes into play. But what drives us to create or seek out summaries? Let’s discuss.

Makes Important Things Easy to Remember

At the heart of summarisation is the goal to understand. A well-written summary aids in digesting complex material. By distilling larger works into their core points, we reinforce the primary messages, making them easier to remember. This is especially crucial for students who need to retain knowledge for exams or professionals prepping for a meeting based on a lengthy report.

Simplification of Complex Topics

Not everyone is an expert in every field. Often, topics come laden with jargon, intricate details, and nuanced arguments. Summaries act as a bridge, translating this complexity into accessible and straightforward content. This is especially beneficial for individuals new to a topic or those who need just the highlights without the intricacies.

Aid in Researching and Understanding Diverse Sources

Researchers, writers, and academics often wade through many sources when working on a project. This involves finding sources of different types, such as primary or secondary sources , and then understanding their content. Sifting through each source in its entirety can be time-consuming. Summaries offer a streamlined way to understand each source’s main arguments or findings, making synthesising information from diverse materials more efficient.

Condensing Information for Presentation or Sharing

In professional settings, there is often a need to present findings, updates, or recommendations to stakeholders. An executive might not have the time to go through a 50-page report, but they would certainly appreciate a concise summary highlighting the key points. Similarly, in our personal lives, we often summarise movie plots, book stories, or news events when sharing with friends or family.

Characteristics of a Good Summary

Crafting an effective summary is an art. It’s more than just shortening a piece of content; it is about capturing the essence of the original work in a manner that is both accessible and true to its intent. Let’s explore the primary characteristics that distinguish a good summary from a mediocre one:

Conciseness

At the core of a summary is the concept of brevity. But being concise doesn’t mean leaving out vital information. A good summary will:

• Eliminate superfluous details or repetitive points.
• Focus on the primary arguments, events, or findings.
• Use succinct language without compromising the message.

Objectivity

Summarising is not about infusing personal opinions or interpretations. A quality summary will:

• Stick to the facts as presented in the original content.
• Avoid introducing personal biases or perspectives.
• Represent the original author’s intent faithfully.

A summary is meant to simplify and make content accessible. This is only possible if the summary itself is easy to understand. Ensuring clarity involves:

• Avoiding jargon or technical terms unless they are essential to the content. If they are used, they should be clearly defined.
• Structuring sentences in a straightforward manner.
• Making sure ideas are presented in a way that even someone unfamiliar with the topic can grasp the primary points.

A jumble of ideas, no matter how concise, will not make for a good summary. Coherence ensures that there’s a logical flow to the summarised content. A coherent summary will:

• Maintain a logical sequence, often following the structure of the original content.
• Use transition words or phrases to connect ideas and ensure smooth progression.
• Group related ideas together to provide structure and avoid confusion.

Steps of Writing a Summary

The process of creating a compelling summary is not merely about cutting down content. It involves understanding, discerning, and crafting. Here is a step-by-step guide to writing a summary that encapsulates the essence of the original work:

Reading Actively

Engage deeply with the content to ensure a thorough understanding.

• Read the entire document or work first to grasp its overall intent and structure.
• On the second read, underline or highlight the standout points or pivotal moments.
• Make brief notes in the margins or on a separate sheet, capturing the core ideas in your own words.

Identifying the Main Idea

Determine the backbone of the content, around which all other details revolve.

• Ask yourself: “What is the primary message or theme the author wants to convey?”
• This can often be found in the title, introduction, or conclusion of a piece.
• Frame the main idea in a clear and concise statement to guide your summary.

List Key Supporting Points

Understand the pillars that uphold the main idea, providing evidence or depth to the primary message.

• Refer back to the points you underlined or highlighted during your active reading.
• Note major arguments, evidence, or examples that the author uses to back up the main idea.
• Prioritise these points based on their significance to the main idea.

Draft the Summary

Convert your understanding into a condensed, coherent version of the original.

• Start with a statement of the main idea.
• Follow with the key supporting points, maintaining logical order.
• Avoid including trivial details or examples unless they’re crucial to the primary message.
• Use your own words, ensuring you are not plagiarising the original content.

Fine-tune your draft to ensure clarity, accuracy, and brevity.

• Read your draft aloud to check for flow and coherence.
• Ensure that your summary remains objective, avoiding any personal interpretations or biases.
• Check the length. See if any non-essential details can be removed without sacrificing understanding if it is too lengthy.
• Ensure clarity by ensuring the language is straightforward, and the main ideas are easily grasped.

The research done by our experts have:

• Precision and Clarity
• Zero Plagiarism
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Dos and Don’ts of Summarising Key Points

Summarising, while seemingly straightforward, comes with its nuances. Properly condensing content demands a balance between brevity and fidelity to the original work. To aid in crafting exemplary summaries, here is a guide on the essential dos and don’ts:

Use your Own Words

This ensures that you have truly understood the content and are not merely parroting it. It also prevents issues of plagiarism.

Tip: After reading the original content, take a moment to reflect on it. Then, without looking at the source, write down the main points in your own words.

Attribute Sources Properly

Giving credit is both ethical and provides context to readers, helping them trace back to the original work if needed. How to cite sources correctly is a skill every writer should master.

Tip: Use signal phrases like “According to [Author/Source]…” or “As [Author/Source] points out…” to seamlessly incorporate attributions.

Ensure Accuracy of the Summarised Content

A summary should be a reliable reflection of the original content. Distorting or misrepresenting the original ideas compromises the integrity of the summary.

Tip: After drafting your summary, cross-check with the original content to ensure all key points are represented accurately and ensure you are referencing credible sources .

Avoid Copy-Pasting Chunks of Original Content

This not only raises plagiarism concerns but also shows a lack of genuine engagement with the material.

Tip: If a particular phrase or sentence from the original is pivotal and cannot be reworded without losing its essence, use block quotes , quotation marks, and attribute the source.

Do not Inject your Personal Opinion

A summary should be an objective reflection of the source material. Introducing personal biases or interpretations can mislead readers.

Tip: Stick to the facts and arguments presented in the original content. If you find yourself writing “I think” or “In my opinion,” reevaluate the sentence.

Do not Omit Crucial Information

While a summary is meant to be concise, it shouldn’t be at the expense of vital details that are essential to understanding the original content’s core message.

Tip: Prioritise information. Always include the main idea and its primary supports. If you are unsure whether a detail is crucial, consider its impact on the overall message.

Examples of Summaries

Here are a few examples that will help you get a clearer view of how to write a summary. 

Example 1: Summary of a News Article

Original Article: The article reports on the recent discovery of a rare species of frog in the Amazon rainforest. The frog, named the “Emerald Whisperer” due to its unique green hue and the soft chirping sounds it makes, was found by a team of researchers from the University of Texas. The discovery is significant as it offers insights into the biodiversity of the region, and the Emerald Whisperer might also play a pivotal role in understanding the ecosystem balance.

Summary: Researchers from the University of Texas have discovered a unique frog, termed the “Emerald Whisperer,” in the Amazon rainforest. This finding sheds light on the region’s biodiversity and underscores the importance of the frog in ecological studies.

Example 2: Summary of a Research Paper

Original Paper: In a study titled “The Impact of Urbanisation on Bee Populations,” researchers conducted a year-long observation on bee colonies in three urban areas and three rural areas. Using specific metrics like colony health, bee productivity, and population size, the study found that urban environments saw a 30% decline in bee populations compared to rural settings. The research attributes this decline to factors like pollution, reduced green spaces, and increased temperatures in urban areas.

Summary: A study analysing the effects of urbanisation on bee colonies found a significant 30% decrease in bee populations in urban settings compared to rural areas. The decline is linked to urban factors such as pollution, diminished greenery, and elevated temperatures.

Example 3: Summary of a Novel

Original Story: In the novel “Winds of Fate,” protagonist Clara is trapped in a timeless city where memories dictate reality. Throughout her journey, she encounters characters from her past, present, and imagined future. Battling her own perceptions and a menacing shadow figure, Clara seeks an elusive gateway to return to her real world. In the climax, she confronts the shadow, which turns out to be her own fear, and upon overcoming it, she finds her way back, realising that reality is subjective.

Summary: “Winds of Fate” follows Clara’s adventures in a surreal city shaped by memories. Confronting figures from various phases of her life and battling a symbolic shadow of her own fear, Clara eventually discovers that reality’s perception is malleable and subjective.

Frequently Asked Questions

How long is a summary.

A summary condenses a larger piece of content, capturing its main points and essence.  It is usually one-fourth of the original content.

What is a summary?

A summary is a concise representation of a larger text or content, highlighting its main ideas and points. It distils complex information into a shorter form, allowing readers to quickly grasp the essence of the original material without delving into extensive details. Summaries prioritise clarity, brevity, and accuracy.

When should I write a summary?

Write a summary when you need to condense lengthy content for easier comprehension and recall. It’s useful in academic settings, professional reports, presentations, and research to highlight key points. Summaries aid in comparing multiple sources, preparing for discussions, and sharing essential details of extensive materials efficiently with others.

How can I summarise a source without plagiarising?

To summarise without plagiarising: Read the source thoroughly, understand its main ideas, and then write the summary in your own words. Avoid copying phrases verbatim. Attribute the source properly. Use paraphrasing techniques and cross-check your summary against the original to ensure distinctiveness while retaining accuracy. Always prioritise understanding over direct replication.

What is the difference between a summary and an abstract?

A summary condenses a text, capturing its main points from various content types like books, articles, or movies. An abstract, typically found in research papers and scientific articles, provides a brief overview of the study’s purpose, methodology, results, and conclusions. Both offer concise versions, but abstracts are more structured and specific.

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The ability to effectively incorporate multiple sources into one’s work is not just a skill, but a necessity. Whether we are talking about research papers, articles, or even simple blog posts, synthesising sources can elevate our content to a more nuanced, comprehensive, and insightful level.

In academic writing and research, integrating sources plays a pivotal role in shaping the quality and credibility of your work.

When researching or exploring a new topic, the distinction between primary and secondary sources is paramount. The validity, reliability, and relevance of the information you gather will heavily depend on the type of source you consult. 

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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.

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Research Summary: What is it & how to write one

The Research Summary is used to report facts about a study clearly. You will almost certainly be required to prepare a research summary during your academic research or while on a research project for your organization.

If it is the first time you have to write one, the writing requirements may confuse you. The instructors generally assign someone to write a summary of the research work. Research summaries require the writer to have a thorough understanding of the issue.

This article will discuss the definition of a research summary and how to write one.

What is a research summary?

A research summary is a piece of writing that summarizes your research on a specific topic. Its primary goal is to offer the reader a detailed overview of the study with the key findings. A research summary generally contains the article’s structure in which it is written.

You must know the goal of your analysis before you launch a project. A research overview summarizes the detailed response and highlights particular issues raised in it. Writing it might be somewhat troublesome. To write a good overview, you want to start with a structure in mind. Read on for our guide.

Why is an analysis recap so important?

Your summary or analysis is going to tell readers everything about your research project. This is the critical piece that your stakeholders will read to identify your findings and valuable insights. Having a good and concise research summary that presents facts and comes with no research biases is the critical deliverable of any research project.

We’ve put together a cheat sheet to help you write a good research summary below.

Research Summary Guide

• Why was this research done?  – You want to give a clear description of why this research study was done. What hypothesis was being tested?
• Who was surveyed? – The what and why or your research decides who you’re going to interview/survey. Your research summary has a detailed note on who participated in the study and why they were selected. 
• What was the methodology? – Talk about the methodology. Did you do face-to-face interviews? Was it a short or long survey or a focus group setting? Your research methodology is key to the results you’re going to get. 
• What were the key findings? – This can be the most critical part of the process. What did we find out after testing the hypothesis? This section, like all others, should be just facts, facts facts. You’re not sharing how you feel about the findings. Keep it bias-free.
• Conclusion – What are the conclusions that were drawn from the findings. A good example of a conclusion. Surprisingly, most people interviewed did not watch the lunar eclipse in 2022, which is unexpected given that 100% of those interviewed knew about it before it happened.
• Takeaways and action points – This is where you bring in your suggestion. Given the data you now have from the research, what are the takeaways and action points? If you’re a researcher running this research project for your company, you’ll use this part to shed light on your recommended action plans for the business.

