findings in research brainly

• Chapter Seven: Presenting Your Results

This chapter serves as the culmination of the previous chapters, in that it focuses on how to present the results of one's study, regardless of the choice made among the three methods. Writing in academics has a form and style that you will want to apply not only to report your own research, but also to enhance your skills at reading original research published in academic journals. Beyond the basic academic style of report writing, there are specific, often unwritten assumptions about how quantitative, qualitative, and critical/rhetorical studies should be organized and the information they should contain. This chapter discusses how to present your results in writing, how to write accessibly, how to visualize data, and how to present your results in person.  

• Chapter One: Introduction
• Chapter Two: Understanding the distinctions among research methods
• Chapter Three: Ethical research, writing, and creative work
• Chapter Four: Quantitative Methods (Part 1)
• Chapter Four: Quantitative Methods (Part 2 - Doing Your Study)
• Chapter Four: Quantitative Methods (Part 3 - Making Sense of Your Study)
• Chapter Five: Qualitative Methods (Part 1)
• Chapter Five: Qualitative Data (Part 2)
• Chapter Six: Critical / Rhetorical Methods (Part 1)
• Chapter Six: Critical / Rhetorical Methods (Part 2)

Written Presentation of Results

Once you've gone through the process of doing communication research – using a quantitative, qualitative, or critical/rhetorical methodological approach – the final step is to  communicate  it.

The major style manuals (the APA Manual, the MLA Handbook, and Turabian) are very helpful in documenting the structure of writing a study, and are highly recommended for consultation. But, no matter what style manual you may use, there are some common elements to the structure of an academic communication research paper.

Title Page :

This is simple: Your Paper's Title, Your Name, Your Institutional Affiliation (e.g., University), and the Date, each on separate lines, centered on the page. Try to make your title both descriptive (i.e., it gives the reader an idea what the study is about) and interesting (i.e., it is catchy enough to get one's attention).

For example, the title, "The uncritical idealization of a compensated psychopath character in a popular book series," would not be an inaccurate title for a published study, but it is rather vague and exceedingly boring. That study's author fortunately chose the title, "A boyfriend to die for: Edward Cullen as compensated psychopath in Stephanie Meyer's  Twilight ," which is more precisely descriptive, and much more interesting (Merskin, 2011). The use of the colon in academic titles can help authors accomplish both objectives: a catchy but relevant phrase, followed by a more clear explanation of the article's topic.

In some instances, you might be asked to write an abstract, which is a summary of your paper that can range in length from 75 to 250 words. If it is a published paper, it is useful to include key search terms in this brief description of the paper (the title may already have a few of these terms as well). Although this may be the last thing your write, make it one of the best things you write, because this may be the first thing your audience reads about the paper (and may be the only thing read if it is written badly). Summarize the problem/research question, your methodological approach, your results and conclusions, and the significance of the paper in the abstract.

Quantitative and qualitative studies will most typically use the rest of the section titles noted below. Critical/rhetorical studies will include many of the same steps, but will often have different headings. For example, a critical/rhetorical paper will have an introduction, definition of terms, and literature review, followed by an analysis (often divided into sections by areas of investigation) and ending with a conclusion/implications section. Because critical/rhetorical research is much more descriptive, the subheadings in such a paper are often times not generic subheads like "literature review," but instead descriptive subheadings that apply to the topic at hand, as seen in the schematic below. Because many journals expect the article to follow typical research paper headings of introduction, literature review, methods, results, and discussion, we discuss these sections briefly next.

Introduction:

As you read social scientific journals (see chapter 1 for examples), you will find that they tend to get into the research question quickly and succinctly. Journal articles from the humanities tradition tend to be more descriptive in the introduction. But, in either case, it is good to begin with some kind of brief anecdote that gets the reader engaged in your work and lets the reader understand why this is an interesting topic. From that point, state your research question, define the problem (see Chapter One) with an overview of what we do and don't know, and finally state what you will do, or what you want to find out. The introduction thus builds the case for your topic, and is the beginning of building your argument, as we noted in chapter 1.

By the end of the Introduction, the reader should know what your topic is, why it is a significant communication topic, and why it is necessary that you investigate it (e.g., it could be there is gap in literature, you will conduct valuable exploratory research, or you will provide a new model for solving some professional or social problem).

Literature Review:

The literature review summarizes and organizes the relevant books, articles, and other research in this area. It sets up both quantitative and qualitative studies, showing the need for the study. For critical/rhetorical research, the literature review often incorporates the description of the historical context and heuristic vocabulary, with key terms defined in this section of the paper. For more detail on writing a literature review, see Appendix 1.

The methods of your paper are the processes that govern your research, where the researcher explains what s/he did to solve the problem. As you have seen throughout this book, in communication studies, there are a number of different types of research methods. For example, in quantitative research, one might conduct surveys, experiments, or content analysis. In qualitative research, one might instead use interviews and observations. Critical/rhetorical studies methods are more about the interpretation of texts or the study of popular culture as communication. In creative communication research, the method may be an interpretive performance studies or filmmaking. Other methods used sometimes alone, or in combination with other methods, include legal research, historical research, and political economy research.

In quantitative and qualitative research papers, the methods will be most likely described according to the APA manual standards. At the very least, the methods will include a description of participants, data collection, and data analysis, with specific details on each of these elements. For example, in an experiment, the researcher will describe the number of participants, the materials used, the design of the experiment, the procedure of the experiment, and what statistics will be used to address the hypotheses/research questions.

Critical/rhetorical researchers rarely have a specific section called "methods," as opposed to quantitative and qualitative researchers, but rather demonstrate the method they use for analysis throughout the writing of their piece.

Helping your reader understand the methods you used for your study is important not only for your own study's credibility, but also for possible replication of your study by other researchers. A good guideline to keep in mind is  transparency . You want to be as clear as possible in describing the decisions you made in designing your study, gathering and analyzing your data so that the reader can retrace your steps and understand how you came to the conclusions you formed. A research study can be very good, but if it is not clearly described so that others can see how the results were determined or obtained, then the quality of the study and its potential contributions are lost.

After you completed your study, your findings will be listed in the results section. Particularly in a quantitative study, the results section is for revisiting your hypotheses and reporting whether or not your results supported them, and the statistical significance of the results. Whether your study supported or contradicted your hypotheses, it's always helpful to fully report what your results were. The researcher usually organizes the results of his/her results section by research question or hypothesis, stating the results for each one, using statistics to show how the research question or hypothesis was answered in the study.

The qualitative results section also may be organized by research question, but usually is organized by themes which emerged from the data collected. The researcher provides rich details from her/his observations and interviews, with detailed quotations provided to illustrate the themes identified. Sometimes the results section is combined with the discussion section.

Critical/rhetorical researchers would include their analysis often with different subheadings in what would be considered a "results" section, yet not labeled specifically this way.

Discussion:

In the discussion section, the researcher gives an appraisal of the results. Here is where the researcher considers the results, particularly in light of the literature review, and explains what the findings mean. If the results confirmed or corresponded with the findings of other literature, then that should be stated. If the results didn't support the findings of previous studies, then the researcher should develop an explanation of why the study turned out this way. Sometimes, this section is called a "conclusion" by researchers.

References:

In this section, all of the literature cited in the text should have full references in alphabetical order. Appendices: Appendix material includes items like questionnaires used in the study, photographs, documents, etc. An alphabetical letter is assigned for each piece (e.g. Appendix A, Appendix B), with a second line of title describing what the appendix contains (e.g. Participant Informed Consent, or  New York Times  Speech Coverage). They should be organized consistently with the order in which they are referenced in the text of the paper. The page numbers for appendices are consecutive with the paper and reference list.

Tables/Figures:

Tables and figures are referenced in the text, but included at the end of the study and numbered consecutively. (Check with your professor; some like to have tables and figures inserted within the paper's main text.) Tables generally are data in a table format, whereas figures are diagrams (such as a pie chart) and drawings (such as a flow chart).

Accessible Writing

As you may have noticed, academic writing does have a language (e.g., words like heuristic vocabulary and hypotheses) and style (e.g., literature reviews) all its own. It is important to engage in that language and style, and understand how to use it to  communicate effectively in an academic context . Yet, it is also important to remember that your analyses and findings should also be written to be accessible. Writers should avoid excessive jargon, or—even worse—deploying jargon to mask an incomplete understanding of a topic.

The scourge of excessive jargon in academic writing was the target of a famous hoax in 1996. A New York University physics professor submitted an article, " Transgressing the Boundaries: Toward a Transformative Hermeneutics of Quantum Gravity ," to a special issue of the academic journal  Social Text  devoted to science and postmodernism. The article was designed to point out how dense academic jargon can sometimes mask sloppy thinking. As the professor, Alan Sokal, had expected, the article was published. One sample sentence from the article reads:

It has thus become increasingly apparent that physical "reality", no less than social "reality", is at bottom a social and linguistic construct; that scientific "knowledge", far from being objective, reflects and encodes the dominant ideologies and power relations of the culture that produced it; that the truth claims of science are inherently theory-laden and self-referential; and consequently, that the discourse of the scientific community, for all its undeniable value, cannot assert a privileged epistemological status with respect to counter-hegemonic narratives emanating from dissident or marginalized communities. (Sokal, 1996. pp. 217-218)

According to the journal's editor, about six reviewers had read the article but didn't suspect that it was phony. A public debate ensued after Sokal revealed his hoax. Sokal said he worried that jargon and intellectual fads cause academics to lose contact with the real world and "undermine the prospect for progressive social critique" ( Scott, 1996 ). The APA Manual recommends to avoid using technical vocabulary where it is not needed or relevant or if the technical language is overused, thus becoming jargon. In short, the APA argues that "scientific jargon...grates on the reader, encumbers the communication of information, and wastes space" (American Psychological Association, 2010, p. 68).

Data Visualization

Images and words have long existed on the printed page of manuscripts, yet, until recently, relatively few researchers possessed the resources to effectively combine images combined with words (Tufte, 1990, 1983). Communication scholars are only now becoming aware of this dimension in research as computer technologies have made it possible for many people to produce and publish multimedia presentations.

Although visuals may seem to be anathema to the primacy of the written word in research, they are a legitimate way, and at times the best way, to present ideas. Visual scholar Lester Faigley et al. (2004) explains how data visualizations have become part of our daily lives:

Visualizations can shed light on research as well. London-based David McCandless specializes in visualizing interesting research questions, or in his words "the questions I wanted answering" (2009, p. 7). His images include a graph of the  peak times of the year for breakups  (based on Facebook status updates), a  radiation dosage chart , and some  experiments with the Google Ngram Viewer , which charts the appearance of keywords in millions of books over hundreds of years.

The  public domain image  below creatively maps U.S. Census data of the outflow of people from California to other states between 1995 and 2000.