LEARN ABOUT:   Action Research

If you’re doing any research, you will write a summary, which will be the most viewed and more important part of the project. So keep a guideline in mind before you start. Focus on the content first and then worry about the length. Use the cheat sheet/checklist in this article to organize your summary, and that’s all you need to write a great research summary!

But once your summary is ready, where is it stored? Most teams have multiple documents in their google drives, and it’s a nightmare to find projects that were done in the past. Your research data should be democratized and easy to use.

We at QuestionPro launched a research repository for research teams, and our clients love it. All your data is in one place, and everything is searchable, including your research summaries! 

Authors: Prachi, Anas

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How to Write the Results/Findings Section in Research

What is the research paper Results section and what does it do?

The Results section of a scientific research paper represents the core findings of a study derived from the methods applied to gather and analyze information. It presents these findings in a logical sequence without bias or interpretation from the author, setting up the reader for later interpretation and evaluation in the Discussion section. A major purpose of the Results section is to break down the data into sentences that show its significance to the research question(s).

The Results section appears third in the section sequence in most scientific papers. It follows the presentation of the Methods and Materials and is presented before the Discussion section —although the Results and Discussion are presented together in many journals. This section answers the basic question “What did you find in your research?”

What is included in the Results section?

The Results section should include the findings of your study and ONLY the findings of your study. The findings include:

• Data presented in tables, charts, graphs, and other figures (may be placed into the text or on separate pages at the end of the manuscript)
• A contextual analysis of this data explaining its meaning in sentence form
• All data that corresponds to the central research question(s)
• All secondary findings (secondary outcomes, subgroup analyses, etc.)

If the scope of the study is broad, or if you studied a variety of variables, or if the methodology used yields a wide range of different results, the author should present only those results that are most relevant to the research question stated in the Introduction section .

As a general rule, any information that does not present the direct findings or outcome of the study should be left out of this section. Unless the journal requests that authors combine the Results and Discussion sections, explanations and interpretations should be omitted from the Results.

How are the results organized?

The best way to organize your Results section is “logically.” One logical and clear method of organizing research results is to provide them alongside the research questions—within each research question, present the type of data that addresses that research question.

Let’s look at an example. Your research question is based on a survey among patients who were treated at a hospital and received postoperative care. Let’s say your first research question is:

“What do hospital patients over age 55 think about postoperative care?”

This can actually be represented as a heading within your Results section, though it might be presented as a statement rather than a question:

Attitudes towards postoperative care in patients over the age of 55

Now present the results that address this specific research question first. In this case, perhaps a table illustrating data from a survey. Likert items can be included in this example. Tables can also present standard deviations, probabilities, correlation matrices, etc.

Following this, present a content analysis, in words, of one end of the spectrum of the survey or data table. In our example case, start with the POSITIVE survey responses regarding postoperative care, using descriptive phrases. For example:

“Sixty-five percent of patients over 55 responded positively to the question “ Are you satisfied with your hospital’s postoperative care ?” (Fig. 2)

Include other results such as subcategory analyses. The amount of textual description used will depend on how much interpretation of tables and figures is necessary and how many examples the reader needs in order to understand the significance of your research findings.

Next, present a content analysis of another part of the spectrum of the same research question, perhaps the NEGATIVE or NEUTRAL responses to the survey. For instance:

  “As Figure 1 shows, 15 out of 60 patients in Group A responded negatively to Question 2.”

After you have assessed the data in one figure and explained it sufficiently, move on to your next research question. For example:

  “How does patient satisfaction correspond to in-hospital improvements made to postoperative care?”

This kind of data may be presented through a figure or set of figures (for instance, a paired T-test table).

Explain the data you present, here in a table, with a concise content analysis:

“The p-value for the comparison between the before and after groups of patients was .03% (Fig. 2), indicating that the greater the dissatisfaction among patients, the more frequent the improvements that were made to postoperative care.”

Let’s examine another example of a Results section from a study on plant tolerance to heavy metal stress . In the Introduction section, the aims of the study are presented as “determining the physiological and morphological responses of Allium cepa L. towards increased cadmium toxicity” and “evaluating its potential to accumulate the metal and its associated environmental consequences.” The Results section presents data showing how these aims are achieved in tables alongside a content analysis, beginning with an overview of the findings:

“Cadmium caused inhibition of root and leave elongation, with increasing effects at higher exposure doses (Fig. 1a-c).”

The figure containing this data is cited in parentheses. Note that this author has combined three graphs into one single figure. Separating the data into separate graphs focusing on specific aspects makes it easier for the reader to assess the findings, and consolidating this information into one figure saves space and makes it easy to locate the most relevant results.

Following this overall summary, the relevant data in the tables is broken down into greater detail in text form in the Results section.

• “Results on the bio-accumulation of cadmium were found to be the highest (17.5 mg kgG1) in the bulb, when the concentration of cadmium in the solution was 1×10G2 M and lowest (0.11 mg kgG1) in the leaves when the concentration was 1×10G3 M.”

Captioning and Referencing Tables and Figures

Tables and figures are central components of your Results section and you need to carefully think about the most effective way to use graphs and tables to present your findings . Therefore, it is crucial to know how to write strong figure captions and to refer to them within the text of the Results section.

The most important advice one can give here as well as throughout the paper is to check the requirements and standards of the journal to which you are submitting your work. Every journal has its own design and layout standards, which you can find in the author instructions on the target journal’s website. Perusing a journal’s published articles will also give you an idea of the proper number, size, and complexity of your figures.

Regardless of which format you use, the figures should be placed in the order they are referenced in the Results section and be as clear and easy to understand as possible. If there are multiple variables being considered (within one or more research questions), it can be a good idea to split these up into separate figures. Subsequently, these can be referenced and analyzed under separate headings and paragraphs in the text.

To create a caption, consider the research question being asked and change it into a phrase. For instance, if one question is “Which color did participants choose?”, the caption might be “Color choice by participant group.” Or in our last research paper example, where the question was “What is the concentration of cadmium in different parts of the onion after 14 days?” the caption reads:

 “Fig. 1(a-c): Mean concentration of Cd determined in (a) bulbs, (b) leaves, and (c) roots of onions after a 14-day period.”

Steps for Composing the Results Section

Because each study is unique, there is no one-size-fits-all approach when it comes to designing a strategy for structuring and writing the section of a research paper where findings are presented. The content and layout of this section will be determined by the specific area of research, the design of the study and its particular methodologies, and the guidelines of the target journal and its editors. However, the following steps can be used to compose the results of most scientific research studies and are essential for researchers who are new to preparing a manuscript for publication or who need a reminder of how to construct the Results section.

Step 1 : Consult the guidelines or instructions that the target journal or publisher provides authors and read research papers it has published, especially those with similar topics, methods, or results to your study.

• The guidelines will generally outline specific requirements for the results or findings section, and the published articles will provide sound examples of successful approaches.
• Note length limitations on restrictions on content. For instance, while many journals require the Results and Discussion sections to be separate, others do not—qualitative research papers often include results and interpretations in the same section (“Results and Discussion”).
• Reading the aims and scope in the journal’s “ guide for authors ” section and understanding the interests of its readers will be invaluable in preparing to write the Results section.

Step 2 : Consider your research results in relation to the journal’s requirements and catalogue your results.

• Focus on experimental results and other findings that are especially relevant to your research questions and objectives and include them even if they are unexpected or do not support your ideas and hypotheses.
• Catalogue your findings—use subheadings to streamline and clarify your report. This will help you avoid excessive and peripheral details as you write and also help your reader understand and remember your findings. Create appendices that might interest specialists but prove too long or distracting for other readers.
• Decide how you will structure of your results. You might match the order of the research questions and hypotheses to your results, or you could arrange them according to the order presented in the Methods section. A chronological order or even a hierarchy of importance or meaningful grouping of main themes or categories might prove effective. Consider your audience, evidence, and most importantly, the objectives of your research when choosing a structure for presenting your findings.

Step 3 : Design figures and tables to present and illustrate your data.

• Tables and figures should be numbered according to the order in which they are mentioned in the main text of the paper.
• Information in figures should be relatively self-explanatory (with the aid of captions), and their design should include all definitions and other information necessary for readers to understand the findings without reading all of the text.
• Use tables and figures as a focal point to tell a clear and informative story about your research and avoid repeating information. But remember that while figures clarify and enhance the text, they cannot replace it.

Step 4 : Draft your Results section using the findings and figures you have organized.

• The goal is to communicate this complex information as clearly and precisely as possible; precise and compact phrases and sentences are most effective.
• In the opening paragraph of this section, restate your research questions or aims to focus the reader’s attention to what the results are trying to show. It is also a good idea to summarize key findings at the end of this section to create a logical transition to the interpretation and discussion that follows.
• Try to write in the past tense and the active voice to relay the findings since the research has already been done and the agent is usually clear. This will ensure that your explanations are also clear and logical.
• Make sure that any specialized terminology or abbreviation you have used here has been defined and clarified in the  Introduction section .

Step 5 : Review your draft; edit and revise until it reports results exactly as you would like to have them reported to your readers.

• Double-check the accuracy and consistency of all the data, as well as all of the visual elements included.
• Read your draft aloud to catch language errors (grammar, spelling, and mechanics), awkward phrases, and missing transitions.
• Ensure that your results are presented in the best order to focus on objectives and prepare readers for interpretations, valuations, and recommendations in the Discussion section . Look back over the paper’s Introduction and background while anticipating the Discussion and Conclusion sections to ensure that the presentation of your results is consistent and effective.
• Consider seeking additional guidance on your paper. Find additional readers to look over your Results section and see if it can be improved in any way. Peers, professors, or qualified experts can provide valuable insights.

One excellent option is to use a professional English proofreading and editing service  such as Wordvice, including our paper editing service . With hundreds of qualified editors from dozens of scientific fields, Wordvice has helped thousands of authors revise their manuscripts and get accepted into their target journals. Read more about the  proofreading and editing process  before proceeding with getting academic editing services and manuscript editing services for your manuscript.

As the representation of your study’s data output, the Results section presents the core information in your research paper. By writing with clarity and conciseness and by highlighting and explaining the crucial findings of their study, authors increase the impact and effectiveness of their research manuscripts.

For more articles and videos on writing your research manuscript, visit Wordvice’s Resources page.

Wordvice Resources

• How to Write a Research Paper Introduction 
• Which Verb Tenses to Use in a Research Paper
• How to Write an Abstract for a Research Paper
• How to Write a Research Paper Title
• Useful Phrases for Academic Writing
• Common Transition Terms in Academic Papers
• Active and Passive Voice in Research Papers
• 100+ Verbs That Will Make Your Research Writing Amazing
• Tips for Paraphrasing in Research Papers

Get science-backed answers as you write with Paperpal's Research feature

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

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• 2. Invest enough time to understand the topic deeply 

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• Mistakes to avoid while writing your research paper summary 

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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. 

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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.

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• Research Summary: What Is It & How To Write One

Introduction

A research summary is a requirement during academic research and sometimes you might need to prepare a research summary during a research project for an organization.

Most people find a research summary a daunting task as you are required to condense complex research material into an informative, easy-to-understand article most times with a minimum of 300-500 words.

In this post, we will guide you through all the steps required to make writing your research summary an easier task. 

What is a Research Summary?

A research summary is a piece of writing that summarizes the research of a specific topic into bite-size easy-to-read and comprehend articles. The primary goal is to give the reader a detailed outline of the key findings of a research.

It is an unavoidable requirement in colleges and universities. To write a good research summary, you must understand the goal of your research, as this would help make the process easier. 

A research summary preserves the structure and sections of the article it is derived from.

Research Summary or Abstract: What’s The Difference?

The Research Summary and Abstract are similar, especially as they are both brief, straight to the point, and provide an overview of the entire research paper. However, there are very clear differences.

To begin with, a Research summary is written at the end of a research activity, while the Abstract is written at the beginning of a research paper. 

A Research Summary captures the main points of a study, with an emphasis on the topic, method , and discoveries, an Abstract is a description of what your research paper would talk about and the reason for your research or the hypothesis you are trying to validate.

Let us take a deeper look at the difference between both terms.

What is an Abstract?

An abstract is a short version of a research paper. It is written to convey the findings of the research to the reader. It provides the reader with information that would help them understand the research, by giving them a clear idea about the subject matter of a research paper. It is usually submitted before the presentation of a research paper.

What is a Summary?

A summary is a short form of an essay, a research paper, or a chapter in a book. A research summary is a narration of a research study, condensing the focal points of research to a shorter form, usually aligned with the same structure of the research study, from which the summary is derived.

What Is The Difference Between an Abstract and a Summary?

An abstract communicates the main points of a research paper, it includes the questions, major findings, the importance of the findings, etc.

An abstract reflects the perceptions of the author about a topic, while a research summary reflects the ideology of the research study that is being summarized.

Getting Started with a Research Summary

Before commencing a research summary, there is a need to understand the style and organization of the content you plan to summarize. There are three fundamental areas of the research that should be the focal point:

• When deciding on the content include a section that speaks to the importance of the research, and the techniques and tools used to arrive at your conclusion.
• Keep the summary well organized, and use paragraphs to discuss the various sections of the research.
• Restrict your research to 300-400 words which is the standard practice for research summaries globally. However, if the research paper you want to summarize is a lengthy one, do not exceed 10% of the entire research material.

Once you have satisfied the requirements of the fundamentals for starting your research summary, you can now begin to write using the following format:

• Why was this research done?   – A clear description of the reason the research was embarked on and the hypothesis being tested.
• Who was surveyed? – Your research study should have details of the source of your information. If it was via a survey, you should document who the participants of the survey were and the reason that they were selected.
• What was the methodology? – Discuss the methodology, in terms of what kind of survey method did you adopt. Was it a face-to-face interview, a phone interview, or a focus group setting?
• What were the key findings? – This is perhaps the most vital part of the process. What discoveries did you make after the testing? This part should be based on raw facts free from any personal bias.
• Conclusion – What conclusions did you draw from the findings?
• Takeaways and action points – This is where your views and perception can be reflected. Here, you can now share your recommendations or action points.
• Identify the focal point of the article –  In other to get a grasp of the content covered in the research paper, you can skim the article first, in a bid to understand the most essential part of the research paper. 
• Analyze and understand the topic and article – Writing a summary of a research paper involves being familiar with the topic –  the current state of knowledge, key definitions, concepts, and models. This is often gleaned while reading the literature review. Please note that only a deep understanding ensures efficient and accurate summarization of the content.
• Make notes as you read – Highlight and summarize each paragraph as you read. Your notes are what you would further condense to create a draft that would form your research summary.

How to Structure Your Research Summary

• Title – This highlights the area of analysis, and can be formulated to briefly highlight key findings.
• Abstract – this is a very brief and comprehensive description of the study, required in every academic article, with a length of 100-500 words at most. 
• Introduction – this is a vital part of any research summary, it provides the context and the literature review that gently introduces readers to the subject matter. The introduction usually covers definitions, questions, and hypotheses of the research study. 
• Methodology –This section emphasizes the process and or data analysis methods used, in terms of experiments, surveys, sampling, or statistical analysis. 
• Results section – this section lists in detail the results derived from the research with evidence obtained from all the experiments conducted.
• Discussion – these parts discuss the results within the context of current knowledge among subject matter experts. Interpretation of results and theoretical models explaining the observed results, the strengths of the study, and the limitations experienced are going to be a part of the discussion. 
• Conclusion – In a conclusion, hypotheses are discussed and revalidated or denied, based on how convincing the evidence is.
• References – this section is for giving credit to those who work you studied to create your summary. You do this by providing appropriate citations as you write.

Research Summary Example 1

Below are some defining elements of a sample research summary.

Title – “The probability of an unexpected volcanic eruption in Greenwich”

Introduction – this section would list the catastrophic consequences that occurred in the country and the importance of analyzing this event. 

Hypothesis –  An eruption of the Greenwich supervolcano would be preceded by intense preliminary activity manifesting in advance, before the eruption.

Results – these could contain a report of statistical data from various volcanic eruptions happening globally while looking critically at the activity that occurred before these events. 

Discussion and conclusion – Given that Greenwich is now consistently monitored by scientists and that signs of an eruption are usually detected before the volcanic eruption, this confirms the hypothesis. Hence creating an emergency plan outlining other intervention measures and ultimately evacuation is essential. 

Research Summary Example 2

Below is another sample sketch.

Title – “The frequency of extreme weather events in the UK in 2000-2008 as compared to the ‘60s”

Introduction – Weather events bring intense material damage and cause pain to the victims affected.

Hypothesis – Extreme weather events are more frequent in recent times compared to the ‘50s

Results – The frequency of several categories of extreme events now and then are listed here, such as droughts, fires, massive rainfall/snowfalls, floods, hurricanes, tornadoes, etc.

Discussion and conclusion – Several types of extreme events have become more commonplace in recent times, confirming the hypothesis. This rise in extreme weather events can be traced to rising CO2 levels and increasing temperatures and global warming explain the rising frequency of these disasters. Addressing the rising CO2 levels and paying attention to climate change is the only to combat this phenomenon.

A research summary is the short form of a research paper, analyzing the important aspect of the study. Everyone who reads a research summary has a full grasp of the main idea being discussed in the original research paper. Conducting any research means you will write a summary, which is an important part of your project and would be the most read part of your project.

Having a guideline before you start helps, this would form your checklist which would guide your actions as you write your research summary. It is important to note that a Research Summary is different from an Abstract paper written at the beginning of a research paper, describing the idea behind a research paper.

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• abstract in research papers
• abstract writing
• action research
• research summary
• research summary vs abstract
• research surveys
• Angela Kayode-Sanni

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How To Write The Results/Findings Chapter

For qualitative studies (dissertations & theses).

By: Jenna Crossley (PhD). Expert Reviewed By: Dr. Eunice Rautenbach | August 2021

So, you’ve collected and analysed your qualitative data, and it’s time to write up your results chapter. But where do you start? In this post, we’ll guide you through the qualitative results chapter (also called the findings chapter), step by step. 

Overview: Qualitative Results Chapter

• What (exactly) the qualitative results chapter is
• What to include in your results chapter
• How to write up your results chapter
• A few tips and tricks to help you along the way
• Free results chapter template

What exactly is the results chapter?

The results chapter in a dissertation or thesis (or any formal academic research piece) is where you objectively and neutrally present the findings of your qualitative analysis (or analyses if you used multiple qualitative analysis methods ). This chapter can sometimes be combined with the discussion chapter (where you interpret the data and discuss its meaning), depending on your university’s preference.  We’ll treat the two chapters as separate, as that’s the most common approach.

In contrast to a quantitative results chapter that presents numbers and statistics, a qualitative results chapter presents data primarily in the form of words . But this doesn’t mean that a qualitative study can’t have quantitative elements – you could, for example, present the number of times a theme or topic pops up in your data, depending on the analysis method(s) you adopt.

Adding a quantitative element to your study can add some rigour, which strengthens your results by providing more evidence for your claims. This is particularly common when using qualitative content analysis. Keep in mind though that qualitative research aims to achieve depth, richness and identify nuances , so don’t get tunnel vision by focusing on the numbers. They’re just cream on top in a qualitative analysis.

So, to recap, the results chapter is where you objectively present the findings of your analysis, without interpreting them (you’ll save that for the discussion chapter). With that out the way, let’s take a look at what you should include in your results chapter.

What should you include in the results chapter?

As we’ve mentioned, your qualitative results chapter should purely present and describe your results , not interpret them in relation to the existing literature or your research questions . Any speculations or discussion about the implications of your findings should be reserved for your discussion chapter.

In your results chapter, you’ll want to talk about your analysis findings and whether or not they support your hypotheses (if you have any). Naturally, the exact contents of your results chapter will depend on which qualitative analysis method (or methods) you use. For example, if you were to use thematic analysis, you’d detail the themes identified in your analysis, using extracts from the transcripts or text to support your claims.

While you do need to present your analysis findings in some detail, you should avoid dumping large amounts of raw data in this chapter. Instead, focus on presenting the key findings and using a handful of select quotes or text extracts to support each finding . The reams of data and analysis can be relegated to your appendices.

While it’s tempting to include every last detail you found in your qualitative analysis, it is important to make sure that you report only that which is relevant to your research aims, objectives and research questions .  Always keep these three components, as well as your hypotheses (if you have any) front of mind when writing the chapter and use them as a filter to decide what’s relevant and what’s not.

Need a helping hand?

How do I write the results chapter?

Now that we’ve covered the basics, it’s time to look at how to structure your chapter. Broadly speaking, the results chapter needs to contain three core components – the introduction, the body and the concluding summary. Let’s take a look at each of these.

Section 1: Introduction

The first step is to craft a brief introduction to the chapter. This intro is vital as it provides some context for your findings. In your introduction, you should begin by reiterating your problem statement and research questions and highlight the purpose of your research . Make sure that you spell this out for the reader so that the rest of your chapter is well contextualised.

The next step is to briefly outline the structure of your results chapter. In other words, explain what’s included in the chapter and what the reader can expect. In the results chapter, you want to tell a story that is coherent, flows logically, and is easy to follow , so make sure that you plan your structure out well and convey that structure (at a high level), so that your reader is well oriented.

The introduction section shouldn’t be lengthy. Two or three short paragraphs should be more than adequate. It is merely an introduction and overview, not a summary of the chapter.

Pro Tip – To help you structure your chapter, it can be useful to set up an initial draft with (sub)section headings so that you’re able to easily (re)arrange parts of your chapter. This will also help your reader to follow your results and give your chapter some coherence.  Be sure to use level-based heading styles (e.g. Heading 1, 2, 3 styles) to help the reader differentiate between levels visually. You can find these options in Word (example below).

Section 2: Body

Before we get started on what to include in the body of your chapter, it’s vital to remember that a results section should be completely objective and descriptive, not interpretive . So, be careful not to use words such as, “suggests” or “implies”, as these usually accompany some form of interpretation – that’s reserved for your discussion chapter.

The structure of your body section is very important , so make sure that you plan it out well. When planning out your qualitative results chapter, create sections and subsections so that you can maintain the flow of the story you’re trying to tell. Be sure to systematically and consistently describe each portion of results. Try to adopt a standardised structure for each portion so that you achieve a high level of consistency throughout the chapter.

For qualitative studies, results chapters tend to be structured according to themes , which makes it easier for readers to follow. However, keep in mind that not all results chapters have to be structured in this manner. For example, if you’re conducting a longitudinal study, you may want to structure your chapter chronologically. Similarly, you might structure this chapter based on your theoretical framework . The exact structure of your chapter will depend on the nature of your study , especially your research questions.

As you work through the body of your chapter, make sure that you use quotes to substantiate every one of your claims . You can present these quotes in italics to differentiate them from your own words. A general rule of thumb is to use at least two pieces of evidence per claim, and these should be linked directly to your data. Also, remember that you need to include all relevant results , not just the ones that support your assumptions or initial leanings.

In addition to including quotes, you can also link your claims to the data by using appendices , which you should reference throughout your text. When you reference, make sure that you include both the name/number of the appendix , as well as the line(s) from which you drew your data.

As referencing styles can vary greatly, be sure to look up the appendix referencing conventions of your university’s prescribed style (e.g. APA , Harvard, etc) and keep this consistent throughout your chapter.

Section 3: Concluding summary

The concluding summary is very important because it summarises your key findings and lays the foundation for the discussion chapter . Keep in mind that some readers may skip directly to this section (from the introduction section), so make sure that it can be read and understood well in isolation.

In this section, you need to remind the reader of the key findings. That is, the results that directly relate to your research questions and that you will build upon in your discussion chapter. Remember, your reader has digested a lot of information in this chapter, so you need to use this section to remind them of the most important takeaways.

Importantly, the concluding summary should not present any new information and should only describe what you’ve already presented in your chapter. Keep it concise – you’re not summarising the whole chapter, just the essentials.