Visualizing one's research is possible in multiple ways. A simple technology, for example, is to enter data into a spreadsheet such as Excel, and select  Charts  or  SmartArt  to generate graphics. A number of free web tools can also transform raw data into useful charts and graphs.  Many Eyes , an open source data visualization tool (sponsored by IBM Research), says its goal "is to 'democratize' visualization and to enable a new social kind of data analysis" (IBM, 2011). Another tool,  Soundslides , enables users to import images and audio to create a photographic slideshow, while the program handles all of the background code. Other tools, often open source and free, can help visual academic research into interactive maps; interactive, image-based timelines; interactive charts; and simple 2-D and 3-D animations. Adobe Creative Suite (which includes popular software like Photoshop) is available on most computers at universities, but open source alternatives exist as well.  Gimp  is comparable to Photoshop, and it is free and relatively easy to use.

One online performance studies journal,  Liminalities , is an excellent example of how "research" can be more than just printed words. In each issue, traditional academic essays and book reviews are often supported photographs, while other parts of an issue can include video, audio, and multimedia contributions. The journal, founded in 2005, treats performance itself as a methodology, and accepts contribution in html, mp3, Quicktime, and Flash formats.

For communication researchers, there is also a vast array of visual digital archives available online. Many of these archives are located at colleges and universities around the world, where digital librarians are spearheading a massive effort to make information—print, audio, visual, and graphic—available to the public as part of a global information commons. For example, the University of Iowa has a considerable digital archive including historical photos documenting American railroads and a database of images related to geoscience. The University of Northern Iowa has a growing Special Collections Unit that includes digital images of every UNI Yearbook between 1905 and 1923 and audio files of UNI jazz band performances. Researchers at he University of Michigan developed  OAIster , a rich database that has joined thousands of digital archives in one searchable interface. Indeed, virtually every academic library is now digitizing all types of media, not just texts, and making them available for public viewing and, when possible, for use in presenting research. In addition to academic collections, the  Library of Congress  and the  National Archives  offer an ever-expanding range of downloadable media; commercial, user-generated databases such as Flickr, Buzznet, YouTube and Google Video offer a rich resource of images that are often free of copyright constraints (see Chapter 3 about Creative Commons licenses) and nonprofit endeavors, such as the  Internet Archive , contain a formidable collection of moving images, still photographs, audio files (including concert recordings), and open source software.

Presenting your Work in Person

As Communication students, it's expected that you are not only able to communicate your research project in written form but also in person.

Before you do any oral presentation, it's good to have a brief "pitch" ready for anyone who asks you about your research. The pitch is routine in Hollywood: a screenwriter has just a few minutes to present an idea to a producer. Although your pitch will be more sophisticated than, say, " Snakes on a Plane " (which unfortunately was made into a movie), you should in just a few lines be able to explain the gist of your research to anyone who asks. Developing this concise description, you will have some practice in distilling what might be a complicated topic into one others can quickly grasp.

Oral presentation

In most oral presentations of research, whether at the end of a semester, or at a research symposium or conference, you will likely have just 10 to 20 minutes. This is probably not enough time to read the entire paper aloud, which is not what you should do anyway if you want people to really listen (although, unfortunately some make this mistake). Instead, the point of the presentation should be to present your research in an interesting manner so the listeners will want to read the whole thing. In the presentation, spend the least amount of time on the literature review (a very brief summary will suffice) and the most on your own original contribution. In fact, you may tell your audience that you are only presenting on one portion of the paper, and that you would be happy to talk more about your research and findings in the question and answer session that typically follows. Consider your presentation the beginning of a dialogue between you and the audience. Your tone shouldn't be "I have found everything important there is to find, and I will cram as much as I can into this presentation," but instead "I found some things you will find interesting, but I realize there is more to find."

Turabian (2007) has a helpful chapter on presenting research. Most important, she emphasizes, is to remember that your audience members are listeners, not readers. Thus, recall the lessons on speech making in your college oral communication class. Give an introduction, tell them what the problem is, and map out what you will present to them. Organize your findings into a few points, and don't get bogged down in minutiae. (The minutiae are for readers to find if they wish, not for listeners to struggle through.) PowerPoint slides are acceptable, but don't read them. Instead, create an outline of a few main points, and practice your presentation.

Turabian  suggests an introduction of not more than three minutes, which should include these elements:

• The research topic you will address (not more than a minute).
• Your research question (30 seconds or less)
• An answer to "so what?" – explaining the relevance of your research (30 seconds)
• Your claim, or argument (30 seconds or less)
• The map of your presentation structure (30 seconds or less)

As Turabian (2007) suggests, "Rehearse your introduction, not only to get it right, but to be able to look your audience in the eye as you give it. You can look down at notes later" (p. 125).

Poster presentation

In some symposiums and conferences, you may be asked to present at a "poster" session. Instead of presenting on a panel of 4-5 people to an audience, a poster presenter is with others in a large hall or room, and talks one-on-one with visitors who look at the visual poster display of the research. As in an oral presentation, a poster highlights just the main point of the paper. Then, if visitors have questions, the author can informally discuss her/his findings.

To attract attention, poster presentations need to be nicely designed, or in the words of an advertising professor who schedules poster sessions at conferences, "be big, bold, and brief" ( Broyles , 2011). Large type (at least 18 pt.), graphics, tables, and photos are recommended.

A poster presentation session at a conference, by David Eppstein (Own work) [CC-BY-SA-3.0 ( www.creativecommons.org/licenses/by-sa/3.0 )], via Wikimedia Commons]

The Association for Education in Journalism and Mass Communication (AEJMC) has a  template for making an effective poster presentation . Many universities, copy shops, and Internet services also have large-scale printers, to print full-color research poster designs that can be rolled up and transported in a tube.

Judging Others' Research

After taking this course, you should have a basic knowledge of research methods. There will still be some things that may mystify you as a reader of other's research. For example, you may not be able to interpret the coefficients for statistical significance, or make sense of a complex structural equation. Some specialized vocabulary may still be difficult.

But, you should understand how to critically review research. For example, imagine you have been asked to do a blind (i.e., the author's identity is concealed) "peer review" of communication research for acceptance to a conference, or publication in an academic journal. For most  conferences  and  journals , submissions are made online, where editors can manage the flow and assign reviews to papers. The evaluations reviewers make are based on the same things that we have covered in this book. For example, the conference for the AEJMC ask reviewers to consider (on a five-point scale, from Excellent to Poor) a number of familiar research dimensions, including the paper's clarity of purpose, literature review, clarity of research method, appropriateness of research method, evidence presented clearly, evidence supportive of conclusions, general writing and organization, and the significance of the contribution to the field.

Beyond academia, it is likely you will more frequently apply the lessons of research methods as a critical consumer of news, politics, and everyday life. Just because some expert cites a number or presents a conclusion doesn't mean it's automatically true. John Allen Paulos, in his book  A Mathematician reads the newspaper , suggests some basic questions we can ask. "If statistics were presented, how were they obtained? How confident can we be of them? Were they derived from a random sample or from a collection of anecdotes? Does the correlation suggest a causal relationship, or is it merely a coincidence?" (1997, p. 201).

Through the study of research methods, we have begun to build a critical vocabulary and understanding to ask good questions when others present "knowledge." For example, if Candidate X won a straw poll in Iowa, does that mean she'll get her party's nomination? If Candidate Y wins an open primary in New Hampshire, does that mean he'll be the next president? If Candidate Z sheds a tear, does it matter what the context is, or whether that candidate is a man or a woman? What we learn in research methods about validity, reliability, sampling, variables, research participants, epistemology, grounded theory, and rhetoric, we can consider whether the "knowledge" that is presented in the news is a verifiable fact, a sound argument, or just conjecture.

American Psychological Association (2010). Publication manual of the American Psychological Association (6th ed.). Washington, DC: Author.

Broyles, S. (2011). "About poster sessions." AEJMC.  http://www.aejmc.org/home/2013/01/about-poster-sessions/ .

Faigley, L., George, D., Palchik, A., Selfe, C. (2004).  Picturing texts . New York: W.W. Norton & Company.

IBM (2011). Overview of Many Eyes.  http://www.research.ibm.com/social/projects_manyeyes.shtml .

McCandless, D. (2009).  The visual miscellaneum . New York: Collins Design.

Merskin, D. (2011). A boyfriend to die for: Edward Cullen as compensated psychopath in Stephanie Meyer's  Twilight. Journal of Communication Inquiry  35: 157-178. doi:10.1177/0196859911402992

Paulos, J. A. (1997).  A mathematician reads the newspaper . New York: Anchor.

Scott, J. (1996, May 18). Postmodern gravity deconstructed, slyly.  New York Times , http://www.nytimes.com/books/98/11/15/specials/sokal-text.html .

Sokal, A. (1996). Transgressing the boundaries: towards a transformative hermeneutics of quantum gravity.  Social Text  46/47, 217-252.

Tufte, E. R. (1990).  Envisioning information . Cheshire, CT: Graphics Press.

Tufte, E. R. (1983).  The visual display of quantitative information . Cheshire, CT: Graphics Press.

Turabian, Kate L. (2007).  A manual for writers of research papers, theses, and dissertations: Chicago style guide for students and researchers  (7th ed.). Chicago: University of Chicago Press.

How to Synthesize Written Information from Multiple Sources

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Shona McCombes is the content manager at Scribbr, Netherlands.

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Saul McLeod, PhD

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

On This Page:

When you write a literature review or essay, you have to go beyond just summarizing the articles you’ve read – you need to synthesize the literature to show how it all fits together (and how your own research fits in).

Synthesizing simply means combining. Instead of summarizing the main points of each source in turn, you put together the ideas and findings of multiple sources in order to make an overall point.

At the most basic level, this involves looking for similarities and differences between your sources. Your synthesis should show the reader where the sources overlap and where they diverge.

Unsynthesized Example

Franz (2008) studied undergraduate online students. He looked at 17 females and 18 males and found that none of them liked APA. According to Franz, the evidence suggested that all students are reluctant to learn citations style. Perez (2010) also studies undergraduate students. She looked at 42 females and 50 males and found that males were significantly more inclined to use citation software ( p < .05). Findings suggest that females might graduate sooner. Goldstein (2012) looked at British undergraduates. Among a sample of 50, all females, all confident in their abilities to cite and were eager to write their dissertations.

Synthesized Example

Studies of undergraduate students reveal conflicting conclusions regarding relationships between advanced scholarly study and citation efficacy. Although Franz (2008) found that no participants enjoyed learning citation style, Goldstein (2012) determined in a larger study that all participants watched felt comfortable citing sources, suggesting that variables among participant and control group populations must be examined more closely. Although Perez (2010) expanded on Franz’s original study with a larger, more diverse sample…

Step 1: Organize your sources

After collecting the relevant literature, you’ve got a lot of information to work through, and no clear idea of how it all fits together.