Tips for writing an A-grade results chapter

Now that you’ve got a clear picture of what the qualitative results chapter is all about, here are some quick tips and reminders to help you craft a high-quality chapter:

• Your results chapter should be written in the past tense . You’ve done the work already, so you want to tell the reader what you found , not what you are currently finding .
• Make sure that you review your work multiple times and check that every claim is adequately backed up by evidence . Aim for at least two examples per claim, and make use of an appendix to reference these.
• When writing up your results, make sure that you stick to only what is relevant . Don’t waste time on data that are not relevant to your research objectives and research questions.
• Use headings and subheadings to create an intuitive, easy to follow piece of writing. Make use of Microsoft Word’s “heading styles” and be sure to use them consistently.
• When referring to numerical data, tables and figures can provide a useful visual aid. When using these, make sure that they can be read and understood independent of your body text (i.e. that they can stand-alone). To this end, use clear, concise labels for each of your tables or figures and make use of colours to code indicate differences or hierarchy.
• Similarly, when you’re writing up your chapter, it can be useful to highlight topics and themes in different colours . This can help you to differentiate between your data if you get a bit overwhelmed and will also help you to ensure that your results flow logically and coherently.

If you have any questions, leave a comment below and we’ll do our best to help. If you’d like 1-on-1 help with your results chapter (or any chapter of your dissertation or thesis), check out our private dissertation coaching service here or book a free initial consultation to discuss how we can help you.

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20 Comments

This was extremely helpful. Thanks a lot guys

Hi, thanks for the great research support platform created by the gradcoach team!

I wanted to ask- While “suggests” or “implies” are interpretive terms, what terms could we use for the results chapter? Could you share some examples of descriptive terms?

I think that instead of saying, ‘The data suggested, or The data implied,’ you can say, ‘The Data showed or revealed, or illustrated or outlined’…If interview data, you may say Jane Doe illuminated or elaborated, or Jane Doe described… or Jane Doe expressed or stated.

I found this article very useful. Thank you very much for the outstanding work you are doing.

What if i have 3 different interviewees answering the same interview questions? Should i then present the results in form of the table with the division on the 3 perspectives or rather give a results in form of the text and highlight who said what?

I think this tabular representation of results is a great idea. I am doing it too along with the text. Thanks

That was helpful was struggling to separate the discussion from the findings

this was very useful, Thank you.

Very helpful, I am confident to write my results chapter now.

It is so helpful! It is a good job. Thank you very much!

Very useful, well explained. Many thanks.

Hello, I appreciate the way you provided a supportive comments about qualitative results presenting tips

I loved this! It explains everything needed, and it has helped me better organize my thoughts. What words should I not use while writing my results section, other than subjective ones.

Thanks a lot, it is really helpful

Thank you so much dear, i really appropriate your nice explanations about this.

Thank you so much for this! I was wondering if anyone could help with how to prproperly integrate quotations (Excerpts) from interviews in the finding chapter in a qualitative research. Please GradCoach, address this issue and provide examples.

what if I’m not doing any interviews myself and all the information is coming from case studies that have already done the research.

Very helpful thank you.

This was very helpful as I was wondering how to structure this part of my dissertation, to include the quotes… Thanks for this explanation

This is very helpful, thanks! I am required to write up my results chapters with the discussion in each of them – any tips and tricks for this strategy?

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Research Paper Summary

Ai generator.

Whether you are a student, an academic scholar, or even working in business, there is no denying that a research paper summary is the one tool that you are going to expect when it comes to writing your research paper or research studies. There is also no denying how useful the summary is going to be when you have to report it to your superiors or your professors without having to go through the entire research paper. Students know for themselves that writing a summary of their research paper is useful. With that, here are examples of research paper summaries to download.

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What Is a Research Paper Summary?

Research paper summaries are short but descriptive writings that are expected in a research paper . What goes in a research paper summary is the main topic or the main plot of your research paper. However, what is and should never be included are any new discoveries, arguments and new leads that help your research. The purpose of the summary is to simply give out the general point of view or the outline of your research paper and nothing else. This is often the mistake made by students when they think of a research paper summary. The need to add all new leads to help their research in the summary. The only main thing to focus on your summary is the overview and the general outline . 

How to Write a Research Paper Summary

Being able to write a research paper summary is important and quite a useful skill. As this does not only work for students on their research paper, but it also works for employees who are given the task to write a project summary. It basically works just the same. To get a glimpse of what you can do to make your research paper summary, here are simple steps you can follow.

Step 1: Take the Main Part of Your Research

When you make your summary, the first paragraph will mainly be about your research paper. The first part is to take the main part of your research. The main part or the main topic should be what it is about. Make sure what you are writing is what your research paper is about, as there are times when your topic may not be the main goal of your paper.

Step 2: Break It Down to Smaller Topics

Since the first paragraph is focused on the introduction and the main topic, the second paragraph will focus mainly on breaking down your main or general topic into smaller subtopics. By doing this, it is easier for you to divide and explain every single important detail of your research paper. Students are often tasked to do this in order for them to get a better outlook of their research paper and how they are able to piece together the smaller topics to the main topic.

Step 3: Get the Gist

The third and final paragraph will be the gist of your research paper. This includes the heart or the main part, the findings and the conclusion. The gist has to be a general summary of your research paper. It should have the facts that support it, the findings of your research and the hypothesis. Add in your conclusion at the end.

Step 4: Proofread Your Work

Lastly, make sure to proofread your entire research paper summary. This is just to make sure you did not misspell any words, your punctuations are in the correct place and the tone of your writing fits the paper you are making.

What is a research paper summary?

Research paper summaries are short but descriptive writings  that are expected in a research paper. What goes in a research paper summary is the main topic or the main plot of your research paper.

What are the characteristics of a research paper summary?

The characteristics of a research paper summary are the following:

• The introduction and the main topic
• The breaking of the main topic to sub topics
• The gist of the research paper summary
• The conclusion

How lengthy can a research paper summary be?

The normal length of a research paper summary should not exceed more than a page. However, when it comes to the number of words for a summary, your wording should not exceed the maximum number of four hundred words.

When it comes to writing a research paper, there is no denying that you must also write a summary for it. Since a research paper can sometimes be overwhelming to those who will be listening to you talk about it, you can relieve it by making a summary of your paper. This will also help them follow what you are discussing and what it is about.

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Improved Surface Drainage of Pavements: Final Report (1998)

Chapter: chapter 5 summary, findings, and recommendations.

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

CHAPIER 5 SI~MARY, FINDINGS, AND RECOMMENDATIONS SUGARY The primary objective of this research was to identify unproved methods for draining rainwater from the surface of multi-lane pavements and to develop guidelines for their use. The guidelines, along with details on the rationale for their development, are presented in a separate document' "Proposed Design Guidelines for Improving Pavement Surface Drainage" (2J. The guidelines support an interactive computer program, PAVDRN, that can be used by practicing engineers In the process of designing new pavements or rehabilitating old pavements' is outlined In figure 39. The intended audience for the guidelines is practicing highway design engineers that work for transportation agencies or consulting firms. Improved pavement surface drainage is needed for two reasons: (~) to minimize splash and spray and (2) to control the tendency for hydroplaning. Both issues are primary safety concerns. At the request of the advisory panel for the project, the main focus of this study was on ~mprov~g surface drainage to mammae the tendency for hydroplaning. In terms of reducing the tendency for hydroplaTuT g, the needed level of drainage is defined in terms of the thickness of the film of water on the pavement. Therefore, the guidelines were developed within the context of reducing the thickness of the water film on pavement surfaces to the extent that hydroplaning is unlikely at highway design speeds. Since hydroplaning is ~7

DESIGN CRITERIA Pavement Geometry Number of lanes Section type - Tangent - Horizontal curve - Transition - Vertical crest curve - Vertical sag curve Enviromnental oramaters Rainfall intensity ~ Temperature Pavement Tvpe Dense-graded asphalt Porous asphalt Portland cement concrete ~ Grooved Portland cement concrete Desion Soeed Allowable speed for onset of hydroplaning Recommend Desion Changes Alter geometry Alter pavement surface Add appurtenances Groove (Portland cement concrete) CALCULATIONS Lenoth of flow path Calculate on basis of pavement geometry IT Hydraulic Analvses .  No? Water film thickness Equation No. 10 Equation No.'s. 16-19 1 Hvdroolanino Analvsis Hydroplaning speed Equation No.'s 21-24 Rainfall Intensity Equation No. 25 -A I / Meet Design ~ \ Cntena? / \<es? Accent Desinn | Figure 39. Flow diagram representing PAVI)RN design process In "Proposed Guidelines for Improving Pavement Surface DrmT~age" (2). 118

controlled primarily by the thickness of the water film on the pavement surface, the design guidelines focus on the prediction and control of ache depth of water flowing across the pavement surface as a result of rainfall, often referred to as sheet flow. Water film thickness on highway pavements can be controlled In three fundamental ways, by: I. Minimizing the length of the longest flow path of the water over We pavement and thereby the distance over which the flow can develop; 2. Increasing the texture of the pavement surface; and 3. Removing water from the pavement's surface. In the process of using PAVDRN to implement the design guidelines, the designer is guided to (~) minimize the longest drainage path length of the section under design by altering the pavement geometry and (2) reduce the resultant water film thickness that will develop along that drainage path length by increasing the mean texture depth, choosing a surface that maximizes texture, or using permeable pavements, grooving, and appurtenances to remove water from the surface. Through the course of a typical design project, four key areas need to be considered in order to analyze and eventually reduce the potential for hydroplaning. These areas are: ~9

I. Environmental conditions: 2. Geometry of the roadway surface; 3. Pavement surface (texture) properties; and 4. Appurtenances. Each of these areas and their influence on the resulting hydroplaning speed of the designed section are discussed In detail In the guidelines (21. The environmental conditions considered are rainfall ~ntensibr and water temperature, which determines the kinematic viscosity of the water. The designer has no real control over these environmental factors but needs to select appropriate values when analyzing the effect of flow over the pavement surface and hydroplaning potential. Five section types, one for each of the basic geometric configurations used In highway design, are examined. These section are: 1. TaIlgent; 2. Superelevated curve; 3. Transition; 4. Vertical crest curve; and 5. Vertical sag curve. 120

Pavement properties that affect the water fihn thickness mclude surface characteristics, such as mean texture depth and grooving of Portland cement concrete surfaces, are considered In the process of applying PAVDRN. Porous asphalt pavement surfaces can also reduce He water film thickness and thereby contribute to the reduction of hydroplaning tendency and their presence can also be accounted for when using PAVDRN. Finally, PAVDRN also allows the design engineer to consider the effect of drainage appurtenances, such as slotted drain inlets. A complete description of the various elements that are considered In the PAVDRN program is illustrated In figure 40. A more complete description of the design process, the parameters used in the design process, and typical values for the parameters is presented In the "Proposed Design Guidelines for Improving Pavement Surface Drainage" (2) alla in Appendix A. fIN1)INGS The following findings are based on the research accomplished during the project, a survey of the literature, and a state-of-the-art survey of current practice. I. Model. The one~unensional mode} is adequate as a design tool. The simplicity and stability of the one~imensional mode} offsets any increased accuracy afforded by a two-d~mensional model. The one~mensional model as a predictor of water fiDn thickness and How path length was verified by using data from a previous study (11). 121

No. of Planes Length of Plane Grade Step Increment Wdth of Plane Cross Slope Section T,rne 1) Tangent 2) Honzontal Curare 3) Transition 4) Vertical Crest 5) Vertical Sag U=tS 1)U.S. 2) S. I. Rainfall Intenstity ~ , \ |Kinematic Viscosity |Design Speed Note: PC = Point of Curvature PI. = Point of Tangency PCC = Portland cement concrete WAC = Dense graded asphalt concrete 0GAC = 0pcn~raded asphalt concrete where OGAC includes all types of intentally draining asphalt surfaces GPCC = Grooved Ponland cement concrete Taneent Pavement Type Mean Texture Depth 1) PCC 2) DGAC 3) OGAC 4) GPCC Horizontal Cun~c  Grade Cross Slope Radius of Cunran~re Wdth Pavement Type _ 2) DGAC 3) OGAC 4) GPCC Mean Texture Depth Step Increment _ Transition Length of Plane Super Elevation Tangent Cross Slope Tangent Grade width of Curve Transition Width Pavement Type_ 1) PCC 3) OGAC 4) GPCC Mean Texture Depth Step Increment Horizontal Length Cross slope width PC Grade PI' Grade Elevation: Pr-PC Vertical Crest Flow Direction Step Increment Pavement Type 1) PC Side I 2) PI. Side | 1)PCC 2) DGAC 3) OGAC 4) GPCC Mean Tex~rc Depth _ _ ~ Figure 40. Factors considered in PAVDRN program. 122 ~1 r - . , Vertical Sad | Horizontal Length | Cross slope Wldth PC Grade PI Grade Elevation: PIE Flow Direction  Step Increment / Stored :_ ~ cats ~ 1) PC Side | 2) PI Side | . Pavement Typed 1) PCC 3) OGAC 14) GPCC Mean Texture Depth I I

~ Stored data V ~ 3 L IN1T For use with a second nut using data from the first run.) , 1 EPRINT (Echos input to output ) 1 CONVERT (Converts units to and from SI and English.) ~ , ADVP  (Advances Page of output.) KINW (Calculates Minning's n, Water Film Thickness (WEIR), and Hydroplaning Speed UPS).) , EDGE (Determines if flow has reached the edge of the pavement.) out roar Figure 40. Factors considered in PAVDRN program (continued). 123

2. Occurrence of Hydropl~r g. In general, based on the PAVDRN mode! and the assumptions inherent in its development, hydroplaning can be expected at speeds below roadway design speeds if the length of the flow path exceeds two lane widths. 3. Water Film Thickness. Hydroplaning is initiated primarily by the depth of the water film thickness. Therefore, the primary design objective when controlling hydroplaning must be to limit the depth of the water film. 4. Reducing Water Film Thickness. There are no simple means for controlling water John thickness, but a number of methods can effectively reduce water film thickness and consequently hydroplaning potential. These include: Optimizing pavement geometry, especially cross-slope. Providing some means of additional drainage, such as use of grooved surfaces (PCC) or porous mixtures (HMA). Including slotted drains within the roadway. 5. Tests Needed for Design. The design guidelines require an estimate of the surface texture (MTD) and the coefficient of permeability Porous asphalt only). The sand patch is an acceptable test method for measuring surface texture, except for the more open (20-percent air voids) porous asphalt mixes. In these cases, an estimate of the surface texture, based on tabulated data, is sufficient. As an alternative, 124

sand patch measurements can be made on cast replicas of the surface. For the open mixes, the glass beads flow into the voids within the mixture, giving an inaccurate measure of surface texture. Based on the measurements obtained In the laboratory, the coefficient of permeability for the open-graded asphalt concrete does not exhibit a wide range of values, and values of k may be selected for design purposes from tabulated design data (k versus air voids). Given the uncertainty of this property resulting from compaction under traffic and clogging from contaminants and anti-skid material, a direct measurement (e.g., drainage lag permeameter) of k is not warranted. Based on the previous discussion, no new test procedures are needed to adopt the design guidelines developed during this project. 6. Grooving. Grooving of PCC pavements provides a reservoir for surface water and can facilitate the removal of water if the grooves are placed parallel to the flow oath. Parallel orientation is generally not practical because the flow on highway pavements is typically not transverse to the pavement. Thus, the primary contribution offered by grooving is to provide a surface reservoir unless the grooves comlect with drainage at the edge of the pavement. Once the grooves are filled with water, the tops of the grooves are the datum for the Why and do not contribute to the reduction in the hydroplaning potential. 125

7. Porous Pavements. These mixtures can enhance the water removal and Hereby reduce water film tHch~ess. They merit more consideration by highway agencies In the United States, but they are not a panacea for eliminating hydroplaning. As with grooved PCC pavements, the internal voids do not contribute to the reduction of hydroplaning; based on the field tests done In this study. hv~ronImiina can be if, , , ~ expected on these mixtures given sufficient water fiLn thickness. Other than their ability to conduct water through internal flow, the large MTD offered by porous asphalt is the main contribution offered by the mixtures to the reduction of hydroplaning potential. The high-void ~ > 20 percent), modified binder mixes used In Europe merit further evaluation in the United States. They should be used In areas where damage from freezing water and the problems of black ice are not likely. 8. Slotted Drains. These fixtures, when installed between travel lanes, offer perhaps the most effective means of controlling water film thickness from a hydraulics standpoint. They have not been used extensively In the traveled lanes and questions remain unanswered with respect to their installation (especially in rehabilitation situations) and maintenance. The ability to support traffic loads and still maintain surface smoothness has not been demonstrated and they may be susceptible to clogging from roadway debris, ice, or snow. 126

RECOMMENDATIONS AND CONCLUSIONS The following recommendations are offered based on the work accomplished during this project and on the conclusions given previously: I. Implementation. The PAVDRN program and associated guidelines need to be field tested and revised as needed. The program and the guidelines are sufficiently complete so that they can be used in a design office. Some of the parameters and algorithms will I~ely need to be modified as experience is gained with the program. 2. Database of Material Properties. A database of material properties should be gathered to supplement the information contained in PAVDRN. This information should Include typical values for the permeability of porous asphalt and topical values for the surface texture (MTD) for different pavement surfaces to include toned Portland cement concrete surfaces. A series of photographs of typical pavement sections and their associated texture depths should be considered as an addition to the design guide (21. 3. Pavement Geometry. The AASHTO design guidelines (~) should be re-evaluated In terms of current design criteria to determine if they can be modified to enhance drainage without adversely affecting vehicle handling or safety. ~27

4. Use of appurtenances. Slotted drams should be evaluated In the field to determine if they are practical when Installed In the traveled way. Manufacturers should reconsider the design of slotted drains and their Installation recommendations currently In force to maximize them for use In multi-lane pavements and to determine if slotted drains are suitable for installations In the traveled right of way. 5. Porous Asphalt Mixtures. More use should be made of these mixtures, especially the modified high a~r-void mixtures as used In France. Field trials should be conducted to monitor HPS and the long-term effectiveness of these mixtures and to validate the MPS and WDT predicted by PAVDRN. 6. Two-D~mensional Model. Further work should be done with two~mensional models to determine if they improve accuracy of PAVDRN and to determine if they are practical from a computational standpoint. ADDITIONAL STUDIES On the basis of the work done during this study, a number of additional items warrant furler study. These Include: 1. Full-scale skid resistance studies to validate PAVDRN in general and the relationship between water film thickness and hydroplaning potential in particular are needed in light of the unexpectedly low hvdronlanin~ speeds predicted during 128 , . ~. , ~

this study. The effect of water infiltration into pavement cracks and loss of water by splash and spray need to be accounted for In the prediction of water fihn Sickness. Surface Irregularities, especially rutting, need to be considered in the prediction models. 2. Field trials are needed to confirm the effectiveness of alternative asphalt and Portland cement concrete surfaces. These include porous Portland cement concrete surfaces, porous asphalt concrete, and various asphalt m~cro-surfaces. 3. The permeability of porous surface mixtures needs to be confirmed with samples removed from the field, and the practicality of a simplified method for measuring in-situ permeability must be investigated and compared to alternative measurements, such as the outflow meter. 4. For measuring pavement texture, alternatives to the sand patch method should be investigated, especially for use with porous asphalt mixtures. 129

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• Research article
• Open access
• Published: 09 May 2024

Causal relationship between serum metabolites and juvenile idiopathic arthritis: a mendelian randomization study

• Han Zhang 1   na1 ,
• Xiao Ma 1   na1 ,
• Wanlu Liu 2   na1 ,
• Ze Wang 3 ,
• Zian Zhang 1 ,
• GuanHong Chen 2 ,
• Yingze Zhang 1 , 4 ,
• Tianrui Wang 1 ,
• Tengbo Yu 5 &
• Yongtao Zhang 1  

Pediatric Rheumatology volume  22 , Article number:  51 ( 2024 ) Cite this article

161 Accesses

Metrics details

Juvenile Idiopathic Arthritis (JIA) is a condition that occurs when individuals under the age of 16 develop arthritis that lasts for more than six weeks, and the cause is unknown. The development of JIA may be linked to serum metabolites. Nevertheless, the association between JIA pathogenesis and serum metabolites is unclear, and there are discrepancies in the findings across studies.

In this research, the association between JIA in humans and 486 serum metabolites was assessed using genetic variation data and genome-wide association study. The identification of causal relationships was accomplished through the application of univariate Mendelian randomization (MR) analysis. Various statistical methods, including inverse variance weighted and MR-Egger, were applied to achieve this objective. To ensure that the findings from the MR analysis were trustworthy, a number of assessments were carried out. To ensure the accuracy of the obtained results, a range of techniques were utilised including the Cochran Q test, examination of the MR-Egger intercept, implementation of the leave-one-out strategy, and regression analysis of linkage disequilibrium scores. In order to identify the specific metabolic pathways associated with JIA, our primary objective was to perform pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes.

Two-sample summary data MR analyses and sensitivity analyses showed that five metabolites were significantly causally associated with JIA, including two risk factors—kynurenine (odds ratio [OR]: 16.39, 95% confidence interval [CI]: 2.07-129.63, p  = 5.11 × 10 − 6 ) and linolenate (OR: 16.48, 95% CI: 1.32-206.22, p  = 0.030)—and three protective factors—3-dehydrocarnitine (OR: 0.32, 95% CI: 0.14–0.72, p  = 0.007), levulinate (4-oxovalerate) (OR: 0.40, 95% CI: 0.20–0.80, p  = 0.010), and X-14,208 (phenylalanylserine) (OR: 0.68, 95% CI: 0.51–0.92, p  = 0.010). Furthermore, seven metabolic pathways, including α-linolenic acid metabolism and pantothenate and CoA biosynthesis, are potentially associated with the onset and progression of JIA.

Five serum metabolites, including kynurenine and 3-dehydrocarnitine, may be causally associated with JIA. These results provide a theoretical framework for developing effective JIA prevention and screening strategies.

Introduction

Juvenile idiopathic arthritis (JIA) encompasses a variety of intricate and diverse disorders characterized by persistent inflammation, mainly observed in the synovial membranes and this chronic inflammatory process significantly heightens the risk of degenerative changes occurring in the osteocartilaginous tissues [ 1 ]. The prevalence of JIA is 3.8–400 per 100,000 proportion [ 1 ]. JIA, a condition primarily affecting children under the age of 16, is characterized by symptoms such as swelling, pain, and restricted joint movement that persists for a minimum of 6 weeks, according to research conducted by the International League of Associations for Rheumatology [ 2 , 3 ]. In the early stage, there may be severe symptom, including macrophage activation syndrome and synovitis, potentially leading to multi-organ damage [ 4 ]. Cartilage damage and bone erosion may occur as the disease progresses, leading to joint deformities and functional impairment, affecting the quality of life and increasing morbidity.JIA is a condition whose development is thought to be influenced by various factors, such as genetic and environmental factors, as well as infections and it is believed that these factors can trigger inflammatory responses and lead to the onset of autoimmune disorders [ 5 , 6 , 7 ]. Nonetheless, the influence of serum metabolites on disease pathogenesis is unclear [ 8 ]. Therefore, the early identification of changes in serum metabolites can help prevent JIA.