Before you can start writing, you need to organize your notes in a way that allows you to see the relationships between sources.

One way to begin synthesizing the literature is to put your notes into a table. Depending on your topic and the type of literature you’re dealing with, there are a couple of different ways you can organize this.

Summary table

A summary table collates the key points of each source under consistent headings. This is a good approach if your sources tend to have a similar structure – for instance, if they’re all empirical papers.

Each row in the table lists one source, and each column identifies a specific part of the source. You can decide which headings to include based on what’s most relevant to the literature you’re dealing with.

For example, you might include columns for things like aims, methods, variables, population, sample size, and conclusion.

For each study, you briefly summarize each of these aspects. You can also include columns for your own evaluation and analysis.

The summary table gives you a quick overview of the key points of each source. This allows you to group sources by relevant similarities, as well as noticing important differences or contradictions in their findings.

Synthesis matrix

A synthesis matrix is useful when your sources are more varied in their purpose and structure – for example, when you’re dealing with books and essays making various different arguments about a topic.

Each column in the table lists one source. Each row is labeled with a specific concept, topic or theme that recurs across all or most of the sources.

Then, for each source, you summarize the main points or arguments related to the theme.

The purposes of the table is to identify the common points that connect the sources, as well as identifying points where they diverge or disagree.

Step 2: Outline your structure

Now you should have a clear overview of the main connections and differences between the sources you’ve read. Next, you need to decide how you’ll group them together and the order in which you’ll discuss them.

For shorter papers, your outline can just identify the focus of each paragraph; for longer papers, you might want to divide it into sections with headings.

There are a few different approaches you can take to help you structure your synthesis.

If your sources cover a broad time period, and you found patterns in how researchers approached the topic over time, you can organize your discussion chronologically .

That doesn’t mean you just summarize each paper in chronological order; instead, you should group articles into time periods and identify what they have in common, as well as signalling important turning points or developments in the literature.

If the literature covers various different topics, you can organize it thematically .

That means that each paragraph or section focuses on a specific theme and explains how that theme is approached in the literature.

Source Used with Permission: The Chicago School

If you’re drawing on literature from various different fields or they use a wide variety of research methods, you can organize your sources methodologically .

That means grouping together studies based on the type of research they did and discussing the findings that emerged from each method.

If your topic involves a debate between different schools of thought, you can organize it theoretically .

That means comparing the different theories that have been developed and grouping together papers based on the position or perspective they take on the topic, as well as evaluating which arguments are most convincing.

Step 3: Write paragraphs with topic sentences

What sets a synthesis apart from a summary is that it combines various sources. The easiest way to think about this is that each paragraph should discuss a few different sources, and you should be able to condense the overall point of the paragraph into one sentence.

This is called a topic sentence , and it usually appears at the start of the paragraph. The topic sentence signals what the whole paragraph is about; every sentence in the paragraph should be clearly related to it.

A topic sentence can be a simple summary of the paragraph’s content:

“Early research on [x] focused heavily on [y].”

For an effective synthesis, you can use topic sentences to link back to the previous paragraph, highlighting a point of debate or critique:

“Several scholars have pointed out the flaws in this approach.” “While recent research has attempted to address the problem, many of these studies have methodological flaws that limit their validity.”

By using topic sentences, you can ensure that your paragraphs are coherent and clearly show the connections between the articles you are discussing.

As you write your paragraphs, avoid quoting directly from sources: use your own words to explain the commonalities and differences that you found in the literature.

Don’t try to cover every single point from every single source – the key to synthesizing is to extract the most important and relevant information and combine it to give your reader an overall picture of the state of knowledge on your topic.

Step 4: Revise, edit and proofread

Like any other piece of academic writing, synthesizing literature doesn’t happen all in one go – it involves redrafting, revising, editing and proofreading your work.

Checklist for Synthesis

•   Do I introduce the paragraph with a clear, focused topic sentence?
•   Do I discuss more than one source in the paragraph?
•   Do I mention only the most relevant findings, rather than describing every part of the studies?
•   Do I discuss the similarities or differences between the sources, rather than summarizing each source in turn?
•   Do I put the findings or arguments of the sources in my own words?
•   Is the paragraph organized around a single idea?
•   Is the paragraph directly relevant to my research question or topic?
•   Is there a logical transition from this paragraph to the next one?

Further Information

How to Synthesise: a Step-by-Step Approach

Help…I”ve Been Asked to Synthesize!

Learn how to Synthesise (combine information from sources)

How to write a Psychology Essay

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Home » Research Summary – Structure, Examples and Writing Guide

Research Summary – Structure, Examples and Writing Guide

Table of Contents

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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• Research Guides

Organizing Your Social Sciences Research Paper

• 9. The Conclusion
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
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• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

The conclusion is intended to help the reader understand why your research should matter to them after they have finished reading the paper. A conclusion is not merely a summary of the main topics covered or a re-statement of your research problem, but a synthesis of key points derived from the findings of your study and, if applicable based on your analysis, explain new areas for future research. For most college-level research papers, two or three well-developed paragraphs is sufficient for a conclusion, although in some cases, more paragraphs may be required in describing the key findings and highlighting their significance.

Conclusions. The Writing Center. University of North Carolina; Conclusions. The Writing Lab and The OWL. Purdue University.

Importance of a Good Conclusion

A well-written conclusion provides important opportunities to demonstrate to the reader your understanding of the research problem. These include:

• Presenting the last word on the issues you raised in your paper . Just as the introduction gives a first impression to your reader, the conclusion offers a chance to leave a lasting impression. Do this, for example, by highlighting key findings in your analysis that advance new understanding about the research problem, that are unusual or unexpected, or that have important implications applied to practice.
• Summarizing your thoughts and conveying the larger significance of your study . The conclusion is an opportunity to succinctly re-emphasize  your answer to the "So What?" question by placing the study within the context of how your research advances past studies about the topic.
• Identifying how a gap in the literature has been addressed . The conclusion can be where you describe how a previously identified gap in the literature [first identified in your literature review section] has been addressed by your research and why this contribution is significant.
• Demonstrating the importance of your ideas . Don't be shy. The conclusion offers an opportunity to elaborate on the impact and significance of your findings. This is particularly important if your study approached examining the research problem from an unusual or innovative perspective.
• Introducing possible new or expanded ways of thinking about the research problem . This does not refer to introducing new information [which should be avoided], but to offer new insight and creative approaches for framing or contextualizing the research problem based on the results of your study.

Bunton, David. “The Structure of PhD Conclusion Chapters.” Journal of English for Academic Purposes 4 (July 2005): 207–224; Conclusions. The Writing Center. University of North Carolina; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion. San Francisco Edit, 2003-2008; Conclusions. The Writing Lab and The OWL. Purdue University; Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8.

Structure and Writing Style

I.  General Rules

The general function of your paper's conclusion is to restate the main argument . It reminds the reader of your main argument(s) strengths and reiterates the most important evidence supporting those argument(s). Do this by clearly summarizing the context, background, and the necessity of examining the research problem in relation to an issue, controversy, or a gap found in the literature. However, make sure that your conclusion is not simply a repetitive summary of the findings. This reduces the impact of the argument(s) you have developed in your paper.

When writing the conclusion to your paper, follow these general rules:

• Present your conclusions in clear, concise language. Re-state the purpose of your study, then describe how your findings differ or support those of other studies and why [i.e., describe what were the unique, new, or crucial contributions your study made to the overall research about your topic].
• Do not simply reiterate your findings or the discussion of your results. Provide a synthesis of arguments presented in the paper to show how these converge to address the research problem and the overall objectives of your study.
• Indicate opportunities for future research if you haven't already done so in the discussion section of your paper. Highlighting the need for further research provides the reader with evidence that you have an in-depth awareness of the research problem but that further analysis should take place beyond the scope of your investigation.

Consider the following points to help ensure your conclusion is presented well:

• If the argument or purpose of your paper is complex, you may need to summarize the argument for your reader.
• If, prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the end of your paper to describe your main points and explain their significance.
• Move from a detailed to a general level of consideration that returns the topic to the context provided by the introduction or within a new context that emerges from the data [this is opposite of the introduction, which begins with general discussion of the context and ends with a detailed description of the research problem]. 

The conclusion also provides a place for you to persuasively and succinctly restate the research problem, given that the reader has now been presented with all the information about the topic . Depending on the discipline you are writing in, the concluding paragraph may contain your reflections on the evidence presented. However, the nature of being introspective about the research you have conducted will depend on the topic and whether your professor wants you to express your observations in this way. If asked to think introspectively about the topic, do not delve into idle speculation. Being introspective means looking within yourself as an author to try and understand an issue more deeply, not to guess at possible outcomes or make up scenarios not supported by the evidence.

II.  Developing a Compelling Conclusion

Although an effective conclusion needs to be clear and succinct, it does not need to be written passively or lack a compelling narrative. Strategies to help you move beyond merely summarizing the key points of your research paper may include any of the following:

• If your paper addresses a critical, contemporary problem, warn readers of the possible consequences of not attending to the problem proactively based on the evidence presented in your study.
• Recommend a specific course or courses of action that, if adopted, could address a specific problem in practice or in the development of new knowledge leading to positive change.
• Cite a relevant quotation or expert opinion already noted in your paper in order to lend authority and support to the conclusion(s) you have reached [a good source would be from a source cited in your literature review].
• Explain the consequences of your research in a way that elicits action or demonstrates urgency in seeking change.
• Restate a key statistic, fact, or visual image to emphasize the most important finding of your paper.
• If your discipline encourages personal reflection, illustrate your concluding point by drawing from your own life experiences.
• Return to an anecdote, an example, or a quotation that you presented in your introduction, but add further insight derived from the findings of your study; use your interpretation of results from your study to recast it in new or important ways.
• Provide a "take-home" message in the form of a succinct, declarative statement that you want the reader to remember about your study.

III. Problems to Avoid

Failure to be concise Your conclusion section should be concise and to the point. Conclusions that are too lengthy often have unnecessary information in them. The conclusion is not the place for details about your methodology or results. Although you should give a summary of what was learned from your research, this summary should be relatively brief, since the emphasis in the conclusion is on the implications, evaluations, insights, and other forms of analysis that you make. Strategies for writing concisely can be found here .

Failure to comment on larger, more significant issues In the introduction, your task was to move from the general [topic studied within the field of study] to the specific [the research problem]. However, in the conclusion, your task is to move the discussion from specific [your research problem] back to a general discussion framed around the implications and significance of your findings [i.e., how your research contributes new understanding or fills an important gap in the literature]. In short, the conclusion is where you should place your research within a larger context [visualize the structure of your paper as an hourglass--start with a broad introduction and review of the literature, move to the specific method of analysis and the discussion, conclude with a broad summary of the study's implications and significance].