Metabolomics has emerged as a burgeoning field that focuses on the detection, analysis, and measurement of naturally occurring small-molecule metabolites in biological samples and this field holds the potential to enhance diagnoses by identifying biomarkers and pathway components, as well as analyzing changes in serum metabolite levels [ 9 , 10 , 11 ]. JIA is associated with changes in serum metabolites. Currently, only a limited number of molecular, immune, and clinical markers with JIA have been suggested in these studies [ 12 , 13 ]. For instance, calprotectin (also known as MRP8/14 and S100A8/A9) is useful for diagnosing JIA [ 14 ]. In turn, circulating levels of 25-(OH)D appear to have no detectable effect on the incidence of JIA [ 15 ]. In particular, the occurrence of JIA is linked to the activation of endothelial cells, the activation of macrophages, heightened levels of pro-inflammatory cytokines (such as IL-6, IL-10, and IFN-γ), and increased levels of adipokines [ 16 ]. These findings highlight the close connection between lipid profiles, inflammatory responses, and the pathogenesis and progression of autoimmune diseases [ 17 ]. High-mobility group box 1 and matrix metalloproteinase 3 are markers of JIA [ 18 ]. Population-based observational studies have identified various metabolites associated with JIA but are influenced by potential confounding factors or limited by sample size. Therefore, large studies are needed to identify and characterize serum biomarkers that are clinically useful for the early diagnosis of JIA.

The Mendelian randomization method utilizes genetic variants, particularly single nucleotide polymorphisms (SNPs), that are strongly linked to exposure factors, serving as instrumental variables (IVs) and these instrumental variables are then used to estimate the causal effects of exposure factors on health outcomes [ 19 ]. Moreover, MR eliminates potential confounders and reverses causation effects, making it somewhat similar to randomized controlled trials and capable of evaluating genetic correlations across complex diseases [ 20 ]. MR studies based on genome-wide association study (GWAS) datasets utilize genetic variation data as IVs to estimate causal effects. This MR study inferred the causal relationships of 486 serum metabolites (exposure factors) with JIA (outcome), thus providing a basis for identifying JIA biomarkers and metabolic pathways.

Materials and methods

Experimental design.

MR analysis was performed using publicly available GWAS catalog and FinnGen datasets to investigate the causal relationship of 486 serum metabolites (exposure factors) with JIA (outcome). Three fundamental assumptions were met to ensure the reliability of inferences [ 21 , 22 ]: (1) IVs were strongly correlated with serum metabolites; (2) IVs were not affected by confounders of JIA, such as body mass index (BMI), body fat percentage, body weight, smoking, and inflammatory bowel disease; (3) there was no genetic pleiotropy, i.e., the effects of IVs on JIA were mediated solely by the exposure. Therefore, it is currently impossible to completely exclude SNPs related to outcomes. The extent of bias can be assessed by evaluating the magnitude of horizontal pleiotropy. Additionally, considering the possibility of non-reproducibility of GWAS results [ 23 ], two sets of JIA genetic variation data were used in reproducibility analysis. Combining the results of two MR studies increases confidence in causal estimates (Fig.  1 ).

Flowchart of the study design

Source of GWAS data on JIA

Data on JIA were obtained from the FinnGen consortium release 9 [ 24 ], which includes 286,529 participants of European descent (1,494 JIA patients and 285,035 healthy controls). The phenotype of interest is JIA. The genetic variation data for JIA used in the replication analysis were sourced from the GWAS catalog dataset [ 25 ] containing 12,501 participants of European ancestry (3,305 JIA patients and 9,196 healthy controls) (Accession Code GCST90010715). The JIA diagnostic criteria used in this study adhere to the International Classification of Diseases, 10th Edition (ICD-10) ( https://icd.who.int/browse10/2016/en# ). Ethical approval and informed consent were waived because this study was based on previously published articles and open-source databases.

We used genome-wide association summary datasets containing 486 human serum metabolites [ 26 ], Among these metabolites, 177 had undisclosed biochemical characteristics, while 309 were categorized into eight distinct biochemical groups, namely amino acids, peptides, energy, cofactors and vitamins, lipids, xenobiotics, carbohydrates, and nucleotides. Ultimately, the GWAS dataset consisted of roughly 2.1 million SNPs, collected from the KORA and TwinsUK datasets, which encompassed a total of 7,824 adult subjects.

Identifying appropriate IVs for screening

To ensure the validity and reliability of the results, we met three key assumptions that served as the basis for selecting IVs. We established a threshold of p  < 1 × 10 − 5 for selecting SNPs significantly associated with the exposure. The strength of SNPs was evaluated by calculating the F statistic and in order to avoid any potential bias resulting from weak instruments, SNPs with an F statistic value below 10 were excluded from the analysis [ 27 , 28 ]. F was calculated using the following equations:

The minor allele frequency (MAF), effect size (β), and standard error (SD) of β play important roles in the analysis.

The exposure GWAS study’s sample size, denoted by N, the number of IVs, denoted by K, and the degree to which the IVs explain the exposure (as measured by R², the coefficient of determination in the regression equation) are considered for analysis.

MR analysis

Genetic variant data were sourced from the FinnGen dataset. Given the advantages of the inverse variance weighted (IVW) method in testing efficiency and statistical power, we selected it as the primary method for establishing causal relationships. Other methods were employed, including simple mode, MR-Egger, weighted median, and weighted model. The IVW method calculates the Wald ratio for each IV using inverse variance weights and combines the results through meta-analysis. The weight of each IV was determined by the inverse of its effect variance, i.e., larger studies with smaller standard errors have more weight than smaller studies. This weight allocation approach reduces inaccuracies in estimating combined effects. The slope corresponds to the causal impact of the exposure factor on the outcome. The variance of the effect can be estimated using a fixed or random effects model.

The desired objective of establishing a reliable association between exposure and outcome can be accomplished by utilizing different SNPs and assuming that each genetic variant satisfies the instrumental variable assumptions, thus enabling the combination of Wald ratio estimates [ 29 ]. Nevertheless, the implementation of the IVW approach may introduce estimation bias in assessing causal effects if the instrumental variables exhibit pleiotropy and the estimation of causal effects is represented by the slope of MR-Egger regression, while the intercept corresponds to the average pleiotropic effect of a genetic variant [ 30 ]. Through the utilization of weighted models, causal effect estimations can be obtained by giving weights to each SNP, with the largest weight being considered [ 31 ].

Sensitivity analysis

In MR studies, the accuracy of causal estimates is increased using IVs. However, this approach may also introduce IVs with pleiotropy and heterogeneity, resulting in bias. Various techniques are employed to enhance the dependability of results, which encompass the application of the MR-Egger procedure [ 32 ], adoption of the Cochran Q test [ 33 ], and implementation of the leave-one-out strategy [ 34 ]. The MR-Egger intercept test evaluates the impact of pleiotropy on the causal effect of interest; a nonzero intercept is evidence of pleiotropy. The Cochran Q test assesses heterogeneity among IVs.The approach of leaving one out investigates the impact of each IV and examines the robustness of the results by consecutively excluding each IV and determining the collective effect of the remaining IVs.

Analysis of metabolic pathways

Metabolic pathways associated with JIA were identified using the KEGG database ( https://new.metaboanalyst.ca/MetaboAnalyst/ ). Differentially expressed metabolites were selected based on a significance level of p  < 0.05. This analysis was performed using MetaboAnalyst version 5.0. The metabolic pathways that showed a significance level of p  < 0.1 are listed in Supplementary Table 2 .

Exclusion of confounding factors

In spite of the exclusion of inadequate independent variables (F < 10) and the execution of sensitivity analyses to evaluate the dependability of Mendelian randomization (MR) findings, certain independent variables can breach assumptions (2) and (3).IVs associated with potential confounders of JIA, including BMI, body fat percentage, body weight, smoking, and inflammatory bowel disease, were identified using PhenoScanner version 2 ( http://www.phenoscanner.medschl.cam.ac.uk/ ).

Replication analysis and meta-analysis

To increase the reliability of MR estimates, we performed a replication analysis using a second set of JIA genetic variation data obtained from the GWAS dataset. Then, we merged the findings of two MR studies to identify metabolites causally associated with JIA.

Linkage disequilibrium score regression (LDSC) and reverse causality analysis

Once the cause-and-effect relationship between the exposure and outcome is established, LDSC becomes a valuable tool for examining the genetic association among intricate characteristics.This type of regression helps avoid overestimations and confounding from polygenicity. LDSC involves measuring the linkage disequilibrium (LD) score for each SNP to evaluate its degree of association with complex traits. This score quantifies the strength of LD between a SNP and neighboring SNPs. Further, LD analysis reduces the potential confounding effects of shared genetic factors on MR results [ 35 ].

To prevent endogeneity resulting from reverse causation and improve the reliability of MR findings, we performed a reverse causation analysis on the identified group of metabolites.

Following the screening process, a total of 8,845 SNPs directly related to 486 metabolites were identified. The range of SNPs associated with each metabolite varied from a minimum of 3 to a maximum of 413. Moreover, it is noteworthy that all of these SNPs exhibited F values exceeding the threshold of 10, thereby confirming their potential as reliable instruments for MR investigations (Supplementary Tables 1 and 2 ).

The MR findings are presented in (Supplementary Table 3 ). The IVW results indicated that JIA was causally related to 24 serum metabolites. It emphasize the presence of unknown metabolites with unknown properties. Additionally, It highlights the classification of 18 metabolites into eight distinct categories. These categories include amino acids, peptides, energy, cofactors and vitamins, lipids, xenobiotics, carbohydrates, and nucleotides. The study found several notable findings regarding specific metabolites. Firstly, the metabolite kynurenine (Kyn) demonstrated a strong association with the studied condition (odds ratio [OR]: 16.39, 95% confidence interval [CI]: 2.07-129.63, p  = 5.11 × 10 − 6). On the other hand, the metabolites 3-dehydrocarnitine (OR:0.32, 95%CI: 0.14–0.72, p  = 0.0068), levulinate (4-oxovalerate) (OR: 0.40, 95%CI: 0.20–0.80, p  = 0.0098), X-14,208 (phenylalanylserine) (OR: 0.68, 95%CI: 0.51–0.92, p  = 0.010), and linolenate (OR: 16.48, 95% CI: 1.32-206.22, p  = 0.030) were found to have significant associations as well. These findings suggest the potential involvement of these metabolites in the studied condition.

There was evidence of heterogeneity in Kyn, acetylcarnitine, and cholate; thus, their causal relationship with JIA was assessed using the IVW random effects model. IVs related to acetylcarnitine showed horizontal pleiotropy, while IVs related to other metabolites did not exhibit heterogeneity or horizontal pleiotropy (Supplementary Table 4 ) (Supplementary file 1 ).

Confounding analysis, replicate analysis, and meta-analysis

Although 17 metabolites (excluding acetylcarnitine because of horizontal pleiotropy) passed tests for heterogeneity and horizontal pleiotropy, we further investigated the associations of IVs with other phenotypes. Based on the PhenoScanner results, we found that SNPs related to stearoylcarnitine, linolenate, 3-carboxy-4-methyl-5-propyl-2-furanpropanoate (CMPF), ursodeoxycholate, levulinate, and X-14,208 (phenylalanylserine) were not associated with confounders of JIA. However, SNPs related to Kyn, 3-dehydrocarnitine, cysteine, pantothenate, phenylalanine, N-acetylglycine, tryptophan betaine, and cholate were associated with confounding factors such as BMI, body fat percentage, body weight, smoking, and inflammatory bowel disease (Supplementary Table 5 ).

After excluding SNPs associated with these confounding factors, we discovered that Kyn, 3-dehydrocarnitine, cysteine, and pantothenate were causally related to JIA, while phenylalanine, N-acetylglycine, tryptophan betaine, and cholate were not causally associated with JIA. To validate the MR analysis, we obtained independent JIA genetic data from the FinnGen dataset for replication analysis, which revealed that five metabolites had characteristics consistent with the MR analysis (Fig.  2 ) (Supplementary Tables 6 , 7 and 8 ). Then, a meta-analysis was conducted to combine the results of two studies, confirming that Kyn, 3-dehydrocarnitine, levulinate, X-14,208 (phenylalanylserine), and linolenate were causally associated with JIA (Fig.  3 ). CMPF and ursodeoxycholate were excluded because of inconsistent directions in the two meta-analyses.