Failure to reveal problems and negative results Negative aspects of the research process should never be ignored. These are problems, deficiencies, or challenges encountered during your study. They should be summarized as a way of qualifying your overall conclusions. If you encountered negative or unintended results [i.e., findings that are validated outside the research context in which they were generated], you must report them in the results section and discuss their implications in the discussion section of your paper. In the conclusion, use negative or surprising results as an opportunity to explain their possible significance and/or how they may form the basis for future research.

Failure to provide a clear summary of what was learned In order to discuss how your research fits within your field of study [and possibly the world at large], you need to summarize briefly and succinctly how it contributes to new knowledge or a new understanding about the research problem. This element of your conclusion may be only a few sentences long, but it often represents the key takeaway for your reader.

Failure to match the objectives of your research Often research objectives in the social and behavioral sciences change while the research is being carried out due to unforeseen factors or unanticipated variables. This is not a problem unless you forget to go back and refine the original objectives in your introduction. As these changes emerge they must be documented so that they accurately reflect what you were trying to accomplish in your research [not what you thought you might accomplish when you began].

Resist the urge to apologize If you've immersed yourself in studying the research problem, you presumably should know a good deal about it [perhaps even more than your professor!]. Nevertheless, by the time you have finished writing, you may be having some doubts about what you have produced. Repress those doubts! Don't undermine your authority as a researcher by saying something like, "This is just one approach to examining this problem; there may be other, much better approaches that...." The overall tone of your conclusion should convey confidence to the reader concerning the validity and realiability of your research.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8; Concluding Paragraphs. College Writing Center at Meramec. St. Louis Community College; Conclusions. The Writing Center. University of North Carolina; Conclusions. The Writing Lab and The OWL. Purdue University; Freedman, Leora  and Jerry Plotnick. Introductions and Conclusions. The Lab Report. University College Writing Centre. University of Toronto; Leibensperger, Summer. Draft Your Conclusion. Academic Center, the University of Houston-Victoria, 2003; Make Your Last Words Count. The Writer’s Handbook. Writing Center. University of Wisconsin Madison; Miquel, Fuster-Marquez and Carmen Gregori-Signes. “Chapter Six: ‘Last but Not Least:’ Writing the Conclusion of Your Paper.” In Writing an Applied Linguistics Thesis or Dissertation: A Guide to Presenting Empirical Research . John Bitchener, editor. (Basingstoke,UK: Palgrave Macmillan, 2010), pp. 93-105; Tips for Writing a Good Conclusion. Writing@CSU. Colorado State University; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion. San Francisco Edit, 2003-2008; Writing Conclusions. Writing Tutorial Services, Center for Innovative Teaching and Learning. Indiana University; Writing: Considering Structure and Organization. Institute for Writing Rhetoric. Dartmouth College.

Writing Tip

Don't Belabor the Obvious!

Avoid phrases like "in conclusion...," "in summary...," or "in closing...." These phrases can be useful, even welcome, in oral presentations. But readers can see by the tell-tale section heading and number of pages remaining that they are reaching the end of your paper. You'll irritate your readers if you belabor the obvious.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8.

Another Writing Tip

New Insight, Not New Information!

Don't surprise the reader with new information in your conclusion that was never referenced anywhere else in the paper. This is why the conclusion rarely has citations to sources that haven't been referenced elsewhere in your paper. If you have new information to present, add it to the discussion or other appropriate section of the paper. Note that, although no new information is introduced, the conclusion, along with the discussion section, is where you offer your most "original" contributions in the paper; the conclusion is where you describe the value of your research, demonstrate that you understand the material that you have presented, and position your findings within the larger context of scholarship on the topic, including describing how your research contributes new insights to that scholarship.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8; Conclusions. The Writing Center. University of North Carolina.

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eTable 1. Health Deficits of the Frailty Index in the UK Biobank Cohort

eTable 2. Association of Wine Preference and Drinking During Meals With Mortality in Older Drinkers From the UK Biobank Cohort

eTable 3. Association of Average Alcohol Intake Status With Mortality in Older Drinkers From the UK Biobank Cohort, Excluding Participants With Prevalent Cancer at Baseline for Cancer Mortality, or Those With Prevalent CVD at Baseline for CVD Mortality

eTable 4. Association of Wine Preference or Drinking During Meals With Mortality in Older Drinkers From the UK Biobank Cohort, Excluding Participants With Prevalent Cancer at Baseline for Cancer Mortality, or Those With Prevalent CVD at Baseline for CVD Mortality

eTable 5. Association of Wine Preference and Drinking During Meals With Mortality in Older Drinkers From the UK Biobank Cohort, Excluding Participants With Prevalent Cancer at Baseline for Cancer Mortality, or Those With Prevalent CVD at Baseline for CVD Mortality

eTable 6. Association of Average Alcohol Intake Status With Mortality in Older Drinkers From the UK Biobank Cohort, by Drinking Patterns, Excluding Participants With Prevalent Cancer at Baseline for Cancer Mortality, or Those With Prevalent CVD at Baseline for CVD Mortality

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Ortolá R , Sotos-Prieto M , García-Esquinas E , Galán I , Rodríguez-Artalejo F. Alcohol Consumption Patterns and Mortality Among Older Adults With Health-Related or Socioeconomic Risk Factors. JAMA Netw Open. 2024;7(8):e2424495. doi:10.1001/jamanetworkopen.2024.24495

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Alcohol Consumption Patterns and Mortality Among Older Adults With Health-Related or Socioeconomic Risk Factors

• 1 Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid, Madrid, Spain
• 2 Center for Biomedical Research in Epidemiology and Public Health, Madrid, Spain
• 3 Department of Environmental Health and Nutrition, Harvard T.H. Chan School of Public Health. Boston, Massachusetts
• 4 Madrid Institute for Advanced Studies Food Institute, Campus of International Excellence Universidad Autónoma de Madrid + Spanish National Research Council, Madrid, Spain
• 5 Department of Chronic Diseases, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain

Question   Do health-related or socioeconomic risk factors modify the associations of alcohol consumption patterns with mortality among older drinkers?

Findings   This cohort study in 135 103 older drinkers found that even low-risk drinking was associated with higher mortality among older adults with health-related or socioeconomic risk factors. Wine preference and drinking only with meals were associated with attenuating the excess mortality associated with alcohol consumption.

Meaning   This cohort study identified inequalities in the detrimental health outcomes associated with alcohol that should be addressed to reduce the high disease burden of alcohol use.

Importance   Alcohol consumption is a leading cause of morbidity and mortality that may be more important in older adults with socioeconomic or health-related risk factors.

Objective   To examine the association of alcohol consumption patterns with 12-year mortality and its modification by health-related or socioeconomic risk factors.

Design, Setting, and Participants   This prospective cohort study used data from the UK Biobank, a population-based cohort. Participants were current drinkers aged 60 years or older. Data were analyzed from September 2023 to May 2024.

Exposure   According to their mean alcohol intake in grams per day, participants’ drinking patterns were classified as occasional: ≤2.86 g/d), low risk (men: >2.86-20.00 g/d; women: >2.86-10.00 g/d), moderate risk (men: >20.00-40.00 g/d; women: >10.00-20.00 g/d) and high risk (men: >40.00 g/d; women: >20.00 g/d).

Main Outcomes and Measures   Health-related risk factors were assessed with the frailty index, and socioeconomic risk factors were assessed with the Townsend deprivation index. All-cause and cause-specific mortality were obtained from death certificates held by the national registries. Analyses excluded deaths in the first 2 years of follow-up and adjusted for potential confounders, including drinking patterns and preferences.

Results   A total of 135 103 participants (median [IQR] age, 64.0 [62.0-67.0] years; 67 693 [50.1%] women) were included. In the total analytical sample, compared with occasional drinking, high-risk drinking was associated with higher all-cause (hazard ratio [HR], 1.33; 95% CI, 1.24-1.42), cancer (HR, 1.39; 95% CI, 1.26-1.53), and cardiovascular (HR, 1.21; 95% CI, 1.04-1.41) mortality; moderate-risk drinking was associated with higher all-cause (HR, 1.10; 95% CI, 1.03-1.18) and cancer (HR, 1.15; 95% CI, 1.05-1.27) mortality, and low-risk drinking was associated with higher cancer mortality (HR, 1.11; 95% CI, 1.01-1.22). While no associations were found for low- or moderate-risk drinking patterns vs occasional drinking among individuals without socioeconomic or health-related risk factors, low-risk drinking was associated with higher cancer mortality (HR, 1.15; 95% CI, 1.01-1.30) and moderate-risk drinking with higher all-cause (HR, 1.10; 95% CI, 1.01-1.19) and cancer (HR, 1.19; 95% CI, 1.05-1.35) mortality among those with health-related risk factors; low-risk and moderate-risk drinking patterns were associated with higher mortality from all causes (low risk: HR, 1.14; 95% CI, 1.01-1.28; moderate risk: HR, 1.17; 95% CI, 1.03-1.32) and cancer (low risk: HR, 1.25; 95% CI, 1.04-1.50; moderate risk: HR, 1.36; 95% CI, 1.13-1.63) among those with socioeconomic risk factors. Wine preference (>80% of alcohol from wine) and drinking with meals showed small protective associations with mortality, especially from cancer, but only in drinkers with socioeconomic or health-related risk factors and was associated with attenuating the excess mortality associated with high-, moderate- and even low-risk drinking.

Conclusions and Relevance   In this cohort study of older drinkers from the UK, even low-risk drinking was associated with higher mortality among older adults with health-related or socioeconomic risk factors. The attenuation of mortality observed for wine preference and drinking only during meals requires further investigation, as it may mostly reflect the effect of healthier lifestyles, slower alcohol absorption, or nonalcoholic components of beverages.

Alcohol consumption is a leading cause of morbidity and mortality, accounting for approximately 5.1% of the global burden of disease and 5.3% of all deaths and being responsible for significant social and economic losses, thus representing a major public health problem. 1 Additionally, the assumed benefits of drinking low amounts of alcohol, especially on cardiovascular disease (CVD) mortality, 2 - 4 are being questioned due to selection biases, reverse causation, and residual confounding, 5 supporting health messaging that the safest level of drinking is no drinking at all or less is better. 6 , 7 Selection biases are often overlooked, but they can lead to a systematic underestimation of alcohol-related burden. That is the case of the abstainer bias, whereby the apparently lower mortality of light drinkers compared with abstainers could be explained by the higher death risk of the abstainers because they include former drinkers who quit alcohol due to poor health, as well as lifetime abstainers, 5 who often have worse lifestyle and health characteristics than regular drinkers. 8 Also, the healthy drinker/survivor bias, caused by overrepresentation of healthier drinkers who have survived the deleterious effects of alcohol, can distort comparisons, especially in older age. 5 In addition, drinking habits may influence the association between the amount of alcohol consumed and health. In this context, wine preference has been associated with lower risk of death, 9 CVD morbimortality, 10 and diabetes, 11 attributing the beneficial associations of wine to its high content in polyphenols. 12 Furthermore, drinking with meals has been associated with lower risk of all-cause, non-CVD, and cancer deaths 13 and frailty, 14 so this might be a safer option for alcohol drinkers along with moderate consumption. 15

The health impact of alcohol consumption may be greater in individuals with socioeconomic or health-related risk factors. On one hand, older adults with health-related risk factors are more susceptible to the harmful outcomes associated with alcohol due to their greater morbidity, higher use of alcohol-interacting drugs, and reduced tolerance. 16 , 17 However, some studies have observed benefits of alcohol on unhealthy aging or frailty, especially of light alcohol intake 18 , 19 and of a Mediterranean alcohol drinking pattern, defined as moderate alcohol consumption, preferably wine and accompanying meals, 14 , 20 suggesting that the protective associations of these potentially beneficial drinking patterns might be greater in individuals with ill health, although they might be due to the aforementioned methodological issues. 5 Therefore, it would be of interest to examine whether health-related risk factors modify the associations between alcohol consumption patterns and mortality.

On the other hand, there is evidence that socioeconomically disadvantaged populations have higher rates of alcohol-related harms for equivalent and even lower amounts of alcohol, probably due to the coexistence of other health challenges, including less healthy lifestyles, and lower social support or access to health care. 21 , 22 Also, the potentially beneficial associations of wine preference and drinking during meals might be more important in individuals with socioeconomic risk factors. However, to our knowledge, no previous research has examined whether socioeconomic status modifies the associations between these potentially beneficial drinking patterns and health.

Therefore, the aim of our study is to examine the associations of several potentially beneficial alcohol consumption patterns, that is, consumption of low amounts of alcohol, wine preference, and drinking only during meals, with all-cause, cancer, and CVD mortality in older adults and their modification by health-related or socioeconomic risk factors, while addressing the main methodological issues deemed to bias such associations. Thus, we restrict analyses to current drinkers and use occasional drinkers instead of abstainers as the reference group to prevent selection biases, exclude deaths in the first 2 years of follow-up to reduce reverse causation, and adjust analyses for many sociodemographic, lifestyle, and clinical variables to palliate residual confounding. We also restrict analyses to older adults because most deaths occur in this population group, which also has a high prevalence of health-related risk factors and because the protective associations of alcohol consumption have been specifically observed in older adults, 6 which is consistent with our aim to study potentially beneficial drinking patterns.

This cohort study was approved by the North West Multi-Centre Research Ethics Committee, and all participants provided written informed consent before enrollment. This study is reported following the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline.

We used data from the UK Biobank cohort, a multicenter, prospective, population-based study with more than 500 000 participants aged 40 to 69 years identified from National Health Service primary care registers and enrolled at 22 assessment sites across England, Scotland, and Wales between 2006 and 2010. At the baseline assessment visit, they completed a computer-assisted interview and a touch-screen questionnaire on sociodemographic, lifestyle, and clinical characteristics, provided biological samples, and underwent physical and medical examinations. They were followed-up for mortality through linkage to national death registries. Additional information on the UK Biobank study has been reported elsewhere. 23 , 24

At the baseline assessment visit, study participants were asked about the frequency and mean amount of the main types of alcoholic beverages that they consumed, and alcohol content was estimated by multiplying the volume ingested (in milliliters) by the volume percentage of alcohol (4.5% for beer and cider, 11.5% for white and sparkling wine, 13% for red wine, 20% for fortified wine, and 40% for spirits) and by the specific gravity of ethanol (0.789 g/mL). According to their mean alcohol intake, drinking patterns were classified into occasional (≤2.86 g/d), low risk (men: >2.86-20.00 g/d; women: >2.86-10.00 g/d), moderate risk (men: >20.00-40.00 g/d; women: >10-20.00 g/d), and high risk (men: >40.00 g/d; women: >20.00 g/d), a categorization based on the recommendations from health authorities that we have used in previous studies. 25 - 27 When more than 80% of alcohol came from a certain type of beverage, drinkers were classified as with preference for wine, with preference for other drinks, or with no preference. 27 Participants were also classified as drinkers only during meals and as drinkers either only outside of meals or at any time. Finally, participants were classified as drinkers with no wine preference nor drinking only during meals, drinkers with wine preference or drinking only during meals, and drinkers with wine preference and drinking only during meals.

Health-related risk was assessed at baseline using the frailty index (FI) developed specifically for the UK Biobank 28 based on the procedure used by Rockwood et al. 29 A total of 49 health deficits were considered, most dichotomously (1 point if present and 0 points otherwise), and a few according to severity (0 points for no deficit, 0.25-0.75 points for mild to moderate deficits, and 1 point for severe deficit). The FI score was calculated as the total sum of points assigned to each health deficit divided by the number of deficits considered and ranged from 0.00 to 0.57. The complete list of health deficits and associated scores can be found in eTable 1 in Supplement 1 . Participants were considered to have health-related risk factors if they were prefrail or frail (FI > 0.12). 28

Socioeconomic risk was assessed at baseline using the Townsend deprivation index (TDI), 30 which measures the level of an area’s socioeconomic deprivation. TDI ranges from −6.26 to 10.16, with higher score indicating greater deprivation. Participants were considered to have socioeconomic risk factors if they lived in more deprived areas (TDI > 0) and not if they lived in more affluent areas (TDI ≤ 0).

Information on mortality was obtained from death certificates held by the National Health Service (NHS) Information Centre (NHS England) up to September 30, 2021, for participants in England and Wales, and by the NHS Central Register Scotland (National Records of Scotland) up to October 31, 2021, for participants in Scotland. 31 , 32 Length of follow-up was estimated as the time from the baseline assessment visit to the date of death or administrative censoring, whichever came first. Cause-specific mortality was ascertained with the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision ( ICD-10 ) classification 33 : codes C00 to C97 as primary cause of death for cancer and codes I00 to I99 for CVD.

We also used baseline information on sociodemographic, lifestyle, and clinical characteristics, including sex, age, self-reported race and ethnicity, education (college or university degree; A levels, AS levels, or equivalent; O levels, General Certificate of Secondary Education, or equivalent; Certificate of Secondary Education or equivalent; National Vocational Qualification, Higher National Diploma, Higher National Certificate, or equivalent; other professional qualifications; and no qualifications), tobacco smoking (never, former, or current), leisure-time physical activity (metabolic equivalents of task-hours per week), time spent watching television (hours per day), and prevalent morbidities (diabetes, CVD, and cancer) that could have a potential effect on the amount of alcohol consumed. In the UK Biobank, race and ethnicity are classified as Asian (Indian, Pakistani, Bangladeshi, any other Asian background), Black (Caribbean, African, any other Black background), Chinese, multiple (White and Black Caribbean, White and Black African, White and Asian, any other mixed background), White (British, Irish, any other White background), and other (any group not specified, eg, Arab).

From 217 462 participants aged at least 60 years in the UK Biobank cohort, we excluded 36 284 with incomplete information on alcohol consumption, 10 456 never drinkers, 8295 former drinkers, and 20 167 known binge drinkers (those who consumed ≥6 units of alcohol in 1 session) to avoid classifying binge drinkers with low mean alcohol intake as low-risk drinkers. We additionally excluded 1140 participants who died in the first 2 years of follow-up and 6017 participants with missing information on the FI (194 participants), the TDI (116 participants), and potential confounders (5707 participants). Thus, the analytical sample included 135 103 individuals.

The associations of alcohol consumption patterns (mean alcohol intake status, wine preference, and drinking during meals) at baseline with all-cause and cause-specific mortality were summarized with hazard ratios (HRs) and their 95% CIs obtained from Cox regression; the models included interactions between alcohol consumption patterns and health-related or socioeconomic risk factors and adjusted for baseline sociodemographic (sex, age, race and ethnicity, education, and TDI [except when stratifying by socioeconomic risk factors]), lifestyle (tobacco smoking, leisure-time physical activity, and time spent watching television), and clinical characteristics (diabetes, CVD, cancer, and FI score [except when stratifying by health-related risk factors]) of study participants. Analyses of alcohol intake were further adjusted for wine preference and drinking during meals, whereas analyses of wine preference and drinking during meals were further adjusted for mean alcohol intake and the other drinking pattern.

To characterize whether wine preference and drinking during meals modified the association of mean alcohol intake with mortality, we tested interaction terms defined as the product of the categories of mean alcohol intake by 3 categories of drinking patterns (no wine preference nor drinking only during meals, wine preference or drinking only during meals, and wine preference and drinking only during meals).

Additionally, we assessed whether sociodemographic and lifestyle variables modified the study associations by testing interaction terms defined as the product of alcohol consumption patterns by categories of such variables (except mean alcohol intake status by sex, as sex was included in the definition of alcohol intake status). Since no interactions were found, the results are presented for the total sample. Finally, we performed additional sensitivity analyses excluding participants with prevalent cancer at baseline for cancer mortality or those with prevalent CVD at baseline for CVD mortality.

Statistical significance was set at 2-sided P  < .05. Analyses were performed with Stata software version 17 (StataCorp). Data were analyzed from September 2023 to May 2024.

A total of 135 103 participants (median [IQR] age, 64.0 [62.0-67.0] years; 67 693 [50.1%] women) were included. Occasional drinkers less often identified as White; were more frequently residents in England, women, and never smokers; were less physically active; had a lower educational level, a lower prevalence of CVD; and had a higher prevalence of diabetes, cancer, and health-related risk factors. Having socioeconomic risk factors was less frequent in low- and moderate-risk drinkers ( Table 1 ).

Over a median (range) follow-up of 12.4 (2.0 to 14.8) years, 15 833 deaths were recorded, including 7871 cancer deaths and 3215 CVD deaths. Compared with occasional drinking, low-risk drinking was associated with higher cancer mortality (HR, 1.11; 95% CI, 1.01-1.22); moderate-risk drinking was associated with higher all-cause (HR, 1.10; 95% CI, 1.03-1.18) and cancer (HR, 1.15; 95% CI, 1.05-1.27) mortality; and high-risk drinking was associated with higher all-cause (HR, 1.33; 95% CI, 1.24-1.42), cancer (HR, 1.39; 95% CI, 1.26-1.53), and CVD (HR, 1.21; 95% CI, 1.04-1.41) mortality ( Table 2 ). Hazards were greater in individuals with health-related or socioeconomic risk factors vs those without across categories of alcohol intake. Interestingly, while no associations with mortality were found in participants without health-related or socioeconomic risk factors among low- or moderate-risk drinkers, low-risk drinkers with health-related risk factors had higher cancer mortality (HR, 1.15; 95% CI, 1.01-1.30) and moderate-risk drinkers with health-related risk factors had higher all-cause (HR, 1.10; 95% CI, 1.01-1.19) and cancer (HR, 1.19; 95% CI, 1.05-1.35) mortality ( Table 2 ). Likewise, both low-risk and moderate-risk drinkers with socioeconomic risk factors showed higher mortality from all causes (low risk: HR, 1.14; 1.01-1.28; moderate risk: 1.17; 95% CI, 1.03-1.32) and cancer (low-risk: HR, 1.25; 95% CI, 1.04-1.50; moderate risk: HR, 1.36; 95% CI, 1.13-1.63) ( Table 2 ).