Meta-analysis of the causal associations of serum metabolites with juvenile idiopathic arthritis. OR, odds ratio; CI, confidence interval

Scatter plot of five metabolites( Kyn, 3-dehydrocarnitine, levulinate, X−14,208 (phenylalanylserine), and linolenate )

Metabolic pathway analysis

JIA was found to have significant associations with seven metabolic pathways. These include the biosynthesis of pantothenate and Coenzyme A (CoA) ( p  = 0.002, KEGG), the biosynthesis of aminoacyl-tRNA ( p  = 0.013, KEGG), the biosynthesis of phenylalanine, tyrosine, and tryptophan (Trp) ( p  = 0.015, KEGG), the metabolism of thiamine ( p  = 0.027, KEGG), the metabolism of taurine and hypotaurine ( p  = 0.030, KEGG), the metabolism of phenylalanine ( p  = 0.038, KEGG), and the metabolism of α-linolenic acid ( p  = 0.049, KEGG).

LDSC and reverse causality analyses

Based on LDSC analysis, there was no notable genetic correlation observed between JIA and Kyn (rg: 0.148, SE: 0.118, p  = 0.210), levulinate (rg: 0.041, SE: 0.092, p  = 0.654), and 3-dehydrocarnitine (rg: 0.041, SE: 0.092, p  = 0.654). These findings indicate that the MR outcomes were not impacted by common genetic elements.

The reverse causality analysis revealed no significant genetic evidence supporting a cause-and-effect relationship between JIA and Kyn, 3-dehydrocarnitine, levulinate, X-14,208 (phenylalanylserine), and linolenate (Supplementary Table 9 ). This analysis helps mitigate the potential influence of environmental endogeneity on these factors.

To investigate the causality between JIA and 486 serum metabolites in humans, this research utilized FinnGen datasets and the GWAS catalog through a two-sample MR approach.The findings suggest that elevated levels of Kyn and linolenate increase the risk of JIA, whereas increased levels of 3-dehydrocarnitine, levulinate, and X-14,208 (phenylalanylserine) protect against this condition. Furthermore, the LDSC analysis indicated no genetic correlation of these metabolites with JIA, demonstrating that the MR analysis was reliable and unaffected by pleiotropy. Moreover, seven metabolic pathways were significantly associated with JIA, including pantothenate and CoA biosynthesis and α-linolenic acid metabolism. JIA is a condition resulting from a combination of genetic and environmental factors that subsequently induces systemic immune reactions, which means timely and precise identification and intervention play a crucial role in enhancing patient outcome [ 4 ]. In the United States, JIA affects about one in a thousand children, being the most prevalent pediatric rheumatic disease and a leading cause of disability acquired in childhood [ 36 , 37 ]. This MR research has deepened our understanding of the mechanisms behind JIA, playing a significant role in the disease’s prevention and treatment.

The causal relationship between Kyn and JIA remains unclear.However, previous research has shown that kyn is a significant byproduct of Trp catabolism through tryptophan 2,3-dioxygenase (TDO) or indoleamine 2,3-dioxygenase (IDO) [ 38 ]. The ultimate metabolic product of Kyn is NAD+, which plays a crucial role in immune regulation [ 39 ]. Additionally, under certain physiological conditions, Kyn can be converted into kynurenic acid and xanthurenic acid, both of which are involved in inflammation and immunity in mammals [ 40 , 41 ]. The three rate-limiting enzymes of the Trp-Kyn pathway are IDO1, IDO2, and TDO2, with IDO1 promoting inflammation in rheumatoid arthritis (RA) [ 42 ]. Because of its high homology with IDO1, IDO2 may also be implicated in the onset and progression of autoimmune arthritis [ 43 ]. Moreover, a significant increase in serum Kyn levels is associated with chronic low-grade inflammation [ 44 ].JIA is a multifactorial disease with heterogeneous manifestations, including many forms of chronic arthritis [ 2 ]. The levels of Trp-Kyn pathway metabolites are elevated in the serum, urine, and synovial fluid of RA patients [ 45 ]. Moreover, RA is correlated with increased Trp catabolism, increased Kyn concentrations, and immune cell activation in patients and animal models [ 46 ]. These data suggest that the Trp-Kyn metabolic pathway is involved in the pathogenesis of RA. Moreover, there is increased evidence of the role of Kyn metabolites in physiological and disease states. Therefore, increased Kyn levels may be implicated in the pathophysiology of JIA, as demonstrated in this study.

Although the causal relationship between linolenate and JIA is unclear, the findings suggest that linolenate increases the risk of JIA via alpha-linolenic acid metabolism. Research demonstrates that Wuwei Shexiang pill treatment has been linked to a reduction in γ-linolenic acid and other components of the linoleic acid metabolic pathway, suggesting its anti-inflammatory properties by inhibiting linoleic acid metabolism and affecting arachidonic acid metabolism [ 47 ]. Alpha-linolenic acid has multiple biological functions and is involved in endoplasmic reticulum (ER) stress and lipid metabolism. Linolenate induces ER stress by inhibiting the expression of fatty acid synthase, thereby affecting fatty acid synthesis and inflammatory immune responses [ 48 ]. Some drugs can influence the production of inflammatory mediators, including PGE2 and leukotrienes, by regulating alpha-linolenic acid and arachidonic acid metabolism [ 49 , 50 ]. These data and our findings suggest that linolenate is implicated in the development and progression of JIA.

We found that three serum metabolites—3-dehydrocarnitine, levulinate, and X-14,208 (phenylalanylserine)—protected against JIA. Nonetheless, little is known about the causal relationship of these metabolites with JIA. Specifically, 3-dehydrocarnitine affects fatty acid metabolism in gout arthritis [ 51 ]. Levulinate has a genetic causal relationship with RA [ 52 ]. Additionally, 5-aminolevulinic acid (5-ALA) has anti-inflammatory and immunomodulatory properties and 5-ALA combined with sodium ferrous citrate (SFC) increases the expression and release of heme oxygenase 1 (HO-1) and its metabolites in macrophages and has been utilized in the treatment of inflammatory diseases [ 53 , 54 , 55 ]. These data suggest that the interaction between levulinate and JIA may be mediated by the upregulation of HO-1 by 5-ALA/SFC in macrophages. However, this hypothesis needs to be validated by experimental research. We found that the increased expression of X-14,208 (phenylalanylserine) was associated with a reduced risk of JIA. A study indicates that serum levels of threonine, phenylalanine, and leucine exhibit a positive correlation with the expression of synovial IL-1β and IL-8 in RA patients [ 56 ]. Wine-processed Curculigo orchioides (pCO)’s potential anti-inflammatory actions might be due to its modulation of the phenylalanine metabolic pathway [ 57 ]. Additionally, another study aimed at correlating serum metabolic profiles of RA patients undergoing methotrexate treatment with synovial gene expression discovered associations between serine/glycine/phenylalanine metabolism and aminoacyl-tRNA biosynthesis with TNF-α/CD3E and B cell/plasma related signatures, suggesting a role in lymphocyte regulation within the RA synovium [ 58 ].

Metabolomics, an advanced technology, provides a comprehensive means to explore variations in metabolite levels within biological frameworks, offering invaluable insights into the disruption of metabolic pathways across various diseases [ 59 ]. For instances, a study highlights the pivotal role of metabolomics in revealing that exclusive enteral nutrition can effectively trigger remission in JIA by significantly altering the microbiome and metabolome [ 60 ]. This approach has pinpointed seven critical metabolic pathways associated with JIA, encompassing the biosynthesis of pantothenate and CoA, aminoacyl-tRNA, phenylalanine, tyrosine, and tryptophan, as well as the metabolism of thiamine, taurine and hypotaurine, phenylalanine, and α-linolenic acid. These pathways play essential roles in cellular energy metabolism and the activation of inflammatory cells, highlighting their importance in the pathogenesis of diseases. Employing Ultra Performance Liquid Chromatography-Tandem Mass Spectrometry technology, research has shown that Munziq Balgam, a herbal medicine, can modulate collagen-induced arthritis (CIA) in rat models by affecting these specific pathways, including linoleic acid, alpha-linolenic acid, and the biosynthesis of pantothenate and CoA [ 61 ]. Additionally, Wuwei Shexiang pills have been observed to indirectly affect mitochondrial function and the tricarboxylic acid cycle by altering the synthesis of pantothenic acid and CoA, influencing phenylalanine metabolism [ 47 ]. Further investigations into blood metabolomics of RA rats revealed the impact of Phellodendri Amurensis Cortex, berberine, and palmatine on aminoacyl-tRNA biosynthesis, phenylalanine metabolism, tryptophan metabolism, and the biosynthesis of pantothenic acid and coenzyme A, showcasing anti-RA effect [ 62 ]. Thiamine enhances neurotransmission, muscle function, and immune response in CIA by adjusting metabolism to meet increased energy needs and reduce cellular stress, highlighting the importance of thiamine and arachidonic acid levels in CIA treatment [ 63 ]. Furthermore, research indicates that pCO treatment targeting taurine metabolism can mitigate RA inflammation and bone degradation by modulating anti-inflammatory responses and protecting against oxidative stress [ 57 ]. These studies indicate that targeted regulation of specific metabolic pathways provides a meaningful pathway for the treatment and comprehension of JIA.

This study has strengths. First, IVs and exposure factors were strongly correlated (F > 10). Second, we obtained JIA genetic variation data from multiple sources, conducted several MR analyses, and combined the results of two MR studies to enhance the confidence of MR estimates. Third, MR can eliminate confounding factors and is unaffected by reverse causality. Fourth, the results of MR studies are more robust than those of traditional observational studies. Fifth, we addressed the problem of endogeneity due to reverse causation. To address multiple comparisons, we implemented the Bonferroni correction. The significance level was adjusted to p  < 0.00024 (0.05/486) for the analysis.

This study also has limitations. First, factors such as the Beavis effect, compensatory mechanisms (e.g., canalization), low statistical power, and genetic complexity can limit the application of MR studies [ 35 ]. Second, causal inferences were drawn from the results of MR studies and should be further validated through molecular experiment and real-world clinical studies. Third, the SNP data were obtained from European populations, limiting the generalizability of the findings. Fourth, data on age, gender, and other demographic characteristics were unavailable. Fifth, there was heterogeneity in the MR analysis of serum metabolites and JIA. Although heterogeneity was reduced to acceptable levels after removing outliers, the results should be interpreted with caution.

This study utilized GWAS datasets and MR to assess the causal relationships of circulating metabolites with JIA and found that several metabolites, including Kyn, linolenate, and 3-dehydrocarnitine, were genetically associated with JIA. Thus, the study provides theoretical support for the development of early screening and prevention strategies for JIA and has significant clinical implications.

Data availability

The original contributions presented in the study are included in the article( https://www.finngen.fi/en/access_results , https://www.ebi.ac.uk/gwas/ ) and supplementary material, further inquiries can be directed to the corresponding authors.

Abbreviations

Juvenile Idiopathic Arthritis

• Mendelian randomization

confidence interval

single nucleotide polymorphisms

genome-wide association study

body mass index

inverse variance weighted

the Kyoto Encyclopedia of Genes and Genomes

linkage disequilibrium score regression

linkage disequilibrium

3-carboxy-4-methyl-5-propyl-2-furanpropanoate

tryptophan 2,3-dioxygenase

indoleamine 2,3-dioxygenase

rheumatoid arthritis

endoplasmic reticulum

6- 5-aminolevulinic acid

sodium ferrous citrate

oxygenase 1

collagen-induced arthritis

wine-processed Curculigo orchioides

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Acknowledgements

We gratefully acknowledge the support of the Shandong Provincial Natural Science Foundation of China for funding this study (Grant No. ZR2021MH090).

Funding for this study was provided by the Shandong Provincial Natural Science Foundation, China [grant number ZR2021MH090]. Supported by Qingdao Outstanding Health Professional Development Fund. Young Elite Sponsorship Program of Shandong Provincial Medical Association.

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Han Zhang, Xiao Ma and Wanlu Liu contributed equally to this work and share first authorship.

Authors and Affiliations

Department of Orthopedics, Affiliated Hospital of Qingdao University, Qingdao, China

Han Zhang, Xiao Ma, Zian Zhang, Yingze Zhang, Tianrui Wang & Yongtao Zhang

Shanxian Central Hospital, Heze, Shandong Province, China

Wanlu Liu & GuanHong Chen

Department of Neurology, Qingdao Haici Hospital, Qingdao, China

Department of Orthopedics, The Third Hospital of Hebei Medical University, Shijiazhuang, China

Yingze Zhang

Qingdao Municipal Hospital, Qingdao, China

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ZH: Writing – original draft, review & editing, Conceptualization, Methodology, Project administration; MX, LWL: Writing – review & editing, Conceptualization, Methodology; WZ, ZZA, CGH: Writing – original draft, Conceptualization, Methodology; WTR, ZYZ: Writing – review & editing, Formal Analysis; YTB: Writing – review & editing; ZYT: Writing – review & editing.

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Correspondence to Tianrui Wang , Tengbo Yu or Yongtao Zhang .

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Zhang, H., Ma, X., Liu, W. et al. Causal relationship between serum metabolites and juvenile idiopathic arthritis: a mendelian randomization study. Pediatr Rheumatol 22 , 51 (2024). https://doi.org/10.1186/s12969-024-00986-0

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Meditation: a simple, fast way to reduce stress.

Meditation can wipe away the day's stress, bringing with it inner peace. See how you can easily learn to practice meditation whenever you need it most.

If stress has you anxious, tense and worried, you might try meditation. Spending even a few minutes in meditation can help restore your calm and inner peace.

Anyone can practice meditation. It's simple and doesn't cost much. And you don't need any special equipment.

You can practice meditation wherever you are. You can meditate when you're out for a walk, riding the bus, waiting at the doctor's office or even in the middle of a business meeting.

Understanding meditation

Meditation has been around for thousands of years. Early meditation was meant to help deepen understanding of the sacred and mystical forces of life. These days, meditation is most often used to relax and lower stress.

Meditation is a type of mind-body complementary medicine. Meditation can help you relax deeply and calm your mind.

During meditation, you focus on one thing. You get rid of the stream of thoughts that may be crowding your mind and causing stress. This process can lead to better physical and emotional well-being.

Benefits of meditation

Meditation can give you a sense of calm, peace and balance that can benefit your emotional well-being and your overall health. You also can use it to relax and cope with stress by focusing on something that calms you. Meditation can help you learn to stay centered and keep inner peace.

These benefits don't end when your meditation session ends. Meditation can help take you more calmly through your day. And meditation may help you manage symptoms of some medical conditions.

Meditation and emotional and physical well-being

When you meditate, you may clear away the information overload that builds up every day and contributes to your stress.

The emotional and physical benefits of meditation can include:

• Giving you a new way to look at things that cause stress.
• Building skills to manage your stress.
• Making you more self-aware.
• Focusing on the present.
• Reducing negative feelings.
• Helping you be more creative.
• Helping you be more patient.
• Lowering resting heart rate.
• Lowering resting blood pressure.
• Helping you sleep better.

Meditation and illness

Meditation also might help if you have a medical condition. This is most often true if you have a condition that stress makes worse.

A lot of research shows that meditation is good for health. But some experts believe there's not enough research to prove that meditation helps.

With that in mind, some research suggests that meditation may help people manage symptoms of conditions such as:

• Chronic pain.
• Depression.
• Heart disease.
• High blood pressure.
• Irritable bowel syndrome.
• Sleep problems.
• Tension headaches.

Be sure to talk to your healthcare professional about the pros and cons of using meditation if you have any of these or other health conditions. Sometimes, meditation might worsen symptoms linked to some mental health conditions.

Meditation doesn't replace medical treatment. But it may help to add it to other treatments.

Types of meditation

Meditation is an umbrella term for the many ways to get to a relaxed state. There are many types of meditation and ways to relax that use parts of meditation. All share the same goal of gaining inner peace.

Ways to meditate can include:

Guided meditation. This is sometimes called guided imagery or visualization. With this method of meditation, you form mental images of places or things that help you relax.

You try to use as many senses as you can. These include things you can smell, see, hear and feel. You may be led through this process by a guide or teacher.

• Mantra meditation. In this type of meditation, you repeat a calming word, thought or phrase to keep out unwanted thoughts.

Mindfulness meditation. This type of meditation is based on being mindful. This means being more aware of the present.

In mindfulness meditation, you focus on one thing, such as the flow of your breath. You can notice your thoughts and feelings. But let them pass without judging them.

• Qigong. This practice most often combines meditation, relaxation, movement and breathing exercises to restore and maintain balance. Qigong (CHEE-gung) is part of Chinese medicine.
• Tai chi. This is a form of gentle Chinese martial arts training. In tai chi (TIE-CHEE), you do a series of postures or movements in a slow, graceful way. And you do deep breathing with the movements.
• Yoga. You do a series of postures with controlled breathing. This helps give you a more flexible body and a calm mind. To do the poses, you need to balance and focus. That helps you to focus less on your busy day and more on the moment.

Parts of meditation

Each type of meditation may include certain features to help you meditate. These may vary depending on whose guidance you follow or who's teaching a class. Some of the most common features in meditation include:

Focused attention. Focusing your attention is one of the most important elements of meditation.

Focusing your attention is what helps free your mind from the many things that cause stress and worry. You can focus your attention on things such as a certain object, an image, a mantra or even your breathing.

• Relaxed breathing. This technique involves deep, even-paced breathing using the muscle between your chest and your belly, called the diaphragm muscle, to expand your lungs. The purpose is to slow your breathing, take in more oxygen, and reduce the use of shoulder, neck and upper chest muscles while breathing so that you breathe better.

A quiet setting. If you're a beginner, meditation may be easier if you're in a quiet spot. Aim to have fewer things that can distract you, including no television, computers or cellphones.

As you get more skilled at meditation, you may be able to do it anywhere. This includes high-stress places, such as a traffic jam, a stressful work meeting or a long line at the grocery store. This is when you can get the most out of meditation.

• A comfortable position. You can practice meditation whether you're sitting, lying down, walking, or in other positions or activities. Just try to be comfortable so that you can get the most out of your meditation. Aim to keep good posture during meditation.
• Open attitude. Let thoughts pass through your mind without judging them.

Everyday ways to practice meditation

Don't let the thought of meditating the "right" way add to your stress. If you choose to, you can attend special meditation centers or group classes led by trained instructors. But you also can practice meditation easily on your own. There are apps to use too.

And you can make meditation as formal or informal as you like. Some people build meditation into their daily routine. For example, they may start and end each day with an hour of meditation. But all you really need is a few minutes a day for meditation.

Here are some ways you can practice meditation on your own, whenever you choose:

Breathe deeply. This is good for beginners because breathing is a natural function.

Focus all your attention on your breathing. Feel your breath and listen to it as you inhale and exhale through your nostrils. Breathe deeply and slowly. When your mind wanders, gently return your focus to your breathing.

Scan your body. When using this technique, focus attention on each part of your body. Become aware of how your body feels. That might be pain, tension, warmth or relaxation.

Mix body scanning with breathing exercises and think about breathing heat or relaxation into and out of the parts of your body.

• Repeat a mantra. You can create your own mantra. It can be religious or not. Examples of religious mantras include the Jesus Prayer in the Christian tradition, the holy name of God in Judaism, or the om mantra of Hinduism, Buddhism and other Eastern religions.

Walk and meditate. Meditating while walking is a good and healthy way to relax. You can use this technique anywhere you're walking, such as in a forest, on a city sidewalk or at the mall.

When you use this method, slow your walking pace so that you can focus on each movement of your legs or feet. Don't focus on where you're going. Focus on your legs and feet. Repeat action words in your mind such as "lifting," "moving" and "placing" as you lift each foot, move your leg forward and place your foot on the ground. Focus on the sights, sounds and smells around you.

Pray. Prayer is the best known and most widely used type of meditation. Spoken and written prayers are found in most faith traditions.

You can pray using your own words or read prayers written by others. Check the self-help section of your local bookstore for examples. Talk with your rabbi, priest, pastor or other spiritual leader about possible resources.

Read and reflect. Many people report that they benefit from reading poems or sacred texts and taking a few moments to think about their meaning.

You also can listen to sacred music, spoken words, or any music that relaxes or inspires you. You may want to write your thoughts in a journal or discuss them with a friend or spiritual leader.

• Focus your love and kindness. In this type of meditation, you think of others with feelings of love, compassion and kindness. This can help increase how connected you feel to others.

Building your meditation skills

Don't judge how you meditate. That can increase your stress. Meditation takes practice.

It's common for your mind to wander during meditation, no matter how long you've been practicing meditation. If you're meditating to calm your mind and your mind wanders, slowly return to what you're focusing on.

Try out ways to meditate to find out what types of meditation work best for you and what you enjoy doing. Adapt meditation to your needs as you go. Remember, there's no right way or wrong way to meditate. What matters is that meditation helps you reduce your stress and feel better overall.

Related information

• Relaxation techniques: Try these steps to lower stress - Related information Relaxation techniques: Try these steps to lower stress
• Stress relievers: Tips to tame stress - Related information Stress relievers: Tips to tame stress
• Video: Need to relax? Take a break for meditation - Related information Video: Need to relax? Take a break for meditation

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• Meditation: In depth. National Center for Complementary and Integrative Health. https://nccih.nih.gov/health/meditation/overview.htm. Accessed Dec. 23, 2021.
• Mindfulness meditation: A research-proven way to reduce stress. American Psychological Association. https://www.apa.org/topics/mindfulness/meditation. Accessed Dec. 23, 2021.
• AskMayoExpert. Meditation. Mayo Clinic. 2021.
• Papadakis MA, et al., eds. Meditation. In: Current Medical Diagnosis & Treatment 2022. 61st ed. McGraw Hill; 2022. https://accessmedicine.mhmedical.com. Accessed Dec. 23, 2021.
• Hilton L, et al. Mindfulness meditation for chronic pain: Systematic review and meta-analysis. Annals of Behavioral Medicine. 2017; doi:10.1007/s12160-016-9844-2.
• Seaward BL. Meditation. In: Essentials of Managing Stress. 5th ed. Jones & Bartlett Learning; 2021.
• Seaward BL. Managing Stress: Principles and Strategies for Health and Well-Being. 9th ed. Burlington, Mass.: Jones & Bartlett Learning; 2018.

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Enhancing Variant of Uncertain Significance (VUS) Interpretation in Neurogenetics: Collaborative Experiences from a Tertiary Care Centre

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Background: The findings of variants of uncertain significance (VUS) on a clinical genetic testing report pose a challenge for attending healthcare professionals (HCPs) in patient care. Here, we describe the outcomes of multidisciplinary VUS Rounds, implemented at a neurological disease tertiary care centre, which aid in interpreting and communicating VUS identified in our neurogenetics patient population. Methods: VUS Rounds brought together genetic counsellors, molecular geneticists, and scientists to evaluate VUS against genomic and phenotypic evidence and assign an internal temperature classification "VUS Hot", "True VUS", or "VUS Cold", corresponding to potential pathogenicity. Biweekly meetings were held among the committee to deliberate variant classifications, determine additional clinical management actions, and discuss nuances of VUS result communication. Results: In total, 143 VUS identified in 72 individuals with neurological disease were curated between October 2022 and December 2023. Of these, 12.6% were classified as VUS Hot, carried by 22.2% of the individuals, allowing for prioritization of additional evaluation to determine potential pathogenicity of the variants, such as clinical follow-up or segregation analysis. In contrast, 45.4% of VUS were Cold and could be eliminated from further consideration in the carrier's care. Herein, we thoroughly evaluated the various evidence that contributed to our VUS classifications and resulting clinical actions. Conclusions: The assessment of VUS leveraging multidisciplinary collaboration allowed us to delineate required follow-up analyses for our neurology patient population. Integration of VUS Rounds into healthcare practices, ensures equitable knowledge dissemination amongst HCPs and effective incorporation of uncertain genetic results into patient care.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This study did not receive any funding.

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

Approval for our quality improvement (QI) study design was obtained from Montreal Neurological Institute-Hospital's Director of Professional Services, and the Montreal Neurological Institute-Hospital Institutional Review Board waived the need for ethical approval.

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

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

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The data are not available publicly due to information that could compromise the privacy of the patients. All summary data produced in the present work are contained in the manuscript

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