Wine preference and drinking only during meals were associated with lower all-cause mortality only in participants with health-related risk factors (wine preference: HR, 0.92; 95% CI, 0.87-0.97; drinking only during meals: HR, 0.93; 95% CI, 0.89-0.97), as well as in participants with socioeconomic risk factors (wine preference: HR, 0.84; 95% CI, 0.78-0.90; drinking only during meals: HR, 0.83; 95% CI, 0.78-0.89) ( Table 3 ). Drinking only during meals was also associated with lower cancer mortality in participants with health-related risk factors (HR, 0.92; 95% CI, 0.86-0.99) or socioeconomic risk factors (HR, 0.85; 95% CI, 0.78-0.94) ( Table 3 ). Furthermore, in individuals with socioeconomic risk factors, wine preference was associated with lower cancer mortality (HR, 0.89; 95% CI, 0.80-0.99) and drinking only during meals with lower CVD mortality (HR, 0.86; 95% CI, 0.75-1.00) ( Table 3 ). Adhering to both drinking patterns was associated with lower all-cause, cancer, and CVD mortality in drinkers with health-related or socioeconomic risk factors, and to a lesser extent, with lower all-cause death in drinkers without health-related risk factors (eTable 2 in Supplement 1 ). Importantly, wine preference and drinking during meals modified the association of mean alcohol intake with mortality: the excess risk of all-cause, cancer, and CVD death for high-risk drinkers, of all-cause and cancer death for moderate-risk drinkers, and of cancer death for low-risk drinkers vs occasional drinkers was attenuated and even lost among individuals with these drinking patterns ( Table 4 ). Analyses excluding participants with prevalent cancer at baseline for cancer mortality, or those with prevalent CVD at baseline for CVD mortality showed consistent results (eTables 3-6 in Supplement 1 ).

This cohort study in older alcohol drinkers from the UK found that compared with occasional drinkers, low-risk drinkers had higher cancer mortality, moderate-risk drinkers had higher all-cause and cancer mortality, and high-risk drinkers had higher all-cause, cancer, and CVD mortality. The excess mortality associated with alcohol consumption was higher in individuals with health-related and socioeconomic risk factors, among whom even low-risk drinkers had higher mortality, especially from cancer. Wine preference and drinking only with meals showed small protective associations with mortality, especially from cancer, among drinkers with health-related and socioeconomic risk factors, and these 2 drinking patterns attenuated the excess mortality associated with high-, moderate-, and even low-risk drinking.

In line with recent research on the associations between alcohol use and health, 6 , 34 , 35 our results corroborate the detrimental outcomes associated with heavy drinking in older adults. However, we also found higher risk for all-cause and cancer deaths in moderate-risk drinkers, unlike most previous research, which has reported protective associations of low to moderate alcohol consumption, mainly for all-cause 2 - 4 , 36 and CVD 3 , 36 , 37 mortality, ischemic heart disease, 3 , 6 , 34 and diabetes, 6 or null associations with all-cause mortality, 38 CVD, 39 and unhealthy aging. 20 This discrepancy may be due to the implementation of an important methodological improvement in our analyses, that is, using occasional drinkers as the reference group instead of lifetime abstainers, to prevent selection bias caused by misclassification of former drinkers as abstainers, and to palliate residual confounding because they are more like light drinkers than are never drinkers. 40 , 41 In fact, another analysis of the UK Biobank cohort that also avoided selection biases found an increased CVD risk in the general population for drinking up to 14 units per week. 42

To our knowledge, there are no studies examining the potential modification of health-related risk factors on the association between alcohol use and health. The stronger associations between mean alcohol intake and mortality observed in older adults with health-related risk factors make sense, since they have more morbid conditions potentially aggravated by alcohol and greater use of alcohol-interacting medications than their counterparts without health-related risk factors. 16 , 17 The fact that even low-risk drinkers with these risk factors had higher risk of cancer death is an important finding, which is consistent with the reported increased risk of several types of cancer and cancer mortality even with very low amounts of alcohol. 6 , 36 , 37 , 43

Our results also suggest that socioeconomic status acts as a modifier of the association between the amount of alcohol consumed and mortality, as mortality hazard was much greater in individuals with socioeconomic risk factors than in individuals without, in line with previous research. 21 , 22 , 44 , 45 We even found a detrimental association of low amounts of alcohol with all-cause and cancer mortality in this group, unlike the MORGAM study by DiCasetnuovo et al 44 reporting a lower mortality associated with consuming no more than 10 g/d of alcohol, which was clearer in individuals with higher vs lower education. 44 These discrepant results could again be explained by the different reference groups used: occasional drinkers in our study and never drinkers in the MORGAM study. Importantly, although older adults with socioeconomic risk factors have a higher risk of ill health and death, probably due to the coexistence of other health challenges, especially poorer lifestyles, 21 , 22 the observed associations in our study were independent of lifestyles, suggesting that other factors should account for them.

Regarding the potentially beneficial drinking patterns, that is, wine preference and drinking during meals, the literature is inconsistent. A 2018 pool of studies 34 reported a nondifferential association of specific types of alcoholic drinks with all-cause mortality and several CVD outcomes, whereas other studies have found protective health associations for wine but not other beverages. 15 , 46 Drinking with meals has also shown protective associations with several health outcomes. 15 In our analysis, these drinking patterns modified the association between alcohol intake and death risk. On one hand, the protective association for mortality of these patterns was only observed in individuals with socioeconomic or health-related risk factors, independently of the amount of alcohol consumed. On the other hand, the detrimental association of alcohol intake was more evident in individuals without these patterns. These findings suggest that the less detrimental associations of alcohol intake from wine or during meals are not due to alcohol itself, but to other factors, including nonalcoholic components of wine, such as antioxidants, slower absorption of alcohol ingested with meals and its consequent reduced alcoholaemia, as well as spacing drinks when drinking only with meals, or more moderate attitudes in individuals who choose to adhere to these drinking patterns.

Our study has several strengths, such as the large sample size, the long follow-up, and the methodological improvements implemented to prevent selection biases and reduce reverse causation. However, it also has some limitations. First, alcohol intake was self-reported, and therefore prone to some degree of misclassification. Also, alcohol intake was measured only at baseline and not at multiple time points over the life span, not allowing us to take into account changes in alcohol intake before the baseline assessment or to redistribute former drinkers among categories of current drinkers to reduce selection bias; this may have led to an underestimation of the true effects of alcohol consumption. 5 Second, as in any observational study, we cannot entirely rule out residual confounding, despite adjusting for many potential confounders. And third, this study was conducted in older adults in the UK with a high proportion of White participants, so our results may not be generalizable to other racial ethnic groups or populations with different lifestyles, drinking patterns, or socioeconomic development.

This cohort study among older drinkers from the UK did not find evidence of a beneficial association between low-risk alcohol consumption and mortality; however, we observed a detrimental association of even low-risk drinking in individuals with socioeconomic or health-related risk factors, especially for cancer deaths. The attenuation of the excess mortality associated with alcohol among individuals who preferred to drink wine or drink only during meals requires further investigation to elucidate the factors that may explain it. Finally, these results have important public health implications because they identify inequalities in the detrimental health outcomes associated with alcohol that should be addressed to reduce the high burden of disease of alcohol use.

Accepted for Publication: May 30, 2024.

Published: August 12, 2024. doi:10.1001/jamanetworkopen.2024.24495

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Ortolá R et al. JAMA Network Open .

Corresponding Author: Rosario Ortolá, MD, PhD, Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid, Calle del Arzobispo Morcillo 4, 28029 Madrid, Spain ( [email protected] ).

Author Contributions: Dr Ortolá had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Ortolá.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Ortolá.

Critical review of the manuscript for important intellectual content: Sotos-Prieto, García-Esquinas, Galán, Rodríguez-Artalejo.

Statistical analysis: Ortolá.

Obtained funding: Sotos-Prieto, Rodríguez-Artalejo.

Administrative, technical, or material support: Rodríguez-Artalejo.

Supervision: García-Esquinas, Galán.

Conflict of Interest Disclosures: None reported.

Funding/Support: This work was supported by the Plan Nacional sobre Drogas, Ministry of Health of Spain (grant No. 2020/17), Instituto de Salud Carlos III, State Secretary of R+D+I and Fondo Europeo de Desarrollo Regional/Fondo Social Europeo (Fondo de Investigación en Salud grants No. 19/319, 20/896, and 22/1111), Agencia Estatal de Investigación (grant No. CNS2022-135623), Carlos III Health Institute and the European Union “NextGenerationEU (grant No. PMP21/00093), and the Fundación Francisco Soria Melguizo (Papel de la Disfunción Mitocondrial en la Relación Entre Multimorbilidad Crónica y Deterioro Funcional en Ancianos project grant). Mercedes Sotos-Prieto holds a Ramón y Cajal contract (contract No. RYC-2018-025069-I) from the Ministry of Science, Innovation and Universities.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2 .

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Aug. 12, 2024

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Methodology

• What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

A research design is a strategy for answering your   research question  using empirical data. Creating a research design means making decisions about:

• Your overall research objectives and approach
• Whether you’ll rely on primary research or secondary research
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

• Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
• Descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

• Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

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As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

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

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

 Statistics

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

Research bias

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

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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• v.317(7150); 1998 Jul 4

Looking forward

Making better use of research findings, andrew haines.

a Department of Primary Care and Population Sciences, Royal Free and University College London Schools of Medicine, London NW3 2PF, b Department of Epidemiology and Public Health, University College London Medical School

Anna Donald

There is increasing interest in implementing research findings in practice both because of a growing awareness of the gap between clinical practice and the findings of research and also because of the need to show that public investment in research results in benefits for patients. Improved understanding of the reasons for the uptake of research findings requires insights from a range of disciplines. In order to promote the uptake of research findings it is necessary to identify potential barriers to implementation and to develop strategies to overcome them. Specific interventions that can be used to promote change in practice include using clinical guidelines and computerised decision support systems, developing educational programmes, communicating research findings to patients, and developing strategies for organisational change.

Interest in how best to promote the uptake of research findings has been fuelled by a number of factors including the well documented disparities between clinical practice and research evidence of effective interventions. Examples include interventions in the management of cardiac failure, secondary prevention of heart disease, 1 atrial fibrillation, 2 menorrhagia, 3 and pregnancy and childbirth. 4 In the United Kingdom the advent of the NHS research and development programme has led to greater involvement of NHS personnel in setting priorities 5 and to the establishment of a programme to evaluate different methods of promoting the implementation of research findings. 6 The concept of pay back on research 7 has also been developed, resulting in a framework that can be used to assess the benefits arising from research.

Relying on the passive diffusion of information to keep health professionals’ knowledge up to date is doomed to failure in a global environment in which about 2 million articles on medical issues are published annually. 8 There is also growing awareness that conventional continuing education activities, such as conferences and courses, which focus largely on the passive acquisition of knowledge have little impact on the behaviour of health professionals. 9 The circulation of guidelines without an implementation strategy is also unlikely to result in changes in practice. 10

Summary points

• Reasons for failing to get research findings into practice are many and include the lack of appropriate information at the point of decision making and social, organisational, and institutional barriers to change
• All people within an organisation who will have to implement the change or who can influence change should be involved in developing strategies for change
• Better links between clinical audit, continuing education, and research and development need to be developed
• Evidence of the effectiveness of specific interventions to promote change is still incomplete, but a combination of interventions will probably be needed
• The pressure for more effective and efficient implementation of research findings is likely to grow

Health professionals need to plan for rapid changes in knowledge, something that is likely to persist throughout our professional lifetimes and which encompasses not only diagnostic techniques, drug treatment, behavioural interventions, and surgical procedures but also ways of delivering and organising health services and developing health policy. Many health professionals already feel overburdened, and therefore a radical change in approach is required so that they can manage change rather than feel like its victims. A number of steps are necessary in order to support this process.

Keeping abreast of new knowledge

Health professionals need timely, valid, and relevant information to be available at the point of decision making. Despite extensive investment in information technology by the NHS the rapid delivery of such information is not widely available. Relatively simple prompting and reminder systems can improve clinicians’ performance 11 ; the price of useful databases such as Best Evidence (which comprises Evidence-Based Medicine and the American College of Physicians Journal Club on CD ROM) and The Cochrane Library is little more than the cost of subscribing to a journal. There are an increasing number of journals, such as Evidence-Based Medicine, that review important papers rigorously and present the results in a way that busy clinicians can rapidly absorb. The NHS reviews and dissemination centre in York compiles systematic reviews that are relevant to clinicians and policymakers. Nevertheless, many clinicians still do not receive such information, 12 and more needs to be done to provide a wider range of high quality information that is usable in practice settings.

Librarians’ roles are changing rapidly; in North America, for example, some librarians are involved in clinical practice through programmes such as literature attached to the chart (LATCH). 13 In these programmes, hospital librarians participate in ward rounds and actively support clinical decision making at the bedside. Requests for information are documented in the notes, and articles are subsequently delivered to the ward. Similar programmes could be introduced elsewhere after appropriate evaluation, but information support is also needed in primary care settings. In the United Kingdom many health professionals, such as nurses, may not be permitted to use their hospital library since they are not formally affiliated with the (medical) body that funds them.

Implementing knowledge

Research findings can influence decisions at many levels—in caring for individual patients, in developing practice guidelines, in commissioning health care, in developing prevention and health promotion strategies, in developing policy, in designing educational programmes, and in performing clinical audit—but only if clinicians know how to translate knowledge into action. The acquisition of database searching and critical appraisal skills should give health professionals greater confidence in finding and assessing the quality of publications, but this does not necessarily help in applying new knowledge to day to day problems. 14 Much attention has been paid to the use of best evidence during consultations with individual patients—that is, using evidence based medicine derived largely from epidemiological methods. 15 , 16 However, organisational change is often also necessary to implement clinical change. Even a step as simple as ensuring that all patients with a history of myocardial infarction are offered aspirin requires that a number of smaller steps are taken including identifying patients, contacting them, explaining the rationale, checking for contraindications, and prescribing aspirin or advising patients to buy it over the counter. Furthermore, health professionals have their own experiences, beliefs, and perceptions about appropriate practice; attempts to change practice which ignore these factors are unlikely to succeed. Awareness of these pitfalls has led to greater emphasis on understanding social, behavioural, and organisational factors which may act as barriers to change. 17

A wide spectrum of approaches for promoting implementation has been used. These approaches are underpinned by a number of theoretical perspectives on behavioural change such as cognitive theories which focus on rational information seeking and decision making; management theories which emphasise organisational conditions needed to improve care; learning theories which lead to behavioural approaches involving, for example, audit and feedback and reminder systems; and social influence theories which focus on understanding and using the social environment to promote and reinforce change. 18

Clearly these approaches are not mutually exclusive. For example, the transmission of information from research to single practitioners or small groups of health professionals through educational outreach has a strong educational component but might also include aspects of social influence interventions 19 in pointing out the use of a particular treatment by local colleagues. The marketing strategies used by the pharmaceutical industry depend on segmentation of the target audience into groups that are likely to share characteristics so that a message can be tailored to that group. 20 Similar techniques might be adapted for non-commercial use within the NHS. The evidence for the effectiveness of different approaches and interventions is still incomplete and will be reviewed in a subsequent article in the series. 21 In many cases a combination of approaches will be more effective than a single intervention. 22 No single theoretical perspective has been adequately validated to guide the choice of implementation strategies.

Steps in promoting the uptake of research findings

• Determine that there is an appreciable gap between research findings and practice
• Define the appropriate message (for example, the information to be used)
• Decide which processes need to be altered
• Involve the key players (for example those people who will implement change or who are in a position to influence change)
• Identify the barriers to change and decide how to overcome them
• Decide on specific interventions to promote change (for example the use of guidelines or educational programmes)
• Identify levers for change—that is, existing mechanisms which can be used to promote change (for example, financial incentives to attend educational programmes or placing appropriate questions in professional examinations)
• Determine whether practice has changed in the way desired; use clinical audit to monitor change

The study of the diffusion of innovations—how new ideas are transmitted through social networks—has been influential in illustrating that those who adopt new ideas early tend to differ in a number of ways from those who adopt the ideas later. For example, those who adopt new ideas early tend to have more extensive social and professional networks. 23 Much of the medical literature has a bias towards innovation and the underlying assumption is that innovations are bound to be beneficial. However, in health care the challenge is to promote the uptake of innovations that have been shown to be effective, to delay the spread of those that have not yet been shown to be effective, and to prevent the uptake of ineffective innovations. 24

Although different people can promote the uptake of research findings—including policymakers, commissioning authorities, educators, and provider managers—it is largely clinicians and their patients who will implement findings. A number of steps need to be taken in order to get research findings into practice (box previous page). The characteristics of the message should also be considered; they may influence the degree to which the message is incorporated into practice (box above).

Important characteristics of the message

• Generalisability (settings in which the intervention is relevant)
• Applicability (the patients to whom the intervention is relevant)
• Format and presentation (for example, will there be written or computerised guidelines, will absolute and relative risk reductions be presented)

Other characteristics

• Source of the message (for example, professional organisation, Department of Health)
• Channels of communication (how the message will be disseminated)
• Target audiences (the recipients)
• Timing of the initial launch and frequency of updating
• Mechanism for updating the message

The choice of key players—those people in the organisation who will have to implement change or who can influence change—will depend on the processes to be changed; in primary care, for example, nurses and administrative staff should be involved in many cases, in addition to general practitioners, since their cooperation will be essential for organisational change to be effective. If the innovation involves the acquisition of specific skills, such as training in certain procedures, then those who organise postgraduate and continuing education are also key players.

The identification of barriers to change and the development of strategies to overcome them are likely to be of fundamental importance in promoting the uptake of research findings. Some examples of barriers to the application of research findings to patients are given in the box on the next page. A future article will propose a conceptual framework for analysing and overcoming barriers. 25 Since some of the strongest resistance to change may be related to the experiences and beliefs of health professionals, the early involvement of key players is essential in identifying and, when necessary, overcoming such impediments to change. Barriers need to be reviewed during the process of implementation as their nature may change over time.

Interventions to promote change must be tailored to the problem, audience, and the resources available. Educational outreach, for example, may be particularly appropriate for updating primary care practitioners in the management of specific conditions because they tend to work alone or in small groups. Guidelines based on research evidence may be developed and endorsed by national professional organisations and adapted for local use as part of clinical audit and educational programmes.

Linking research with practice

There need to be closer links between research and practice, so that research is relevant to practitioners’ needs and so that practitioners are willing to participate in research. While there is evidence that some researchers can promote their own work, 26 in general researchers have not been systematically involved in the implementation of their own findings and may not be well equipped to do this. In the United Kingdom, the NHS research and development programme is seeking views about priorities for research through a broad consultation process. 5 Better methods of involving those who are most likely to use the results of research are needed to ensure that research questions are framed appropriately and tested in relevant contexts using interventions that can be replicated in everyday practice. For example, there is little point conducting trials of a new intervention in hospital practice if virtually all of the treatments for a particular disorder are carried out in primary care settings. Contextual relevance is particularly important in studies of the organisation and delivery of services, 27 such as stroke units, hospital at home schemes, and schemes for improving hospital discharge procedures to reduce readmissions among elderly patients. If unaccounted for, differences in skill mix and management structures between innovative services and most providers can make it difficult for providers to have a clear view of how they should best implement findings in their own units.

Interaction between purchasers and providers

—In the NHS, purchasers as well as providers should be involved in applying research findings to practice. Purchasers can help create an environment conducive to change, for example, by ensuring that health professionals have access to information, that libraries are financially supported, and that continuing education and audit programmes are configured to work together to promote effective practice. Purchasers could also ensure that the organisation and delivery of services takes into account the best available research evidence. However, it is clear that the degree of influence exerted by purchasers on the practice of providers is limited, 28 and that priority must be given to helping providers develop the capacity to understand and use research findings.

Making implementation an integral part of training

—For many health professionals, involvement in implementation may be far more relevant to their careers and to the development of the NHS than undertaking laboratory research, yet pressures to undertake research remain strong. Greater encouragement should be given to clinicians to spend time learning to use and implement research findings effectively.

Potential barriers to change

Environmental

In the practice

• Limitations of time
• Limitations of the organisation of the practice (for example, a lack of disease registers or mechanisms to monitor repeat prescribing)

In education

• Inappropriate continuing education and failure to connect with programmes to promote better quality of care
• Lack of incentives to participate in effective educational activities

In health care

• Lack of financial resources
• Lack of defined practice populations
• Health policies which promote ineffective or unproved activities
• Failure to provide practitioners with access to appropriate information
• Influence of the media on patients in creating demands or beliefs
• Impact of disadvantage on patients’ access to care

Factors associated with the practitioner

• Obsolete knowledge
• Influence of opinion leaders (such as health professionals whose views influence their peers)
• Beliefs and attitudes (for example, a previous adverse experience of innovation)

Factors associated with the patient

• Demands for care
• Perceptions or cultural beliefs about appropriate care

Factors which in some circumstances might be perceived as barriers to change can also be levers for change. For example, patients may influence practitioners’ behaviour towards clinically effective practice by requesting interventions that have been proved to be effective. Practitioners might be influenced positively by opinion leaders.

Learning to evaluate and use research findings in daily practice is an important and lifelong part of professional development. This requires not only changes in educational programmes, but also a realignment of institutions so that management structures can support changes in knowledge and the implementation of changes in procedures.

There are major structural difficulties that need to be overcome in the NHS. For example, better coordination at national, regional, and local levels is required between the education and training of health professionals, clinical audit, and research and development. This type of coordination should be a priority for the proposed national institute for clinical excellence in the United Kingdom. 29

It has been suggested that financial considerations, rather than the potential for gaining useful knowledge, affect general practitioners’ choice of continuing education courses. 30 One of the aims of continuing education should be to ensure that practitioners stay up to date with research findings of major importance for patient care and change their practice accordingly. Continuing education activities need to take into account evidence about the ineffectiveness of many traditional approaches. To develop a more integrated approach to promoting the uptake of research findings, health systems need to have coordinated mechanisms that can manage the continuing evolution of medical knowledge.

The advent of research based information that is available to patients 31 and the increasing accessibility of information of variable quality through the internet and other sources suggests that doctors have the potential to act as information brokers and interpreters for patients. Doctors could also work together with user groups representing patients or their carers, a number of which have demonstrated an interest in and commitment to providing quality research based information to their members. 32 The pace of change in knowledge is unlikely to slow. As health systems around the world struggle to reconcile change with limited resources and rising expectations, pressure to implement research findings more effectively and efficiently is bound to grow.

Funding: None.

Conflict of interest: None.

The articles in this series are adapted from Coping with Loss , edited by Colin Murray Parkes and Andrew Markus, which will be published in July.

Higgins Releases Preliminary Investigative Report

Aug 15, 2024 | Law & Crime , Media , Press Releases

WASHINGTON, D.C. – Congressman Clay Higgins (R-LA), a member of the Task Force on the Attempted Assassination of Donald J. Trump, released his preliminary investigative report, candidly discussing some of his objective findings following his “boots on the ground” trip to Butler, PA on August 4th, 5th and 6th.

The preliminary investigative report was submitted to Task Force Chairman Mike Kelly (R-PA) on August 12, 2024. The document was intended to foster discussion amongst Task Force members. It has been embargoed for several days pending authorization to release from the Task Force chain of command.

“As I have said, every question will be answered, every theory explored, and every doubt erased. The American people deserve the full truth on the attempted assassination of President Trump,” said Congressman Higgins. “Our investigative efforts are moving forward in good faith. The release of my preliminary investigative report is reflective of my desire to deliver transparency and reassurance to the American people.”

The preliminary report details some of Congressman Higgins’ findings thus far. However, it is not exhaustive, nor final.

Notable observations include:

• “U.S. Secret Service did not retrieve the radios that had been set aside for them by Butler County tactical command. The radio comms were properly and perfectly arranged during the extensive pre-mission planning.”
• “All 8 casings (from shots fired by Crooks) were recovered and are allegedly in proper possession of the FBI.”
• “The 9th shot fired on J13 was from a Butler SWAT operator from the ground about 100 yards away from the AGR building. Shot 9 hit Crooks’ rifle stock and fragged his face/neck/right shoulder area from the stock breaking up.”
• “The 10th (and, I believe, final) shot was fired from the southern counter-sniper team.”
• “My effort to examine Crooks’ body on Monday, August 5, caused quite a stir and revealed a disturbing fact… the FBI released the body for cremation 10 days after J13.”
• “The water tower was cleared by drone J13 AM by the County tactical commander, ESU Commander Lenz himself.”

Read Congressman Higgins’ preliminary investigative report here.

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10 Key Findings in Hiring Trends for H1 2024

• Posted on: August 15, 2024
• Topic: Higher Education

Are your programs meeting labor market demands?

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How Can We Make a Progressive Tax System More Efficient?

Key takeaways.

• In a progressive tax system, taxes as a share of income increase as income increases.
• A progressive tax system reduces inequality but also diminishes the incentive for individuals to strive for higher incomes.
• I discuss ways to maintain a progressive tax system without imposing such disincentives on workers.

In the U.S., income tax rates rise as households earn more. However, such a system means workers have a reduced incentive to increase their earnings. In this article, I discuss a finding from one of my papers that explores the possible effects of targeting tax rates on additional characteristics besides income.

The U.S.'s Progressive Income Tax System

Federal income taxes are the primary source of revenue for the federal government. According to estimates from 2022, 54 percent of federal revenues came from individual income taxes, 30 percent from Social Security taxes, 8 percent from corporate income taxes, and the remaining from other types of taxation such as estate taxes. 1

A fundamental characteristic of the U.S. income tax system is its progressivity. A tax system is considered progressive if the tax burden as a share of income rises as income increases. For example, in a progressive tax system, a family with an income of $100,000 might pay a total of 20 percent in taxes, while a family with an income of $200,000 might pay a total of 25 percent of its income in taxes.

In contrast, a proportional (or flat) tax system maintains a constant tax rate regardless of income, and a regressive tax system decreases the tax rate as income rises. The degree of progressivity is linked to the concept of vertical equity, which concerns how the tax burden is distributed among households with different levels of well-being.

Income Inequality and the U.S. Tax System

Many view a progressive tax system as fair because an extra dollar holds less value for a high-income household than for a low-income household. Therefore, asking higher-income households to contribute a larger fraction of their additional income is seen as a reasonable policy. However, some argue it is unfair to require certain taxpayers to pay more than others or pay a larger share of their income.

One principle guiding economists in evaluating tax policy fairness is the benefit principle, which suggests that the tax burden should correspond to the benefits received from government services. Based on this principle, it is argued that higher-income individuals — who benefit from public infrastructure and government spending — should contribute more significantly to the tax burden.

The public discussion about how progressive the tax system should be is often motivated by the rise in income inequality. The top 10 percent of earners in the U.S. now receive around 45 percent of national income, up from 35 percent 50 years ago. 2 Economist Thomas Piketty attributes this rise in inequality primarily to an unprecedented increase in wage disparity , stemming from the income rise of top executives and managers. 3

Of course, inequality itself may not be problematic if there is sufficient economic mobility. For instance, if low-income and high-income workers frequently change places, income inequality is less concerning. However, mobility at the top of the income distribution has remained stable , not offsetting the rise in inequality since the 1970s. 4

Taxes can also impose hidden economic costs. When high-income levels are taxed more heavily, it can diminish the incentive for individuals to strive for higher incomes. Conversely, if everyone pays the same amount of taxes, there is no disincentive to work harder, as one's efforts do not affect the amount of tax paid. Every economic tax system needs to resolve this trade-off: A more progressive tax system may reduce income inequality but often imposes larger disincentives to economic agents.

A More Efficient Income Tax System?

A basic principle of public finance is that the government should decrease tax distortions on workers who are more likely to respond adversely to a rise in their taxes. (In economics jargon, these would be workers with a larger value of labor supply elasticity.)

But how can the government distinguish between workers with a low or high elasticity of labor supply? In my 2016 paper " A Road Map for Efficiently Taxing Heterogeneous Agents ," I propose using information on the observable characteristics of the workers. For example, workers closer to retirement are more likely to quit their jobs if their taxes increase. Also, secondary earners in dual-income households may be the first to drop out of the labor market if their taxes increase.

So, how could a more efficient tax system work? Think of an economy with 10 potential workers. Each worker has a wage level that makes the worker exactly indifferent between participating in or staying out of the labor market. And this "reservation wage" is not the same across workers. For example, young workers may be willing to work for lower wages to build experience and skills. Other workers may not accept a job unless it is high paying, such as workers with enough accumulated assets or financial support who can afford to stay out of the labor force.

Let's rank workers in terms of reservation wages from bottom to top and consider a company that offers a wage equal to the reservation wage of worker 5. How many workers can the company attract? Workers 1 to 4 would happily accept the job position, worker 5 would be just indifferent about accepting, and workers 6 to 10 would decline to work.

Now, imagine that the government levies taxes of 1 percent of workers' labor income. These taxes effectively reduce the (after-tax) wage received by the workers. As a result, worker 5 now also rejects the offer, so the company's pool of workers becomes even smaller.

But there is a way to impose taxes while also keeping worker 5 in the workforce: increase taxes only on workers 1 to 4. This tax system would keep taxes low for workers who are the most likely to respond to a lower after-tax wage (worker 5 in our example).

How can such a tax system be implemented in practice? Since labor supply elasticity is unobservable, the government can rely on information on workers' age and wealth holdings, which are strong predictors of how low or high workers' reservation wages are.

Summary of Findings

In my paper, I evaluate the potential of a tax system that explicitly depends on such characteristics. I find that, regarding age, the tax rates should be lower for young and old households and higher for mid-career households. Tax rates should additionally decrease in household assets and as households get closer to retirement. Finally, I suggest that when a spouse joins the workforce, households should get a tax credit. Using a quantitative model, I find that these reforms have significant economic gains: Capital increases by up to 20 percent, and labor supply increases by up to around 3 percent.

Marios Karabarbounis is a senior economist in the Research Department at the Federal Reserve Bank of Richmond.

See the 2023 article " Your Income Taxes Are Due. Here's Who Pays the Most. " by Laura Saunders.

See the 2017 paper " Distributional National Accounts: Methods and Estimates for the United States " by Thomas Piketty, Emmanual Saez and Gabriel Zucman.

See Piketty's 2013 book Capital in the 21st Century .

See the 2010 article " Earnings Inequality and Mobility in the United States: Evidence from Social Security Data Since 1937 " by Wojciech Kopchuk, Emmanuel Saez and Jae Song.

To cite this Economic Brief, please use the following format: Karabarbounis, Marios. (August 2024) "How Can We Make a Progressive Tax System More Efficient?" Federal Reserve Bank of Richmond Economic Brief , No. 24-26.

This article may be photocopied or reprinted in its entirety. Please credit the author, source, and the Federal Reserve Bank of Richmond and include the italicized statement below.

Views expressed in this article are those of the author and not necessarily those of the Federal Reserve Bank of Richmond or the Federal Reserve System.

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